diff --git a/char-based.ipynb b/char-based.ipynb index 1d0ab18..abe075f 100644 --- a/char-based.ipynb +++ b/char-based.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 1, "metadata": {}, "outputs": [ { @@ -25,12 +25,12 @@ ], "source": [ "import codecs\n", - "from keras.utils.np_utils import to_categorical\n", + "from tensorflow.keras.utils import to_categorical\n", "import numpy as np\n", "\n", "def load_data(filename):\n", - " data = list(codecs.open(filename, 'r', 'utf-8').readlines())\n", - " x, y = zip(*[d.strip().split('\\t') for d in data])\n", + " with codecs.open(filename, 'r', 'utf-8') as f:\n", + " x, y = zip(*[d.strip().split('\\t') for d in f])\n", " x = np.asarray(list(x))\n", " y = to_categorical(y, 3)\n", " \n", @@ -58,7 +58,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -73,7 +73,7 @@ } ], "source": [ - "from keras.preprocessing import text, sequence\n", + "from tensorflow.keras.preprocessing import text, sequence\n", "\n", "def tokenizer(x_train, x_test, vocabulary_size, char_level):\n", " tokenize = text.Tokenizer(num_words=vocabulary_size, \n", @@ -110,15 +110,15 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Token OOV ratio: 0.03508771929824561 (8 out of 228)\n", - "Morph OOV ratio: 0.03508771929824561 (8 out of 228)\n" + "Token OOV ratio: 0.0 (0 out of 228)\n", + "Morph OOV ratio: 0.0 (0 out of 228)\n" ] } ], @@ -136,13 +136,13 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "\n", - "def plot_loss_and_accuracy(history):\n", + "def plot_loss_and_accuracy(history, model_name, dataset_kind):\n", " \n", " fig, axs = plt.subplots(1, 2, sharex=True)\n", " \n", @@ -151,11 +151,12 @@ " axs[0].set_title('Model Loss')\n", " axs[0].legend(['Train', 'Validation'], loc='upper left')\n", " \n", - " axs[1].plot(history.history['acc'])\n", - " axs[1].plot(history.history['val_acc'])\n", + " axs[1].plot(history.history['accuracy'])\n", + " axs[1].plot(history.history['val_accuracy'])\n", " axs[1].set_title('Model Accuracy')\n", " axs[1].legend(['Train', 'Validation'], loc='upper left')\n", " \n", + " fig.suptitle('{}-{}'.format(model_name, dataset_kind), fontsize=16)\n", " fig.tight_layout()\n", " plt.show()" ] @@ -169,20 +170,12 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ - "from keras.models import Sequential, Model\n", - "from keras.layers import Dense, Dropout, Activation, Flatten, Input, Concatenate\n", - "from keras.layers import Embedding\n", - "from keras.layers import LSTM, Bidirectional\n", - "from keras.layers.convolutional import Conv1D\n", - "from keras.layers.pooling import MaxPool1D\n", - "from keras.layers import BatchNormalization\n", - "from keras import optimizers\n", - "from keras import metrics\n", - "from keras import backend as K" + "from tensorflow.keras.models import Sequential, Model\n", + "from tensorflow.keras import optimizers, metrics, layers" ] }, { @@ -194,962 +187,665 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ - "dropout_keep_prob = 0.5\n", - "embedding_size = 300\n", - "batch_size = 50\n", - "lr = 1e-4\n", - "dev_size = 0.2" + "import os\n", + "try:\n", + " os.mkdir('word_saved_models')\n", + "except FileExistsError:\n", + " pass\n", + "\n", + "dropout_keep_prob=0.5\n", + "embedding_size=300\n", + "\n", + "token_dataset = (\"Token\", (x_token_train, y_token_train), (x_token_test, y_token_test))\n", + "morph_dataset = (\"Morph\", (x_morph_train, y_morph_train), (x_morph_test, y_morph_test))\n", + "\n", + "def run_experiment(model, dataset, num_epochs,\n", + " optimizer=optimizers.Adam(lr=1e-4),\n", + " batch_size=50,\n", + " dev_size=0.2):\n", + " [dataset_kind, (x_train, y_train), (x_test, y_test)] = dataset\n", + " \n", + " model.compile(loss='categorical_crossentropy', optimizer=optimizer, metrics=['accuracy'])\n", + " \n", + " # Train the model\n", + " history = model.fit(x_train, y_train,\n", + " batch_size=batch_size,\n", + " epochs=num_epochs,\n", + " verbose=1,\n", + " validation_split=dev_size)\n", + "\n", + " # Plot training accuracy and loss\n", + " plot_loss_and_accuracy(history, model.name, dataset_kind)\n", + "\n", + " # Evaluate the model\n", + " [_, accuracy, *_] = model.evaluate(x_test, y_test, batch_size=batch_size, verbose=1)\n", + " print()\n", + " print('Accuracy: {:.4f}'.format(accuracy))\n", + "\n", + " # Save the model\n", + " model.save('word_saved_models/{}-{}-{:.3f}.h5'.format(model.name, dataset_kind, accuracy * 100))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Linear - Token" + "## Linear" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "def construct_linear():\n", + " return Sequential([\n", + " layers.Input(shape=(max_document_length,)),\n", + " layers.Dense(100),\n", + " layers.Dropout(dropout_keep_prob),\n", + " layers.Dense(3, activation='softmax')\n", + " ], name=\"Linear\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Linear - Token" + ] + }, + { + "cell_type": "code", + "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Train on 8195 samples, validate on 2049 samples\n", "Epoch 1/10\n", - "8195/8195 [==============================] - 1s 133us/step - loss: 4.6573 - acc: 0.5634 - val_loss: 3.4261 - val_acc: 0.6837\n", + "164/164 [==============================] - 0s 3ms/step - loss: 7.2598 - accuracy: 0.5463 - val_loss: 4.3958 - val_accuracy: 0.6628\n", "Epoch 2/10\n", - "8195/8195 [==============================] - 1s 90us/step - loss: 3.9497 - acc: 0.6367 - val_loss: 3.3253 - val_acc: 0.6886\n", + "164/164 [==============================] - 0s 2ms/step - loss: 6.0476 - accuracy: 0.5980 - val_loss: 3.9234 - val_accuracy: 0.6759\n", "Epoch 3/10\n", - "8195/8195 [==============================] - 1s 96us/step - loss: 3.7765 - acc: 0.6476 - val_loss: 3.1227 - val_acc: 0.6950\n", + "164/164 [==============================] - 0s 2ms/step - loss: 5.4845 - accuracy: 0.6050 - val_loss: 3.4190 - val_accuracy: 0.6769\n", "Epoch 4/10\n", - "8195/8195 [==============================] - 1s 81us/step - loss: 3.7338 - acc: 0.6401 - val_loss: 3.2283 - val_acc: 0.7013\n", + "164/164 [==============================] - 0s 2ms/step - loss: 4.9600 - accuracy: 0.6060 - val_loss: 3.0746 - val_accuracy: 0.6696\n", "Epoch 5/10\n", - "8195/8195 [==============================] - 1s 87us/step - loss: 3.4944 - acc: 0.6491 - val_loss: 2.9340 - val_acc: 0.7003\n", + "164/164 [==============================] - 0s 2ms/step - loss: 4.4767 - accuracy: 0.6040 - val_loss: 2.8641 - val_accuracy: 0.6818\n", "Epoch 6/10\n", - "8195/8195 [==============================] - 1s 86us/step - loss: 3.4322 - acc: 0.6454 - val_loss: 2.6599 - val_acc: 0.7013\n", + "164/164 [==============================] - 0s 2ms/step - loss: 4.3279 - accuracy: 0.6044 - val_loss: 2.6827 - val_accuracy: 0.6857\n", "Epoch 7/10\n", - "8195/8195 [==============================] - 1s 86us/step - loss: 3.2137 - acc: 0.6420 - val_loss: 2.4780 - val_acc: 0.6920\n", + "164/164 [==============================] - 0s 2ms/step - loss: 3.9206 - accuracy: 0.6055 - val_loss: 2.3026 - val_accuracy: 0.6789\n", "Epoch 8/10\n", - "8195/8195 [==============================] - 1s 90us/step - loss: 3.1566 - acc: 0.6459 - val_loss: 2.4656 - val_acc: 0.7013\n", + "164/164 [==============================] - 0s 2ms/step - loss: 3.7205 - accuracy: 0.6098 - val_loss: 2.3426 - val_accuracy: 0.6891\n", "Epoch 9/10\n", - "8195/8195 [==============================] - 1s 108us/step - loss: 3.0975 - acc: 0.6428 - val_loss: 2.4278 - val_acc: 0.7072\n", + "164/164 [==============================] - 0s 2ms/step - loss: 3.5093 - accuracy: 0.6142 - val_loss: 2.0795 - val_accuracy: 0.6925\n", "Epoch 10/10\n", - "8195/8195 [==============================] - 1s 85us/step - loss: 2.9606 - acc: 0.6515 - val_loss: 2.2618 - val_acc: 0.7062\n" + "164/164 [==============================] - 0s 2ms/step - loss: 3.3066 - accuracy: 0.6117 - val_loss: 1.9321 - val_accuracy: 0.6867\n" ] }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ - "2560/2560 [==============================] - 0s 28us/step\n", + "52/52 [==============================] - 0s 2ms/step - loss: 1.8047 - accuracy: 0.6871\n", "\n", - "Accurancy: 0.6938\n" + "Accuracy: 0.6871\n" ] } ], "source": [ - "num_epochs = 10\n", - "\n", - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Dense(100)(text_input)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_token_train, y_token_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_token_test, y_token_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.4f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('char_saved_models/Linear-Token-{:.3f}.h5'.format((scores[1] * 100)))" + "run_experiment(construct_linear(), token_dataset, num_epochs=10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Linear - Morph" + "### Linear - Morph" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Train on 8195 samples, validate on 2049 samples\n", "Epoch 1/10\n", - "8195/8195 [==============================] - 1s 118us/step - loss: 4.3945 - acc: 0.5639 - val_loss: 3.2610 - val_acc: 0.6925\n", + "164/164 [==============================] - 0s 3ms/step - loss: 6.3427 - accuracy: 0.5650 - val_loss: 3.5468 - val_accuracy: 0.6828\n", "Epoch 2/10\n", - "8195/8195 [==============================] - 0s 60us/step - loss: 3.8549 - acc: 0.6339 - val_loss: 3.2650 - val_acc: 0.6974\n", + "164/164 [==============================] - 0s 2ms/step - loss: 4.6179 - accuracy: 0.5989 - val_loss: 2.9943 - val_accuracy: 0.6935\n", "Epoch 3/10\n", - "8195/8195 [==============================] - 1s 69us/step - loss: 3.7139 - acc: 0.6430 - val_loss: 3.0271 - val_acc: 0.6959\n", + "164/164 [==============================] - 0s 2ms/step - loss: 4.1173 - accuracy: 0.5989 - val_loss: 2.4201 - val_accuracy: 0.6901\n", "Epoch 4/10\n", - "8195/8195 [==============================] - 0s 57us/step - loss: 3.5929 - acc: 0.6361 - val_loss: 2.9381 - val_acc: 0.6989\n", + "164/164 [==============================] - 0s 2ms/step - loss: 3.6135 - accuracy: 0.6082 - val_loss: 2.3026 - val_accuracy: 0.6896\n", "Epoch 5/10\n", - "8195/8195 [==============================] - 1s 66us/step - loss: 3.4279 - acc: 0.6482 - val_loss: 2.8578 - val_acc: 0.6950\n", + "164/164 [==============================] - 0s 2ms/step - loss: 3.3664 - accuracy: 0.6052 - val_loss: 2.1194 - val_accuracy: 0.6920\n", "Epoch 6/10\n", - "8195/8195 [==============================] - 0s 56us/step - loss: 3.3378 - acc: 0.6392 - val_loss: 2.7722 - val_acc: 0.6959\n", + "164/164 [==============================] - 0s 2ms/step - loss: 3.0516 - accuracy: 0.6066 - val_loss: 1.9442 - val_accuracy: 0.6969\n", "Epoch 7/10\n", - "8195/8195 [==============================] - 0s 54us/step - loss: 3.2074 - acc: 0.6430 - val_loss: 2.5296 - val_acc: 0.6901\n", + "164/164 [==============================] - 0s 2ms/step - loss: 2.8247 - accuracy: 0.6132 - val_loss: 1.8321 - val_accuracy: 0.6935\n", "Epoch 8/10\n", - "8195/8195 [==============================] - 0s 57us/step - loss: 3.0877 - acc: 0.6473 - val_loss: 2.5663 - val_acc: 0.6959\n", + "164/164 [==============================] - 0s 2ms/step - loss: 2.7186 - accuracy: 0.6157 - val_loss: 1.8127 - val_accuracy: 0.6906\n", "Epoch 9/10\n", - "8195/8195 [==============================] - 0s 54us/step - loss: 3.0295 - acc: 0.6487 - val_loss: 2.3091 - val_acc: 0.6964\n", + "164/164 [==============================] - 0s 2ms/step - loss: 2.5637 - accuracy: 0.6144 - val_loss: 1.6044 - val_accuracy: 0.6955\n", "Epoch 10/10\n", - "8195/8195 [==============================] - 0s 54us/step - loss: 2.9823 - acc: 0.6427 - val_loss: 2.1973 - val_acc: 0.7023\n" + "164/164 [==============================] - 0s 2ms/step - loss: 2.4661 - accuracy: 0.6067 - val_loss: 1.5342 - val_accuracy: 0.6881\n" ] }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ - "2560/2560 [==============================] - 0s 20us/step\n", + "52/52 [==============================] - 0s 2ms/step - loss: 1.4126 - accuracy: 0.7000\n", "\n", - "Accurancy: 0.6871\n" + "Accuracy: 0.7000\n" ] } ], "source": [ - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Dense(100)(text_input)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_morph_train, y_morph_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_morph_test, y_morph_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.4f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('char_saved_models/Linear-Morph-{:.3f}.h5'.format((scores[1] * 100)))" + "run_experiment(construct_linear(), morph_dataset, num_epochs=10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## CNN - Token" + "### CNN" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "def construct_cnn():\n", + " text_input = layers.Input(shape=(max_document_length,))\n", + " x = layers.Embedding(vocabulary_size, embedding_size)(text_input)\n", + " convs = [layers.MaxPool1D()(layers.Conv1D(128, fsz, padding='valid', activation='relu')(x))\n", + " for fsz in [10, 30]]\n", + " x = layers.Concatenate(axis=1)(convs)\n", + " x = layers.Flatten()(x)\n", + " x = layers.Dense(128, activation='relu')(x)\n", + " x = layers.Dropout(dropout_keep_prob)(x)\n", + " preds = layers.Dense(3, activation='softmax')(x)\n", + "\n", + " return Model(text_input, preds, name=\"CNN\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### CNN - Token" + ] + }, + { + "cell_type": "code", + "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Train on 8195 samples, validate on 2049 samples\n", "Epoch 1/5\n", - "8195/8195 [==============================] - 963s 118ms/step - loss: 0.6787 - acc: 0.7087 - val_loss: 0.6599 - val_acc: 0.7091\n", + "164/164 [==============================] - 7s 42ms/step - loss: 0.6623 - accuracy: 0.7158 - val_loss: 0.5846 - val_accuracy: 0.7428\n", "Epoch 2/5\n", - "8195/8195 [==============================] - 899s 110ms/step - loss: 0.6171 - acc: 0.7451 - val_loss: 0.5897 - val_acc: 0.7438\n", + "164/164 [==============================] - 7s 40ms/step - loss: 0.5221 - accuracy: 0.7836 - val_loss: 0.5109 - val_accuracy: 0.7853\n", "Epoch 3/5\n", - "8195/8195 [==============================] - 1610s 196ms/step - loss: 0.5314 - acc: 0.7863 - val_loss: 0.5533 - val_acc: 0.7589\n", + "164/164 [==============================] - 7s 40ms/step - loss: 0.4116 - accuracy: 0.8408 - val_loss: 0.4494 - val_accuracy: 0.8224\n", "Epoch 4/5\n", - "8195/8195 [==============================] - 1429s 174ms/step - loss: 0.4513 - acc: 0.8253 - val_loss: 0.5300 - val_acc: 0.7823\n", + "164/164 [==============================] - 7s 40ms/step - loss: 0.2950 - accuracy: 0.8986 - val_loss: 0.4103 - val_accuracy: 0.8326\n", "Epoch 5/5\n", - "8195/8195 [==============================] - 968s 118ms/step - loss: 0.3758 - acc: 0.8630 - val_loss: 0.4583 - val_acc: 0.8199\n" + "164/164 [==============================] - 7s 41ms/step - loss: 0.2185 - accuracy: 0.9304 - val_loss: 0.3993 - val_accuracy: 0.8414\n" ] }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ - "2560/2560 [==============================] - 80s 31ms/step\n", + "52/52 [==============================] - 1s 11ms/step - loss: 0.3943 - accuracy: 0.8570\n", "\n", - "Accurancy: 0.824\n" + "Accuracy: 0.8570\n" ] } ], "source": [ - "num_epochs = 5\n", - "\n", - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "convs = []\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Embedding(vocabulary_size, embedding_size)(text_input)\n", - "for fsz in [10, 30]:\n", - " conv = Conv1D(128, fsz, padding='valid', activation='relu')(x)\n", - " pool = MaxPool1D()(conv)\n", - " convs.append(pool)\n", - "x = Concatenate(axis=1)(convs)\n", - "x = Flatten()(x)\n", - "x = Dense(128, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_token_train, y_token_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_token_test, y_token_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.3f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('char_saved_models/CNN-Token-{:.3f}.h5'.format((scores[1] * 100)))\n" + "run_experiment(construct_cnn(), token_dataset, num_epochs=5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## CNN - Morph" + "### CNN - Morph" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Train on 8195 samples, validate on 2049 samples\n", "Epoch 1/5\n", - "8195/8195 [==============================] - 879s 107ms/step - loss: 0.6855 - acc: 0.7013 - val_loss: 0.6589 - val_acc: 0.7096\n", + "164/164 [==============================] - 7s 41ms/step - loss: 0.6701 - accuracy: 0.7086 - val_loss: 0.6002 - val_accuracy: 0.7321\n", "Epoch 2/5\n", - "8195/8195 [==============================] - 812s 99ms/step - loss: 0.6271 - acc: 0.7353 - val_loss: 0.5972 - val_acc: 0.7496\n", + "164/164 [==============================] - 7s 40ms/step - loss: 0.5379 - accuracy: 0.7684 - val_loss: 0.5134 - val_accuracy: 0.7809\n", "Epoch 3/5\n", - "8195/8195 [==============================] - 807s 98ms/step - loss: 0.5391 - acc: 0.7780 - val_loss: 0.5406 - val_acc: 0.7716\n", + "164/164 [==============================] - 7s 40ms/step - loss: 0.4375 - accuracy: 0.8246 - val_loss: 0.4641 - val_accuracy: 0.8033\n", "Epoch 4/5\n", - "8195/8195 [==============================] - 802s 98ms/step - loss: 0.4715 - acc: 0.8148 - val_loss: 0.4960 - val_acc: 0.7916\n", + "164/164 [==============================] - 7s 40ms/step - loss: 0.3377 - accuracy: 0.8754 - val_loss: 0.4193 - val_accuracy: 0.8287\n", "Epoch 5/5\n", - "8195/8195 [==============================] - 802s 98ms/step - loss: 0.4075 - acc: 0.8461 - val_loss: 0.5182 - val_acc: 0.7897\n" + "164/164 [==============================] - 7s 40ms/step - loss: 0.2464 - accuracy: 0.9218 - val_loss: 0.4021 - val_accuracy: 0.8438\n" ] }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ - "2560/2560 [==============================] - 78s 30ms/step\n", + "52/52 [==============================] - 1s 11ms/step - loss: 0.4216 - accuracy: 0.8426\n", "\n", - "Accurancy: 0.7855\n" + "Accuracy: 0.8426\n" ] } ], "source": [ - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "convs = []\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Embedding(vocabulary_size, embedding_size)(text_input)\n", - "for fsz in [10, 30]:\n", - " conv = Conv1D(128, fsz, padding='valid', activation='relu')(x)\n", - " pool = MaxPool1D()(conv)\n", - " convs.append(pool)\n", - "x = Concatenate(axis=1)(convs)\n", - "x = Flatten()(x)\n", - "x = Dense(128, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_morph_train, y_morph_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_morph_test, y_morph_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.4f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('char_saved_models/CNN-Morph-{:.3f}.h5'.format((scores[1] * 100)))" + "run_experiment(construct_cnn(), morph_dataset, num_epochs=5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## LSTM - Token" + "## LSTM" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "def construct_lstm(units=93):\n", + " return Sequential([\n", + " layers.Embedding(vocabulary_size, embedding_size, input_length=max_document_length),\n", + " layers.LSTM(units, return_sequences=True),\n", + " layers.LSTM(units),\n", + " layers.Dense(128, activation='relu'),\n", + " layers.Dropout(dropout_keep_prob),\n", + " layers.Dense(3, activation='softmax'),\n", + " ], name=\"LSTM\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### LSTM - Token" + ] + }, + { + "cell_type": "code", + "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Train on 8195 samples, validate on 2049 samples\n", "Epoch 1/7\n", - "8195/8195 [==============================] - 272s 33ms/step - loss: 0.8362 - acc: 0.6589 - val_loss: 0.7334 - val_acc: 0.6603\n", + "164/164 [==============================] - 8s 49ms/step - loss: 0.7405 - accuracy: 0.6892 - val_loss: 0.7098 - val_accuracy: 0.6994\n", "Epoch 2/7\n", - "8195/8195 [==============================] - 268s 33ms/step - loss: 0.7338 - acc: 0.6835 - val_loss: 0.7153 - val_acc: 0.7003\n", + "164/164 [==============================] - 7s 44ms/step - loss: 0.7115 - accuracy: 0.7005 - val_loss: 0.7107 - val_accuracy: 0.6994\n", "Epoch 3/7\n", - "8195/8195 [==============================] - 255s 31ms/step - loss: 0.7200 - acc: 0.6979 - val_loss: 0.7114 - val_acc: 0.6994\n", + "164/164 [==============================] - 7s 44ms/step - loss: 0.7107 - accuracy: 0.7009 - val_loss: 0.7096 - val_accuracy: 0.6994\n", "Epoch 4/7\n", - "8195/8195 [==============================] - 252s 31ms/step - loss: 0.7188 - acc: 0.6995 - val_loss: 0.7151 - val_acc: 0.6994\n", + "164/164 [==============================] - 7s 44ms/step - loss: 0.7111 - accuracy: 0.7009 - val_loss: 0.7108 - val_accuracy: 0.6999\n", "Epoch 5/7\n", - "8195/8195 [==============================] - 254s 31ms/step - loss: 0.7155 - acc: 0.7007 - val_loss: 0.7100 - val_acc: 0.6999\n", + "164/164 [==============================] - 7s 44ms/step - loss: 0.7081 - accuracy: 0.7016 - val_loss: 0.7097 - val_accuracy: 0.7013\n", "Epoch 6/7\n", - "8195/8195 [==============================] - 251s 31ms/step - loss: 0.7119 - acc: 0.7015 - val_loss: 0.7092 - val_acc: 0.6999\n", + "164/164 [==============================] - 7s 44ms/step - loss: 0.7095 - accuracy: 0.7020 - val_loss: 0.7083 - val_accuracy: 0.7013\n", "Epoch 7/7\n", - "8195/8195 [==============================] - 252s 31ms/step - loss: 0.7103 - acc: 0.7014 - val_loss: 0.7094 - val_acc: 0.7008\n" + "164/164 [==============================] - 7s 44ms/step - loss: 0.7075 - accuracy: 0.7015 - val_loss: 0.7107 - val_accuracy: 0.7008\n" ] }, { "data": { - "image/png": "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\n", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAEdCAYAAABZtfMGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOzdeXhV1bn48e+bOYEQkhCmDECZZJIpgkMVFAfAAXGoYhWordZWW22rrfa2lU6/WlHrbetwrVrUqtTrSBVQ5BasAyoqIKPMSZjJISRkHt7fH3snHI8JOUnOlOT9PM95krP2XvusHVjn3WvttfYSVcUYY4yJNFHhLoAxxhjTGAtQxhhjIpIFKGOMMRHJApQxxpiIZAHKGGNMRLIAZYwxJiJZgDIRTUTmioiKyKAmtkeJyLdE5CMR8YhIqYhsF5GFIjLB3Uf9eO1y953nvi8XkZQTlOdEZfL785o59wUiUtCSv5cxHUlMuAtgTBvdB/wQeBCYB1QDQ4CZwETgI+A0nzyvAGvd/etV+uxTDVwBPOGTPhsoAZJPUKbWfJ4xxocFKNNuiUgicDPwF1W93WvTMuAhEYkCUNVVPvkqgcO+6T5eBq7DK0CJSDYwCXgamNtUxlZ+njHGh3XxmfasCxAH7G9so6rWteHYTwNniUg/r7TrgDzgnTYcFwARmSAib4vIMbdbcnl9l2Qz+b4lItUicqdX2g0islZEKkTksIg8ISJpPvlURH4nIj8UkZ0iUiIiK0VkRFvPxZhgsQBl2i1VPQzsBG4XkZtEJCeAh/8PsAv4plfadcA/gDY9H0xETgZWAqk4LbHZQDdgpYiMPkG+u4D/AW5Q1XvctHuAh4G3gUuAO4CpwBIRifY5xLXAhcCtwLeAHOA1EbGeFBORLEB1ECLS371KbvbLxr3R/24oyhUC1wClwCPAbhHZ47Ygmm2NNENxgtF14LR4gJNwWlZt9Suce1BTVPVFVX0JmAKUA3f77uwOBPkL8AtgpqoucNP74wSk36rqT1T1LVX9O/ANYAJwsc+hqoGLVHWRqr7o5h3o7tuhdOL60KFYgAoDEdklIlUi0sMnfY1bqfqHp2Qtq9iRwL2vMxSYBtyP0+qZA3wgIrPbePingZNE5BScVs4qVd3qu5MbQGK8Xr4tF19nAa+rapHXeRQDi3DucXmLARbiBOJzVfUNr23n4dThZ70/H/gQKHY/x9syVa32ev+5+zOQLc8Wi+T64FWWLm537OJwl6UzsQAVPjuBWfVvRGQUkBi+4rRfqlqpqktV9XZVPQMYjnNf6oE2Hncb8AHwbeBqmm49/QqndVL/Wt7ModOAfY2k78fp9vPWDadb7n2cEYneero/t/l8frWbL91nf4/P+/qRhAnNlDcUIr0+XIHz9zpfRPqE8oPby8ViMFiACp9ncK7K683B5wtQRFJE5GkROSQiu0XkF/Uj00QkWkTuc2+K78D5EvPN+4SI7HO7vX7nx5X9CYlIXxFZJM58o20icoPXtgkislpEikXkgIg84KYniMg/RKRQRIpE5GMR6dWWcjRHVb8A/gmki0jP5vZvxtPADTjDyv/ZxD6PAad4vb7bzDE9QO9G0nvz1SDiwfm3PRt43ufLqtD9eb7P59e/5jVTjkgS6fVhDvAosI4v35dERL4uIu+7/7/zRWSum54oIve7ZT0qIu+6aZPFZ36b24o81/19noi86NabYmCuW78+cD9jn4j8VUTivPKPEJFlbt08ICI/F5HeIlImIule+413/36xLTj3sLEAFT6rgG4iMsytKFfh3PPw9hcgBfgaTtfPbJyb2+B8aV4EjAVyca7wvD0F1ACD3H3OB77TxjI/DxQAfd3P+38iMsXd9t/Af6tqN5z7Gi+46XPcc8jGuaK/CedeS5uJSOwJgt1J7uccbePH/BOn6+0eVfUNHgCo6l5VXe312tLMMVcCF4pIw1wq9/eL3W2+x1+B04U5DVjoFaSWAXVAjs/n1792tvBcwyli64M4g28mA8+6r9k+25a4ZcsAxgBr3M33AeOB03FazT/F+ffyxwzgRaC7+5m1wI+AHjjz7KYA33fLkIwzSGYpTt0cBCxX1f3ACpx7kvWuBRb6dPVGrE7bdIwQ9VeNK4HNwJ76DV6VdKyqlgAlInI/x+fmfAN4UFXz3f3/gFOJcL+0pwHdVbUcKBWRPwE34owCazFx5gB9HecmewWwRkQed8uzHKdbaZCI9HBH19XP+anGCUyDVHUd8ElrPh+YKiK+w8kF+IeIvAAsxgme6TjdcdOAe1W1TRNiVfUIzqTfQPotzpfpchH5I86AjJ8BScBvmijHf0RkKs6X4T9F5GpV3e7m/6uIDMX5f1SBczFwHvC4qv47wGUPpkitD7OBdaq6UUSKgHtFZKyqfobTmnpbVZ939y0ECt2W3fXAqapafx7vu+Xx52/xgaq+6v5ezpfrzS4R+R+cIP0gzv+l/ap6v7u9Auc+JDiB+YfAI+7fcBbOaM92wQJUeD2DM6dmAF+9v9EDZ47Pbq+03UCm+3tfIN9nW71+QCywz6syRPns31J9AY/75eD9mbnu79/G+XLdLCI7gV+r6us455iNc+XfHeeq+L9acQX3l0bSNuGMbDsPmI9zT6YC2IDTzfa3Fn5GSKjqOhGZDPwe5wtEcAL6JFVde4J874nIBThXyv8rIt9Q1Z+LyCacCcs34wS7fJyLhq8M6IhwkVofZuP+X1LVvSKyEqdn4DOc/9vbG8nTA+feXmPb/PGlsonIEJx7qrk4FzIxHA9aTZUB4DXgURH5Gs4TVo6qqu+9zMilqvYK8QtnpNm57u8rcEZcdcH5T6dAfyAaqAKGe+W7EVjh/v5v4Cavbee5eWOAPjhXXTFNfP5c4N0mtvWvP45PejZON0OyV9r/Axb47BeF071SAXRp5NgbgW+H+9/AXpHzivD6cLp7HA/OIJb9ONMaDrjHvgt4pZF8Ue5njm5k2yk4F3v176PdY9b/DeYB//DJsxynyzDZfX9bfZlxWkWfneDv+z/AL3G6Cn8R7n/vlrzsHlT4fRs4R1VLvRNVtRbnPs7vRSRZnCca/Jjj/fIvAD8UkSwRSQXu9Mq7D3gLuF9EuokzDHqgiPgOYT6ReHeAQ4KIJOB0t7wP/MFNO9kt+7MAInKtiGSo8/SG+uHTtSJytoiMcrsXinG6/GpbUA7TuURafZiDc69vOM79pTHASJxWzDSc///nisg3xBnmny4iY9x68CTwgDiDi6JF5DQRiQe+ABJE5EJ3sMIvgPhmypGMU3+OichJwPe8tr0O9BaR20Qk3v37TPTaXv9orkv46n29iGYBKsxUdbuqrm5i8w9wrqx2AO8Cz+H8pweny+FNnIeQforz7Dhvs3G6RDYCR3BuuLZkeOwxnCvA+tc5OFdq/YG9OA9AvVtVl7n7TwU2iMgxnAETV6tzr6q3+9nFOF1yK2lnlcSETiTVB/fC7Bs4z3rc7/XaidMdOUdV84DpwE9wWllrgPqngdyOM9fsY3fbH4EoVT2KM8DhcZwLv1Kc+6cncjvOXLgS91wbRpSq0+1+Hs4gm/04Xbtne21/D2dwxqeququZz4ko4jYBjTHGdFAi8n/Ac6r6eLjL0hIWoIwxpgMT50koy4Bs/fIgp4hnXXzGGNNBichTOHOkbmtvwQmsBWWMMSZCWQvKGGNMRGpXE3V79Oih/fv3D3cxjAHgk08+OayqGeEuR2tYXTKRpKm61K4CVP/+/Vm9uqkRqMaElojsbn6vyGR1yUSSpuqSdfEZY4yJSBagjDHGRCQLUMYYYyJSu7oH1Zjq6moKCgqoqKgId1E6jISEBLKysoiNbRdrmpkAsboUWFaP2q7dB6iCggKSk5Pp37+/v+usmBNQVQoLCykoKGDAgAHhLo4JIatLgWP1KDDafRdfRUUF6enpVqECRERIT0+3q+hOyOpS4Fg9Cox2H6DA7xUqjZ/s7xkcIjJVRLaIyDYRubOR7XeIyBr3tV5EakUk7UR5RWS+iGwWkXUi8oq7KGRbytiW7MaL/S3brkMEKGMinbse1kM4awgNB2aJyHDvfVR1vqqOUdUxOAvhrVRVTzN5lwEjVfVknHWG7grNGRkTfO3+HhRASUU1B4sryUlPIjY6tDG3sLCQKVOmALB//36io6PJyHAmRH/00UfExcU1mXf16tU8/fTT/PnPfw5JWU1YTQC2qeoOABFZCMzAWZ+oMbOA55vLq6pveeVZhbOacbtj9Si0DpVU8vEuDx/uKORgSSWTh2Zw3vDepHVp+u8cDn4FKBGZirMIXTTwuKre47P9DuCbXsccBmSoqsfdHg2sBvao6kVuWhrOolv9cZZ8/oaqHmnNSShQWlVDVU1dyANUeno6a9asAWDevHl07dqV22+/vWF7TU0NMTGN/5lzc3PJzc0NSTlN2GUC+V7vC4CJje0oIkk4C0De0sK81+O1kF0jx70RZ5l0cnJy/C13SFg9Cq59R8v5cIeHD3d6+GhnIdsPOQsWJ8ZG0z0pliXr9/PzV9YzcUAa00b25oIRvenZLSHMpfYjQHl1L5yHUzE+FpFFqtpw5aeq84H57v4XAz+qD06uW3FWU+3mlXYnsFxV73H71O8Eftaak4hzg1JVbR1dWnOAAJs7dy5paWl89tlnjBs3jquuuorbbruN8vJyEhMT+fvf/87QoUNZsWIF9913H6+//jrz5s0jLy+PHTt2kJeXx2233cYPf/jDcJ+KCZzGbkg0tZTAxcB7XnWo2bwi8l9ADc4S5I1S1ceAxwByc3MjfhkDq0eto6rke8pZtbOQj3Z6+HBnIfmecgCS42M4ZUAaV+ZmM3FAGiMzU4iJEjbsLWbJ+n0sWb+fX762gV8t2kBuv1SmjuzD1JG9yeyeGJZz8acF1ZauCUQkC7gQ+D3wY6/9ZgCT3d+fAlbQxgB1z5LN7Dpc2ppDNGl4327cffGIFuf74osvePvtt4mOjqa4uJh33nmHmJgY3n77bX7+85/z0ksvfSXP5s2b+fe//01JSQlDhw7le9/7ns2h6DgKgGyv91nA3ib2vRqvOtRcXhGZA1wETNEArZ/z639tYOPe4kAcqkFr6pLVo+apKtsPHePDnR4+3OHho50e9hc7owdTk2KZMCCNuacPYOKANIb16UZ01Fevd0ZmpjAyM4Xbzx/K1oPHWPL5fpas38dvX9/Ib1/fyOjs7kwb2ZtpI3vTLz10zQB/AlRbuiYAHgR+CiT77N5LVfcBqOo+EenZxDGb7ZaIihJio6Ooq4uci8Irr7yS6OhoAI4ePcqcOXPYunUrIkJ1dXWjeS688ELi4+OJj4+nZ8+eHDhwgKysrFAW2wTPx8BgERkA7MEJQtf47iQiKcAk4Fp/8rrd7z8DJqlqWVDPIAysHn1VXZ2yeX8JH+0sdLvsPBSWVgGQkRzPxAFpTPxaOhMHpDEooytRjQSkpogIQ3olM6RXMreeO5idh0tZsn4fS9fv554lm7lnyWaG9enG9JG9mTaqN4N6+n6tB5Y/AarVXRMichFwUFU/EZHJrSmgv90ScTFR3DRpIAN7dm3NxwRcly7HrzJ++ctfcvbZZ/PKK6+wa9cuJk+e3Gie+Pj4ht+jo6OpqakJdjFNiKhqjYjcAryJcy/3SVXdICI3udsfdXedCbylqqXN5XU3/xWIB5a5w5pXqepNbS1va3oNgsHqEdTU1rFhbzEful12H+30UFzhnFNm90QmDc1g4oA0JgxIp396UkCHtw/o0YXvTx7E9ycPIt9Txpsb9rNk/X7uX/YF9y/7gkE9uzJtZG+mjuzN8D7dAj603p8A1ZauiTOAS0RkOpAAdBORf6jqtcABEenjtp76AAdbXvzj4qKjOFYZmf8Rjx49SmZmJgALFiwIb2FM2KjqYmCxT9qjPu8XAAv8yeumDwpoISNYZ6pHdXXKsk0HeO7DPFbv8lBaVQs4AWP6qD5MGJDGhAFpZKUmhaxM2WlJfOfMr/GdM7/G/qMVbrDax0P/3sZf/m8b/dKTmDqyN9NG9mF0VkpAgpU/AarVXROqehfuvAy3BXW7G5wAFgFzgHvcn6+1+ixwWlDVZXXU1WmLmrSh8NOf/pQ5c+bwwAMPcM4554S7OMa0S52hHtXWKUvW7+Ov/7eNzftLyEpN5LJxWUwYkMbEAWkRMbIOoHdKAnNO78+c0/tz+Fglb204wJL1+3jiPzv5n5U76JuSwAUjezN9VB/G56S2+jtZ/Lmn6raAHuR498LvfbsmRGQuMFVVr27iGJNxAlT9MPN04AUgB8gDrvQZ+fcVubm56rvI2qZNmxg2bBhFZVXkecoY0iuZhNjoZs/JnFj939U0TUQ+UdV2Ob75RHXJBI6/f9Oa2joWrd3LQ//exvZDpQzM6MIt5wzi4pP7EhPiqTNtUVRWxdubDrLk8338Z+thqmrryEiOZ+qI3tx98fAmz6WpuuTXPKi2dE14bV+BM1Kv/n0hMMWfz/dH/fynqpo6C1DGmHahqqaOVz4r4OEV29ldWMZJvZP56zVjmTayT6Oj7SJd96Q4rhifxRXjsyipqOb/Nh9k6fr9bNlf0qpA2yGeJAFOFx84c6GMMSaSVVTX8r+fFPDoiu3sKSpnVGYKj103nnOH9Yq4WxStlZwQy4wxmcwYk0lrZz90mAAVEyVEiVBVYwHKGBOZyqtqee6jPB57ZzsHiisZl9Od380cyeQhGV8dVKAKB9ZDdZCfiB6fDBlDIYgPt23tgIkOE6BEhLiYKAtQxpiIU1pZwzOrdvP4f3Zw+FgVEwek8cA3xnD6wCaWN6mrhX/9ED77R2gK2L0fDL8Ehs2AzPEQFRn3vTpMgAJnqLl18RljIkWdKn9ZvpUn3ttJUVk1Zw7uwQ/OGcyEAWknyFQLr34f1i2E026Br50d3EIWF8Cmf8GqR+H9v0C3TBh2MQy7BHJOhajw3dPvWAEqxpkLpaq2FosxJmxqaus4fKyK/UcruH/ZTqac1JNbzhnE2JzUE2esrYZXvgvrX4KzfwGT7ghNgcfPhfIi+GIpbHwNVv8dPnwUuvSEYRc5war/mRAd2pARGe24AImLiaJOlZoQPvJo8uTJvPnmm19Ke/DBB/n+97/f5P71w3unT59OUVHRV/aZN28e99133wk/99VXX2XjxuOPQ/zVr37F22+/3dLiGxMxOkJdqq6tY9/RcjbvL+FgSQXxMdG8/oOv88TcU5oPTjVV8OL1TnA699ehC071ErvD6Kth1vPw0+1wxZPQ73RYuxCeuRTuGwSv3QxfvAU1lSEpUscKUF5DzUNl1qxZLFy48EtpCxcuZNasWc3mXbx4Md27t24BVN9K9Zvf/IZzzz23VccyJhK057pUXVvH3qJytuwv4VBJJd0SYhnSK5n0rnGMzExp/gA1lfDCbNi0CC74A3z9tpaeRmDFJ8PIy+EbT8Ed2+Gqf8Cg82DjInjuSpg/CF66wekarC4PWjE6VoAKw1DzK664gtdff53KSueKYteuXezdu5fnnnuO3NxcRowYwd13391o3v79+3P48GEAfv/73zN06FDOPfdctmzZ0rDP3/72N0455RRGjx7N5ZdfTllZGe+//z6LFi3ijjvuYMyYMWzfvp25c+fy4osvArB8+XLGjh3LqFGjuP766xvK1r9/f+6++27GjRvHqFGj2Lx5czD/NMa0SHusS2PHjuOk4SNZ8u4nFB6rIiXRCUw56Un+z8esLoeF18AXS2D6fXBa4y3GsIlLcu5JXf43uGMbXPOC0+W3bRn881q4dyC8MMdp+VUeC+hHd6h7UPFv/5yv7V7jBKpAzb7uPQqm3dPk5vT0dCZMmMDSpUuZMWMGCxcu5KqrruKuu+4iLS2N2tpapkyZwrp16zj55JMbPcYnn3zCwoUL+eyzz6ipqWHcuHGMHz8egMsuu4wbbrgBgF/84hc88cQT/OAHP+CSSy7hoosu4oorvryAakVFBXPnzmX58uUMGTKE2bNn88gjj3Dbbc4VWY8ePfj00095+OGHue+++3j88ccD8VcyHc2SO2H/54E9Zgjq0kcfr+a5559nyYoPqK6uZurk0xk8/GT2FpVz2pRpXHil86S1P/5uHg/89VGuv/F7nDv1Qs69YBoXzZgJQFlVLZ7SKnbsP8J1s+fwz9cWM3DQYH5403e454E/c8P3bqG2TolK7MbTr/+bhU89zvOPP8SCvz9BfEwLBxRUlcHCWbBjJVz8Zxg/p2X5Qy0mHoZc4LxqH4Rd7zqtvk3/go2vQkwCDJzijAgcMtXpNmyDDtWCEgQRZ+RMKHl3TdR3SbzwwguMGzeOsWPHsmHDhi91Ifj6z3/+w8yZM0lKSqJbt25ccsklDdvWr1/PmWeeyahRo3j22WfZsGFDk8cB2LJlCwMGDGDIkCEAzJkzh3feeadh+2WXXQbA+PHj2bVrV2tP2ZigaGldqqmto7i8mto6Z02kF99YxtfPnU5pbTQ10Qmcde5UyqpqOVJaxepP13LxBVOYfGouL72wkHWfr+dIaRVVNbWUVtRwpLTqS+8/+3wDfbNzSOvTjyOlVUybeRX/eecdjpRWUafKmedNJ61LHNMmnc6hfQUtD06Vx+DZK2HnO3Dpw5EfnHxFx8LAs+GiP8FPtsDcxc5gi72fOQM95g+Cf1wBnz4NpYWt+ogO1YJi2j3sP3gMBAZmhG7ZjUsvvZQf//jHfPrpp5SXl5Oamsp9993Hxx9/TGpqKnPnzqWi4sST7ZoadTh37lxeffVVRo8ezYIFC1ixYsUJj9PcjO36pQg6wjIEJohO0NIJpubq0uw5c/AcPcaeonLKq2rZebiUpMJS6lSJEugaH0N0lziG93UW5kvvGk/vlARGZKZw0R23fKUujchMoXtSHNnpSYxw7xXVvx+Y0ZWkuJiG9P09utAtMZYRmSnERkdxcr8MenRPZF98bMvrUkWxE5wKPoaZj8HJVwb6TxlaUdHQ/wzndcEfYM8nsOk1557Voh9A4q/g9m0tHgXYoVpQQFgm63bt2pXJkydz/fXXM2vWLIqLi+nSpQspKSkcOHCAJUuWnDD/WWedxSuvvEJ5eTklJSX861//athWUlJCnz59qK6u5tlnj6/mnZycTElJyVeOddJJJ7Fr1y62bdsGwDPPPMOkSZMCdKbGBJdvXSr0FJGQmERJXSzvfb6dNxYvodBt6YhAWpc4BmZ0JTY6igE9unLRBVN441+LqKqsiNy6VF4Ez8yEPaudkXLtPTj5ioqC7FPg/N/BrWvhu+/AhQ+0aoh6hwxQ1bV1IV9dd9asWaxdu5arr76a0aNHM3bsWEaMGMH111/PGWecccK848aN46qrrmLMmDFcfvnlnHnmmQ3bfvvb3zJx4kTOO+88TjrppIb0q6++mvnz5zN27Fi2b9/ekJ6QkMDf//53rrzySkaNGkVUVBQ33dTm9euMCTpVpbKmlotmXsnatWuZMOUi4noNYOBJI5l86nh++eObOfW00+iZHM/wvt1IiI0mvWs8XeKPf/FFfF0q88DTl8C+tfCNp2HEpW07XqQTgT6jYeRlrcve2of4hYM/SwQcKasi35bdaDNbeqF5ttxG2zgBqY7SyhpKK2spraqh2h2BGxMldImPoUtcDF3io0mIjW6Xk++/9DctPQxPz4DDW51h20POD2/hIkiblttoTxrmQtXashvGRKKj5dUUlVVRWllLTZ0bkKKj6BoXTZd4p0UUHxPVLgNSk0oOOC2nI7vgmoUwsGMuuBhoHS9AxYR+sq4xxn97jpQBQnKC0zrqEhdDXEcLSN6K98FTF0PxHvjm/8KAs8JdonajQwQo72fv2bIbbdeeun1NYAX7OZY1dXXU1Cl9UuLJSI6M5cuDRVWhrgYWTIdjB+Hal6HfaeEuVrvS7gdJJCQkUFhY2PClastutI2qUlhYSEJCx/7yMF/lW5eCodqtl/U9HR2VqlJ4cD8J+1c7956ue9WCUyu0+xZUVlYWBQUFHDp0qCGt8FglNXVK+SH7km2NhIQEsrKywl0ME2KN1aVAK6+qpbC0CoriiQ3U014iUV0NCftXk7XmTzD7NcgcF+4StUvtPkDFxsYyYMCAL6X95l8b+efHeaz/9QUdt1/bmABrrC4F2v+s3M4fluxm3bzz6ZYQG9TPCpvDW+Gpmc4DYGe/Bn0afyyTaV6HvITJSUuk1H2eljEmcuQfKaN7UmzHDU4HN8Hfpzv3nua+YcGpjTpmgEpPAiDPUxbmkhhznIhMFZEtIrJNRO5sZPsdIrLGfa0XkVoRSTtRXhFJE5FlIrLV/dnMokPhlecpJyctKdzFCI79n8OCC0GinOfS9Roe7hK1ex0zQKVZgDKRRUSigYeAacBwYJaIfOkbTFXnq+oYVR0D3AWsVFVPM3nvBJar6mBgufs+YuV7ysjuiAFq7xpnKHlMAnxrMWQMCXeJOgS/AlRrr/xEJEFEPhKRtSKyQUR+7ZVnnojs8co3PVAnlZXqBqhCC1AmYkwAtqnqDlWtAhYCM06w/yzgeT/yzgCecn9/CojYZ+fU1ikFR8o6Xguq4BNnEm5cshOc0geGu0QdRrMBqi1XfkAlcI6qjgbGAFNF5FSvrH+qz6eqiwN0TiTERtOrW7y1oEwkyQTyvd4XuGlfISJJwFTgJT/y9lLVfQDuz55NFUBEbhSR1SKyOpgj9Zqyv7iC6lrtWAEqb5Xz+KLEVPjWG5DaP9wl6lD8aUG1+spPHfVLLMa6r5DMAs1JS7IAZSJJY8NJm6oLFwPvuRd5Lc3bJFV9TFVzVTU3IyOjpdnbrL5Ho8MEqF3vwjOXQXIv+NYS6J4T7hJ1OP4EqLZc+SEi0SKyBjgILFPVD72y3CIi60TkyaZu7rb2qi87LYl8C1AmchQA2V7vs4C9Tex7Nce795rLe0BE+gC4Pw8GpLRBUF8fs1PbcYCqLHGWNn9hthOcUrKc0Xrd+oa7ZB2SPwGqLVd+qGqt2/WXBUwQkZHupkeAgThdf/uA+xs7YGuv+nLSkthXXEFlTa3feYwJoo+BwSIyQETicILQIt+dRCQFmAS85mfeRUD9UqxzfPJFlPwjZURHCX26t7MJ9OVHYM3z8PwsuHcgvHg97P4Axl7rBKfk3uEuYYflz0Tdtlz5NVDVIhFZgUx6wfYAACAASURBVNPCWq+qB+q3icjfgNf9KbC/ctKSUIU9R8r5WghX1zWmMapaIyK3AG8C0cCTqrpBRG5ytz/q7joTeEtVS5vL626+B3hBRL4N5AERu/pdnqeMvt0T2scTJEoPw+Y3YNMi2LHCmdfULRNyr4fhl0D2RGcVWRNU/gSohqs3YA9OELrGdyevK79rvdIygGo3OCUC5wJ/dLf1qb+5i1Mp17flRHx5DzW3AGUigTsQaLFP2qM+7xcAC/zJ66YXAlMCWc5gyfNE+Ai+kv2w6V+w8TXY/R5onTPo4dTvw/AZ0Hecs1qsCZlmA1RbrvyAPsBT7kjAKOAFVa1vKd0rImNwugt3Ad8NxAnVq68Idh/KmMiQ7ynjvOG9wl2MLyvKPx6U8j8EFHoMgTN/AsMugd6jnFVhTVj49Sy+1l75qeo6YGwTx7yuBeVssYzkeOJjomwknzERoLSyhsPHqiJjkm7hdqfrbuMi2Pupk9ZrFJz9cyco9TzpxPlNyLT7h8U2RURsqLkxESL/SJiHmB/cfDwoHfjcSes7Ds6d5wQlm1wbkTpsgIL6uVDl4S6GMZ1e/RyokA0xV3WejVcflA5vAcQZ3HDBH2DYxdA9u9nDmPDq0AEqOy2JD3d6gr5KqDEdxgtzIP+jgB/2jKoaPoivodc/40NzT6e2EsoKnQe39jsDJtzgBCUbEt6udOgAlZOWxLHKGo6UVZPWJS7cxTEm8mWOh/jkgB92S14ROytKuWxwo3P8A08EMnPhpAuhS4/QfKYJuA4doPp5LbthAcoYP5zxw6Ac9q8LPmZ/XQWXzzgzKMc3HVOHHtRvy24YExkifg6UiUgdOkDVL7thc6GMCZ+6OiXfU9awkKgx/urQASoxLpqeyfG2LpQxYXToWCWVNXWRMQfKtCsdOkCBLbthTLjlNTzFPDHMJTHtjQUoY0xQ1Xex2z0o01IdPkBlpyWx92g5VTV14S6KMZ1SnqfMGfVtLSjTQh0+QDUsu1FkT5QwJhzyPGX06ZZAfIwtT2FapuMHqHQbam5MOOV7ymyAhGmVjh+gbC6UMWFlc6BMa3X4AJXR1Vl2w+ZCGRN6FdW1HCiutABlWqXDB6ioKCE7LcnmQhkTBgXuMhvWxWdao8MHKLCh5saES8McKAtQphU6TYDK95ShquEuijGdSr67Hpt18ZnW6BQBKjstiZLKGorKqsNdFGM6lTxPGYmx0fToaqsJmJbrFAHKRvIZEx71I/hswVDTGhagjDFBY3OgTFt0igCVneY8YsUClDGho6o2B8q0SacIUElxMfToGm9zoUxYichUEdkiIttE5M4m9pksImtEZIOIrPRKv1VE1rvpt3mljxGRVW6e1SIyIRTn4o/C0irKqmobLhCNaSm/AlRzFUtE7nAryBq3EtWKSJqIJIjIRyKy1q1Yv/bKkyYiy0Rkq/szNZAn5isnLdFaUCZsRCQaeAiYBgwHZonIcJ99ugMPA5eo6gjgSjd9JHADMAEYDVwkIoPdbPcCv1bVMcCv3PcRIc+eYm7aqNkA5U/FUtX5qjrGrSR3AStV1QNUAueo6mhgDDBVRE51s90JLFfVwcBy933Q9EvvYgHKhNMEYJuq7lDVKmAhMMNnn2uAl1U1D0BVD7rpw4BVqlqmqjXASmCmu02Bbu7vKcDeIJ5Di9gyG6at/GlB+VOxvM0CngdQxzE3PdZ91U9GmgE85f7+FHBpC8veItlpSewtKqe61pbdMGGRCeR7vS9w07wNAVJFZIWIfCIis9309cBZIpIuIknAdCDb3XYbMF9E8oH7cC4QGyUiN7rdgKsPHToUgFM6sfoAlZVqAcq0jj8Byp+KBYBbeaYCL3mlRYvIGuAgsExVP3Q39VLVfQDuz54tL77/ctKSqFPYa8tumPBobJy178zxGGA8cCFwAfBLERmiqpuAPwLLgKXAWqDGzfM94Eeqmg38CHiiqQKo6mOqmququRkZGW06GX/kecromRxPYpwts2Fax58A5U/Fqncx8J7bvefsqFrrdv1lARPc/nS/Beqqz4aamzAr4HirB5z64NsdVwAsVdVSVT0MvINzzwlVfUJVx6nqWYAH2OrmmQO87P7+vzg9HhHBRvCZtvInQPlTsepdjdu950tVi4AVOC0sgAMi0gfA/XmwiXwBueqrryi77aGxJjw+BgaLyAARicOpK4t89nkNOFNEYtzeiInAJgAR6en+zAEu43g92wtMcn8/h+OBK+zyPeUWoEybxPixT0PFAvbgVKxrfHcSkRScinKtV1oGUK2qRSKSCJyL01UBTuWcA9zj/nytDefRrJ7J8cTZshsmTFS1RkRuAd4EooEnVXWDiNzkbn9UVTeJyFJgHVAHPK6q691DvCQi6UA1cLOqHnHTbwD+W0RigArgxhCeVpOqaurYe7ScLAtQpg2aDVD+VCx315nAW6pa6pW9D/CUOxIwCnhBVV93t90DvCAi3wbycIfUBktUlJCdakPNTfio6mJgsU/aoz7v5wPzG8l7ZhPHfBfnvlVE2VNUjqqN4DNt408Lyt+KtQBY4JO2DhjbxDELgSn+F7XtbNkNY0LDhpibQOgUT5Kol+MuXGjLbhgTXDZJ1wRCpwpQ9ctuHC23ZTeMCaZ8TxlxMVH0TI4Pd1FMO9apApQNNTcmNPI8ZWSnJhIVZctsmNbrXAEq3QKUMaFgc6BMIHSqAJWdagHKmGBTVfIKLUCZtutUAapLfAw9usbZXChjguhoeTUllTW2UKFps04VoMAZKGEtKGOCp75+WYAybdXpApTNhTImuPI9zgOZrYvPtFWnDFB7iyps2Q1jgsRaUCZQOl2Ayk5LorZO2VdUEe6iGNMh5XnKSO8SR9d4vx5UY0yTOl2AsrlQxgRXvqfMWk8mIDpdgOpnc6GMCSqbA2UCpdMFqF7JCcRFR1mAMiYIamrr2FNUTnZaYriLYjqAThegoqKErLREmwtlTBDsO1pBbZ1aC8oERKcLUGBDzY0JlnwbwWcCqNMGqN2Fpc3vaIxpEVtmwwRSpw1QxRU1HC2zZTeMCaQ8TxkxUUKfFLsHZdquUwaobBtqbkxQ5HnKyEpNJNqW2TAB0CkDlM2FMiY4bA6UCaROGaCsBWVMcORZgDIB1CkDVNf4GNK7xFmAMiaASiqqOVJWbQMkTMB0ygAFTivK5kIZEzj2FHMTaJ02QNlcKGMCy4aYm0Dr1AFqT1E5NbbshgkREZkqIltEZJuI3NnEPpNFZI2IbBCRlV7pt4rIejf9Np88P3CPu0FE7g32eTTFJumaQPMrQDVXsUTkDrdSrXErUa2IpIlItoj8W0Q2uZXnVq8880Rkj1e+6YE8sebk1C+7cdSW3TDBJyLRwEPANGA4MEtEhvvs0x14GLhEVUcAV7rpI4EbgAnAaOAiERnsbjsbmAGc7Oa5LzRn9FV5njJSEmNJSYwNVxFMB9NsgPKnYqnqfFUdo6pjgLuAlarqAWqAn6jqMOBU4GafvH+qz6eqiwN0Tn6xkXwmxCYA21R1h6pWAQtxAou3a4CXVTUPQFUPuunDgFWqWqaqNcBKYKa77XvAPapa6ZMn5Owp5ibQ/GlB+VOxvM0CngdQ1X2q+qn7ewmwCchsW5EDI8eW3TChlQnke70v4Kt1YQiQKiIrROQTEZntpq8HzhKRdBFJAqYD2V55zhSRD0VkpYicEsRzOCFnDpQ9QcIEjj8Byp+KBYBbeaYCLzWyrT8wFvjQK/kWEVknIk+KSGoTx7xRRFaLyOpDhw75UVz/9O6WQGy0WIAyodLYoxXU530MMB64ELgA+KWIDFHVTcAfgWXAUmAtTu9EfZ5UnB6KO4AXRKTRxzgEqy4B1NUpBUfK7f6TCSh/ApQ/FavexcB7bvfe8QOIdMUJWreparGb/AgwEBgD7APub+yAqvqYquaqam5GRoYfxfVPdJSQlWoj+UzIFHC81QOQBextZJ+lqlqqqoeBd3DuOaGqT6jqOFU9C/AAW73yvKyOj4A6oEdjBQhWXQI4UFJBVW2ddfGZgPInQPlTsepdjdu9V09EYnGC07Oq+nJ9uqoeUNVaVa0D/obTlRhSNhfKhNDHwGARGSAicTh1ZZHPPq/hdNfFuL0RE3G6xRGRnu7PHOAyjtezV4Fz3G1DgDjgcJDP5SvyCm2IuQm8GD/2aahYwB6cinWN704ikgJMAq71ShPgCWCTqj7gs38fVd3nvp2J088eUjlpiawrKAr1x5pOSFVrROQW4E0gGnhSVTeIyE3u9kdVdZOILAXW4bSEHlfV+nrxkoikA9XAzap6xE1/EnhSRNYDVcAcVW2qhyNobA6UCYZmA5Q/FcvddSbwlqp6L7R0BnAd8LmIrHHTfu6O2LtXRMbgdBfuAr4biBNqiX5pXSgqq+ZoebUNjTVB5/6/X+yT9qjP+/nA/EbyntnEMavwuigMl3xPGVECfbvbIAkTOP60oPytWAuABT5p79L4PSxU9boWlDMo6m/o5nvKSMlMCXNpjGm/8jxl9O2eSGx0p537b4KgU/9vyvEKUMaY1svzlJGdat17JrA6dYCqn7Ox2wKUMW2S5ym3+08m4Dp1gEpOiCXNlt0wpk3Kqmo4fKyyYfK7MYHSqQMU2FBzY9qq4IizzIZN0jWB1ukDlC27YUzb2BwoEywWoNIS2XPElt0wprVsDpQJFgtQaUnU2LIbxrRanqeMrvExpCbZXEITWJ0+QGXbUHNj2iTfU0ZWaiJNPKPWmFbr9AEqx9aFMqZNbB0oEyydPkD1SUkkJsqW3TCmNVSV/CMWoExwdPoA5Sy7kWgByphWOHSskorqOpsDZYKi0wcosLlQxrRWfb2xOVAmGCxAYXOhjGktG2JugskCFE7lOlJWTXFFdbiLYky7kldYjghk2jIbJggsQGFPNTemtfI8ZfRKTiAhNjrcRTEdkAUobC6UMa2Vb0PMTRBZgIKGEUh2H8qYlsnzlNkACRM0FqCAbgmxpCbFWoAypgUqqms5UFJhLSgTNBagXM5IvvJwF8OYdmNPUTmqkJNuAyRMcFiActlcKGNaxoaYm2CzAOXKSUui4EgZtXUa7qIY0y7YJF0TbBagXDlpSVTXKvuOWjefMf7IKywjITaKjK7x4S6K6aAsQLnsqebGtEyep4zs1CRbZsMEjV8BSkSmisgWEdkmInc2sv0OEVnjvtaLSK2IpIlItoj8W0Q2icgGEbnVK0+aiCwTka3uz9RAnlhL2VwoY1rGltkwwdZsgBKRaOAhYBowHJglIsO991HV+ao6RlXHAHcBK1XVA9QAP1HVYcCpwM1eee8ElqvqYGC5+z5s+qQk2LIbJqiau9Bz95nsXuhtEJGVXum3uhd/G0Tktkby3S4iKiI9gnkO9VSVgiPldv/JBJU/LagJwDZV3aGqVcBCYMYJ9p8FPA+gqvtU9VP39xJgE5Dp7jcDeMr9/Sng0pYXP3BioqPITE20oeYmKPy50BOR7sDDwCWqOgK40k0fCdyAUxdHAxeJyGCvfNnAeUBeCE4FgCNl1RyrrLEWlAkqfwJUJpDv9b6A40HmS0QkCZgKvNTItv7AWOBDN6mXqu4DJ5ABPZs45o0islpEVh86dMiP4raePdXcBJE/F3rXAC+rah6Aqh5004cBq1S1TFVrgJXATK98fwJ+CoRsCKoNMTeh4E+AauwOaFMV4WLgPbd77/gBRLriBK3bVLW4JQVU1cdUNVdVczMyMlqStcVsLpQJIn8u9IYAqSKyQkQ+EZHZbvp64CwRSXcvAqcD2QAicgmwR1XXNleAQF7sNQQoW6jQBFGMH/sU4FYGVxawt4l9r8bt3qsnIrE4welZVX3Za9MBEemjqvtEpA9wkDDLSUvCU1pFSUU1yQmx4S6O6Vj8udCLAcYDU4BE4AMRWaWqm0Tkj8Ay4BiwFqhxg9V/Aef7UwBVfQx4DCA3N7dNra36C7msVHuKhAkef1pQHwODRWSAiMThBKFFvjuJSAowCXjNK02AJ4BNqvqAT5ZFwBz39zne+cLl+LIbdh/KBJw/F3oFwFJVLVXVw8A7OPecUNUnVHWcqp4FeICtwEBgALBWRHa5x/xURHoH9Uxw5kD16BpPUpw/17jGtE6zAcrt874FeBNnkMMLqrpBRG4SkZu8dp0JvKWqpV5pZwDXAed4DUOf7m67BzhPRLbi3OC9JwDn0yY2F8oEkT8Xeq8BZ4pIjNs6mohT5xCRnu7PHOAy4HlV/VxVe6pqf1XtjxPgxqnq/mCfjDPE3FpPJrj8uvxR1cXAYp+0R33eLwAW+KS9S+NdG6hqIU5XRsSwuVAmWFS1RkTqL/SigSfrL/Tc7Y+6XXlLgXVAHfC4qq53D/GSiKQD1cDNqnokDKfRIM9Txin9wzp10XQC1j73kpIYS0qiLbthgsPPC735wPxG8p7px/H7t7GIfqmurWPf0XJy0hodzGtMwNijjnzYUHNjTmxvUTl1ag+JNcFnAcpHjg01N+aEbA6UCRULUD6y05IoOFJuy24Y04Q8W2bDhIgFKB/90pOoqq3jQHFFuItiTETK85QRFx1Fr24J4S6K6eAsQPmwoebGnFi+p4ys1ESio2yZDRNcFqB8WIAy5sTyPGXWvWdCwgKUjz4pCURHCXmFFqCMaUy+p9wGSJiQsADlIyY6iszuidaCMqYRR8uqOVpebQHKhIQFqEbYXChjGpd/xEbwmdCxANUIW3bDmMYdH2Juz+EzwWcBqhE5aUkUllZxrLIm3EUxJqLYHCgTShagGpFjD401plF5njJSk2LpZuulmRCwANUIG2puTOPyPWU2QMKEjAWoRlgLypjG5dscKBNCFqAakZIUS7eEGGtBGeOltk4pOGJzoEzoWIBqQk66DTU3xtu+o+XU1KkFKBMyFqCaYHOhjPkyG8FnQs0CVBOy05Io8JRTZ8tuGAMcvydrLSgTKhagmpCT5i67UWLLbhgDTgsqOkrok2LLbJjQsADVhIah5vbQWGMAyPOUk9k9kZho+9owoWH/05pgc6GM+TKbA2VCzQJUE/p2TyRKbC6UMfVsDpQJNb8ClIhMFZEtIrJNRO5sZPsdIrLGfa0XkVoRSXO3PSkiB0VkvU+eeSKyxyvf9MCcUmDERkfR15bdMAaAY5U1FJZWWQvKhFSzAUpEooGHgGnAcGCWiAz33kdV56vqGFUdA9wFrFRVj7t5ATC1icP/qT6fqi5u7UkESz+bC2UMYCP4THj404KaAGxT1R2qWgUsBGacYP9ZwPP1b1T1HcDT9O6Ry5kLVR7uYpgOormeCHefyW6PwgYRWemVfqvbO7FBRG7zSp8vIptFZJ2IvCIi3YNRdltmw4SDPwEqE8j3el/gpn2FiCThtJZe8vPzb3Er1pMiktrEMW8UkdUisvrQoUN+HjYwstOSOHysklJbdsO0kT89EW5weRi4RFVHAFe66SOBG3AuFkcDF4nIYDfbMmCkqp4MfIHTgxFw1oIy4eBPgJJG0pqavXox8J5X996JPAIMBMYA+4D7G9tJVR9T1VxVzc3IyPDjsIHT8NDYI9bNZ9rMn56Ia4CXVTUPQFUPuunDgFWqWqaqNcBKYKa7z1tuGsAqICsYhc/zlJGcEENKoi2zYULHnwBVAGR7vc8C9jax79V4de+diKoeUNVaVa0D/oZTgSOKzYUyAeRPT8QQIFVEVojIJyIy201fD5wlIuluL8V0vlwn610PLGmqAG3pjchzh5iLNHa9akxwxPixz8fAYBEZAOzBCULX+O4kIinAJOBafz5YRPqo6j737UycShhRbC6UCSB/eiJigPHAFCAR+EBEVqnqJhH5I0533jFgLfClfmcR+S837dmmCqCqjwGPAeTm5rboGV75njKG9EpuSRZj2qzZFpTbfXAL8CawCXhBVTeIyE0icpPXrjOBt1S11Du/iDwPfAAMFZECEfm2u+leEflcRNYBZwM/CsD5BFRKYizJCTE2F8oEgj89EQXAUlUtVdXDwDs495xQ1SdUdZyqnoUz6GhrfSYRmQNcBHxTVQP+8Mi6OiXfltkwYeBPCwp3CPhin7RHfd4vwBlS7pt3VhPHvM7fQoaLiNhTzU2g+NMT8RrwVxGJAeKAicCfAESkp6oeFJEc4DLgNDd9KvAzYJKqBuU/6sGSSqpq6mySrgk5vwJUZ5aTlsQXB0rCXQzTzqlqjYjU90REA0/W90S42x91u/KWAuuAOuBxVa3v+n5JRNKBauBmVT3ipv8ViAeWufeHVqmqd89Gm9kyGyZcLEA1IyctieWbD1JXp0RF2Q1i03p+9kTMB+Y3kvfMJo45KJBlbEyeDTE3YWLP4mtGdloSVTV1HCypDHdRjAmLPE8ZIpDZ3SbpmtCyANUMG8lnOrt8Txl9UxKJi7GvCxNa9j+uGRagTGfnPMXcWk8m9CxANaN+2Q0LUKazyrN1oEyYWIBqRlxMFH1SEm0ulOmUyqtqOVhSaQHKhIUFKD/YXCjTWRUcsSHmJnwsQPnBApTprGwOlAknC1B+yElP4lBJJeVVteEuijEhZXOgTDhZgPJDti27YTqpPE8ZSXHRpHeJC3dRTCdkAcoP/WzZDdNJ5XvKbZkNEzYWoPxgc6FMZ+XMgbLuPRMeFqD80D0pluT4GAtQplNRVZsDZcLKApQfRIRsG8lnOpnDx6oor64lO9WeImHCwwKUn2youelsGkbwpVsLyoSHBSg/5aQnsfNwKTc/9ymPrNjOu1sPU1RWFe5iGRM0+TbE3ISZrQflpyvHZ5HvKWNtfhFvrNvXkJ6VmsjIvimMykphRN9ujMpMIb1rfBhLakxg1LegslItQJnwsADlp8G9knnk2vEAFJVVsX5PMev3HuXzPUfZsOcoSzfsb9i3T0oCI/qmMCozhZGZTtDq2S0hLOVWVY6UVXOwpIKDxZUcKqlkeN9uDOvTLSzlMe1HvqeMXt3iSYiNDndRTCdlAaoVuifF8fXBPfj64B4NaUfLq9m4t5j1e442BK7lmw+g6mzPSI53AlbfbozMTGFkZgp9UhJaPb+kpraOw8eqGgLPwZJK5/cSJwgdLKnkUHEFh45VUl2rX8obEyX84sJhzDm9v81vMU2yEXwm3CxA+auqFMqLICWz0c0pibGcNjCd0wamN6Qdq6xh075iPi9wgtb6PUdZseUgdW68SO8Sxwg3aI1yg1ZGcrzT0jnmE3gafq/kUEkFhaVVDcHPW1qXOHomx5ORHM+gjB707BZPz+R4+iTUMPjo+/Tcs4xN+0t49o3hbNo5jV9deTpd4u2/QaOO7mny37szyPeUcarX/2djQs2+mZpy7CDkrXJfH8D+dVBXAz2GwJCpMHQ6ZE+AqKa7P7rGx3BK/zRO6Z/WkFZeVcvGfcVs2HvUDVzFPPbODmrqGok2rugoIaOrE3T6piQwJjuFjOQEeiY7wadnN+f3Hl3jv7zqaXkRfLEUNr4G25ZDbSV06ckpwIS4FdRsfZTP7x1B9mmX02PcpZA2IAB/uA6gqgzemQ/v/wVmPQ+Dzwt3iUKusqaWfcUVZNv9JxNGFqAAVOHwVsj3CkieHc62mATIzIUzboWkdNi6DFY9Au//GRLTYPD5MHQaDDwHEpq/r5MYF834fqmM75fakFZRXcuW/SV8vucoR8uryagPPMkJ9OwWT1pSHFFRfnbFlRbCljdg4yLYsQLqqqFbJuReD8NnQPYEBIG9n7LvgxfpuuENerw7D96dBxnDnHMZOh0yx0NUJxzkuWUpLLkDivJg9DXQZ0y4SxQWe46Uo2oj+Ex4+RWgRGQq8N9ANPC4qt7js/0O4JtexxwGZKiqR0SeBC4CDqrqSK88acA/gf7ALuAbqnqkTWfjr5oq2LfmeAspfxWUFTrbktIh5zQY/y3nZ5/REOP1oMzTboaKYti+HLYsga1vwrqFEBUL/b/ufLkPnQrdc/wuTkJsNKOzuzM6u3vrzufYQdj0L6eltOtd0Fro3g9OvQmGXwp9x3012GTlkn1lLnvPu5vvPv0GmQdWMLtiI/3e+2/k3QegS08YcgGcdCEMmARxHfyLqigflt4Jm1+HjJNg7mLof0a4SxU2NgfKRALRxm5keO8gEg18AZwHFAAfA7NUdWMT+18M/EhVz3HfnwUcA572CVD3Ah5VvUdE7gRSVfVnJypLbm6url692u+Ta1BeBPkfHW8h7fkEaiqcbWkDnUCUM9H5mT4IWjJwoLYGCj5ygtWWJVC41UnvOcJtjUxrPEC0VfHe40Fp9/uAOmUfPgOGXeIEVj/Po7Kmlt+9volnVu3m7H6xPDj+ECm734Ztb0NlMcQkwsCznXMZMhW69gzsuYRTbTV88BCs/KPzftJP4dSbv3xR0gQR+URVc4NcwqBori4988EufvnaBj78+RR6hWkEquk8mqpL/rSgJgDbVHWHe6CFwAyg0QAFzAKer3+jqu+ISP9G9psBTHZ/fwpYAZwwQPlFFY7mH++qy/sQDm4EFKJinC/uU74D2RMh59S2f9lGx0C/053X+b+Fwu3Hg9W7f4L/3Oe2Rs53WldfmwxxXVr3WUd2w6ZFTvddwUdOWsYwmPQzJzD1HNay4OqKj4nmt5eOZFy/7tz18uec5+nFQ9+8n1NmdoXd77nns9h5IZCVe7wrMOOkVn1mRNj9Prz+Yzi0CYZeCNPuaVHLtyPL85QRHxNFhs3pM2HkTwvqCmCqqn7HfX8dMFFVb2lk3yScVtYgVfV4pfcHXvdpQRWpanev90dUNRUfInIjcCNATk7O+N27d3+1kEX5zpdo3geQ/yEU73HS45KdgQz1LaTM8a0PDq1R5nEGJ2xZ7PysPArR8fC1ScdbI936nvgYhdudVtLG15xuSYDeJ8PwS2DYDMgYEtAib95fzE3PfELBkXLumj6M689wh6KrwoH1x4PV3s+cDKn93W7Nac7fOTo2oOUJitLD8NYvYe1zkJID0+91yt9CLW1BNddV7u4zGXgQiAUOq+okN/1W4AZAgL+p6oNutTIt+AAADLpJREFUequ6yptrQd30zCdsO3SMt388yd/TM6bV2tKCauzyuKmodjHwnndwaitVfQx4DJxK1ehOBR87N7a7ZTqtopzTnJ89h59wlF3QJaXByVc6r9pq54p9yxL4YglsfQv4kdOiGzrdCVb13XIHNzsBadMiJyiAE1zP+43TfRfE0XYn9e7Goh98ndtfWMtvX9/Ip3lH+OPlJ9M1PgZ6j3Jek37qdDF+sdQ5n4+fgFUPQ0L344NGBp8H8clBK2er1NXBp0/B2/Og6hh8/Udw1h0huWhxu8ofwqurXEQWeXeVi0h34GGcC8I8Eenppo/ECU4TgCpgqYi8oapbgTuB5V5d5XcSgJ4ImwNlIoE/Aarg/7d371FV1VkAx7+be1FRwUpFEUwFRXykolZWmppivk3LVZpN2TQu7elY02tNzfxRWU7TuylLq6msliNajZqPGTXLsjFwUkkhQ1NUSktGhQiQPX+ca5KJXhA4h8v+rOXSe7lH9k/83X3P/u3zO0DrMo/jgL3lvPYaypT3TuNbEYlR1X0iEgN8F+Rxv9YhBaZvgbNan/61bvGFO2dO8f1h6EzYn+mciWQtgzWPwpqZENkK6jeGA1mAOGXIy2dCp1E1OraoBuHMvq4Xs9dmM2vZNjJzD/PipJ60jy6TcKJaOZ2BvW+En45A9upA8l0Gm+c7Z4odUqDLWCf51m9cZfEVFh9lw84f6BwTFfy2Uvs2wZIZzoeZNn1hxF8hOqnKYgpCMKXyicBCVd0FoKrH5kQnYL2qFgSO/RAYC8yiGkrlqsruHwo4v+2vChrG1KhgEtQGoIOItAP24CShiSe+SESaAP2BSUF+7/eB64FHA7+/F+Rxv1Y/0nuf1k9FxHlzjE6CfjPgyH7njCrrA+fN/oIpkDQSomJcDFGY2j+BbnFNuP3tjYx5bh2zrurOiG4nial+YyeJdhoFpUedMmvGu/Dlu05XnD/CWYPrMs45w6pER6Cqkr7rIAvS9rB4014OF5bQsJ6PyZe0ZUq/BJo0LKe0WHgIVj8C/5ntXBYwdjZ0u9qNdbNYYHeZxznAhSe8JhEIF5E1QCTwtKq+DmwBHhaRpsCPwHDgWH2uharuAwh82Ct3UfWEcnm5geYVFHP4pxK7UaFx3WkTlKqWiMitwHKc2vkrqpohIlMDX38x8NKxwApVzS97vIi8jfMJr5mI5AB/UtW5OIlpvoj8FtgFjK+iMdU+jZtD8rXOL4+5OKEZi2/rx83z0rjlrXTSd7Xj3mFJhPvK6UoM8x1vGhk601kXzFh0fB0tvJHTht9lLLRPgfBTd4jtyfuRhWk5LNy4hx0H8okI9zGsa0uGdGnBks25PL/6a17/9Bt+1y+eyZe0JbJBIFGpOt93+f1wOBd6T4ZBD0KEa2cFwZTK/UAvYBAQAXwqIutVdauIPAasxOmI/QIoqWgAQZXLKdNibgnKuCyo66BUdSmw9ITnXjzh8WvAayc5dkI5f+f3OBPReFzLJg14Z8pFPLJ0K3M/3sGmnDyen9jz9Bvghvmca8Pa9oVhs5xrtDIWOWtrW1KdJpaOw6DrOOdCZ79TrisoKuGDzbmkpufwafb3qMKF7c5h2oAEhp8X46yHAUO7xnDzgASeXJnFEyuzeHXdDqb2T+D6jqU0WHk3fL3KWde7eh7E9aruf6bTCaZUnoPTGJEP5IvIWqA7kBX4UDcXQEQeCbwWqrJUHmDXQBmvsJ0kTFDq+cP48+guJJ97Fvembmb4Mx/z/MRkLowPcq+2MN/xNbjhj8POtbBloXMt1+b5aP0o9sem8H7JBTy7M47/FQnnntOQ6YMSGdczttxyU6eYKF76TW++2J3Hsyu28OPKh5DV/6TIXx8Z8ijhfaa42yhzXDCl8veA50TED9TDKQE+CSAi0ar6nYicC4wDLgocU3Wl8oBjCcq2OTJuswRlKmRMj1iSWkYx7c00Js75jHuHJnFTv3YV2xXd53fOmBIu45uLHiJt9SLqZ71Pv68/4CZJZWJ4JPmJw2jW5xqkXdugWte7/5TGnPy7wJ/NuogBTD84Hv+HMdzm28P43nHllyRrSDCl8kApbxmwCSjFaUUPtHGSGliDKgZuKdNKXuWl8pyDBTRrXM82ETauO+11UF5S6Z0kTJU7XFjMH/6xiWUZuQzr2pJZV3U7vv4TxLFLNu0jNT2HDTsPIgJ92zdjfPdoLo/YSv3Md2HbUig67DQ2dB7trFm16eskt7IO7YPl9zmlw6btnbOzhIF8sv0Aj6/IJH1XHq3PieCOQYlc0aMV/ipMVKG6k8S1c9ZTUHSURTfX3a2eTM0qby5ZgjKVpqq8/FE2jy3LpE3Thrw4qReJLU7eTXm0VFm3/QCp6Tksz8ilsLiU+OaNuKpXHGOTY4lpEvHLA4oLnf0Otyx02teL86FRc+c6sK7jIO4C+HwurHoYjhbBpXc5G/r6j7edqyprMvfz+IpMMvYeIr55I34/OJER58UEv/nuKYRqguo3axXJrc/mmQnJNRyVqassQZlqsz77e259ayMFRSU8emU3Rnc/vjvG9u+OkJqew6L0PeQeKiSqgZ/RPVpxZc84erQ+K7jSYPGPTht+xiLIWg7FBc4u8yWF0H4wDP8LnBNf7uGqyvKMb3liZSZZ3x4hqWUkM1ISSenc4oxu2BiKCar4aClJDyxjWv8E7rq8owuRmbroTHaSMOaU+sQ3ZcntfbllXjq3v72R9G8OkhDdmAVpOXyxOw9fmNA/sTkPjOzMoE7RFb+FeHiEs9dg5zHOjSOzljsXBrcf7JxRnSbJiAhDu7YkpXMLFm/ay1P/+oopb6TRLa4JM1IS6Z/Y3O4sHLAvr5CjpWot5sYTLEGZKtEiqgFvT+nDzKXbeGXdDgCSWkbyxxGdGN2jFdGRVbQjdr1GTomv67gKH+oLE8b0iGXEeTEs2riHp//9FTe8uoHebc7mziEdf3E35Lrq5w4+S1DGAyxBmSoT7gvjwVGdGdU9hnBfGF1aRXnyzMTvC2N879aM6RHL/M9389yq7Ux4eT0XJzTlziEdf3EzybrGroEyXmIJylS55HNrxxt8PX8Yk/q04apecbz12S7+tmY7V77wCQM7NufOIR3pGtvE7RBr3O6DBYT7hJZ2DyjjAXXwnt7G/FKDcB839m3H2rsHcs/QJNJ35THy2Y+Z+kYa2fuPuB1ejdr1QwFxZzfEVwVdjsacKUtQxgQ0rOdn2oAEPrpnINMHd2Dd9gP8kF/kdlg1qrDoKG2svGc8wkp8xpwgqkE40wcnclO/+J/3/asr5t5wPrXp0hMT2uwMyphy1LXkdIwXG1tM3WQJyhhjjCdZgjLGGONJlqCMMcZ4kiUoY4wxnmQJyhhjjCdZgjLGGONJlqCMMcZ4kiUoY4wxnlSrblgoIvuBb8r5cjPgQA2GU11sHN5yqnG0UdXmNRlMVbG5VGuEwhjg9OM46VyqVQnqVETk89p6d9OybBzeEirjqIhQGXMojCMUxgCVH4eV+IwxxniSJShjjDGeFEoJ6iW3A6giNg5vCZVxVESojDkUxhEKY4BKjiNk1qCMMcaEllA6gzLGGBNCLEEZY4zxpJBIUCIyVEQyRWS7iNzrdjyVISKtRWS1iGwVkQwRucPtmCpLRHwislFEFrsdS2WJyFkiskBEtgV+Jhe5HVN1s3nkPXV9LtX6NSgR8QFZQAqQA2wAJqjql64GVkEiEgPEqGq6iEQCacAVtW0cACIyA+gNRKnqSLfjqQwR+TvwkarOEZF6QENVzXM7rupi88ib6vpcCoUzqAuA7aqarapFwDvAGJdjqjBV3aeq6YE/Hwa2ArHuRlVxIhIHjADmuB1LZYlIFHApMBdAVYtCOTkF2DzyGJtLoZGgYoHdZR7nUEv/Qx4jIm2BZOAzdyOplKeAu4FStwM5A/HAfuDVQHlljog0cjuoambzyHvq/FwKhQQlJ3mu1tYtRaQxkApMV9VDbsdTESIyEvhOVdPcjuUM+YGewAuqmgzkA7VyTaYCbB55iM0lRygkqBygdZnHccBel2I5IyISjjOp5qnqQrfjqYRLgNEishOnRHSZiLzpbkiVkgPkqOqxT94LcCZZKLN55C02lwiNBLUB6CAi7QILcNcA77scU4WJiODUabeq6hNux1MZqnqfqsapalucn8MqVZ3kclgVpqq5wG4R6Rh4ahBQKxfZK8DmkYfYXHL4qyWqGqSqJSJyK7Ac8AGvqGqGy2FVxiXAdcBmEflv4Ln7VXWpizHVZbcB8wJv1tnAZJfjqVY2j0w1qvRcqvVt5sYYY0JTKJT4jDHGhCBLUMYYYzzJEpQxxhhPsgRljDHGkyxBGWOM8SRLUMYYYzzJEpQxxhhP+j/tXF/fPLS6SwAAAABJRU5ErkJggg==\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ - "2560/2560 [==============================] - 20s 8ms/step\n", + "52/52 [==============================] - 1s 14ms/step - loss: 0.7073 - accuracy: 0.6938\n", "\n", - "Accurancy: 0.695\n" + "Accuracy: 0.6938\n" ] } ], "source": [ - "num_epochs = 7\n", - "lstm_units = 93\n", - "\n", - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Embedding(vocabulary_size, embedding_size)(text_input)\n", - "x = LSTM(units=lstm_units, return_sequences=True)(x)\n", - "x = LSTM(units=lstm_units)(x)\n", - "x = Dense(128, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_token_train, y_token_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_token_test, y_token_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.3f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('char_saved_models/LSTM-Token-{:.3f}.h5'.format((scores[1] * 100)))\n" + "run_experiment(construct_lstm(), token_dataset, num_epochs=7)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## LSTM - Morph" + "### LSTM - Morph" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Train on 8195 samples, validate on 2049 samples\n", "Epoch 1/7\n", - "8195/8195 [==============================] - 253s 31ms/step - loss: 0.8080 - acc: 0.6534 - val_loss: 0.7334 - val_acc: 0.6593\n", + "164/164 [==============================] - 8s 49ms/step - loss: 0.7370 - accuracy: 0.6890 - val_loss: 0.7116 - val_accuracy: 0.7033\n", "Epoch 2/7\n", - "8195/8195 [==============================] - 252s 31ms/step - loss: 0.7272 - acc: 0.6704 - val_loss: 0.7250 - val_acc: 0.6593\n", + "164/164 [==============================] - 7s 44ms/step - loss: 0.7149 - accuracy: 0.6969 - val_loss: 0.7115 - val_accuracy: 0.6994\n", "Epoch 3/7\n", - "8195/8195 [==============================] - 252s 31ms/step - loss: 0.7142 - acc: 0.7014 - val_loss: 0.7073 - val_acc: 0.7091\n", + "164/164 [==============================] - 7s 44ms/step - loss: 0.7080 - accuracy: 0.7037 - val_loss: 0.7092 - val_accuracy: 0.6999\n", "Epoch 4/7\n", - "8195/8195 [==============================] - 253s 31ms/step - loss: 0.7039 - acc: 0.7049 - val_loss: 0.7041 - val_acc: 0.7028\n", + "164/164 [==============================] - 7s 44ms/step - loss: 0.7052 - accuracy: 0.7054 - val_loss: 0.7066 - val_accuracy: 0.7028\n", "Epoch 5/7\n", - "8195/8195 [==============================] - 251s 31ms/step - loss: 0.7050 - acc: 0.7053 - val_loss: 0.7071 - val_acc: 0.7038\n", + "164/164 [==============================] - 7s 44ms/step - loss: 0.7020 - accuracy: 0.7045 - val_loss: 0.7072 - val_accuracy: 0.7033\n", "Epoch 6/7\n", - "8195/8195 [==============================] - 251s 31ms/step - loss: 0.7037 - acc: 0.7070 - val_loss: 0.7047 - val_acc: 0.7042\n", + "164/164 [==============================] - 7s 44ms/step - loss: 0.6980 - accuracy: 0.7092 - val_loss: 0.6949 - val_accuracy: 0.7111\n", "Epoch 7/7\n", - "8195/8195 [==============================] - 253s 31ms/step - loss: 0.6972 - acc: 0.7093 - val_loss: 0.6922 - val_acc: 0.7135\n" + "164/164 [==============================] - 7s 44ms/step - loss: 0.6888 - accuracy: 0.7043 - val_loss: 0.7016 - val_accuracy: 0.7042\n" ] }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ - "2560/2560 [==============================] - 20s 8ms/step\n", + "52/52 [==============================] - 1s 14ms/step - loss: 0.6994 - accuracy: 0.6973\n", "\n", - "Accurancy: 0.706\n" + "Accuracy: 0.6973\n" ] } ], "source": [ - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Embedding(vocabulary_size, embedding_size)(text_input)\n", - "x = LSTM(units=lstm_units, return_sequences=True)(x)\n", - "x = LSTM(units=lstm_units)(x)\n", - "x = Dense(128, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_morph_train, y_morph_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_morph_test, y_morph_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.3f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('char_saved_models/LSTM-Morph-{:.3f}.h5'.format((scores[1] * 100)))" + "run_experiment(construct_lstm(), morph_dataset, num_epochs=7)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## BiLSTM - Token" + "## BiLSTM" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Train on 8195 samples, validate on 2049 samples\n", - "Epoch 1/4\n", - "8195/8195 [==============================] - 646s 79ms/step - loss: 0.7930 - acc: 0.6696 - val_loss: 0.6746 - val_acc: 0.6999\n", - "Epoch 2/4\n", - "8195/8195 [==============================] - 647s 79ms/step - loss: 0.6525 - acc: 0.7174 - val_loss: 0.6345 - val_acc: 0.7125\n", - "Epoch 3/4\n", - "8195/8195 [==============================] - 647s 79ms/step - loss: 0.6233 - acc: 0.7236 - val_loss: 0.6086 - val_acc: 0.7291\n", - "Epoch 4/4\n", - "8195/8195 [==============================] - 657s 80ms/step - loss: 0.6046 - acc: 0.7407 - val_loss: 0.6129 - val_acc: 0.7365\n" - ] - }, - { - "data": { - "image/png": "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\n", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2560/2560 [==============================] - 47s 18ms/step\n", - "\n", - "Accurancy: 0.737\n" - ] - } - ], + "outputs": [], "source": [ - "num_epochs = 4\n", - "\n", - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Embedding(vocabulary_size, embedding_size)(text_input)\n", - "x = Bidirectional(LSTM(units=lstm_units, return_sequences=True))(x)\n", - "x = Bidirectional(LSTM(units=lstm_units))(x)\n", - "x = Dense(128, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_token_train, y_token_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_token_test, y_token_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.3f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('char_saved_models/BiLSTM-Token-{:.3f}.h5'.format((scores[1] * 100)))" + "def construct_bilstm(units=93):\n", + " return Sequential([\n", + " layers.Embedding(vocabulary_size, embedding_size, input_length=max_document_length),\n", + " layers.Bidirectional(layers.LSTM(units, return_sequences=True)),\n", + " layers.Bidirectional(layers.LSTM(units)),\n", + " layers.Dense(128, activation='relu'),\n", + " layers.Dropout(dropout_keep_prob),\n", + " layers.Dense(3, activation='softmax'),\n", + " ], name=\"BiLSTM\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## BiLSTM - Morph" + "### BiLSTM - Token" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Train on 8195 samples, validate on 2049 samples\n", - "Epoch 1/4\n", - "8195/8195 [==============================] - 666s 81ms/step - loss: 0.7960 - acc: 0.6636 - val_loss: 0.6901 - val_acc: 0.6789\n", - "Epoch 2/4\n", - "8195/8195 [==============================] - 662s 81ms/step - loss: 0.6700 - acc: 0.6990 - val_loss: 0.6409 - val_acc: 0.7160\n", - "Epoch 3/4\n", - "8195/8195 [==============================] - 661s 81ms/step - loss: 0.6261 - acc: 0.7254 - val_loss: 0.6234 - val_acc: 0.7189\n", - "Epoch 4/4\n", - "8195/8195 [==============================] - 660s 80ms/step - loss: 0.6072 - acc: 0.7304 - val_loss: 0.6061 - val_acc: 0.7384\n" - ] - }, - { - "data": { - "image/png": "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\n", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2560/2560 [==============================] - 46s 18ms/step\n", - "\n", - "Accurancy: 0.731\n" - ] - } - ], + "outputs": [], "source": [ - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Embedding(vocabulary_size, embedding_size)(text_input)\n", - "x = Bidirectional(LSTM(units=lstm_units, return_sequences=True))(x)\n", - "x = Bidirectional(LSTM(units=lstm_units))(x)\n", - "x = Dense(128, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_morph_train, y_morph_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_morph_test, y_morph_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.3f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('char_saved_models/BiLSTM-Morph-{:.3f}.h5'.format((scores[1] * 100)))" + "run_experiment(construct_bilstm(), token_dataset, num_epochs=4)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### BiLSTM - Morph" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "run_experiment(construct_bilstm(), morph_dataset, num_epochs=4)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## MLP - Token" + "## MLP" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, + "outputs": [], + "source": [ + "def construct_mlp():\n", + " return Sequential([\n", + " layers.Embedding(vocabulary_size, embedding_size, input_length=max_document_length),\n", + " layers.Flatten(),\n", + " layers.Dense(256, activation='relu'), layers.Dropout(dropout_keep_prob),\n", + " layers.Dense(128, activation='relu'), layers.Dropout(dropout_keep_prob),\n", + " layers.Dense(64, activation='relu'), layers.Dropout(dropout_keep_prob),\n", + " layers.Dense(3, activation='softmax')\n", + " ], name=\"MLP\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### MLP - Token" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Train on 8195 samples, validate on 2049 samples\n", "Epoch 1/6\n", - "8195/8195 [==============================] - 148s 18ms/step - loss: 0.8018 - acc: 0.6542 - val_loss: 0.6827 - val_acc: 0.7101\n", + "164/164 [==============================] - 4s 25ms/step - loss: 0.7809 - accuracy: 0.6552 - val_loss: 0.6864 - val_accuracy: 0.7121\n", "Epoch 2/6\n", - "8195/8195 [==============================] - 146s 18ms/step - loss: 0.7361 - acc: 0.6790 - val_loss: 0.6675 - val_acc: 0.7130\n", + "164/164 [==============================] - 4s 24ms/step - loss: 0.6869 - accuracy: 0.7038 - val_loss: 0.6357 - val_accuracy: 0.7262\n", "Epoch 3/6\n", - "8195/8195 [==============================] - 146s 18ms/step - loss: 0.7016 - acc: 0.6985 - val_loss: 0.6436 - val_acc: 0.7130\n", + "164/164 [==============================] - 4s 24ms/step - loss: 0.6259 - accuracy: 0.7336 - val_loss: 0.5860 - val_accuracy: 0.7443 2s - loss: 0.6581 - - ETA: 1s - loss: 0.6522 - E\n", "Epoch 4/6\n", - "8195/8195 [==============================] - 146s 18ms/step - loss: 0.6782 - acc: 0.7085 - val_loss: 0.6273 - val_acc: 0.7272\n", + "164/164 [==============================] - 4s 23ms/step - loss: 0.5585 - accuracy: 0.7741 - val_loss: 0.5490 - val_accuracy: 0.7648\n", "Epoch 5/6\n", - "8195/8195 [==============================] - 146s 18ms/step - loss: 0.6321 - acc: 0.7348 - val_loss: 0.5946 - val_acc: 0.7413\n", + "164/164 [==============================] - 4s 23ms/step - loss: 0.4856 - accuracy: 0.8118 - val_loss: 0.5224 - val_accuracy: 0.7775\n", "Epoch 6/6\n", - "8195/8195 [==============================] - 146s 18ms/step - loss: 0.5681 - acc: 0.7640 - val_loss: 0.5611 - val_acc: 0.7516\n" + "164/164 [==============================] - 4s 24ms/step - loss: 0.4202 - accuracy: 0.8411 - val_loss: 0.5075 - val_accuracy: 0.78480.4208 - - ETA: 2s - - ETA: \n" ] }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ - "2560/2560 [==============================] - 5s 2ms/step\n", + "52/52 [==============================] - 0s 6ms/step - loss: 0.5143 - accuracy: 0.7895\n", "\n", - "Accurancy: 0.746\n" + "Accuracy: 0.7895\n" ] } ], "source": [ - "num_epochs = 6\n", - "\n", - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Embedding(vocabulary_size, embedding_size)(text_input)\n", - "x = Flatten()(x)\n", - "x = Dense(256, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "x = Dense(128, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "x = Dense(64, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_token_train, y_token_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_token_test, y_token_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.3f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('char_saved_models/MLP-Token-{:.3f}.h5'.format((scores[1] * 100)))" + "run_experiment(construct_mlp(), token_dataset, num_epochs=6)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## MLP - Morph" + "### MLP - Morph" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Train on 8195 samples, validate on 2049 samples\n", "Epoch 1/6\n", - "8195/8195 [==============================] - 148s 18ms/step - loss: 0.8144 - acc: 0.6342 - val_loss: 0.6832 - val_acc: 0.7052\n", + "164/164 [==============================] - 4s 24ms/step - loss: 0.7910 - accuracy: 0.6539 - val_loss: 0.6620 - val_accuracy: 0.7150\n", "Epoch 2/6\n", - "8195/8195 [==============================] - 146s 18ms/step - loss: 0.7343 - acc: 0.6786 - val_loss: 0.6664 - val_acc: 0.7111\n", + "164/164 [==============================] - 4s 24ms/step - loss: 0.6863 - accuracy: 0.7051 - val_loss: 0.6371 - val_accuracy: 0.7257\n", "Epoch 3/6\n", - "8195/8195 [==============================] - 146s 18ms/step - loss: 0.6986 - acc: 0.6965 - val_loss: 0.6470 - val_acc: 0.7179\n", + "164/164 [==============================] - 4s 23ms/step - loss: 0.6355 - accuracy: 0.7287 - val_loss: 0.5909 - val_accuracy: 0.7472 \n", "Epoch 4/6\n", - "8195/8195 [==============================] - 145s 18ms/step - loss: 0.6575 - acc: 0.7170 - val_loss: 0.6295 - val_acc: 0.7194\n", + "164/164 [==============================] - 4s 23ms/step - loss: 0.5740 - accuracy: 0.7597 - val_loss: 0.5563 - val_accuracy: 0.7609\n", "Epoch 5/6\n", - "8195/8195 [==============================] - 146s 18ms/step - loss: 0.6160 - acc: 0.7378 - val_loss: 0.6030 - val_acc: 0.7335\n", + "164/164 [==============================] - 4s 24ms/step - loss: 0.5046 - accuracy: 0.7996 - val_loss: 0.5322 - val_accuracy: 0.7740 - accuracy: 0.\n", "Epoch 6/6\n", - "8195/8195 [==============================] - 146s 18ms/step - loss: 0.5639 - acc: 0.7667 - val_loss: 0.5822 - val_acc: 0.7452\n" + "164/164 [==============================] - 4s 23ms/step - loss: 0.4458 - accuracy: 0.8278 - val_loss: 0.5213 - val_accuracy: 0.7828\n" ] }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ - "2560/2560 [==============================] - 5s 2ms/step\n", + "52/52 [==============================] - 0s 6ms/step - loss: 0.5201 - accuracy: 0.7781\n", "\n", - "Accurancy: 0.745\n" + "Accuracy: 0.7781\n" ] } ], "source": [ - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Embedding(vocabulary_size, embedding_size)(text_input)\n", - "x = Flatten()(x)\n", - "x = Dense(256, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "x = Dense(128, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "x = Dense(64, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_morph_train, y_morph_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_morph_test, y_morph_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.3f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('char_saved_models/MLP-Morph-{:.3f}.h5'.format((scores[1] * 100)))" + "run_experiment(construct_mlp(), morph_dataset, num_epochs=6)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -1168,9 +864,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.3" + "version": "3.8.2" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/requirements.txt b/requirements.txt index 308bcc7..142d15f 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,4 +1,3 @@ scikit-learn==0.19.1 matplotlib==2.1.1 -tensorflow==1.2.1 -Keras==2.1.5 +tensorflow==2.3.0 diff --git a/word-based.ipynb b/word-based.ipynb index f32be1b..eb24bbf 100644 --- a/word-based.ipynb +++ b/word-based.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 98, + "execution_count": 1, "metadata": {}, "outputs": [ { @@ -26,12 +26,12 @@ "source": [ "import codecs\n", "import re\n", - "from keras.utils.np_utils import to_categorical\n", + "from tensorflow.keras.utils import to_categorical\n", "import numpy as np\n", "\n", "def load_data(filename):\n", - " data = list(codecs.open(filename, 'r', 'utf-8').readlines())\n", - " x, y = zip(*[d.strip().split('\\t') for d in data])\n", + " with codecs.open(filename, 'r', 'utf-8') as f:\n", + " x, y = zip(*[d.strip().split('\\t') for d in f])\n", " # Reducing any char-acter sequence of more than 3 consecutive repetitions to a respective 3-character sequence \n", " # (e.g. “!!!!!!!!”turns to “!!!”)\n", " # x = [re.sub(r'((.)\\2{3,})', r'\\2\\2\\2', i) for i in x]\n", @@ -54,7 +54,7 @@ }, { "cell_type": "code", - "execution_count": 83, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -74,7 +74,7 @@ }, { "cell_type": "code", - "execution_count": 84, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -94,7 +94,7 @@ }, { "cell_type": "code", - "execution_count": 85, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -114,7 +114,7 @@ }, { "cell_type": "code", - "execution_count": 86, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -142,7 +142,7 @@ }, { "cell_type": "code", - "execution_count": 99, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -157,7 +157,7 @@ } ], "source": [ - "from keras.preprocessing import text, sequence\n", + "from tensorflow.keras.preprocessing import text, sequence\n", "\n", "def tokenizer(x_train, x_test, vocabulary_size, char_level):\n", " tokenize = text.Tokenizer(num_words=vocabulary_size, \n", @@ -196,15 +196,15 @@ }, { "cell_type": "code", - "execution_count": 88, + "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Token OOV ratio: 0.08865112724493696 (2552 out of 28787)\n", - "Morph OOV ratio: 0.07624788494077835 (1442 out of 18912)\n" + "Token OOV ratio: 0.0 (0 out of 28787)\n", + "Morph OOV ratio: 0.0 (0 out of 18912)\n" ] } ], @@ -222,13 +222,13 @@ }, { "cell_type": "code", - "execution_count": 100, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "\n", - "def plot_loss_and_accuracy(history):\n", + "def plot_loss_and_accuracy(history, model_name, dataset_kind):\n", " \n", " fig, axs = plt.subplots(1, 2, sharex=True)\n", " \n", @@ -237,11 +237,12 @@ " axs[0].set_title('Model Loss')\n", " axs[0].legend(['Train', 'Validation'], loc='upper left')\n", " \n", - " axs[1].plot(history.history['acc'])\n", - " axs[1].plot(history.history['val_acc'])\n", + " axs[1].plot(history.history['accuracy'])\n", + " axs[1].plot(history.history['val_accuracy'])\n", " axs[1].set_title('Model Accuracy')\n", " axs[1].legend(['Train', 'Validation'], loc='upper left')\n", " \n", + " fig.suptitle('{}-{}'.format(model_name, dataset_kind), fontsize=16)\n", " fig.tight_layout()\n", " plt.show()" ] @@ -255,422 +256,372 @@ }, { "cell_type": "code", - "execution_count": 101, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ - "from keras.models import Sequential, Model\n", - "from keras.layers import Dense, Dropout, Activation, Flatten, Input, Concatenate\n", - "from keras.layers import Embedding\n", - "from keras.layers import LSTM, Bidirectional\n", - "from keras.layers.convolutional import Conv1D\n", - "from keras.layers.pooling import MaxPool1D\n", - "from keras.layers import BatchNormalization\n", - "from keras import optimizers\n", - "from keras import metrics\n", - "from keras import backend as K" + "from tensorflow.keras.models import Sequential, Model\n", + "from tensorflow.keras import layers, optimizers, metrics" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Default Parameters" + "## Experiment setup" ] }, { "cell_type": "code", - "execution_count": 102, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ + "import os\n", + "try:\n", + " os.mkdir('word_saved_models')\n", + "except FileExistsError:\n", + " pass\n", + "\n", "dropout_keep_prob = 0.5\n", "embedding_size = 300\n", - "batch_size = 50\n", - "lr = 1e-4\n", - "dev_size = 0.2" + "\n", + "token_dataset = (\"Token\", (x_token_train, y_token_train), (x_token_test, y_token_test))\n", + "morph_dataset = (\"Morph\", (x_morph_train, y_morph_train), (x_morph_test, y_morph_test))\n", + "\n", + "def run_experiment(model, dataset, num_epochs,\n", + " optimizer=optimizers.Adam(lr=1e-4),\n", + " batch_size=50,\n", + " dev_size=0.2):\n", + " [dataset_kind, (x_train, y_train), (x_test, y_test)] = dataset\n", + " \n", + " model.compile(loss='categorical_crossentropy', optimizer=optimizer, metrics=['accuracy'])\n", + " \n", + " # Train the model\n", + " history = model.fit(x_train, y_train,\n", + " batch_size=batch_size,\n", + " epochs=num_epochs,\n", + " verbose=1,\n", + " validation_split=dev_size)\n", + "\n", + " # Plot training accuracy and loss\n", + " plot_loss_and_accuracy(history, model.name, dataset_kind)\n", + "\n", + " # Evaluate the model\n", + " [_, accuracy, *_] = model.evaluate(x_test, y_test, batch_size=batch_size, verbose=1)\n", + " print()\n", + " print('Accuracy: {:.4f}'.format(accuracy))\n", + "\n", + " # Save the model\n", + " model.save('word_saved_models/{}-{}-{:.3f}.h5'.format(model.name, dataset_kind, accuracy * 100))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Linear" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "def construct_linear():\n", + " return Sequential([\n", + " layers.Input(shape=(max_document_length,)),\n", + " layers.Dense(100),\n", + " layers.Dense(3, activation='softmax')\n", + " ], name=\"Linear\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Linear - Token" + "### Linear - Token" ] }, { "cell_type": "code", - "execution_count": 103, + "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Train on 8195 samples, validate on 2049 samples\n", "Epoch 1/10\n", - "8195/8195 [==============================] - 1s 102us/step - loss: 9.4109 - acc: 0.3852 - val_loss: 8.0918 - val_acc: 0.4700\n", + "164/164 [==============================] - 1s 3ms/step - loss: 190.9581 - accuracy: 0.5140 - val_loss: 115.2639 - val_accuracy: 0.6291\n", "Epoch 2/10\n", - "8195/8195 [==============================] - 0s 56us/step - loss: 7.4096 - acc: 0.5154 - val_loss: 6.4014 - val_acc: 0.5930\n", + "164/164 [==============================] - 0s 2ms/step - loss: 92.9408 - accuracy: 0.5955 - val_loss: 65.4469 - val_accuracy: 0.6462\n", "Epoch 3/10\n", - "8195/8195 [==============================] - 0s 61us/step - loss: 6.3387 - acc: 0.5957 - val_loss: 6.0046 - val_acc: 0.6203\n", + "164/164 [==============================] - 0s 2ms/step - loss: 55.5130 - accuracy: 0.6073 - val_loss: 42.6661 - val_accuracy: 0.6589\n", "Epoch 4/10\n", - "8195/8195 [==============================] - 0s 58us/step - loss: 5.9950 - acc: 0.6190 - val_loss: 5.9001 - val_acc: 0.6276\n", + "164/164 [==============================] - 0s 2ms/step - loss: 35.3865 - accuracy: 0.6155 - val_loss: 31.2421 - val_accuracy: 0.5364\n", "Epoch 5/10\n", - "8195/8195 [==============================] - 0s 54us/step - loss: 5.6493 - acc: 0.6411 - val_loss: 5.5351 - val_acc: 0.6506\n", + "164/164 [==============================] - 0s 2ms/step - loss: 24.2313 - accuracy: 0.6214 - val_loss: 24.4337 - val_accuracy: 0.6418\n", "Epoch 6/10\n", - "8195/8195 [==============================] - 1s 77us/step - loss: 5.4348 - acc: 0.6515 - val_loss: 5.5007 - val_acc: 0.6530\n", + "164/164 [==============================] - 0s 2ms/step - loss: 18.1606 - accuracy: 0.6225 - val_loss: 18.3062 - val_accuracy: 0.6554\n", "Epoch 7/10\n", - "8195/8195 [==============================] - 0s 54us/step - loss: 5.3617 - acc: 0.6582 - val_loss: 5.3959 - val_acc: 0.6613\n", + "164/164 [==============================] - 0s 2ms/step - loss: 14.0054 - accuracy: 0.6238 - val_loss: 16.6209 - val_accuracy: 0.6506\n", "Epoch 8/10\n", - "8195/8195 [==============================] - 0s 58us/step - loss: 5.1730 - acc: 0.6681 - val_loss: 5.1089 - val_acc: 0.6750\n", + "164/164 [==============================] - 0s 2ms/step - loss: 11.7322 - accuracy: 0.6297 - val_loss: 12.9555 - val_accuracy: 0.6491\n", "Epoch 9/10\n", - "8195/8195 [==============================] - 1s 69us/step - loss: 5.0766 - acc: 0.6747 - val_loss: 5.1133 - val_acc: 0.6764\n", + "164/164 [==============================] - 0s 2ms/step - loss: 9.4500 - accuracy: 0.6272 - val_loss: 12.0551 - val_accuracy: 0.5554\n", "Epoch 10/10\n", - "8195/8195 [==============================] - 1s 68us/step - loss: 5.0019 - acc: 0.6816 - val_loss: 5.0307 - val_acc: 0.6833\n" + "164/164 [==============================] - 0s 2ms/step - loss: 8.1176 - accuracy: 0.6284 - val_loss: 10.8180 - val_accuracy: 0.5486\n" ] }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAEYCAYAAAAJeGK1AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4xLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvAOZPmwAAIABJREFUeJzs3Xd8VHXW+PHPSe89kAYECCWhQygKKojYu1hQVGxYHld93HUf3Wd/ruuuu+4+rusWd+1YF8S64KqAYi/0ZgJI6GGSEAKkt8l8f3/cSQwYyEzIZGaS83695pXM3DInIZcz93vPPV8xxqCUUkr5mgBvB6CUUkq1RROUUkopn6QJSimllE/SBKWUUsonaYJSSinlkzRBKaWU8kmaoHyAiGSKiBGRIBfWnSMiX3ZFXEr5Ij1eeg5NUG4SkV0i0iAiSUe9vt550GR6JzL3DlyluoIvHy+tYokUkSoRed/bsagjaYLqmJ3ArOYnIjICCPdeOEr5NF8/XmYC9cCZIpLalW+sHyaPTxNUx7wCXNfq+fXAy61XEJFYEXlZREpFZLeI/FJEApzLAkXkMRE5ICI7gPPa2PZ5ESkSkX0i8lsRCTyRgEUkVESeEBGb8/GEiIQ6lyWJyHsiclhEDorIF61i/R9nDJUislVEpp9IHKpH8vXj5XrgKWAjcM1R++4jIm874yoTkb+3WnaLiGx2Hhv5IjLW+boRkaxW670oIr91fj9VRAqdx1UxME9E4p3HX6mIHHJ+n9Fq+wQRmec8bg+JyLvO178TkQtarRfs/B2NduNn92maoDrmWyBGRLKdB8KVwKtHrfM3IBYYAJyGdYDe4Fx2C3A+MAbIxfoE19pLgB3Icq5zJnDzCcb8v8AkYDQwCpgA/NK57KdAIZAM9AZ+ARgRGQLcCYw3xkQDZwG7TjAO1fP47PEiIn2BqcBrzsd1rZYFAu8Bu4FMIB1Y4Fx2OfCQc/0Y4EKgzJX3BFKABKAfMBfr/+F5zud9gVrg763WfwWIAIYBvYA/O19/GZjdar1zgSJjzHoX4/B9xhh9uPHA+g/6DKz/3H8PnA0sA4IAg/WHHIg1ZJDTartbgU+d3y8Hbmu17EzntkFYCaIeCG+1fBbwifP7OcCXx4gts3k/bSzbDpzb6vlZwC7n9w8D/wayjtomC9jv/HmDvf2714f/PXz5eHEu/yWw3vl9GtAEjHE+PwkoPcbxtAS4+xj7NK2PJeBF4LfO76cCDUDYcWIaDRxyfp8KOID4NtZLAyqBGOfzN4Gfe/vfvDMfOv7Zca8AnwP9OWq4AkgCQrA+eTXbjfUJDKw/rL1HLWvWDwgGikSk+bWAo9bviLQ24klzfv9/WJ8Glzrf8xljzKPGmAIRuce5bJiILAHuNcbYTjAW1fP46vFyHfAsgDHGJiKfYQ35rQP6ALuNMfY2tuuD9aGvI0qNMXXNT0QkAuus6Gwg3vlytPMMrg9w0Bhz6OidOOP9CrhMRN4BzgHu7mBMPkmH+DrIGLMb6+LvucDbRy0+ADRiHTzN+gL7nN8XYf3htV7WbC/WJ8IkY0yc8xFjjBl2giHb2ojH5vxZKo0xPzXGDAAuAO5tvtZkjPmXMWaKc1sD/OEE41A9kC8eLyJyMjAIeEBEip3XhCYCs5zFC3uBvscoZNgLDDzGrmuwhuSapRy1/OgpJH4KDAEmGmNigFObQ3S+T4KIxB3jvV7CGua7HPjGGLPvGOv5JU1QJ+Ym4HRjTHXrF40xTcBC4BERiRaRfsC9/DDuvhC4S0QyRCQeuL/VtkXAUuBPIhIjIgEiMlBETnMjrlARCWv1CADmA78UkWSxSn4fbI5HRM4XkSyxPoJWYA1zNInIEBE53VlMUYc1Nt7k5u9IqWa+drxcjzXcmIM1rDYaGI6VXM4BVmIlx0fFKkUPE5HJzm2fA34mIuPEkuWMG2A9cLWzuONsrGtqxxONdWwdFpEE4FdH/XwfAP9wFlMEi8iprbZ9FxiLdeZ09Jmp39MEdQKMMduNMauPsfgnQDWwA/gS+BfwgnPZs1hj2BuAtfz4E+V1WEMe+cAhrLFld8pfq7D+4JsfpwO/BVZjVSptcr7vb53rDwI+cm73DfAPY8ynQCjwKNYn3GKsC7S/cCMOpVr40vEiImHAFcDfjDHFrR47sYYjr3cmzguwrsXuwSokutL5s7wBPOKMsxIrUSQ4d3+3c7vDWFWB7x4vFuAJrLL7A1gFJR8etfxarDPMLVjXhO9pXmCMqQXewho6Pfr34vfEeXFNKaWUHxKRB4HBxpjZ7a7sZ7RIQiml/JRzSPAmrLOsbkeH+JRSyg+JyC1YRRQfGGM+93Y8nqBDfEoppXySnkEppZTySR65BpWUlGQyMzM9sWulPGrNmjUHjDHJ3o7DFXqcKX/l6nHmkQSVmZnJ6tXHqiZVyneJyO721/INepwpf+XqcaZDfEoppXySJiillFI+SROUUkopn9RlN+o2NjZSWFhIXV1d+ysrl4SFhZGRkUFwcLC3Q1E+Qo+zzqfHmfd0WYIqLCwkOjqazMxMWrXFVx1kjKGsrIzCwkL69+/v7XCUj9DjrHPpceZdXTbEV1dXR2Jioh40nURESExM1E/K6gh6nHUuPc68q0uvQelB07n096naon8XnUt/n96jRRJKKaV8UpcmqNoGO9tLq6ht6No578rKyhg9ejSjR48mJSWF9PT0lucNDQ0u7eOGG25g69atHo5UKf+mx1oPVnsY8hfB4ntg4XWdsssunW4jQITqeju1jU2EhwR22fsmJiayfv16AB566CGioqL42c9+dsQ6xhiMMQQEtJ2z582b5/E4lfJ3eqz1II4m2LcWtn8M25djClcjpomGwEh2xo5niKMJAk7s//kuPYMKCQogQIS6Rt+YNbygoIDhw4dz2223MXbsWIqKipg7dy65ubkMGzaMhx9+uGXdKVOmsH79eux2O3Fxcdx///2MGjWKk046if3793vxp1DK9+mx1k0c3gtrXrTOkP7YH54/A/Ppo+w9UMFLAZdyef2D5FT/k7sdP6WpE9JLl55BiQhhwYE8tnQr+w7Vduq+c9Ji+NUFw9zeLj8/n3nz5vHUU08B8Oijj5KQkIDdbmfatGnMnDmTnJycI7YpLy/ntNNO49FHH+Xee+/lhRde4P777++Un0OpzvLrxXnk2yo6dZ8dPc5AjzW/1FANu76E7cuh4GMo2wZAVUgvVgZO5F37UD63D6PREcfkrCQuGpzM44OT6ZMQ0Slv3+Uz6oYFB9Dk8J05qAYOHMj48eNbns+fP5/nn38eu92OzWYjPz//RwdNeHg455xzDgDjxo3jiy++6NKYlfJHeqz5AYcDSjb9kJD2fAuORuyBYWwLG8n7AXP4oDaHgrp0hqXFctqoZJ4anMzYvvGEBHX+gFyXJ6jw4EBumtKfoSkxHvmB3BUZGdny/bZt2/jLX/7CypUriYuLY/bs2W3e/xASEtLyfWBgIHa7vUtiVcodHT3T8RQ91rqIwwENlVBXAfUVR30tt77WlbexrAIqi6H2IAD7I7L4MvRC3i4fzCrHECJMJKcOTuaOwclMGZREr+gwj/8oXjiDsi6a1TU2+USCaq2iooLo6GhiYmIoKipiyZIlnH322d4OS6luR4+1TrT7G/jsUSjb/kOioZ1RqoBgCIuB0BhMWAx1gdGUSip7gjN5v7Y/y+pyONiQwJg+cZyWm8x9g5MZnh5LYEDX3hPmtQRV29hETLhv9bYaO3YsOTk5DB8+nAEDBjB58mRvh6RUt6THWic4sA0+egi2vAdRKTBwGoTFQmhMS/L54WvsEcvK6oSvdxzkq4IDfFlwgEJnTUBabBinjkjm4cHJnJyVRKyX/48WYzr/elBubq45eiK1zZs3k52dDcCW4grCgwPplxjZ1ubKDa1/r+rEicgaY0yut+NwRXvHmeo8PvV7rSq1zphWz4PgcJh8D5x0B4Qc+//TmgY7q3YdshLStgPkF1nFM9FhQZw8MJEpWUlMzkqif1Jkl3TOcPU46/IzKLCuQ9U1Orzx1kop5Z8aauDbJ+HLv0BjDYybA1Pvh6heP1rV3uRg077yljOktbsP09DkICQwgHH94rnvrCFMzkpihBeG7dzhlQQVFhxIeW0jTQ7j078cpZTyOkcTbJgPyx+BShsMOQ/OeAiSB7esYoxhe2l1S0L6dnsZlfVWQcmwtBhumJzJ5KwkxmcmdGmThBPltQQFVqFEZKhXQlBKKd9X8BEsfRD250H6OJj5PPQ7uWVxSUUdC1ftZeGavew9aF1H6pMQzvmjUpmclcTJA5NIiAw51t59npeG+KzqPU1QSinVhqKNsOxB2PEJxGfCzHkw7BIQoclh+Pz7Uv61cg/Lt+ynyWGYnJXIbacN5JSsZPomds5Nsr7AK9khODCAQB9qeaSUUj6hvBCW/xY2LIDwODjr9zD+JggKpai8loWrCnl91R5s5XUkRYUw99QBXDW+T7ctOPNKgmpueVSrhRJKKWXdOPvlE/DtP8AYOPkncMpPsYfE8OnWUuav3MMnW/fjMHDKoCT+3/k5TM/u7XP3knY2r/10YSGB1DU24Yky97ZMnTqVJUuWHPHaE088wR133HHMbaKiogCw2WzMnDnzmPs9utT3aE888QQ1NTUtz88991wOHz7sauhK+Q09ztxkb4AVz8Bfx8CXj0PORfCT1eyb8Ase/3I/U/7wCTe/vJqN+8q5fepAPr9vGq/cNJFzRqR2++QE3kxQwQE4jKGhqWvOombNmsWCBQuOeG3BggXMmjWr3W3T0tJ48803O/zeRx8477//PnFxcR3en1K+So8zFzQ1Wn3uFv0E/jQYPrgPeg/DfvOnLB3yMDe8U8yUPyznb8u3MSQlmqdmj+Pr+0/nvrOGdqvrS67wWoIKb1XJ1xVmzpzJe++9R319PQC7du3CZrMxevRopk+fztixYxkxYgT//ve/f7Ttrl27GD58OAC1tbVcddVVjBw5kiuvvJLa2h+6st9+++0t0wf86le/AuCvf/0rNpuNadOmMW3aNAAyMzM5cOAAAI8//jjDhw9n+PDhPPHEEy3vl52dzS233MKwYcM488wzj3gfpXyVHmfH0GS3GrAu+gk8NhhevRS+eweyZrD/4gU81vv/OPmlMua+sob8ogrunJbF5/dN46UbJ3D28BSCA7v/2VJbXLoGJSJ3A7cAAjxrjHnihN71g/sJL97IgHpnP77O+OWnjIBzHj3m4sTERCZMmMCHH37IRRddxIIFC7jyyisJDw/nnXfeISYmhgMHDjBp0iQuvPDCY95N/c9//pOIiAg2btzIxo0bGTt2bMuyRx55hISEBJqampg+fTobN27krrvu4vHHH+eTTz4hKSnpiH2tWbOGefPmsWLFCowxTJw4kdNOO434+Hi2bdvG/PnzefbZZ7niiit46623mD179on/nlTP8cH9ULypc/epx5nrmuyw63PIexc2L7aasIZE4Rh8Djt6ncEHdcP4bHsla1YfArYzbUgvZk3oy7QhyQT10IR0tHYTlIgMx0pOE4AG4EMR+Y8xZtuJvLEgBAg4HAa66L6x5uGH5gPnhRdewBjDL37xCz7//HMCAgLYt28fJSUlpKSktLmPzz//nLvuuguAkSNHMnLkyJZlCxcu5JlnnsFut1NUVER+fv4Ry4/25Zdfcskll7R0eb700kv54osvuPDCC+nfvz+jR48GrGkGdu3a1Um/BaU8q0cfZ0122PUF5L1j9cirKcOERFGdOYPVEaey8PAQvthURWW9HZE9jEyP5e7pg7g8tw/pceEn9t7dkCtnUNnAt8aYGgAR+Qy4BPhjh9/V+QmstKya2oYmhqbGdHhX7rj44ou59957Wbt2LbW1tYwdO5YXX3yR0tJS1qxZQ3BwMJmZmW22/W+trU99O3fu5LHHHmPVqlXEx8czZ86cdvdzvAKR0NDQlu8DAwN1iE+57zhnOp7U446z5qSU7zxTqinDBEdi6z2Vj5NOZl7JQHZutK61Z8TXc/6oVKZkJXPywETi/fgm2q7gynnkd8CpIpIoIhHAuUCfo1cSkbkislpEVpeWlrr05uHBgTQ0OWhydE2hRFRUFFOnTuXGG29suWhbXl5Or169CA4O5pNPPmH37t3H3cepp57Ka6+9BsB3333Hxo0bAWv6gMjISGJjYykpKeGDDz5o2SY6OprKyso29/Xuu+9SU1NDdXU177zzDqecckpn/biqi4nI2SKyVUQKRKTNaV9F5AoRyReRPBH5V6vXm0RkvfOxqOui7nzd/jhrarTuVyr4GBbfbRU6vHIxTRsWkh8+jt9F/y/ZVU8yueAa/m/3IAalJ/Obi4bx6c+m8sXPp/H7S0dy3shUTU4uaPcMyhizWUT+ACwDqoANwI9mDTPGPAM8A1aXZVfe/IeWRw4iQ7tmzHXWrFlceumlLZVG11xzDRdccAG5ubmMHj2aoUOHHnf722+/nRtuuIGRI0cyevRoJkyYAMCoUaMYM2YMw4YN+9H0AXPnzuWcc84hNTWVTz75pOX1sWPHMmfOnJZ93HzzzYwZM0aH8/yQiAQCTwIzgEJglYgsMsbkt1pnEPAAMNkYc0hEWnf5rDXGjO7SoD3IL48zY8Bhh/oqcDRaZ0aORishVZXCP26CqmKoKWvZpDEwnDWhE/lX01iW1I3EXhPKmD5x3D7dmtRvVEasXk86AW5PtyEivwMKjTH/ONY6rk4D0GB3sKW4grS4cJKiQlHu86lpALqBjk63ISInAQ8ZY85yPn8AwBjz+1br/BH43hjzXBvbVxljotx5T51uowOMgbrDVmfw5uTjsFtfTVsVxQIBQWzec4Ds7U9jj+jFluoIPtkXyOpDEaxwDCUtOYFTspKYMiiZSQMSiA7zrXnufFGnTrchIr2MMftFpC9wKXDSiQYIEBwoBAZoyyPVLaQDe1s9LwQmHrXOYAAR+QqrNOghY8yHzmVhIrIaa3TiUWPMux6Ot+cxBir2QXUpIBAYbM0sGxQKIVHW8+bXAoOsrwFBIIL9QB6/i32Qhav3crimkUG9oph9fj9+l9Nbixs8yNVWR2+JSCLQCPyXMeZQZ7y5iDjnhtIEpfxeW/XSRw9PBAGDgKlABvCFiAw3xhwG+hpjbCIyAFguIpuMMdt/9CYic4G5AH379u3M+Ls344DDe6D2EEQmQ0w6tDMxnzGGyjo7ZdUNlFTU8/yXxZw1rDfXTspk0oCELpnYr6dzKUEZYzrlyr0x5kf/qGHBgRysbmhzmTq+rmoTpVxSyJHFQxmArY11vjXGNAI7RWQrVsJaZYyxARhjdojIp8AY4EcJypVrvXosHcXhgEM7ob4ColMhqvdxk5O9ycGhmgbKqhtosDsIDBCiwoL46n9OJyU2rAsDV1129S4sLIyysrIf/acaFhyIwxjq7do41h3GGMrKyggL0wPGR6wCBolIfxEJAa4Cjq7GexeYBiAiSVhDfjtEJF5EQlu9PhnIpwOOdZz1WA47HCywklNsBkSnHDM51TTY2Xuwhi3FlRSV1xEcGECf+HB6BTfQOz5ak5MXdFk384yMDAoLCzm6BL3B7mB/ZT2NZSFE+NFMj74gLCyMjIwMb4ehAGOMXUTuBJZgXV96wRiTJyIPA6uNMYucy84UkXygCbjPGFMmIicDT4uIA+tD46Otq//ccazjrEdyNFnXm5oaISIRyg8AB45YxRhDbWMTVfVNNNgdBAhEhAQSGRpEQ2AAxehx5k1uV/G5oq3qomOptzcx7MElzD11AD8/+/ilp0p5Wker+LzBneOsxzm0C16+GKpK4MpXIOuMIxbvPVjDayv2sHD1Xg5WNzAwOZJrJ/Xj0nEZxGgVnsd1ahWfJ4UGBTIwOYrNRRXeDkUp1R2U5MMrl4C9Dq77N/SZ0LKooq6RB97exPubihBgRk5vrjspk5MHJup1Ox/k9QQFkJ0azbc7Dno7DKWUv9u7El67HILC4IYPoHdOy6KSijquf2ElBfuruP20gcye1I80LRH3aT6SoGJ4d72NQ9UN2v5DKdUxBR/B69daVXrXvQvxmS2LtpVUMmfeKg7XNDDvhvGcMijZe3Eql/lED45sZ7NYHeZTSnXId2/Bv66ChIFw45IjktOqXQe57J9f09Dk4PVbT9Lk5Ed8K0EV/7jRo1JKHdeq5+HNmyAjF+a8B9G9WxZ9+F0R1zy3gqToUN6+/WSGp8d6MVDlLp8Y4kuODiUpKlTPoJRSrjMGvngMlv8WBp0Fl78IIT9Mif7S17t4aHEeY/rE8fz14/XygR/yiQQFVqGEJiillEscDlj6S/j2SRhxBVz8D6uPHtYkqH9YsoWnP9vBjJze/PWqMYTrPZZ+ySeG+AByUmPYVlJFY5N2lFBKHUeTHf79X1ZymnArXPJ0S3JqsDu4d+F6nv5sB7Mn9eWp2eM0OfkxHzqDiqGhycGO0mqGpER7OxyllC9qrIU3b4St78O0/4VT72tpXVRZ18htr67hq4Iy7jtrCHdMHaj3Nvk5n0pQYFXyaYJSSv1IXTnMvxp2fwXnPgYTbmlZVFJRx5x5q9hWUsljl49i5jhtTdQd+EyCGpAcSUhgAJuLKrh4TLq3w1FK+YLyfbBtCXy/FHZ8ak0yeNlzMGJmyyoF+yu5/oVVHKpp4Pk54zltsJaRdxc+k6CCAwMY1DuKfC2UUKrncjTBvjXw/RLrUbLJej2uL4y9FkZeBRnjWlZfvesgN720muDAAF6fexIjMrSMvDvxmQQF1jDfp1u1C7NSPUrtYdi+3EpIBcugpgwkEPpOgjN+DYPPhuQhP5om48Pvirl7wTrS4sJ56YYJ9E2MOMYbKH/lcwnqzTWFlFbWkxwd6u1wlFKeYAwc2AbffwjblsLur8E0QXg8ZM2AwWdB1nTr+TG8/M0ufrUoj1EZcbwwZzwJeo9Tt+RjCcoqjthcVEFytI4jK9Vt2Out4obmobtDO63Xew2DyXdbSSljPAQcvyTcGMMfl2zln59u54zs3vxtlt7j1J35VILKaVXJd6pe6FSqe9jyPrw9FxoqrS7j/U+Dk++0uj/E9XF5Nw12B/e/tZG31+3j6ol9efjCYQQF+sytnMoDfCpBxUWEkBobph0llOoudn0Fb8yxpr2Y+gBknnJEOyJX1TTYue3VtXz+fSk/nTGYO0/P0nucegCfSlBgXYfaXKRNY5Xye8XfwfxZEN8PZr8NEQkd2k15bSM3vbiKtXsO8YfLRnDl+L6dHKjyVT53fpydGs320irq7U3eDkUp1VGHdsOrl0FI5AklpwNV9cx65ls2FB7mb7PGanLqYXwwQcVgdxi2lVR5OxSlVEdUH4BXLwV7LVz7tlvXmVqzHa7liqe/YceBKp69LpfzRqZ2cqDK1/lkggKdvFApv1RfCa/NhPJCuHoh9Mru0G52Hqjm8qe+obSinldumsjUIb06OVDlD3zuGlRmYiRhwQF6HUopf2NvsKZcL9oIV71m3WjbAZuLKrj2+ZU4jGH+3Ek6yWAP5nMJKjBAGJISo2dQSvkThwPevR12fAIXPQlDzunQbtbuOcScF1YSERLEqzdPIqtXVCcHqvyJzw3xAeSkRrO5uAJjjLdDUUq1xxhY8gB89yac8RCMmd2h3Xy57QCzn1tBQmQIb9x2kiYn5ZsJKjs1hsM1jRRX1Hk7FKVUe758HFY8BZPugMn3dGgXS/KKufHFVfSJj2DhbSfRJ0H76ikfTlCghRJK+by1L8PHD1vTrp/5yI8aurri7bWF3PHaWnLSYnj91kn0ig7zQKDKH/lkghqa0tyTTwsllPJZW96HxXfDwOnWdacA9/87efmbXdy7cAMT+yfw2s0TiYvQpq/qBz6ZoKLDgumTEK5zQym/IyJni8hWESkQkfuPsc4VIpIvInki8q9Wr18vItucj+u7LuoO2P01vHkDpI2BK16GIPcSizGGJz8p4MF/5zEjpzcvzBlPZKjP1WwpL/PZv4hsreRTfkZEAoEngRlAIbBKRBYZY/JbrTMIeACYbIw5JCK9nK8nAL8CcgEDrHFue6irf452leTB/Ksgtg9c/QaEulfMYIzh0Q+28PTnO7hkTDp/nDmSYG36qtrgs38V2akx7DpQTW2DtjxSfmMCUGCM2WGMaQAWABcdtc4twJPNiccYs9/5+lnAMmPMQeeyZcDZXRS36w7vsVoYBUdYXSIiE93avMlh+MU73/H05zu4dlI//nT5KE1O6ph89i8jOzUGh4GtJXodSvmNdGBvq+eFztdaGwwMFpGvRORbETnbjW0RkbkislpEVpeWdvHs09Vl8Mol0Fhj9deLc68vXmOTg3teX8/8lXv4r2kDefiiYQQEaEdydWw+m6BytJJP+Z+2/rc9+ma+IGAQMBWYBTwnInEubosx5hljTK4xJjc5uQvnTKuv+qGF0azXrekz3FDX2MStr6xh8QYb958zlPvOGqrTZah2+WyCyogPJyo0SBOU8ieFQOvOqBmArY11/m2MaTTG7AS2YiUsV7b1DnsDLLwWitbDzHnQ7yS3Nq9psHP9Cyv5ZOt+HrlkOLedNtBDgarupmsTVH0VFHwMdeXtrhoQIAxNidYEpfzJKmCQiPQXkRDgKmDRUeu8C0wDEJEkrCG/HcAS4EwRiReReOBM52ve5XDAv++A7cvhgr/A0HPd3sUbqwtZsfMgf75iNNdM7OeBIFV31bUJqnij1YZ/9zcurT40NZotRZXa8kj5BWOMHbgTK7FsBhYaY/JE5GERudC52hKgTETygU+A+4wxZcaYg8BvsJLcKuBh52vetez/waY3YPqDMPa6Du1iaX4xA5MjuXjMjy6pKXVcXZugUkeDBELhKpdWz06NobLeTuGhWg8HplTnMMa8b4wZbIwZaIx5xPnag8aYRc7vjTHmXmNMjjFmhDFmQattXzDGZDkf87z1M7SoOQjf/B3GXAtT7u3QLsprGlmx4yAzclI6OTjVE7iUoETkv503FX4nIvNFpGO9SEIioPcw2LfapdWbWx7pDbtKeUHReuvriJkdamEE8MnW/dgdhjOH9e7EwFRP0W6CEpF04C4g1xgzHAjEGlvvmIzxsG+tNbbdjqEp0YhoJZ9SXmFbZ31NHdXhXSzLLyE5OpTRGXGdFJTqSVwmoA31AAAgAElEQVQd4gsCwkUkCIjgRKqLMnKhvgIOfN/uqhEhQWQmRmqCUsobbOshvj+Ex3do83p7E59u3c8Z2b30fifVIe0mKGPMPuAxYA9QBJQbY5YevZ7LNxBmjLe+unwdKlqbxirlDbb1Vq+9DvpmexnVDU3MyNHhPdUxrgzxxWO1a+kPpAGRIvKjGclcvoEwYSCExbqeoFJi2HOwhsq6RpfWV0p1guoyKN8DaaM7vItl+SVEhARy8sCkTgxM9SSuDPGdAew0xpQaYxqBt4GTO/6OAZCeC/vWuLR6c6HE1mI9i1KqyxQ5rz918AzK4TB8tLmEUwclExYc2ImBqZ7ElQS1B5gkIhFi9SaZjnWPR8dljIf9+VDfftLJTtOWR0p1uRMskNi0r5ySinod3lMnxJVrUCuAN4G1wCbnNs+c0Ltm5IJx/HAQHEdabBgxYUHk63UopbqObT0kZlnD8R2wNL+YwADh9KG9Ojkw1ZO4VMVnjPmVMWaoMWa4MeZaY0z9Cb1r+jjra2H790OJCNmpOjeUUl3Ktt66sb6DluWXMD4znvhInSFXdZx3msVGJFifzlxIUGBdh9paXEmTQ1seKeVxVfuhorDD1592l1XzfUmVdo9QJ8x73czTc62OEi702ctJjaG2sYndZdVdEJhSPZzN2UGigwlqWX4JAGfq9Sd1gryXoDJyoaoEyve2u2p2y9xQeh1KKY8rWg8IpI7s0OZL80sYmhJNn4SIzo1L9TjeTVDg0v1Qg3pHERggeh1Kqa5gWwdJgyA02u1ND1Y3sHrXQa3eU53Cewmq93AICoPC9u+HCgsOZECStjxSqkvY1nV4eG/5lv04DJqgVKfwXoIKDLYOAjem3tAEpZSHVRZDZVGHK/iW5hWTEhPGiPSOlacr1Zp3p3xPHwdFG6wppduRnRqDrbyOwzXtr6uU6qATKJCoa2zii20HmJHTG+ng9BxKtebdBJUxHprqoWRTu6tmp1rj4VoooZQH2daBBEDKCLc3/XLbAWobtTms6jzeT1Dg0v1QOana8kgpjytaD0mDITTK7U2X5ZcQHRrEpAGJHghM9UTeTVCx6RCd6lKCSo4OJTEyRBOUUp5iTIcLJJocho+3lHDakGRCgrz734rqPrz/l5SR61KhREvLo2JNUEp5RGWRdW9iBxLU+r2HOFDVoMN7qlN5P0Gl58KhnVB9oN1Vs1Oj+b6kCntT+9PFK6Xc1Fwg0YEKvqX5JQQFCFOHaHNY1Xm8n6Car0O5MD9UdmoMDXYHOw5oyyOlOt0JFEgsyyvhpIGJxIYHeyAw1VN5P0GljQYJdGmYL1sLJZTyHNs6SM6GEPdaFBXsr2LHgWod3lOdzvsJKiQSeue4lKAGJkcRHCjka4JSqnO1FEi4P7zX3Bz2jGxNUKpzeT9BgTXMt28tOI5/bSkkKICsXtF6L5RSna1iH9Qc6FCBxLL8Yoanx5AWF+6BwFRP5jsJqr4CDnzf7qrZqdE6xKdUZ2ue3drNBFVaWc+6vYeZka1zP6nO5xsJKt3Z2XyfazfsllbWc6DqxCb1VUq1YlsHAUHQe5hbm328uQSjzWGVh/hGgkrMgrBYtwoltugwn/IxInK2iGwVkQIRub+N5XNEpFRE1jsfN7da1tTq9UVdGzlWiXlyNgS7N0y3LL+E9LjwllZkSnWmIG8HAEBAgNU41oWOEq0r+aYMSvJ0ZEq5REQCgSeBGUAhsEpEFhlj8o9a9XVjzJ1t7KLWGNOxFuInqrlAYuh5bm1WXW/ni4IDXDOxrzaHVR7hG2dQYF2H2p8P9VXHXS0hMoTeMaF6HUr5mglAgTFmhzGmAVgAXOTlmFxzeA/UHnT7+tMX20ppsDt0eE95jG8lKOP44WLtcWSnxmipufI16cDeVs8Lna8d7TIR2Sgib4pIn1avh4nIahH5VkQuPtabiMhc53qrS0tLOyfyouYpNtw7gVuaX0JseDATMhM6Jw6ljuI7CSp9nPXVhetQI9Nj2ba/ijItlFC+o60xLnPU88VApjFmJPAR8FKrZX2NMbnA1cATIjKwrTcxxjxjjMk1xuQmJyd3RtzOAolga5ZrF9mbHCzfsp/Th/YiKNB3/htR3Yvv/GVFJEDCQJdaHp09PJUmh+HDvOIuCEwplxQCrc+IMgBb6xWMMWXGmOZPVc8C41otszm/7gA+BTo253pH2NZZN8sHhbq8yerdhzhc06jDe8qjfCdBgTXMV7jKumh7HNmp0QxMjmTxBttx11OqC60CBolIfxEJAa4CjqjGE5HUVk8vBDY7X48XkVDn90nAZODo4grPMMaq4HOzQeyy/BJCAgM4dXAnncUp1QYfS1C5Vrv/8sLjriYinD8yjRU7D1JSUddFwSl1bMYYO3AnsAQr8Sw0xuSJyMMicqFztbtEJE9ENgB3AXOcr2cDq52vfwI82kb1n2cc2gV1h90qkDDGsCy/hJOzEokK9Y1CYNU9+V6CApeuQ10wKhVj4P1NRR4OSinXGGPeN8YMNsYMNMY84nztQWPMIuf3DxhjhhljRhljphljtjhf/9oYM8L5+ghjzPNdFnQHOkh8X1LFnoM1nJmj3SOUZ/lWguo9HILCXLofKqtXNNmpMTrMp9SJKFoPgSHQK8flTZY6r/2eka1zPynP8q0EFRhsjYW70PIIrLOotXsOs/dgjYcDU6qbsq2z2hsFhbi8ybLNJYzuE0evmDAPBqaUryUosIb5bOvB3tDuquePSAPgPzrMp5T7jAHbBreG94rL69hYWK7Ve6pL+GaCaqqHkk3trto3MYJRfeJ4b6MO8ynltoM7oL7crQq+ZZutuZ/O1ASluoAPJijnFPCF7d8PBXDByFS+21fBjtLjt0hSSh2lAwUSy/JLyEyMIKtXlIeCUuoHvpegYtIhOtWlSj6A80emIQLvbdRhPqXcYlsHgaHQK9ul1SvrGvlm+wFm5PTW5rCqS/heghKx2h65WCiREhvG+MwEFm2wYdq5wVcp1UrRBkgZbhUnueCz70tpbDLM0PJy1UV8L0GBNcx3cAdUl7m0+gUjUynYX8XWEp0jSimXOBxWMZIbw3tL80pIiAxhXL94Dwam1A98NEG5PsMuwDkjUgkQeG+DDvMp5ZKD26Gh0uUE1djk4JOt+5k+tBeBATq8p7qGbyaotDEgAS7dsAuQFBXK5KwkFm/UYT6lXGJrnmLDtQS1YsdBKuvsWl6uupRvJqiQSOvmQRcLJQAuGJnG7rIaNu0r92BgSnUTtnUQFA5JQ1xafVl+MWHBAZwySJvDqq7jmwkKID3XmnrD4XBp9bOGpRAcKNr6SClX2NZByggIbL/Za3Nz2ClZyYSHBHZBcEpZ2k1QIjJERNa3elSIyD0ejyxjPNRXQNk2l1aPjQjm1EHJ/GdjEQ6HDvMpdUyOJije6PLwXp6tAlt5nd6cq7pcuwnKGLPVGDPaGDMaa4K1GuAdj0fWcsOuG8N8o9Kwldexds8hDwWlVDdQVgANVS5P8b4svwQROF2bw6ou5u4Q33RguzFmtyeCOUJiFoTGulwoAXBGTm9CgwJ0mE+p43Gzg8TS/BJy+8WTFOX6jLtKdQZ3E9RVwPy2FojIXBFZLSKrS0tLOyGyAMgY51aCigoNYnp2L/6zqQh7k2vXrpTqcWzrITgCkga3u+regzVsLqrQ6j3lFS4nKOc01hcCb7S13BjzjDEm1xiTm5zcSZU+6bmwPw/qXe+zd8HINA5UNbBi58HOiUGp7sa2DlJGQkD7BQ8fOZvDavcI5Q3unEGdA6w1xpR4KpgfyRgPxmFNquaiaUN7ERkSqB3OlWpLk92tAoll+SVk9Yqif1KkhwNT6sfcSVCzOMbwnse4MQV8s7DgQGbk9OaD74ppsOswn1JHOPA9NNa4lKBqG5pYufMg07U4QnmJSwlKRCKAGcDbng3nKBEJkDDAretQYFXzHa5p5KuCAx4KTCk/1Twa4UIF3+biCuwOw5g+2ntPeYdLCcoYU2OMSTTGdH2bhozx1hmUGy2MThmUTExYkFbzKXU02zoIibKqZNuRZ6sAYFhajKejUqpNvttJolnGeKgqgfJClzcJCQrgnOGpLM0voa6xyYPBKeVnbOsgdZRLBRL5tnJiw4PJiA/vgsCU+jHfT1Dp46yvLnY2b3b+qFSq6u18urUTSt6V6g6a7FC8yeUp3vNtFeSkxujkhMprfD9B9R4OQWFuX4c6aUAiiZEhLNZqPqUspVvAXudSgYS9ycGW4kod3lNe5fsJKijEGpJwo5IPICgwgHNHpPLx5hKq6+0eCk4pP+JGB4ntpdXU2x3kaIJSXuT7CQqs61BFG8De4NZmF4xKo67R0XKzoVI9WtF6CIm2KmPbkWez6qGGpcV6OiqljslPElSuNTRR8p1bm+X2iyclJoz3NupMu6priMjZIrJVRApE5P42ls8RkdJWswPc3GrZ9SKyzfm4vtODs62zyssD2j/s82wVhAYFMDBZb9BV3uMfCSq9+YZd965DBQQI541M5bOtpZTXNnogMKV+ICKBwJNYXVdygFkiktPGqq83zxBgjHnOuW0C8CtgIjAB+JWIdN4NSE2NUPydyx3M820VDE2JJijQP/6LUN2Tf/z1xWZAVIrblXxgDfM1NDlYmlfsgcCUOsIEoMAYs8MY0wAsAC5ycduzgGXGmIPGmEPAMuDsTots/2Zoqnfp+pMxhjxbOTk6vKe8zD8SlIg1zOdmoQTAqIxY+iSEs1iH+ZTnpQN7Wz0vdL52tMtEZKOIvCkifdzZtsOzBjQXSLhQYl54qJaKOrsWSCiv848EBVaCOrgDatzrUi4iXDAyja8KDlBWVe+h4JQCoK0bho5ugbIYyDTGjAQ+Al5yY9uOzxpgW2fNr+ZSgYR2kFC+wY8SVPMMux0b5mtyGD7UYT7lWYVAn1bPM4AjbsQzxpQZY5o/KT2LNUu1S9uekKL11vUnF266zbeVEyCQnaIJSnmX/ySo1NEgAR0a5huaEs3A5Ejtzac8bRUwSET6O+dPuwpY1HoFEUlt9fRCYLPz+yXAmSIS7yyOONP52omz17tVIJFnq2BAchThIe23Q1LKk/wnQYVGQa9hHSqUEBEuGJXGip0HKamo80BwSoExxg7ciZVYNgMLjTF5IvKwiFzoXO0uEckTkQ3AXcAc57YHgd9gJblVwMPO107c/nxwNLo8B1R+UYUO7ymf4D8JCpyFEmvA4f48T+ePTMMY+I8WSygPMsa8b4wZbIwZaIx5xPnag8aYRc7vHzDGDDPGjDLGTDPGbGm17QvGmCznY16nBWVrnmKj/QR1sLqBovI6TVDKJ/hfgqovh7Jtbm+a1SuKnNQYnWlX9Ty2dRAWB3H92l21uYNETqqWmCvv87ME1fFCCbCKJdbuOczegzWdGJRSPs62zjp7cqFAQiv4lC/xrwSVOMgqle1AoQTA+SOt69P/2aTDfKqHaKyzbtJ18fpTnq2CtNgw4iNDPByYUu3zrwQVEADpYztUKAHQJyGC0X3itJpP9Rz785wFEq62ONIOEsp3+FeCAmuYryQPGqo7tPkFo9LIs1Wwo7SqkwNTyge5McVGTYOdHQeqdXhP+Qw/TFC5YBw/HHhuOm9EKiJoh3PVM9jWQ0QixPZpd9XNRZUYg7Y4Uj7D/xJUBzubN0uJDWNCZgKLNtgw5kedZJTqXmzrnTe5u9ZBArRAQvkO/0tQkYlWP7EOFkoAnD8qjYL9VWwtqezEwJTyMY211k26bhRIxIYHkx4X7uHAlHKN/yUosM6i9nwD1WUd2vyc4SkEBogWS6jurSQPTJPbHSTEhbMtpbqCfyaoCbdAfRW8NhPq3T8LSooK5eSBiSzeUKTDfKr7aimQaL+Cr7HJwZbiSh3eUz7FPxNUnwlw+Two2gALrrGaYbrpglFp7DlYw6Z95R4IUCkfYFsHkckQ09aUVEfaXlpFg93BMC0xVz7EPxMUwNDz4KK/w87P4K2boMnu1uZnDUshOFB45vMdOBx6FqW6IXc6SOyzOkhoBZ/yJf6boABGXw1n/Q42L4b37gE3hutiw4O5Y2oW720s4r8Xrqexyf0GtEr5rIYaKN3i0gy6YBVIhAYFMCAp0sOBKeW6IG8HcMJO+i9rlt0vHoPweDjzNy5v+t8zBhMaHMAfP9xKVZ2dJ68ZS1iwzoGjuoHiTdb9gi5X8JUzNDWGoED//syqupfu8dd4+i8h90b4+q/w5Z/d2vSOqVn85uLhLN+6n+tfWEllXaOHglSqC7nRQcIYo3NAKZ/UPRKUCJz7GAy/DD56CNa86Nbm107qxxNXjmb17kNc89wKDlY3eCRMpbpM0XqISoGY1HZXLTxUS2WdXROU8jndI0EBBATCxU9B1hnw3n9D3rtubX7R6HSeuXYcW4srueLpbygu15l3lR/LGG+NKrjghzmgNEEp39J9EhRAUAhc8Yp1cL51M2xf7tbm07N789KNEygur2PmU1+zu6xjDWmV8rrxN8HU/3Fp1TxbBQECQ1M0QSnf0r0SFEBIBFz9OiQNhgWz3e7ZN2lAIv+6ZSLV9XZmPvUNW4orPBSoUr4hz1bBwOQowkO0QEj5lu6XoMCq5rv2bYhKhlcvsyZsc8PIjDgW3noSAQJXPv0t6/Yc8lCgSnlfvk0LJJRv6p4JCiA6Ba59F4LC4JVL4NButzYf1DuaN287mbiIYK55bgVfFRzwUKBKeU9ZVT3FFXXaQUL5pO6boAAS+ltnUo018MrFULXfrc37JETwxq0n0Sc+ghvmrWJJXrGHAlXKO/Js1hC2nkEpX9S9ExRA72FwzZtQWQyvXAq1h93avFdMGK/fOomctBjueG0tb68t9FCgSnW95gSlLY6UL+r+CQqs5rJXvmK1fpl/ldUGxg1xESG8dvNEJg1I4N6FG3jxq50eClSprpVnKyc9Lpy4iBBvh6LUj/SMBAXW/VGXPg17voU35kCTex0jIkODeP768czI6c1Di/P528fbdKoO5ffybRV69qR8lksJSkTiRORNEdkiIptF5CRPB+YRwy+D8x+HbUvg3dvB4V6D2LDgQP55zVguHZvOn5Z9zyP/2axJSvmt6no7O8uq9fqT8lmuNov9C/ChMWamiIQAER6MybNyb7Sayy7/jVWOfs4fXZqOoFlQYACPzRxFTFgwz325k8o6O7+7dASBAToLqfIvW4orMAat4FM+q90EJSIxwKnAHABjTAPg383qTvkp1B6Cb/5ulZ9nn28NAcakubR5QIDwqwtyiAkL4q/LC6isb+TPV44mNEhvdOzpRORsrA90gcBzxphHj7HeTOANYLwxZrWIZAKbga3OVb41xtzmyVi1QEL5OlfOoAYApcA8ERkFrAHuNsYc0QdIROYCcwH69u3b2XF2LhE487cQHAHrXrWG/AB6D7cS1aAZ0GciBAYfZxfCvWcOISY8mN/+ZzNV9Wt4evY4vRu/BxORQOBJYAZQCKwSkUXGmPyj1osG7gJWHLWL7cYY1yZw6gR5+yqIiwgmLTasq95SKbe4cg0qCBgL/NMYMwaoBu4/eiVjzDPGmFxjTG5ycnInh+kBInD6/8K9+XD713DGr60hv2/+Di+eB3/ob00nv+ZFKN93zN3cfMoA/nDZCL7YVsp1L6ygQqfr6MkmAAXGmB3OkYYFwEVtrPcb4I+AVzsS5xWVMywtBnFjiFupruTKGVQhUGiMaf609yZtJCi/JWLdK9V7GEy5B+oqYOfnULAMtn0EW96z1uuVA1nTIWsG9D3JakzrdOX4vkSGBnHPgvVc/ey3vHTDBBKjQr30AykvSgf2tnpeCExsvYKIjAH6GGPeE5GfHbV9fxFZB1QAvzTGfHH0G3TWSEVjk4Pvi6uYMzmzw/tQytPaTVDGmGIR2SsiQ4wxW4HpQH572/mtsBjrmlT2+dYU8qVbYNsyKPgIvn0Kvv4bhERB/9Ng0BlWworrw/kj04gMCeK2V9dwxdPf8NrNk0jRoZOepq1TkZYyTxEJAP6M83ruUYqAvsaYMhEZB7wrIsOMMUd0KzbGPAM8A5Cbm9vhEtKC/VU0NDm0gk/5NFer+H4CvOas4NsB3OC5kHyICPTKth6T74L6qiPPrrb+x1ovORsu+jvThuby8o0TuOml1cx86mteu3ki/RIjvfszqK5UCPRp9TwDsLV6Hg0MBz51DqulAItE5EJjzGqgHsAYs0ZEtgODAffa8btIWxwpf+DSfVDGmPXO60sjjTEXG2N6Znvv0CgYei6c/2e4ZyP810o48xForLYa0u5dxcRW03Vc/tQ3bC2u9HbUquusAgaJSH/nh7mrgEXNC40x5caYJGNMpjEmE/gWuNBZxZfsLLJARAYAg7A+DHpEnq2csOAA+idFeeotlDphPaeTRGcTgeQhcPKdcMOHEJHoTFIrW6brALjymW/YsNe9/n/KPxlj7MCdwBKskvGFxpg8EXlYRC5sZ/NTgY0isgHrOu9txpiDnoo1z1bB0JQYvX9P+TRNUJ0hNh1ueN+af+qVS2HPipbpOqLDgrj62W/5ZnuZt6NUXcAY874xZrAxZqAx5hHnaw8aYxa1se5U59Aexpi3jDHDjDGjjDFjjTGLPRgjm3UOKOUHNEF1lpg0mPMfiOoFr14Ke76lb2IEb9x6Mmlx4cyZt5LlW0q8HaVS7D1YS2W9XTtIKJ+nCaozNSep6BTrTGr3N6TEhvH6rScxuHc0c19ew+INtvb3o5QH5dnKAS2QUL5PE1Rni0mF69+zktWrl8Hur0mIDOFft0xkbL947lqwjvkr93g7StWD5dkqCAwQhqREezsUpY5LE5QnxKTCnPesa1OvzoRdXxEdFsxLN0zgtMHJPPD2Jp793GMFWkodV56tnIHJkYQFa1su5ds0QXlKdIp1JhWbDq/NhF1fEh4SyDPX5nLeiFQeeX8zjy/dqtN1qC6XZ6vQ60/KL2iC8qTo3tY1qdg+8NrlsPMLQoIC+OusMVyZ24e/Li/g14vzcTg0SamuUVpZz/7Ker3+pPyCJihPi+plDffF9bWS1I7PCAwQHr1sBDdN6c+LX+/i529txN7k3uSJSnVEfpFOsaH8hyaorhDVyxrui8+Ef10JOz5FRPjledncc8Yg3lxTyE/mr6Pe3uTtSFU311zBl5OqCUr5Pk1QXSUq2TqTSuhvJantnyAi3HPGYP7f+Tl88F0xN8xbxd6DNd6OVHVjebYK0uPCiYsIaX9lpbxME1RXikyC6xdDwkCYfxVsXw7ATVP6838zR7Juz2GmP/4Zjy/dSk2D3cvBqu4oXztIKD+iCaqrNSepxCz411VQ8DEAl+f2YfnPTuPsYSn8dXkB0//0GYs32LTKT3Waqno7u8qqtYJP+Q1NUN4QmQjXLYKkwTB/ljXXFJAaG85fZ41h4a0nER8Rwk/mr+PKZ74l31bRzg6Vat+WogqM0Q4Syn9ogvKWyES4fhEkD4b5V1vzSzlN6J/A4p9M4XeXjGBbSSXn/+0L/vedTRysbvBiwMrftcwBla4JSvkHTVDeFJFgnUklD4EFs2DTm1BRBE12AgOEqyf25dOfTeO6kzJZsGov0x77lJe+3qUl6apD8mzlxEcEkxKjMz0r/+DqjLrKUyIS4Lp/wysXw1s3OV8Ua36pqN7ERvXioaje3DU+jvd3OVj53qfkfZXKrNNzGZM9BMLjrbmplGpHcwcJ0b8X5Sc0QfmCiAS44QPY8SlUFkPVfqgq+eHrwe0kVJYwu6me2SFANbDYepiAYCSqt3WvVfPX3sMhazokDvTuz6V8RoPdwbaSKm6YnOntUJRymSYoXxESCUPPO/ZyY6C+Aqr2U3+4iOWrN7E2fwtJjnKmhDUxNKyWwIpC2Lca1r5kbZMwEAbNgKwZkDkZgsO75mdRPqdgfxUNTQ7tIKH8iiYofyECYbEQFkto0iDOyTqVkYdr+f37m/n9xiLS48L53/OyOWd4CnJwh1UZuG0ZrHkRVjwFQWGQeYozYZ2hZ1c9zA9zQGmJufIfmqD8WHpcOH+/eiyzJ5Xx68X53PHaWiYNSGDuqQMYOWwOSRNvhcZa2PUVFCyzEtYHP7c2ThhgnVkNmgGZU/TsqpvLs1UQHhxI/6RIb4eilMs0QXUDkwYk8t5PpjB/5R4eW7qVG19cDUBKTBjD02MZkd6PEf3vZfiUX9Or0WaVtBcsg7Uvw8qnnWdXU35IWHp21e3k2yoYmhpNYIAWSCj/oQmqmwgMEGZP6selY9PZWFjOd/usx6Z95Xy8pYTmhhS9Y0IZkT6G4elTGTUylNEmn/h9n1kJ68P/sR7x/WHQmTDlv63JF5VfczgM+UUVXDwmzduhKOUWTVDdTERIEJMGJDJpQGLLa1X1dvJtFWw6Imntb0laydFnMCL9Mib3q+Rks47+h78mdM2LSN47cPmLVoGF8lt7D9VQVW/X60/K72iC6gGiQoOY0D+BCf0TWl6rrrezuchKWs2J65GttTjMUGAok6LO459NfybupQuQM38Dk+7Q+638VEsHCa3gU35GE1QPFRkaRG5mArmZPyStmgZn0ios58uCXpy6+UH+EvY0py/5BfY9Kwm6+EkIjfJi1Koj8mzlBAYIg3tHezsUpdyiCUq1iAgJYly/BMb1S2DO5P58t28wjy/tx8qC57lv80IO7dlIxLXzCU0Z6u1QlRvybBVkJUcRFhzo7VCUcov24lPHNDw9lhdumMCMuY/yx6Tf46gqxf7UVD599zmd/deP5OkcUMpPaYJS7RrXL54H7ryNXZd9gC24L1PX/5Q3fn8TC1fsoFEb1x5BRM4Wka0iUiAi9x9nvZkiYkQkt9VrDzi32yoiZ3VGPPsr6yitrNcOEsovaYJSLhs3cgRZP/8cW9bVzG56h4z3ruHyP/2bd9YV0uTQiRVFJBB4EjgHyAFmiUhOG+tFA3cBK1q9lgNcBQwDzgb+4dzfCclvKZDQCj7lfzRBKbdIcBhps/+JuehJJoZs57nan/LywoJBCe8AAAkESURBVDc564nPeX9TEY6enagmAAXGmB3GmAZgAXBRG+v9BvgjUNfqtYuABcaYemPMTqDAub8T0lzBp2dQyh9pglIdImNmE3jzMhJjo3gr7Ldc0PA+d7y2hvP+9iXL8kt66lT16cDeVs8Lna+1EJExQB9jzHvubtsR+bYKMuLDiQ0PPtFdKdXlNEGpjksdhcz9lICBU7m77ik+H7QQR301t7y8mouf/IrPvi/taYmqrRvFWn4BIhIA/Bn4qbvbttrHXBFZLSKrS0tL2w0oz1auBRLKb2mCUicmIgGuXghTH6Dv3kV8GP0bnjwnngNVDVz/wkoufvIrnvjoe1bvOtgTCioKgT6tnmcAtlbPo4HhwKcisguYBCxyFkq0ty0AxphnjDH/v717DY7qLuM4/n2ymzuXNBdSyMWkQIsRbaFpQBAtUmoRR/uiM6IjMzo6vKFab2OrL3xRpy8cnU55obVMW33RVmRocWplelFbnakdJIUOEAJyEcomaAiSC4GQbPL44iyYieQiSfacJb/PTCbs5uye327y8Oz5n3P+p97d68vKykYNc+FykpPnLmr/k2QsnQclE5eVBXc/AhV3Yi9+jfXvbODe+7ey7fyH2N6YYMsfj/LEH45SmBOjobaYlQtKWTG/lEU3zyTrxpq8dA+w0MxqgRaCgx6+eOWH7t4JlF65bWZvAd9190YzuwS8YGaPA/OAhcDfJhKm+YxmkJDMpgYlk2fhWtj0FmzfSPa2z7PxEw+zcfPDdPQO8M7xc7x9vJ2/HjvHm0eaASgpzGH5/BI+tqCUlfNLqS4pCDX+RLl70sweBF4DYsCz7t5kZo8Cje7+8iiPbTKz7cAhIAlsdvcJnWzW1KJrQElmU4OSyVVcC199A175Nvz5x3BkF0UFpazzAdYNDkLxAH0z+7lw6TI9vX1c/Hsfg4eT9DLIqRgUZhv5cScvBjEGYXAAfBBmzoWqBqhaBlV3BTOuR3BuQHffBewadt8PR1j27mG3HwMem6wsTa1dlBTmUD4rd7KeUiSt1KBk8mXnw/0/h+plsO856LsAFoOsGGTFycnPpbhgNsVZMdyy6Ol32nsGaOtJcrann95LxiBZzMjLpWx2AeWz8ylPniF7/3ZofCZYR2EZVDakmlYDzFuiiy4O09TaRd28WVgEG7nIeKhBydQwgzu/HHyNthgwI/VVAyQHBjnY2sXbx9rZebydPSfP05cIDq64pTiXtXM7WJV3nNv6D1PS9h5ZR34fPFFWHG7+yH+3sKqWwezKKXt5UdeXHORoWzerbq0NO4rIdRtXg0odcdQNDABJd68f/REi1ycey+KOqiLuqCpi8+oF9PYPsPfUefad7mB/ooPfJYynOhcDizF7gKUlA3y66DR3xY9Re+kgM979Fbb7yeDJZs4bMizYEDSweE6ory9djrZ10z/g2v8kGe3/2YJa7e7tU5ZE5BrysmOsWFDKigVXD37jbPdlDrZ0sj/RyYGWDn6RKOBH3TXAPeRYkk+VtLNmxilu5wgV7zeSc+i3wQNjucHQ44cfCOW1pJOuASU3Ag3xScYpm5nL6kVzWL1oztX7/tXVGzSsRAf7Wzp5NFHNv3uWAVARO8/6mxKsyjtBuVdya1jB0+hQaxcFOTFqSgrDjiJy3cbboBx43cwceMrdtw5fwMw2AZsAqqurJy+hyDiUz8pjbV0ea+vKAXB3Wjt7g4aV6ORAy0J+k1jKT2I106JBnb/YR93cWcRurPPMZJoZb4Na6e6tZjYHeMPMDrv7X4YukGpaWwHq6+un1fw2Ej1mRkVRPhVF+dy3eC4QNK3pMpftlg1LSN74M3fIDW5cUx25e2vqexuwk0mYZVkk3cxsWm1RxGOayUwy25h/wWZWmLp+DWZWCNwLHJzqYCIiMr2NZ4ivHNiZOtkvDrzg7q9OaSoREZn2xmxQ7n4CuD0NWURERK7SILWIiESSGpSIiESSGpSIiESSGpSIiESSGpSIiESSuU/+qfVmdhY4NcoipUBUJp5VlpFFKU+6snzA3cvSsJ4JU51NSJTyTMcs46qzKWlQY67UrDEql+xQlpFFKU+UsmSKKL1nUcoC0cqjLCPTEJ+IiESSGpSIiERSWA3qfy7XESJlGVmU8kQpS6aI0nsWpSwQrTzKMoJQ9kGJiIiMRUN8IiISSWpQIiISSWltUGZ2n5kdMbNjZvZIOtc9LEeVmb1pZs1m1mRmD4WVZSgzi5nZPjN7JeQcRWa2w8wOp96jj4aY5Vup39FBM/u1meWFlSWTqNZGzRSJOktlUa2NIm0NysxiwM+AdUAd8AUzq0vX+odJAt9x9w8Cy4HNIWYZ6iGgOewQwBbgVXdfRHCplVAymVkF8A2g3t0XAzFgQxhZMolqbUxRqTNQrY0qnVtQDcAxdz/h7n3ANuBzaVz/Ve5+xt33pv7dTfBHURFGlivMrBJYDzwdco5ZwMeBZwDcvc/dO0KMFAfyzSwOFACtIWbJFKq1EUSlzlJZVGtjSGeDqgBOD7mdIOSmAGBmNcASYHe4SXgC+B4wGHKOW4CzwC9TwyBPm1lhGEHcvQX4KfA+cAbodPfXw8iSYVRrI4tKnYFqbUzpbFB2jftCPcbdzGYALwLfdPeuEHN8Bmhz93fDyjBEHFgKPOnuS4AeIJR9GGZ2E8En/1pgHlBoZl8KI0uGUa1dO0OU6gxUa2NKZ4NKAFVDblcS4iakmWUTFMzz7v5SWDlSVgKfNbOTBMMxnzSz50LKkgAS7n7lU+4OgiIKwz3AP9z9rLv3Ay8BK0LKkklUa9cWpToD1dqY0tmg9gALzazWzHIIdsC9nMb1X2VmRjDu2+zuj4eRYSh3/767V7p7DcH78id3D+XTi7v/EzhtZrel7loDHAojC8Fww3IzK0j9ztYQnZ3bUaZau4Yo1Vkqj2ptDPF0rcjdk2b2IPAawREiz7p7U7rWP8xKYCNwwMzeS933A3ffFVKeqPk68HzqP7cTwFfCCOHuu81sB7CX4GiwfURsKpYoUq1lFNXaKDTVkYiIRJJmkhARkUhSgxIRkUhSgxIRkUhSgxIRkUhSgxIRkUhSgxIRkUhSgxIRkUj6D5ll66BA8hQbAAAAAElFTkSuQmCC\n", + "image/png": "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\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ - "2560/2560 [==============================] - 0s 27us/step\n", + "52/52 [==============================] - 0s 2ms/step - loss: 13.7095 - accuracy: 0.5461\n", "\n", - "Accurancy: 0.6820\n" + "Accuracy: 0.5461\n" ] } ], "source": [ - "num_epochs = 10\n", - "\n", - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Dense(100)(text_input)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_token_train, y_token_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_token_test, y_token_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.4f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('word_saved_models/Linear-Token-{:.3f}.h5'.format((scores[1] * 100)))" + "run_experiment(construct_linear(), token_dataset, num_epochs=10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Linear - Morph" + "### Linear - Morph" ] }, { "cell_type": "code", - "execution_count": 104, + "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Train on 8195 samples, validate on 2049 samples\n", "Epoch 1/10\n", - "8195/8195 [==============================] - 1s 97us/step - loss: 9.8982 - acc: 0.3519 - val_loss: 8.2902 - val_acc: 0.4573\n", + "164/164 [==============================] - 0s 3ms/step - loss: 118.7563 - accuracy: 0.5539 - val_loss: 60.8787 - val_accuracy: 0.5935\n", "Epoch 2/10\n", - "8195/8195 [==============================] - 0s 52us/step - loss: 7.7296 - acc: 0.5024 - val_loss: 7.0930 - val_acc: 0.5451\n", + "164/164 [==============================] - 0s 2ms/step - loss: 41.4898 - accuracy: 0.5907 - val_loss: 33.4933 - val_accuracy: 0.6257\n", "Epoch 3/10\n", - "8195/8195 [==============================] - 0s 60us/step - loss: 6.5224 - acc: 0.5832 - val_loss: 6.4932 - val_acc: 0.5900\n", + "164/164 [==============================] - 0s 2ms/step - loss: 23.2472 - accuracy: 0.6087 - val_loss: 18.9770 - val_accuracy: 0.6110\n", "Epoch 4/10\n", - "8195/8195 [==============================] - 0s 60us/step - loss: 6.1808 - acc: 0.6079 - val_loss: 6.1911 - val_acc: 0.6091\n", + "164/164 [==============================] - 0s 2ms/step - loss: 14.5355 - accuracy: 0.6023 - val_loss: 15.1386 - val_accuracy: 0.5852\n", "Epoch 5/10\n", - "8195/8195 [==============================] - 0s 61us/step - loss: 5.8964 - acc: 0.6281 - val_loss: 6.0357 - val_acc: 0.6223\n", + "164/164 [==============================] - 0s 2ms/step - loss: 11.3570 - accuracy: 0.6193 - val_loss: 12.3346 - val_accuracy: 0.6042\n", "Epoch 6/10\n", - "8195/8195 [==============================] - 0s 58us/step - loss: 5.7071 - acc: 0.6399 - val_loss: 5.9109 - val_acc: 0.6276\n", + "164/164 [==============================] - 0s 2ms/step - loss: 9.6818 - accuracy: 0.6209 - val_loss: 11.2899 - val_accuracy: 0.6467\n", "Epoch 7/10\n", - "8195/8195 [==============================] - 0s 59us/step - loss: 5.6071 - acc: 0.6470 - val_loss: 5.8021 - val_acc: 0.6374\n", + "164/164 [==============================] - 0s 2ms/step - loss: 8.6330 - accuracy: 0.6105 - val_loss: 10.2450 - val_accuracy: 0.6237\n", "Epoch 8/10\n", - "8195/8195 [==============================] - 0s 57us/step - loss: 5.5011 - acc: 0.6555 - val_loss: 5.6980 - val_acc: 0.6442\n", + "164/164 [==============================] - 0s 2ms/step - loss: 7.6626 - accuracy: 0.6249 - val_loss: 8.7776 - val_accuracy: 0.6374\n", "Epoch 9/10\n", - "8195/8195 [==============================] - 1s 67us/step - loss: 5.4568 - acc: 0.6585 - val_loss: 5.6213 - val_acc: 0.6476\n", + "164/164 [==============================] - 0s 2ms/step - loss: 7.1395 - accuracy: 0.6320 - val_loss: 8.5058 - val_accuracy: 0.6369\n", "Epoch 10/10\n", - "8195/8195 [==============================] - 1s 65us/step - loss: 5.4034 - acc: 0.6616 - val_loss: 5.5811 - val_acc: 0.6506\n" + "164/164 [==============================] - 0s 2ms/step - loss: 6.4400 - accuracy: 0.6377 - val_loss: 7.8913 - val_accuracy: 0.6164\n" ] }, { "data": { - "image/png": "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\n", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAEdCAYAAABZtfMGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOydeXyU1dX4vyeTPYQEQliSAGELmxCWCAIiKChaFcEdF0Ct1taqXdRqW6u19f31ba2vta21bsUFpda64IqACyogO5GwLyGEJUAgIYHsc39/3GfCECbJZPYZ7vfzmc8zz33uvc+ZSe6c55577jmilMJgMBgMhlAjKtgCGAwGg8HgCqOgDAaDwRCSGAVlMBgMhpDEKCiDwWAwhCRGQRkMBoMhJDEKymAwGAwhiVFQhqAjIrNFRIlI32auzxGRwgCL5TUi8qj1uapEJMXFdcfnbvazB0BGJSK/D8a9DYbWMArKEA78DpgebCG8oA642kX5TKAiwLIYDGGDUVCGkEcptUMptTbYcrhCRGJERFqp9jZwc5N23YEJwH99KItNRKJ91Z/BEGyMgjKEPE1NfCKSbZmmfiAij4nIfhEpE5H3RSTLRfvbRWS9iFSLyGEReVFEOjap82MRWSYiR6y+lovIpU3qOO77IxH5o4jsA2qA1FY+wivAeSLS06nsZqAIWOJCXhGRn4rIFhGptT7f30SkfZN6SkQeF5EHRWQXUAsMEZGJ1rWrrO/uqIgcE5G5IpLWzHd8j4jsEpEKEflSRAa38pkMBr9jFJQhnHkI6AvcCtwLjAHmOlcQkT8AzwCLgKnA/cDFwMciYnOqmg28AFwDXAesAj4QkUtc3PdXQA5wB9r0WN2KnF8BhcCNTmU3A68BrmKNPQ48CSwELgf+CMwGPhSRpmN2NnApcJ913Od07Smr/xmWzFOBt1zc7yar7b3ALUAP4D0zGzMEHaWUeYXRC/1DqoBoN+rOBr4OtsxuyqmAvs1cnwMUuvgOvmxS7z6rPMOpXgPwmyb1xln1pjVzvyggGvgUeM/FfdcA4sbnetTxtwIeAzZZ5aOs8n5NPzvQEa3w5jTp6yar3lSnMoVWSAlN6k60rn3SpPxGq3xSkz62ATFOZVdb5WOD/b/Rhv+hiBsX5qXMDMqfiEihZaLp1KR8nWWCyQ6OZKeYq8L5KfnDJuffWcce1vFCtLKZKyLRjhfwLXAMOM/RUERGisgHIlIC1KMdGy4E+ru477vK+qWz2kY36d8VrwADRORstHPEcqXUNhf1zgHi0LMrZ+ZZck1oUv6JUqqqmXu+2eT8P4AdPdN0ZqFSqs7pvOn36FNCeVw4yZIkIpUi8lGwZTmTMQrK/+xCm1gAEJEhQELwxIkojjQ5r7GO8daxs3XcjlY4zq/2QBo0OiwsRs9e7gbGAmcDnzj15cx+xxvrx/SUvl39wCqltgPLgNuA69EKyxWOtbH9zoVKqXqg1On6abK4oKRJH7XAUSCzSb3Wvkd/EOrj4mr093CRiHQL5I3D/KHRpxgF5X9eRT8xO5hFkx8nEUkRkVdE5JCI7BaRXzvWGizPrCesxf2d6LWCpm1ftBbS94rI75usrbQZEckQkfmWw8B2Ebnd6dooEVllLbqXiMiTVnm8iLwmIqWWk8FKEenijRw+oNQ6XoRWOE1fj1rXLwZSgGuVUm8qpZYrpVYBic3067xutM9Fv/tcNUL/3W8HkoF/N1PHoSy6OhdaP1ppTp/JlSxNOeX7F5FYoAOwt4U2gSLUx8Us4Fkgn1PXDhGRc0VkqfV/vkdEZlvlCSLyZ0vWchH52iqbKCLFTfooFJHJ1vtHReQta/wcA2Zb42yZdQ+Hk0ysU/vBIrLQGqMlIvJLEekqIifEyRHGsgwcEpGYNnz2kMEoKP+zHGgvIgOtAXIdp5tv/or+geyNNuHMRC9Wg/5BuwwYDuRx+n6al9Gmn75WnYuA73sp8xtAMZBh3e9/RGSSde0vwF+UUu2BPpw0I82yPkN39A/pnUBzpqdAsRBt0uqhlFrl4rXLqudQRI1mLhHJQa9VtYhSqtZFv7XNVP83MB/4g1Kq6azFwXL0k/v1TcqvQ69lfdmaTE5c2+T8GvSYX9aGPvxFyI4LEemBXseba71mNrn2sSVbOjAMWGddfgIYiZ6BdwQeQP//ucMVaAeWVOueDcBPgU5ok+wk4EeWDMlop59P0GO0L7BYKXUA+IJT/+43AfOamHDDBjOVDAyOp8Uvgc04PcE6Dc7hSqkKoEJE/oz28noR/c/2lFJqj1X//6EHD9YM5RIg1VqHOC4i/4f2LvunJ4Ja5q5zgcuUUtXAOhF5wZJnMfpHvK+IdFJKHUb/0GCVp6EX+/OB1R7c/mIROdCkrNyTzwF6/5SI/C/wNxHpj/7+q9FK9ELgBaXU5+jBXg+8Yn333YDfot3AffYQp5Q6SisbjpVSR6xZ6UMichz4CBgI/B74mtPX3VpisIj8C71+lYP2DvxSKbXYE/n9QKiOi5lAvlJqo4iUAX8UkeFK78W7EViklHrDqlsKlFozu1uBc5RSjs+x1JLHne9imVLqXet9FaeOn0IR+SdaST+FVswHlFJ/tq5Xo9dVQSvme4B/WN/hDLT3ZlhiFFRgeBW936UXp689dAJigd1OZbs5uU6QAexpcs1BTyAG2O80CKKa1G8rGcAR60fB+Z551vvb0B5pm0XvvfmtUuoD9GfsDswTkVT00/Cv2vjk9lcXZQVol2+PUEr9UkQ2AXdZL4X+fhajvddQShWIyI3ozzUf2AE8iDb9TfT03l7wK+AQehb6I/SP4CvAQ0opd5/IQbuNT0XP3GzA++gfr1AhVMfFTOB5AKXUPhH5Em0hWIv+H9/hok0n9Jqdq2vucIps1gz+SfS4S0T/VjuUVnMyALwHPCsivdEPJeVKqRUeyhR8gu1GGMkv9N6Xydb7L9CeY0nofzaFdo21oTdYDnJqdwfwhfX+c+BOp2sXctJ1uRv6aculay0tuNPSjFsu+p+/AUh2KvsfTnd7jkKbVaqBJBd9bwRuC/bf4Ex8cdLNfHKwZWlGvlAeF2Otfo4AB6zXcbTDSTR67907LtpFWffMdXHtbPRDn+PcZvXp+A4eBV5r0mYx2mSYbJ3/xCEzela0toXv95/Aw2hT4a+D/ff25mXWoALHbcAFSqnjzoVKqQb0Os7jIpIsOtrAzzhpj38TuEdEskSkA/rJ3tF2P3qvzp9FpL2IRIlIHxFp6orcEnGWg0O8iMSjzSxLgf9nlQ21ZJ8LICI3iUi60k/yZVYfDSJyvogMscwKx9Amv4Y2yGE4Mwm1cTELvXY5CL2+NAw4Cz2LuQQ9DiaLyLWitxWkicgwazy8BDwp2snIJiJjRCQO2ArEi8illrPCr9FbCVoiGT2OKkVkAPBDp2sfAF1F5CciEmd9P6Odrr+CVsJTOX1dL6wwCipAKB1PrjlT1d3oJ6qd6HWG19H/7KBNDQuA9egNom83aTsTbQrZiHYhfgv9BOkulegnP8frAvQTWjbaG+0d4BGl1EKr/sVAgYhUoh0mrld6raqrde9jwCb0ukJYDw6D/wmlcWE9oF0L/FUpdcDptQttjpyllCoCvgf8HD3LWgfkWl3ch95DttK69r9AlFKqHG2qfQH9AHgc7YTUEvcBN6CDCT+Pk9en0ub3C9FRRg6gTdXnO13/Bu2csUYpVdjKfUIasaaEBoPBYIgQROQz4HWl1AvBlsUbjIIyGAyGCEJ0tJKFQHd1qrNT2GFMfAaDwRAhiMjL6G0TPwl35QRmBmUwGAyGEMXMoAwGg8EQkoTERt1OnTqp7OzsYIthMLjF6tWrDyul0oMtR0uYMWUIJ5obUyGhoLKzs1m1yuNgAQZDQBGR3a3XCi5mTBnCiebGlDHxGQwGgyEkMQrKYDAYDCGJUVAGg8FgCElaXYMSkZfQ4d0PKqXOssr+hA6zUYuOqnuLUqrMuvYQOr5WA3CPUmqBJ4LV1dVRXFxMdXW1J80NLoiPjycrK4uYmLDMXWbwEjOmfIsZT/7HHSeJOcDfODUc/kJ06P96K9/OQ8AvRGQQOtHaYHQ4/EUikmMFfmwTxcXFJCcnk52d7W4+FUMLKKUoLS2luLiYXr16BVscQxAwY8p3mPEUGFo18SmllnAyDbWj7FOlVL11uhzIst5fgc7eWGMFWNwOjPJEsOrqatLS0sxA8hEiQlpamnl6PoMxY8p3mPEUGHyxBnUrOgUy6GRizom3ijmZYKzNmIHkW8z3aTD/A77DfJf+xysFJSK/QqfKnusoclHNZSwlEblDRFaJyKpDhw55I4bBYDAYIhCPFZSIzEI7T9yoTgb0K0ZnZHWQhc4pdBpKqeeUUnlKqbz09OY35R+qqGZ36fFmr/uL0tJShg0bxrBhw+jatSuZmZmN57W1tS22XbVqFffcE0qZtQ2G4HJGjKfi1fDRA2C3B1uSiMGjSBIicjHwC2CCUuqE06X5wOsi8iTaSaIfsMIbAesaFBXV9SilAjqlTktLY926dQA8+uijtGvXjvvuu6/xen19PdHRrr++vLw88vLyAiKnwRAOnBHjad1cWPUiDLkGup8dbGkiglZnUCLyBrAM6C8ixSJyG9qrLxlYKCLrRORZAKVUAToV80bgE+AuTzz4nIm1RWFXigZ78KOuz549m5/97Gecf/75/OIXv2DFihWMHTuW4cOHM3bsWLZs2QLAF198wWWXXQbowXjrrbcyceJEevfuzdNPPx3Mj2AwhAwRN55KCvRx47vBlSOCaHUGpZSa4aL4xRbqPw487o1QzsRER/H8Vzs5UF5NlA9nUIMy2vPI5YPb3G7r1q0sWrQIm83GsWPHWLJkCdHR0SxatIhf/vKX/Pe//z2tzebNm/n888+pqKigf//+/PCHPzR7JwxB5bfvF7Bx3zGf9unJmIqY8aSUk4KaDxf9HowThdeERLDYloi16T+yUrh2wQgw11xzDTabDYDy8nJmzZrFtm3bEBHq6upctrn00kuJi4sjLi6Ozp07U1JSQlZWlsu6BsOZRMSMp7IiqK2ArFFQvAL2roGskcGVKQIIeQUVY4vi9vG9yUhJoFNyXLDFISkpqfH9ww8/zPnnn88777xDYWEhEydOdNkmLu6k3Dabjfr6epf1DIZA4Yn1wB9EzHg6uFEfJzwAb8yAje8YBeUDQj4Wny1KiBKhtiH0PGPKy8vJzNTbvObMmRNcYQyGMCesx1PJBn3sMQZ6T4SC9yyzj8EbQl5BiQgxtijqQlBBPfDAAzz00EOMGzeOhgavfEEMhjOesB5PJQXQIRvi2sHgaVBeBPvWBluqsEdUCGj5vLw81TS52qZNmxg4cCAAuw4fp8Fup2/n5GCIF1E4f68GzxCR1UqpkPZ7bm1MGXxD43f6t7OhUw5cPxdOHIEn+sGYu+DCx4ItYljQ3JgK+RkUQIxNqK0PviI1GAyG06irgtLt0MVa10vsCL0mQMG7xsznJWGhoGJtUdTb7dhDYC+UwWAwnMKhLaDsJxUUaDNf2W7Yvy54ckUAYaGgYmxazFBchzIYDGc4jv1PXc46WTbgMhCbnkUZPCY8FFS0FjMUPfkMBsMZTkkBRCdoJwkHiR2h9wTYaLz5vCEsFJRjs66ZQRnCFRG5WES2iMh2EXmwmToTrdBhBSLyZZNrNhFZKyIfBEZig9uUbIDOAyHKdmr5oCvg6C44kB8cuSKAsFBQ0bYoBKhtME8ihvBDRGzA34FLgEHADCv7tHOdVOAZYKpSajBwTZNu7gU2BUBcQ1sp2XDq+pODAZcbM5+XhIWCihIh2hZFXX3gZlATJ05kwYIFp5Q99dRT/OhHP2q2vsOt93vf+x5lZWWn1Xn00Ud54oknWrzvu+++y8aNGxvPf/Ob37Bo0aK2im8ILUYB25VSO5VStcA8dPZpZ24A3lZKFQEopQ46LohIFnAp8EKA5PULETmm7A1wovTU9ScHSWnQa7wOHmvMfB4RFgoKCPhm3RkzZjBv3rxTyubNm8eMGa5i557KRx99RGpqqkf3bTqYHnvsMSZPnuxRX4aQwZ1M0zlABxH5QkRWi8hMp2tPAQ8ALQ6AUE8CGpFjqsGKF+hqBgUwaBoc2QkHvvPN/c4wwkZBxdqiAuokcfXVV/PBBx9QU1MDQGFhIfv27eP1118nLy+PwYMH88gjj7hsm52dzeHDhwF4/PHH6d+/P5MnT25MHwDw/PPPc/bZZ5Obm8tVV13FiRMnWLp0KfPnz+f+++9n2LBh7Nixg9mzZ/PWW28BsHjxYoYPH86QIUO49dZbG2XLzs7mkUceYcSIEQwZMoTNmzf786sxtB13Mk1HAyPRM6UpwMMikiMilwEHlVKrW7uJu0lAg0VEjim7lWyxOQU10DLzbXyvrV+XgTAIFgvAxw/SZe866hoUKtaG+CKsedchcMkfmr2clpbGqFGj+OSTT7jiiiuYN28e1113HQ899BAdO3akoaGBSZMmkZ+fz9ChQ132sXr1aubNm8fatWupr69nxIgRjBypA0heeeWV3H777QD8+te/5sUXX+Tuu+9m6tSpXHbZZVx99dWn9FVdXc3s2bNZvHgxOTk5zJw5k3/84x/85Cc/AaBTp06sWbOGZ555hieeeIIXXghra1Ck4U6m6WLgsFLqOHBcRJYAucAIYKqIfA+IB9qLyGtKqZu8kujjB33/VH8mjqmGOkjupr32XJHUCbLP1Wa+C35tUnC0kbCZQUUhoE5/7PQnziYJhynizTffZMSIEQwfPpyCgoJTTAdN+eqrr5g+fTqJiYm0b9+eqVOnNl7bsGED48ePZ8iQIcydO5eCgoIWZdmyZQu9evUiJycHgFmzZrFkyZLG61deeSUAI0eOpLCw0NOPbPAPK4F+ItJLRGKB69HZp515DxgvItEikgiMBjYppR5SSmUppbKtdp95rZyCSMSNqYa65mdPDgZdoSNNlLQsj+F0wmMGdckfqKqqo7D0OH3S25EUFxixp02bxs9+9jPWrFlDVVUVHTp04IknnmDlypV06NCB2bNnU11d3WIfzaWpnz17Nu+++y65ubnMmTOHL774osV+WouZ6EhBEDLpBwyNKKXqReTHwALABryklCoQkTut688qpTaJyCdAPnqt6QWl1Aa/CdXCTMefRNSYUnb3FNTAqfDRfXoW1dWFM0WEs3T7YXK6JtOpXdvTJYXNDCo2OvDRJNq1a8fEiRO59dZbmTFjBseOHSMpKYmUlBRKSkr4+OOPW2x/3nnn8c4771BVVUVFRQXvv/9+47WKigq6detGXV0dc+fObSxPTk6moqLitL4GDBhAYWEh27dvB+DVV19lwoQJPvqkBn+jlPpIKZWjlOpjZZ12KKZnner8SSk1SCl1llLqKRd9fKGUuiyQcvuaiBpT9TWAcu3Bd8qHToee4wIbm2/nl/DZ47D0b7DmVdj0PuxaAvvz4ehuqC4Hu39/Sxvsiv9buJUbX/yW/1u41aM+wmMGhQ4YC4HfrDtjxgyuvPJK5s2bx4ABAxg+fDiDBw+md+/ejBs3rsW2I0aM4LrrrmPYsGH07NmT8ePHN1773e9+x+jRo+nZsydDhgxpHEDXX389t99+O08//XTjQi5AfHw8//rXv7jmmmuor6/n7LPP5s477/TPhzYY/EjEjKm6Kn1sbQYFOjbfhz+Hg5ugy6DW63vDiSPw5kyoPt0t/1QE4ttDfCrEp0CCdXQ+T+kBQ69t89rZoYoafvLvtXyzvZSrRmTxq0s9i6IfFuk2HBTsKyc1MZbM1IRAihdRmJQL3mPSbRgAOLaPTQUbGHj2RIiObblu5UF4Ikdn3D3/l/6Va8GvYPkz8IOvILU7VJXpGVN1uVZa1eVOZU7XmpbVndD93fwu9Dnf7dsv21HKPfPWcqyqjt9NO4tr87q32qa5MRU2Myiw9kIFcLOuwWAwNEtdFdhiWldOAO06nzTz+VNBHdkJ3/4Tht90cr0rPsWzvmoq4MnBsP4NtxSU3a545ovtPLlwK9mdknj1tlEM6Nres3tbhM0aFAR+L5TBYDA0i0NBucvgaXB4izbz+YtFvwVbLJz/K+/7ikuGs6br9aua09fwnCmtrGH2nJU88elWLs/NYP6Pz/VaOUGIK6im5seY6NBM/R4uhII51xBczP+Aj7DXoxpqIaoNCmrgVED8F5uv6FvtKTjuXkju6ps+c2/Qpr6NTXdFnGRl4REuffprlu8s5X+mD+Gp64bRzkee1iGroOLj4yktLT1lQMXahAa7osHP3ieRiFKK0tJS4uPjgy2KIUi4GlMGz1C1VZQeryc+pg3OA8ldoOdY/0SVUAo+/RW06wpjf+y7fruPgo59tJmvCXa74tkvd3D9c8uJj4ninR+N5YbRPZrdBuAJIbsGlZWVRXFxMc4xxU7UNnDkeC2UxTUmMTS4T3x8PFlZWcEWwxAkXI0pg4fUVBB/YBVZoy5vW7tB0+Dj+3UW3vT+vpNn47tQvBKm/g1ik3zXrwjkzoDPf6/d0zv0BODo8Vp+/p/1fLb5IJcO6cYfrhpCcnwbZpNuErIKKiYmhl69ep1StqboKLe/sZSXZudxwYAuQZLMYAhPXI0pg4e8f6+eCU35YdvaDbwcPn5Am/km/sI3stTXwMJH9H6sYTf4pk9ncq/TCir/3zDhAdYUHeXHc9dwuLKWx64YzM3n9PTprMmZsJqGONzL95a1vNPcYDAY/EpJgVYIbf1hbt8NepyjZzy+YsXzULYbLvrd6UkTfUFqD8gej1r/Bi8s2cG1zy7DZhPe+uEYZo7J9ptygjBTUOnt4oixCXuPVgVbFIPBcKZit0PJRvc26Lpi0DQ4uBEOeRZd4RROHIElf4S+F0KfC7zvr7nbDLwWObKTjz9+j0kDO/PB3eMZmuVZ+pO2EFYKKipK6JaSwL4yo6AMBkOQKCuEuuNeKCgrwK0vnCWW/Em7gF/4mPd9NcP6PWVc8XkaJ1Qcj/f+jmdvGklKgu/Xm1zRqoISkZdE5KCIbHAq6ygiC0Vkm3Xs4HTtIRHZLiJbRGSKrwXOTE1gr1FQBoMhWJRY0dY9VVDtM6C7D8x8pTu0eW/4zX4Jn6SU4uWlhVz97FJOkEB130sZcHgRUh+4JRZ3ZlBzgIublD0ILFZK9QMWW+eIyCB0SoDBVptnRMSnRtGMVDODMhgMQaSkABBI9yJs1KAroGQDHN7ueR+LHvXdptwmNNgVv3p3A4/ML2BCTjof3nMuHcfNgppjsPlDn9+vOVpVUEqpJcCRJsVXAC9b718GpjmVz1NK1SildgHbgVE+khWAzA4JlByrNht2DQZDcCjZAB17Q2yi530MukIfN77jWfui5bBpPpz7E72/yofU1tu5d95aXv+2iB9O7MPzM/NITYyF7POgfRasn+fT+7WEp2tQXZRS+wGsY2erPBPY41Sv2Co7DRG5Q0RWiciqtuzLyEyNx67gQLnx5DMYDEGgpMBz856DlEzIGgUFHqxDKaUDwiZ3gzF3eSdHE6pqG7jj1VV8kL+fhy4ZwC8uHnDSSy8qSruc71gMFQd8et/m8LWThCt/Q5fb1pVSzyml8pRSeenp6W7fIDNVP7UYM5/BYAg4tcd1QNbWckC5w+BpUPKdXktqCwVvw95VcMHDPt2UW15Vx8yXvmXJ1kP84coh/GBCn9Mr5c7QiRrz3/TZfVvCUwVVIiLdAKzjQau8GHCOrZ4F7PNcvNPJSNWheoyjhMFgCDgHN6OTFHo5gwInM18bnCXqa/TaU5chkHu99zJYHKqoYcZzy1m3p4y/3TCC60f1cF2xUz/IOluHPgpAyCxPFdR8YJb1fhbwnlP59SISJyK9gH7ACu9EPJUMa7OumUEZDIaAc7BAH33hNZeSpX/s2xI89tt/QlmRTzflFh89wbX/XMauw8d5cdbZfG9It5Yb5M7Q+7j2r/fJ/VvCHTfzN4BlQH8RKRaR24A/ABeKyDbgQuscpVQB8CawEfgEuEsp1eBLgeNjbHRqF2tmUAaDIfCUFEBMEqRm+6a/QVfAgXxtNmyNE0dgyRPQ76I2JRBsie0HK7nm2WWUVtbw2vdHcV6OG8stg6dr70EXAWR9jTtefDOUUt2UUjFKqSyl1ItKqVKl1CSlVD/reMSp/uNKqT5Kqf5KqY/9IbTeC2WcJAwGQ4ApKdCzpygfLd87zHzuzKK+/CPU+m5T7nfF5Vz7z2XUNSj+/YMxjOzZ0b2GiR2h/yXw3X+gvtYnsjRHWEWScJCRmsDeoyeCLYbBYDiTUEq7mPti/clBag/IHNl6VInSHbDyeRgxCzp7sf/KYtmOUmY8v5zEWBtv3TmGgd3amFww9wY4UQrbF3otS0uErYLaV1Zt8toYDIbAUbEfqo76xoPPmUHTYP86OLKr+TqLHoHoeJj4kNe3W7SxhFn/WkG3lHjeunMs2Z088ATsOwmS0mHd617L0xJhqaAyUxOoqmvg6Im6YItiMBjOFBwhjjr7OKxQozdfM7Oo3ct02vVx3m/KfWdtMT94bTUDuybz5g/G0DXFwwSmthgYci1sXaDXxvxEWCoo48lnMBgCTokVjtTXce869ISM4a7dze12nSk3OcPrTbkvLy3kp/9ez+heHZl7+zl0SIr1qj+GzQB7HWz4r3f9tEBYKqisDlpBFZu0GwaDIVCUFOhQPwkdWq/bVgZNg31r4WjhqeUFb8Pe1TDpYY9DKymleHrxNh6ZX8BFg7rw0uyzaRfng1y1XYfo/Vh+NPOFpYIyMyiDwRBwfBHiqDkGW+FMN84/WVZXDYt+qxXBUM825drtit9/uIknF27lyhGZPHPjCOJjfBi/e9gM2LdGp7D3A2GpoDokxpAQYzN7oQyGYKAUfHgfFH4dbEkCR30tHN7iPwXVIRu6DTvVzLfin1BeBBc97pFbe32DnQf+m8+LX+9i9thsnrg6l2ibj3/yh1wDYvPbLCosFZSIkJEab2ZQBkMwOLJTuzx/8FOw+3QffuhyeCvY6/2noEDPovau1pEijpfCkj9DvynQe0Kbu6qua+Cu19fw1upifjo5h0cuH0RUlB9Ss7frDH0nQ/6//fK/EJYKCiCzQ6KZQRkMwaBomT4e3qp/mM4EDnqZpNAdnL35vvxfqK3UIY084P638llQULCcaagAACAASURBVMIjlw/i3sn9TkYk9wfDZmgX/J1f+Lzr8FVQZgZlMASHomXaUaDbMPji//k9mkBIULJBh/dJ6+u/e3TsDV2HwsoXYdWLMHIWpPdvczdri47y/vp93DOpH7eM6+UHQZuQcwnEp/gl9FEYK6gEDlfWUl13hpgYDIZQoWi5Tll+wcPaHLX2lWBL5H9KCrSysMX49z6Dp8HRXV5tyv3Tgi2kJcVyx3m9fSxcM8TEw1lXwaYPoPqYT7sOWwVlPPkMhiBQeRBKt0PPMTqaQI8xOoBpXYSPw5IC30eQcMXg6drpYPzP9fpOG/l622GW7ijlrvP7+saV3F1yb4D6qralDnGDsFVQmZaCMutQBkMAKVqujz3GgAhc8Gu9/rDyxeDK5U+Ol+rP6M/1Jwcde8O96+Hcn7a5qVKKPy3YTGZqAjee00w+J3+RlafNn+t8a+YLWwVlZlAGQxAoWqbNT92G6fPsc6H3+fD1k1BTEVzZ/IUjB5SvQxw1R2p3rfzbyIKCA6wvLufeyf2Ii/bhXid3ENF5ooqWthxTsI2ErYLqmhJPlMBeE03CYAgcRcsgMw+incLkXPCwjmy9/NngyeVPHDH4AmHi85AGu+KJT7fSJz2JK4dnBkeI3OsB8alnZ9gqqBhbFF3ax5u8UAZDoKiphP350OOcU8uzRkL/S2HpX3W070ijZAMkdvJoTShQvL2mmO0HK7l/Sn/fb8Z1l5Qs6HWeT9PBh62CAkfiQpMXymAICMUrQTVoB4mmXPArqDkG3zwdeLn8jSPEkT/3EnlBTX0DTy3aRm5WClMGdw2uMMNu0PEEHXvlvCSsFZQjL5TBEOqIyMUiskVEtovIg83UmSgi60SkQES+tMq6i8jnIrLJKr83sJI7UbQcJAqyRp1+rctg7Wr87bPa0y9SsDfAwU3Nmvdq6+3kF5fx6rJC7vvPen7273UB3/oyd3kRe8uquH/KAP9uyHWHAZdBTJLPQh8F0A/R92R2SODjDfux25V/wngYDD5ARGzA34ELgWJgpYjMV0ptdKqTCjwDXKyUKhIRhz2pHvi5UmqNiCQDq0VkoXPbgFG0VP9QxzeTffX8X0LBO/DVk3DJHwIrm784sku7T3cZhN2u2Hm4knV7yskvLmN9cTmb9h2jtsEOQMekWI4cr6V9QgyPTg2Axx9QWVPP3z/fztg+aZzbr1NA7tkice10RIyCd+GSP3ocgd1BWCuojNQE6hoUhypr6NLew8RbBoP/GQVsV0rtBBCRecAVgLOSuQF4WylVBKCUOmgd9wP7rfcVIrIJyGzS1v801EHxKhh+c/N10vpoE8+qF2Hsj/WaRJiilGJfeTUlq75mBPDLbxTz3/2Uypp6AJJibQzJSuGWcdnkdk9laFYKmakJ/O6DTbz0zS7G9e3EhYO8Sy7oDi99vYvS47XcP6XtESf8xrAZsP512PwhDL3Gq67CWkFlOe2FMgrKEMJkAnuczouB0U3q5AAxIvIFkAz8RSl1SogGEckGhgPfurqJiNwB3AHQo4eP98EcyIe6E6c7SDRlwgOwfh58+UeYGj7rUZU19awqPEJ+cTnr9+jZ0eHKGn4a/SW5NmGrymD68C4MzUphWPdUeqe3w+bCavOLS/rz7a5S7n9rPR/fO55uKQl+k/no8VqeX7KTiwZ1YXgPP+So8pSe50JKD62kzmQF5dgLtfdoFSNC6Q9kMJyKK/tzUzenaGAkMAlIAJaJyHKl1FYAEWkH/Bf4iVLKZTwZpdRzwHMAeXl5vnGjcrDbWvTu4cJBwpnUHpB3i964O+5ePasKceob7Ez7+zdsP1iJCPRJb8d5OZ0Y1j2VqZtfRir78tbdk9zqKy7axt9uGMFlT3/FvW+s4/XbR/vNq+4fX+6gsrae+0Jp9gQ6NUjudfDVn+HYPmif4XlXPhQr4GSk6lmT2axrCHGKge5O51nAPhd1PlFKHVdKHQaWALkAIhKDVk5zlVJvB0De0ylapnMWte/Wet3x9+nAql/+r9/F8gWfFBxg+8FKfjt1MPmPXMSin03gyWuHMXNMNqnHthDVtW37n3p1SuJ3085iReER/vrZdr/IfKC8mpeXFjJ9eCY5XZL9cg+vyJ0Byg75b3rVTVgrqOT4GNrHR5twR4ZQZyXQT0R6iUgscD0wv0md94DxIhItIoloE+Am0W5ZLwKblFJPBlRqB0ppD74eY92rn9wFRt+hf5wObvKvbF6ilOL5r3aRnZbITef0JDneKRhsTYV2me7cdoeHK0dkceWITP762TaW7yz1ncAWf1m8DbtS/HRyjs/79glpfaD7aK/3RIW1ggKdF8rMoAyhjFKqHvgxsADYBLyplCoQkTtF5E6rzibgEyAfWAG8oJTaAIwDbgYusFzQ14nI9wL6AUq3w4nDra8/OTPuJxCXDJ8/7j+5fMCq3UdZv6eM287tdfqakkO5ehiD73dXnEXPtCR+Mm8dR4/7LiXJrsPHeXPVHm4c3ZPuHb3zkvMruTPg0GbYt9bjLsJfQaXGU2zCHRlCHKXUR0qpHKVUH6XU41bZs0qpZ53q/EkpNUgpdZZS6imr7GullCilhiqlhlmvjwIqfJGb60/OJHaEMXfBpve9+oHyN88v2UlKQgxXjXThcVhixeDzUEElxUXz1xnDOXK8lvvfWo/yUXSFP3+6hbjoKO4634+5qXzB4Olgi/MqT1TYKyi9WdcoKIPBb+xeBolp0Klf29qd8yOd2PCz3/tHLi8pPHychZtKuOmcHiTGuvAXKymA2GTt+OEhZ2Wm8ND3BrBo00HmLC30XFiLDXvL+SB/P7eO60V6cpzX/fmVhFQYcCl895bHSS3DXkFlpiZwrLqeiuq6YItiMEQmRctOptdoC/Httalv+6KTXoAhxEvf7CI6Spg1Jtt1BR+FOJo9NpvJAzvz/z7azIa95V719cSnW0hJiOH2QCUj9JbcGVB1BLYt8Kh52Cuok2k3TMgjg8HnVBzQGV7bsv7kzKg7oF0X+Ox3Pgsg6gvKTtTyn1XFTM3NpLOrPZRKnVRQXiIi/PHqXDomxXL3G2sbN/u2lRW7jvDFlkP8cGIfUhL8nNnXV/S5AJK76SDDHuCVghKRn1rxwTaIyBsiEi8iHUVkoYhss45+3aCU2cGxWdcEjTUYfE7j+pObHnxNiU3Ubue7v4Gdn/tOLi+Z+20RVXUNfH98L9cVyouhphy6+CYHVMekWJ66fhi7S4/zm/c2tLm9Uoo/frKZzslxzc/4QhFbNPx4lQ4m7AEeKygRyQTuAfKUUmcBNrT77IPAYqVUP2Cxde43TmbWNTMog8HnFC2HmEToNtTzPkbOgpTusDg0ZlG19XZeXlrI+H6dGNitmbiCjQ4SvssBdU7vNO6+oB9vr9nL22uK29T28y0HWbX7KPdM6kdCbICTEXpLXDuPm3pr4osGEkQkGkhEbz68AnjZuv4yMM3Le7RIers4YmxiEhcaDP5g91KdztvmhUkpOg4m/AL2rYEtgXVAdMX89fs4WFHDbec2M3sCpyy6A31677sv6Muo7I78+t0N7Dp83K02drviTwu20jMtkevO7t56gwjCYwWllNoLPAEUoYNZliulPgW6WAEuHYEuXWb5EpE7RGSViKw6dOiQp2IQFSV0SzGefAaDz6k+ppP1tcW9vDlyZ0BaX/jscbDbve/PQ5RSvPDVTnK6tGNCTnrzFUsKtPdefIpP7x9ti+Kp64cRGx3F3W+soaa+9dQc7+fvY9P+Y/zswhxigpWMMEh4Y+LrgJ4t9QIygCQRucnd9kqp55RSeUqpvPT0Fv5R3EAnLjQKymDwKcUrdLgaTx0knLFFw8SH9MykIDjRmgC+2V7K5gMVfP/c3i3nTiop8FuK94zUBP50dS4b9h7jfz/e0mLdugY7Ty7cysBu7bl8qOcx7cIVb9TxZGCXUuqQUqoOeBsYC5SISDcA6+j37GVmL5TB4AeKloPYIOts3/Q3+EodNujz/4EGzzzZvOX5r3bSqV0cVwxv4ce+rhoOb4POvnGQcMWFg7owe2w2L32zi8WbSpqt9++Ve9hdeoL7p+SckTnvvFFQRcA5IpJoxQubhA7jMh+YZdWZhY4x5lcyOyRQcqyauobgmQ4MhoijaDl0HaJDFvmCqCjtzXVkh07FEGC2llTw5dZDzBzTk7joFhwNDm/Rqe194GLeEg9eMoBB3dpz33/Wc6D8dCevqtoGnl68jbyeHTi/v8uVkojHmzWob4G3gDXAd1ZfzwF/AC4UkW3oDKJ+T62ZmRqPXeHyj2wwGDygvhaKV0JPD93Lm6P/9yBzpM4XVV/j275b4cWvdhEfE8VN5/RsuWKJlQvSTyY+B/ExNv56w3Bq6u3cO28tDfZTPRxfXlbIwYoaHrg4BFK5BwmvVtyUUo8opQZYscNuVkrVKKVKlVKTlFL9rOMRXwnbHJmpOmCiWYcyGHzE/vVQX+2b9SdnROCCX0P5Hlg9x7d9t8ChihreWbuXq0Zk0TEptuXKJRsgOh46+j9aQ5/0djx2xVl8u+sIf//8ZGqO8qo6/vHFDib2T2dUr45+lyNUiQiXEJMXymDwMZ4EiHWX3ufrrKtLnoDawGywf3X5bmob7Nzakmu5g5ICSB+gHTsCwFUjMpk2LIOnFm1lxS79PP/8kp2UV9Vx30UhlowwwESIgjqZWddgMPiAomXQsQ+088PahwhMehiOH4QVz/m+/yZU1zXw2vLdTB7YmT7pbmwa9VGII3cREX4/fQg9OiZy77y1bD9YwUvf7OKyod04K9O3bu7hRkQoqPgYG53axbKv3Cgog8Fr7HYrQaEfZk8OepwDfSbB8mf8vi/qv2uKOXK8lu+Pd8NkV3lQK84AKiiAdnHR/HXGCA5X1jDt70upqbfz8zN89gQRoqBA74UyeaEMBh9weKuOQN3TjwoKYOh1UFkC+/2XL8puV7z49S6GZKYw2p21HC9zQHnDkKwUfnHxACpr6rk2rzu9OiUFXIZQIzBG1gCQkZrA1pKKYIthMIQ//lx/cqbvZJAo2Pqp9uzzA59vOcjOQ8f5y/XD3POEOxgYD77muO3cXmR1SOTcfp2Ccv9QI6JmUHvLqnyWtdJgOGMpWg5J6f73YktK05uAt37it1s8/9VOuqXE870h3dxrUFKg04MkBUdBiAgXn9WVdnERM3fwiohRUBmpCVTX2Tl6wiQuNBi8omipZwkKPaHfRbB/nc475WM27C1n+c4j3DIu2/0YdiUb/BpBwtA2IkZBOfJCGVdzg8ELyvdCWZH/zXvAGyuK+J/tVjr1bQt93v8LX+0kKdbGdWe7mbK9oR4Obg7K+pPBNZGjoCxXc+MoYTB4gWP9yc8OEtV1DfxpwRae25rIQUmj8rsPfdr//vIqPsjfz3Vn93A/++yRHdBQE7T1J8PpRJyCMjMog8ELipZDTBJ0GeLX23yQv58jx2t54OIBfMVIZOfnfLmxbUn8WmLON4XYleKWcdnuNyqxMt2aGVTIEDEKKjUxhoQYmwl3ZDB4Q9Fy6H62X6MoKKV4eWkhfTu344cT+jDx8ptIkmpeeO01Xvp6l9eOTpU19by+oohLzupG946J7jcs2aijt6eb/UehQsQoKBEhs4NJu2EweExVmZWg0McBYpuwdk8Z3+0tZ9aYnogIaWdNRtnimJW+lcc+2Mgv39ngVWaCN1fuoaK6nu+PdyOskTMlBdApR2cANoQEEaOgQHvymRmUweAhxSsB5fsAsU14ZWkh7eKimT4iSxfEJiG9xjPJto67zu/DGyuKmPniCo4er21z3/UNdl76Zhd5PTswvEeHtjUuKYAuxoMvlIgoBZVpEhcaDJ6zeylERUNWnt9ucaiihg+/28/VI7NO3euTczFyZAf358Xwf9flsnr3UaY/8w3bD1a2qf9PN5ZQfLTKvbBGzlSXQ3mRWX8KMSJMQcVzuLKW6rqGYItiMIQfRcuhWy7E+i/EzhsriqhrUMwc0yQnU7+L9HHrAqYPz+KNO86hsqae6c98w5Kth9zu//mvdtIzLZELB3Vpm2ABygFlaBsRpaAyjCefweAZ9TWwd7Vf9z/VNdiZ++1uzstJp3fTqOIdeuoUF1ZUiZE9O/DuXePITE3gljkreXlpYavOE6t3H2FtURm3juuFra3p0Y0HX0gSUQrK4Wpu1qEMhjayb63eA+RHBbWg4AAlx2qY1XT25KDfRdrMWKNjamZ1SOS/PxzL+f0788j8Ah5+r2XniRe+2kVKQgzX5GW1XbiDGyE+Bdpntr2twW9ElIIyMyiDwUMaA8T6z0HilaW76d4xgYn9m8kxlTMF7HWw4/PGoqS4aJ67eSR3TujDa8uLmP2vFZSdON15oqj0BAsKDnDD6B4kxnrgIl9SAJ0HBya8k8FtIkpBdU2JJ0pM4kKDoc3sXgZp/fwWJHXjvmOsKDzCzHOymze/dR+tZzHbFpxSHBUlPHjJAP58TS4rdx1l+jNL2XnoVOeJl77ZhS1KmD02u+3CHdsPxaugx+i2tzX4lYhSUDG2KLq0j2dvWXWwRTEYwge7HfYs92t4o1eWFRIfE9Wy+c0Wo5MYblvoMonhVSOzeP320RyrqmPa37/h622HASg/Ucebq/ZweW4GXdrHt124da+BaoDhN7e9rcGvRJSCAkfajRPBFsNgCB8ObdZu1n5afyo7Ucu76/YyfXgmqYmxLVfOmWIlMVzn8nJedkfevWsc3VISmPWvFby6rJDXVxRxoraB75/rQXoQux1WvwK9zoO0Pm1vb/ArEaegMlIT2GdmUAaD+xQt1Uc/Kag3V+2hus7OzDHZrVfuOxkQ2PZps1W6d0zkvz8ay8ScdB5+r4D/W7iVcX3TGJTRvu3C7fxM738aeUvb2xr8TsQpqMwOCewvr8JuN4kLDQa3KFoO7bpCh2yfd91gV7y6fDejenVkYDc3FEhSJ71ReOuCFqu1i4vmuZl5/OC83tTb7fxwQl/PBFz1L0jsBAMu86y9wa9EnILKSE2grkFxqLIm2KIYDOHB7mXae88PHmyfbz7IniNVzHJn9uQgZwrsWwOVB1usZosSHvreQPIfneJZivSKA7DlYxh2A0S3Yno0BIWIU1BZJi+UweA+ZXvgWDH09E+A2JeXFdK1fTwXDW5DZId+U/TRzSSGHqdHX2s5R4yY5Vl7g9+JOAVl9kIZQhERuVhEtojIdhF5sJk6E0VknYgUiMiXbWnrMUXL9dEP+592HKrkq22HuXF0D/dTrgN0HQLJGY1RJfyC3Q5rXobs8dDJQ/Ogwe9EoILSbqYmmoQhVBARG/B34BJgEDBDRAY1qZMKPANMVUoNBq5xt61XFC2F2GS/xKB7ddluYm1RzBjtZsp1ByLQ70K9Ybe+7RHN3WLn5zq1fZ5xjghlIk5BJcfH0D4+2sygDKHEKGC7UmqnUqoWmAdc0aTODcDbSqkiAKXUwTa09Zyi5dB9FETZfNYl6KSBb60u5tKh3ejUzoP8SjkXQ23FyQgXvmb1vyAxzThHhDgRp6AAMjskmmgShlAiE9jjdF5slTmTA3QQkS9EZLWIzGxDWwBE5A4RWSUiqw4dciMC+IkjOgadH9zL315TTGVNPbM8iewA0HsC2OJadDf3mFOcI0xywlDGKwUlIqki8paIbBaRTSIyRkQ6ishCEdlmHduYNawJxath3ettapKZGm9MfIZQwpV7XNN9ENHASOBSYArwsIjkuNlWFyr1nFIqTymVl56e3rpUe1boo48jSDhSuudmpTCse6pnncQmQfa5rbqbe8S6uWCvhxGzfd+3wad4O4P6C/CJUmoAkAtsAh4EFiul+gGLrXPPWfsKfHgf1LmvcDJNZl1DaFEMdHc6zwL2uajziVLquFLqMLAEPabcaesZRcsgKgYyR/qkOwffbC9lx6Hj7m3MbYmcKVC6DUp3+EQuwIocYZwjwgWPFZSItAfOA14EUErVKqXK0Pbxl61qLwPTvJJw8HSoO+62yyloT76K6nqOVdd5dWuDwUesBPqJSC8RiQWuB+Y3qfMeMF5EokUkERiNfuBzp61nFC2DjOEQk+CT7hzMWVpIWlIslw7t5l1HjiSGvjTz7fwcynbDyNm+69PgN7yZQfUGDgH/EpG1IvKCiCQBXZRS+wGso8vY+m7by3ueq3d6F7zjtmCZHYyruSF0UErVAz8GFqCVzptKqQIRuVNE7rTqbAI+AfKBFcALSqkNzbX1Wqi6Kti7xufu5XuOnGDx5hKuH9Wd+BgvHS869oJO/X1r5ls9BxI6wsDLfdenwW94uMOtse0I4G6l1Lci8hfaYM5TSj0HPAeQl5fXfFwiWzQMmgrr50HtCYhNbLVv571QA7p6EJ/LYPAxSqmPgI+alD3b5PxPwJ/caes1e9fo3Es+dpB47dvdRIlw4+hmkhK2lZyL4Nt/6iSGccne9VVRAls+gtF3GueIMMGbGVQxUKyU+tY6fwutsEpEpBuAdWw5Xok7DJ4OdSfcnupnNWbWNUFjDQaX+CFBYXVdA/9euYeLBnVpfEj0mn5ToKEWdn7hfV8O5whj3gsbPFZQSqkDwB4R6W8VTQI2ou3jjtghs9C2de/oOQ6S0t0283VqF0esLcq4mhsMzVG0HNIHQGJHn3U5f90+yk7Uee5a7ooe50BcivdmvlMiR/TzjWwGv+ONiQ/gbmCutXi7E7gFrfTeFJHbgCKsHfFeEWWDQVfA2rlQe1y7oLZUPUrolhpv1qAMBlfYG2DPt3DWVT7rUinFnKWF9O+SzOhevlN62GKg7wXaSUopzwPa7voCjhbCBQ/7TjaD3/HKzVwptc7adzFUKTVNKXVUKVWqlJqklOpnHY/4RNLB06G+yu0nqYwU42puMLjk4EaoOebT9afVu4+ycf8xZo3NRnwdFb3fFKg8APvXe96HwznCRI4IK8InkkSPMdCui9tmvswOCWYGZTC4wg8BYucsLaR9fDTThmf4rM9G+l1Ia0kMW6TyIGz+UEeOiPEgJbwhaISPgnKY+bZ9CjWVrVbPSE2g5Fg1dQ32AAhnMIQRu5dC+0xIbWMQ12YoOVbNJxsOcG1edxJjvV01cEFSJ72Z2NPo5o2RI0xajXAjfBQUWGa+arf+UTNT47ErOFBuPPkMhkaU0h58PkxQOPfbIhqU4uYxPnItd0XOFO0aX+lGjEFnHJEjep4L6Tn+kc3gN8JLQXU/R6emdsPMl5mq90uZdSiDwYmy3VCx32frT7X1dl7/tojz+3emZ1rLzktekTMFULDd/YgyAOz6Eo7uMq7lYUp4KaioKBg8TXv01FS0WNWRF8qsQxkMTjSuP/lGQX28YT+HK2uY6c/ZE0DXoZDcre3u5qvnQEIHEzkiTAkvBQXazNdQA1taNvM5NgqavVAGgxOZeXDhY9B5oE+6e3lpIb06JXFePzeip3tDYxLDz6DBzRiblQdh8weQa5wjwpXwU1BZo3Q66FbMfPExNjq1i2VfuVFQBkMjnfrCuHt9kqDwu+Jy1hSVcfM5PYmK8rFruSv6TdHu8e4mMVz3uhU5wjhHhCvhp6AcZr7tC6H6WItVM1MTKDYzKIPBL7y8rJDEWBtX52UF5oa9J4It1j0zn92uzXs9x0F6/1arG0KT8FNQYJn5anVWzBbISDV7oQwGf3DkeC3z1+/jyhGZtI+PCcxN49rpJIbu7IcqXGKcIyKA8FRQmXnQPqtVM58jcaFSzQdLNxgMbWfeyiJq6+3eJyVsK/2mwOGtcGRXy/VWz4H4VBg4NSBiGfxDeCooh5lvx2KoKmu2WkZqAtV1do6eMIkLDQZfoZRi7vIixvZJI6eLlykw2kqOG0kMKw/Bpg9M5IgIIDwVFLhl5nMkLjSefAaD79hdeoK9ZVVcNtQPYY1ao2NvSOvX8mb99a/rXFfGvBf2hK+CyhwJKd1bNPNlNuaFMgrKYPAV+XvLAcjtnhIcAXKmQOHXrkOeOZwjeow1zhERQPgqKBHLzPcZVB11WcUoKIPB9+TvKSMuOirw5j0HOVYSw11fnn6t8Cs4stPMniKE8FVQoM189jrY7DobdmpiDAkxNuPJZzD4kPzicgZltCfGFqSfjx5jIK69a3dzh3PEIOMcEQmEt4LKGKEjMjdj5hMRMjskmDUog8FHNNgVG/aVk5uVGjwhbDHQ53ztKOHsoXv8MGx6H3JnQIyPUs4bgkp4KygRPYva+TmccJ0XMSM1wUSTMBh8xPaDlZyobWBoVpDWnxz0m6KD3h7IP1m2zjhHRBrhraDAMvPV64RkLshMNTMog8FX5BfrbR1DgzmDgpNJDLda7uZKWc4RY6DzgGBKZvAh4a+gug2DDtnNmvkyU+MpPV5LdV1DYOUyGCKQ/OJy2sVF07uTH1NruEO7zpA5ArZZ61CFX8GRHWb2FGGEv4JqNPN94dLM17gXyjhKGAxek19cxlmZ7QMTHLY1+k2B4lV67Wn1HIhP0Vm3DRFD+Cso0ApKNegF0iZkpGgFZTz5DAbvqK23s2l/RXAdJJzJuQhQsH6ecY6IUCJDQXUdqneYuzDzmWgSBoNv2HzgGLUN9uCvPznomqszbH/2e70vypj3Io7IUFAOM9+uJXq670SX9vFEiZlBGQzekl+sI0gE3YPPQVSUdpaor4Lu5/gsCaMhdIgMBQXNmvlibFF0bR/P3rLqIAlmMEQG+cVldEyKJatDCJnR+l+ij2b2FJFEjoLqchak9XVp5stITWBv2YkgCGUwRA75xeUMyUxBJAQcJBzkXAI3/heGXhdsSQx+IHIUlMPMV/iVDrfvRGaHBPaZGZTB4DEnauvZWlJBbqiY9xxERUG/yfpoiDgi6686eDooO2yaf0pxRmoC+8ursNtN4kKDwRMK9h3DrkJgg67hjCKyFFTnQdAp5zQzX2ZqAnUNikOVNUESzGAIbxodJIKVYsNwRhJZCsph5tv9DVSUNBY70m4UHTHrUAaDJ+QXl9EtJZ7OySZDrSFweK2gRMQmImtFjcQRMwAAF8dJREFU5APrvKOILBSRbdaxg/ditgEXZr6hWSnEx0TxxoqigIpiMEQKDgcJgyGQ+GIGdS+wyen8QWCxUqofsNg6DxydB0L6ACh4t7EorV0cN43uybtr97LzkIssnAaDoVnKq+rYdfg4ud3N+pMhsHiloEQkC7gUeMGp+ArgZev9y8A0b+7hEY1mvgONRT+Y0IfY6Cj++tn2gItjMIQz34XaBl3DGYO3M6ingAcAu1NZF6XUfgDr2NlVQxG5Q0RWiciqQ4cOuariOYOmAQo2njTzpSfHMWtMNu+t28sOM4syBBgRuVhEtojIdhE5zaogIhNFpFxE1lmv3zhd+6mIFIjIBhF5Q0QCuhCUv9dKsZFpZlCGwOKxghKRy4CDSqnVnrRXSj2nlMpTSuWlp6d7KoZrOg/QHn1NvPnuOK838TE2nl68zbf3MxhaQERswN+BS4BBwAwRGeSi6ldKqWHW6zGrbSZwD5CnlDoLsAHXB0h0APL3lNMzLZGUxJhA3tZg8GoGNQ6YKiKFwDzgAhF5DSgRkW4A1vGg11J6wuDpULQMju1rLEprF8fMMdnMX7+P7QcrgiKW4YxkFLBdKbVTKVWLHi9tyQsRDSSISDSQCOxrpb5PyS8uM/ufDEHBYwWllHpIKZWllMpGP9F9ppS6CZgPzLKqzQLe81pKT3Bh5gM9i0qMsfGXxWYtyhAwMoE9TufFVllTxojIehH5WEQGAyil9gJPAEXAfqBcKfWpq5v4w2x+qKKGfeXVoRdBwnBG4I99UH8ALhSRbcCF1nngSc/R8fmamPk6JsUya2w2H+TvY2uJmUUZAoKr4HVNw5qsAXoqpXKBvwLvAljbNK4AegEZQJKI3OTqJv4wm4dMinfDGYlPFJRS6gul1GXW+1Kl1CSlVD/reHqa20AxeBrsWQ7le08pvn18b5Jio/nLIrMWZQgIxUB3p/MsmpjplFLHlFKV1vuPgBgR6QRMBnYppQ4ppeqAt4GxgRFb73+KEhic0T5QtzQYGomsSBJNGTRdHzeeamXskBTL7LHZfPjdfjYfOBYEwQxnGCuBfiLSS0Ri0SbxU2zPItJVrDDhIjIKPTZL0aa9c0Qk0bo+iVP3HfqV/OIy+nZuR1JcdKBuaTA0EtkKqlNf6DrEZQqO74/vRXKcmUUZ/I9Sqh74MbAArVzeVEoViMidInKnVe1qYIOIrAeeBq5Xmm+Bt9AmwO/QY/a5AMlNfnG5Me8ZgkbkPxYNng6LH4OyPZB60sqSmhjLLeOyefqz7Wzcd4xBxoRh8COW2e6jJmXPOr3/G/C3Zto+AjziVwFdsLesitLjtcZBwhA0InsGBZY3H6eZ+QBuO7c3yfHR/GXx1gALZTCEPidTvJsZlCE4RL6CSusD3XJdmvlSEmO4dVwvFhSUULCvPAjCGQyhS35xOTE2YUC35GCLYjhDiXwFBdrMt3cVHNl12qVbz+1Fcnw0T5m1KIPhFPKLyxjQtT1x0bZgi2I4QzkzFNSQayA6HhY+fNqllIQYbh/fm4UbSxqDYhoMZzp2u+K74nITINYQVM4MBZWSBRN+AZveh00fnHb5lnHZpCTE8NQisxZlMADsKj1ORU09uWb9yRBEzgwFBTD2bh1Z4qP7ofrUvU/J8THcPr4XizcfZP2esiAJaDCEDt+ZFO+GEODMUVC2GLj8aajYr93OmzBrbDapiWYWZTAArC8uIyHGRt/0dsEWxXAGc+YoKICskTD6B7DyBdiz4pRLehbVm8+3HGJt0dEgCWgwhAb5xeUMzmhPtO3M+okwhBb/v707j46zOu84/n00q7bRSJas3Su2ZEEA4yW2aQzYSQnghrTNIUCgxCmBJARMIBtJszWnSUopW0MSSAKB4FNaA03BARySUMISDHiRZFtehcFaLdnSaNdopNs/3tFqGRNb6L2Sns85Ou+87yx6NJqrn+673Dv1Pn2r/glCefD0OohFh911zYpZpCf59Iw+NaXFevvYWaMjSCj3Tb2ACqTCJf8Oh3fBq/cOuysl4OW6lXN5cW8DW97WXpSamvbWt9HV08dZevxJuWzqBRRA0UXOCBMv3g6Nw+eF+oflM8lI9uuxKDVllVfrFBvKDlMzoAAu+lfn2qiNN4MZnJonOeDl+pVzeGlfI1vedm+mEKXcUloVITXoZda0JLdLUVPc1A2o1Bz4yPfg4Euwff2wu65ePpPMFD93Pa/HotTU40zxnkZ89g+lXDN1AwrgnGtgxgrY9E1oG5wiO8nv5fqVc3l5fyOvv6W9KDV1dPX0sru2VXfvKStM7YBKSIC/uRt6OmDTbcPuumrZTDJTAtz1vB6LUlNHRW0LsT6jU2woK0ztgALIKoIP3QrlG2Df8wObE/0ePn/+XP5ceYTXKo+4WKBS46e8WqfYUPbQgAL4qy9B5nzYeAtE2wc2f+qDM5ieqr0oNXWUHoqQmeInNy3odilKaUAB4A04wyBF3oEXfjCwOehzelGb3zrKqwcaXSxQqfHhnCAR1hMklBU0oPrNXA6L1sJrP4Ga7QObr1g6g+xQgLuf34cZcjq6UpNNW3eM/Q1tOsWGsoYG1FAf/i4kZ8FTN0JvDHB6UV84/zReP3iUVw/osSg1ee2ojmAMOsWGsoYG1FCJYbjodqgrg80/Hdj8ySWF5ISC3PX8Xu1FqUmrf4qND2gPSllCA2qkkkth/kXOsaimg4DTi7rhgrm8+XYTL+3TY1FqciqtaiY/nEhmSsDtUpQCNKCOJQKX3AGSAL+9dWAYpMuWFJIfTuTLG0rZV9/qcpFKjb0yneJdWUYDajRpBbD627D/97DjCQACXg8PfnoJBrjs/j+zI369iFKTQVN7lHeOduj1T8oqGlDHs+RayF8Ez34NOpzhjopyUtlw/XKS/F6ueOA13jiowyCpyaEs/g+XjiChbHLSASUihSLygohUiMhOEVkX354hIs+LyL74Mn3syh1HCR7n2qiuZvjdtwY2z8pMZsPnlpOVGuDqX27mpX0N7/IiSk0M5VXOFBtnaEApi5xKDyoG3GqMWQAsA24QkRLg68AfjDHzgD/E1yemnDNgxY2w/VGofHFgc144kf+6fjmzpiXzj796k00761wsUqlTV1oVYU5mMqGgz+1SlBpw0gFljKk1xmyN324FKoB84FLg4fjDHgY+fqpFuuq8r0H6bGfeqJ7Ogc1ZqQEeu24ZJXkhvrB+K7/ZVu1ikUqdmv4pNpSyyZgcgxKRWcBCYDOQbYypBSfEgOlj8T1c40t0Rjw/Wgl/umPYXeEkP49e+0GWzsrgS/+9nfWb33apSKVOXn1LF/Ut3XqChLLOKQeUiKQATwA3G2Na/oLnXScib4rImw0Nlh/HmXM+nHUlvHI31JUPuysl4OWhtUu4oGg63/yfHdz/4gFXSlTqZJUeco4/nVWoPShll1MKKBHx4YTTemPMk/HN9SKSG78/Fzg82nONMQ8YYxYbYxZnZWWdShnj48J/gWAYfr4KnvgsvLN54BqpoM/Dz65axCVn5vLDZ3dz5+/26IgTasIor47gSRBKcjWglF1O5Sw+AX4JVBhj7hxy11PANfHb1wD/e/LlWSQpA679vTOg7N7n4MG/hvs/BFsehmgHfm8C916+kMsWF3DvH/fz/Y0VGlJqQiitijBvegqJfo/bpSg1zKn0oM4FrgZWicj2+NfFwI+Aj4jIPuAj8fXJIWM2XHw73FIBa+6Cvj54+ia4sxie+waepkp+9HdnsvbcWTz4ylvc9mQ5vX0aUspexhjKqpp1gFhlJe/JPtEY8zJwvEljVp/s604IgRRY/BmnN/XOn+H1n8Pr98Nr95EwdxXfXnItqf7Z3PvCW7R1x7jrk2fj8+g10co+h4520tzRw5l6/ElZ6KQDSuGM2zdzhfPVWgdbH4E3H0Ieu5Jb0mawouRSvlB2Op+L9nLfp84h6NNdKMoupfELdLUHpWyk/9aPldQcOO+rcHMZXPYIpM9kWeV/8Ebijaw58F1+8MAjtHf1uF2lUsOUV0fwexOYn53qdilKHUMDaqx5fM6UHZ/eCDe8jmfJWtYEtvHPDTdTd8cyOl77FUQ73K5SKcA5xXxBbgi/V/8UKPvop/L9lFUEF/8bvq/sYefC79Db00XSc+vou2M+bFgLZRugs8ntKtU4EJGPisgeEdkvIscM/yUi54tIZMgJR98ecl9YRB4Xkd3xsS+Xj0VNvX2GHdURHSBWWUuPQY2HQCqnX3oLfyq+iu8/+msu632V1Xv/j6SdT4J4nGNYRRdD0UXOmYJqUhERD3AfzlmtVcAbIvKUMWbXiIe+ZIxZM8pL3AM8Z4z5hIj4gaSxqKuyoY32aK+OIKGspQE1jlYWTSf52rX88Jnl3PT2Ec6WA1wZ3snqhi1kHLwNNt0GWQucoCq62JnuI0E7uZPAUmC/MaYSQEQewxmzcmRAHUNEQsBK4NMAxpgoEB2LokqrdIoNZTcNqHG2aGYGj39+BdXNnWwsLeHhskV8pfrjzJR6PpO1mwt7t5L9yj3Iy3dC8nSYf6ETVnPOB/+Y/OOsxl8+cGjIehXwwVEet1xESoEa4MvGmJ3AHKABeEhEzgK2AOuMMe0jnywi1wHXAcyYMeOERZVXNZPk9zAnK+Uv/HGUGh8aUC7JDydy/Xlzuf68uRxoaGNjaS2PlM7hOzXnkZHQznV5lVzi307Brt8g234N3iDMucDpXc3/KKRmu/0jqPdutOsFR17BvRWYaYxpi1/w/htgHk4bPQe40RizWUTuwZnC5lsjno8x5gHgAYDFixef8Arx0qoIZ+Sn4Uk43uWMSrlLA8oCc7NSWPfhedy0+jQqalt5uqyGR0sz+VHVB0j2forPFtby8aRSZta/iOx91nlS/iKYXuJMTx/Kh7R8SCt0bmtPyzZVQOGQ9QKcXtKAoQMtG2OeEZGfiEhm/LlVxpjN8bsfZwzmWIvG+thV28I1y2ee6ksp9b7RgLKIiFCSF6IkL8RXLyxi26Fmntpew/ryRO5uzSfZv4Zr5nbwiZQyZjW9SsLeTdA+yli8iekQKnBCqz+8+tfTCiA1D7z+8f8Bp643gHkiMhuoBi4Hrhz6ABHJAeqNMUZEluKcYXskvn5IRIqMMXtwRmk54bGrE9lb30o01qcnSCiraUBZSkQ4Z0Y658xI51trSthceYSny2pYX17HTzqXkpZ4LgtnhDnj9CBnhzspToyQyxE8bTUQqYaWamd5aPMop7ILpEw/NrxC+YM9stQcZ9p7dcqMMTER+SKwCfAADxpjdorI5+L3/wz4BPB5EYkBncDlZnC04RuB9fEz+CqBtadak44goSYCDagJwJMgrDgtkxWnZfK9j53By/sbeLa8jvLqCK/sb6Sn1/k75veGmZ9dwIKcEAtmhCjOTaUkN0TY2xMPraoh4VXlLBv2woEXINo2/JuKB1JzR++F9QdZcpYz3JM6IWPMM8AzI7b9bMjtHwM/Ps5ztwOLx7Ke8qoI4SQfhRmJY/mySo0pDagJxu9NYFVxNquKnZMkorE+DjS0UVHbQkVtC7vrWnlhz2E2bKkaeE5uWpDinFQW5OZRnFtMSUkqs6Yl4+0fwNYY6IoM9rr6g6w/xGq2we7fQm/38GI8fgjlOce+MudBZhFkzXeWoTwNL4uVVkX4QH4aor8jZTENqAnO701gQW6IBbmhYdsbWruHhVZFbQsv7WskFp/+IxAff21uVjJ54URyw4nkpWWSm1ZIXkGQtETf8D9exkB74+i9sOZ3YMcTTsgNFJYaD635g6GVVQTps8GjHzs3dUZ72VvfyuriuW6XotS70r8Uk1RWaoCs1CxWzh+crbg71suBw+3x0GqhoraVNw42Ud9SOxBc/RJ9HvLCQSe80oLkpiWSFw6Sm1ZA3rTTyJ2TSHJgyMfHGGg7DI17oGEPNO51vt76E5Q9Nvi4BB9MmxsPriJnmTnfCTN/8vv9tihgV22E3j7DmXqBrrKcBtQUEvB6Bs4SHKq3z9DY1k1Ncye1kS5qmjupae6iNtJJTaSLPXUNNLR1M3KC4LREH7lpTohlh4LkhILkpM0iO62YnBnOelqiD+luhcZ9Q8JrHxze5ew2NL2DL+hLAm8APAFn2f/lCTjXgXn98eW7PMaXCIlhCIaHLxPTndfXXVqU9Y8gUagnSCi7aUApPAlCdihIdijIwuM8Jhrro76lazDEIp3UNg+ulx5q5kj7sSPwBH0JA6+dE1pATtpCsguD5JweJDcF8vrqmNZ5EN/R/dAdgVj3kK8u6I06y1gUulog1uAcC+vfFusafOwx176OkOAbPbxGWxYsmbQXQ5dVRZieGiA7FHS7FKXelQaUek/83gQKM5IozDj+RcDdsV4Ot3RT19JFXaSL+viyrsW5ve1QE/U7u4nG+oY9T8TPtOSzSU/ykxL0khr0kRrwkhr0kpIUXw96SQl6CQW9pAQG11ODXkJBHwGPIKYXou3Q1QydzccuO5uGb2tvgCP74usRhgXcFY85o3ZMQqVVzXr9k5oQNKDUmAl4PScMMWMMTR09gwE2JMwinT20dceIdPZQ1dRBW1eM1q4YnT29x329ft4EccIq0Uc4yU9Gko/0pDDhpOlkJMe35fgJJ/nISPaTnuTcDnjj13r19UF3y2CApc8ao3fFLi1dPVQ2tPO3Z+e7XYpSJ6QBpcaViJCR7Ccj2X/MsbDjifX20dbthFVrVyx+u8dZj9/uD7NIZw9NHVEa26LsrW+juSNKe/T4AZfs95AeDyxn6SM9yc/lSxMonoSXCO2IH386U48/qQlAA0pZz+tJIJzkJ5x0csMzdcd6ae5wgutoe5Tmjp74MsrR9h5n2RGlqaOHg43tNHVEOb8oi+Kc9xagE0ltpIuAN4Ez8/UMPmU/DSg16QW8HrJDHj0pAPj7RQVcenbe4EXaSllMP6VKTTEaTmqi0E+qUkopK2lAKaWUspIGlFJKKStpQCmllLKSBpRSSikraUAppZSykgaUUkopK2lAKaWUspKYkZP8uFGESAPw9rs8JBNoHKdyTkRrOZYtdcD41DLTGJN14oe55wRtaqr9vt4rreVY41XHqG3KioA6ERF50xiz2O06QGuxuQ6wqxZb2fQeaS2js6UWt+vQXXxKKaWspAGllFLKShMloB5wu4AhtJZj2VIH2FWLrWx6j7SW0dlSi6t1TIhjUEoppaaeidKDUkopNcVoQCmllLKS9QElIh8VkT0isl9Evu5SDYUi8oKIVIjIThFZ50YdI2ryiMg2Ednoch1hEXlcRHbH35/lLtbypfjvZ4eI/KeI6BS6I9jQnuJ1WNWmtD2NWovr7cnqgBIRD3AfcBFQAlwhIiUulBIDbjXGLACWATe4VMdQ64AKl2sAuAd4zhhTDJyFSzWJSD5wE7DYGHMG4AEud6MWW1nUnsC+NqXtaQhb2pPVAQUsBfYbYyqNMVHgMeDS8S7CGFNrjNkav92K86HJH+86+olIAXAJ8Au3aojXEQJWAr8EMMZEjTHNLpbkBRJFxAskATUu1mIjK9oT2NWmtD0dl+vtyfaAygcODVmvwsVgABCRWcBCYLOLZdwNfBXoc7EGgDlAA/BQfPfIL0Qk2Y1CjDHVwB3AO0AtEDHG/M6NWixmXXsCK9qUtqcRbGlPtgeUjLLNtfPiRSQFeAK42RjT4lINa4DDxpgtbnz/EbzAOcBPjTELgXbAreOE6Ti9gdlAHpAsIle5UYvFrGpP4H6b0vY0Olvak+0BVQUUDlkvwKXdNiLiw2lI640xT7pRQ9y5wMdE5CDOLppVIvKoS7VUAVXGmP7/fB/HaWBu+DDwljGmwRjTAzwJrHCpFltZ057Amjal7Wl0VrQn2wPqDWCeiMwWET/OQbqnxrsIERGc/cIVxpg7x/v7D2WMuc0YU2CMmYXzfvzRGONKT8EYUwccEpGi+KbVwC43asHZFbFMRJLiv6/V2HHQ2yZWtCewp01pezouK9qTd7y/4V/CGBMTkS8Cm3DOInnQGLPThVLOBa4GykVke3zbN4wxz7hQi21uBNbH/+BVAmvdKMIYs1lEHge24pwhtg17houxgkXtCbRNHY+2pyF0qCOllFJWsn0Xn1JKqSlKA0oppZSVNKCUUkpZSQNKKaWUlTSglFJKWUkDSimllJU0oJRSSlnp/wFXP9+JqBHPygAAAABJRU5ErkJggg==\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ - "2560/2560 [==============================] - 0s 20us/step\n", + "52/52 [==============================] - 0s 2ms/step - loss: 8.1796 - accuracy: 0.6223\n", "\n", - "Accurancy: 0.6613\n" + "Accuracy: 0.6223\n" ] } ], "source": [ - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Dense(100)(text_input)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_morph_train, y_morph_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_morph_test, y_morph_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.4f}'.format(scores[1]))\n", + "run_experiment(construct_linear(), morph_dataset, num_epochs=10)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## CNN" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "def construct_cnn():\n", + " text_input = layers.Input(shape=(max_document_length,))\n", + " x = layers.Embedding(vocabulary_size, embedding_size)(text_input)\n", + " convs = [layers.MaxPool1D()(layers.Conv1D(128, fsz, padding='valid', activation='relu')(x))\n", + " for fsz in [3, 8]]\n", + " x = layers.Concatenate(axis=1)(convs)\n", + " x = layers.Flatten()(x)\n", + " x = layers.Dense(128, activation='relu')(x)\n", + " x = layers.Dropout(dropout_keep_prob)(x)\n", + " preds = layers.Dense(3, activation='softmax')(x)\n", "\n", - "# Save the model\n", - "model.save('word_saved_models/Linear-Morph-{:.3f}.h5'.format((scores[1] * 100)))" + " return Model(text_input, preds, name=\"CNN\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## CNN - Token" + "### CNN - Token" ] }, { "cell_type": "code", - "execution_count": 105, + "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Train on 8195 samples, validate on 2049 samples\n", "Epoch 1/5\n", - "8195/8195 [==============================] - 111s 14ms/step - loss: 0.6998 - acc: 0.6997 - val_loss: 0.6503 - val_acc: 0.7291\n", + "164/164 [==============================] - 3s 20ms/step - loss: 0.5658 - accuracy: 0.7730 - val_loss: 0.4082 - val_accuracy: 0.8492\n", "Epoch 2/5\n", - "8195/8195 [==============================] - 108s 13ms/step - loss: 0.5681 - acc: 0.7799 - val_loss: 0.4971 - val_acc: 0.8072\n", + "164/164 [==============================] - 3s 18ms/step - loss: 0.3046 - accuracy: 0.8964 - val_loss: 0.3442 - val_accuracy: 0.8775\n", "Epoch 3/5\n", - "8195/8195 [==============================] - 103s 13ms/step - loss: 0.4006 - acc: 0.8614 - val_loss: 0.4010 - val_acc: 0.8619\n", + "164/164 [==============================] - 3s 18ms/step - loss: 0.2035 - accuracy: 0.9322 - val_loss: 0.3330 - val_accuracy: 0.8873\n", "Epoch 4/5\n", - "8195/8195 [==============================] - 103s 13ms/step - loss: 0.2916 - acc: 0.9042 - val_loss: 0.3629 - val_acc: 0.8751\n", + "164/164 [==============================] - 3s 18ms/step - loss: 0.1529 - accuracy: 0.9479 - val_loss: 0.3453 - val_accuracy: 0.8887\n", "Epoch 5/5\n", - "8195/8195 [==============================] - 108s 13ms/step - loss: 0.2275 - acc: 0.9302 - val_loss: 0.3543 - val_acc: 0.8834\n" + "164/164 [==============================] - 3s 18ms/step - loss: 0.1181 - accuracy: 0.9606 - val_loss: 0.3620 - val_accuracy: 0.8936\n" ] }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ - "2560/2560 [==============================] - 9s 4ms/step\n", + "52/52 [==============================] - 0s 5ms/step - loss: 0.3046 - accuracy: 0.9094\n", "\n", - "Accurancy: 0.892\n" + "Accuracy: 0.9094\n" ] } ], "source": [ - "num_epochs = 5\n", - "\n", - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "convs = []\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Embedding(vocabulary_size, embedding_size)(text_input)\n", - "for fsz in [3, 8]:\n", - " conv = Conv1D(128, fsz, padding='valid', activation='relu')(x)\n", - " pool = MaxPool1D()(conv)\n", - " convs.append(pool)\n", - "x = Concatenate(axis=1)(convs)\n", - "x = Flatten()(x)\n", - "x = Dense(128, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_token_train, y_token_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_token_test, y_token_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.3f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('word_saved_models/CNN-Token-{:.3f}.h5'.format((scores[1] * 100)))\n" + "run_experiment(construct_cnn(), token_dataset, num_epochs=5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## CNN - Morph" + "### CNN - Morph" ] }, { "cell_type": "code", - "execution_count": 106, + "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Train on 8195 samples, validate on 2049 samples\n", "Epoch 1/5\n", - "8195/8195 [==============================] - 121s 15ms/step - loss: 0.7027 - acc: 0.7024 - val_loss: 0.6580 - val_acc: 0.7174\n", + "164/164 [==============================] - 3s 19ms/step - loss: 0.5621 - accuracy: 0.7760 - val_loss: 0.4160 - val_accuracy: 0.8468\n", "Epoch 2/5\n", - "8195/8195 [==============================] - 111s 14ms/step - loss: 0.5823 - acc: 0.7684 - val_loss: 0.4978 - val_acc: 0.8233\n", + "164/164 [==============================] - 3s 18ms/step - loss: 0.3091 - accuracy: 0.8921 - val_loss: 0.3428 - val_accuracy: 0.8780\n", "Epoch 3/5\n", - "8195/8195 [==============================] - 109s 13ms/step - loss: 0.4035 - acc: 0.8576 - val_loss: 0.3968 - val_acc: 0.8536\n", + "164/164 [==============================] - 3s 18ms/step - loss: 0.2116 - accuracy: 0.9314 - val_loss: 0.3169 - val_accuracy: 0.8917\n", "Epoch 4/5\n", - "8195/8195 [==============================] - 111s 14ms/step - loss: 0.2978 - acc: 0.9019 - val_loss: 0.3528 - val_acc: 0.8829\n", + "164/164 [==============================] - 3s 18ms/step - loss: 0.1585 - accuracy: 0.9453 - val_loss: 0.3260 - val_accuracy: 0.8980\n", "Epoch 5/5\n", - "8195/8195 [==============================] - 114s 14ms/step - loss: 0.2364 - acc: 0.9259 - val_loss: 0.3397 - val_acc: 0.8853\n" + "164/164 [==============================] - 3s 18ms/step - loss: 0.1166 - accuracy: 0.9614 - val_loss: 0.3440 - val_accuracy: 0.9004\n" ] }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ - "2560/2560 [==============================] - 8s 3ms/step\n", + "52/52 [==============================] - 0s 5ms/step - loss: 0.3420 - accuracy: 0.9031\n", "\n", - "Accurancy: 0.8906\n" + "Accuracy: 0.9031\n" ] } ], "source": [ - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "convs = []\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Embedding(vocabulary_size, embedding_size)(text_input)\n", - "for fsz in [3, 8]:\n", - " conv = Conv1D(128, fsz, padding='valid', activation='relu')(x)\n", - " pool = MaxPool1D()(conv)\n", - " convs.append(pool)\n", - "x = Concatenate(axis=1)(convs)\n", - "x = Flatten()(x)\n", - "x = Dense(128, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_morph_train, y_morph_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_morph_test, y_morph_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.4f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('word_saved_models/CNN-Morph-{:.3f}.h5'.format((scores[1] * 100)))" + "run_experiment(construct_cnn(), morph_dataset, num_epochs=5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## LSTM" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "def construct_lstm(units=93):\n", + " return Sequential([\n", + " layers.Embedding(vocabulary_size, embedding_size, input_length=max_document_length),\n", + " layers.LSTM(units, return_sequences=True),\n", + " layers.LSTM(units),\n", + " layers.Dense(128, activation='relu'),\n", + " layers.Dropout(dropout_keep_prob),\n", + " layers.Dense(3, activation='softmax'),\n", + " ], name=\"LSTM\")" ] }, { @@ -682,91 +633,49 @@ }, { "cell_type": "code", - "execution_count": 114, + "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Train on 8195 samples, validate on 2049 samples\n", - "Epoch 1/7\n", - "8195/8195 [==============================] - 153s 19ms/step - loss: 0.8279 - acc: 0.6556 - val_loss: 0.7428 - val_acc: 0.6593\n", - "Epoch 2/7\n", - "8195/8195 [==============================] - 156s 19ms/step - loss: 0.7493 - acc: 0.6649 - val_loss: 0.7407 - val_acc: 0.6623\n", - "Epoch 3/7\n", - "8195/8195 [==============================] - 151s 18ms/step - loss: 0.7424 - acc: 0.6709 - val_loss: 0.7399 - val_acc: 0.6686\n", - "Epoch 4/7\n", - "8195/8195 [==============================] - 155s 19ms/step - loss: 0.7361 - acc: 0.6746 - val_loss: 0.7372 - val_acc: 0.6803\n", - "Epoch 5/7\n", - "8195/8195 [==============================] - 147s 18ms/step - loss: 0.7372 - acc: 0.6776 - val_loss: 0.7327 - val_acc: 0.6823\n", - "Epoch 6/7\n", - "8195/8195 [==============================] - 148s 18ms/step - loss: 0.6492 - acc: 0.7402 - val_loss: 0.6796 - val_acc: 0.6906\n", - "Epoch 7/7\n", - "8195/8195 [==============================] - 148s 18ms/step - loss: 0.4769 - acc: 0.8409 - val_loss: 0.4786 - val_acc: 0.8399\n" + "Epoch 1/5\n", + "164/164 [==============================] - 5s 28ms/step - loss: 0.7650 - accuracy: 0.6593 - val_loss: 0.7656 - val_accuracy: 0.6593\n", + "Epoch 2/5\n", + "164/164 [==============================] - 4s 23ms/step - loss: 0.7393 - accuracy: 0.6696 - val_loss: 0.7392 - val_accuracy: 0.6681s - loss: 0.7436 - accura\n", + "Epoch 3/5\n", + "164/164 [==============================] - 4s 23ms/step - loss: 0.7349 - accuracy: 0.6780 - val_loss: 0.7269 - val_accuracy: 0.6837\n", + "Epoch 4/5\n", + "164/164 [==============================] - 4s 23ms/step - loss: 0.7062 - accuracy: 0.7005 - val_loss: 0.6455 - val_accuracy: 0.7438\n", + "Epoch 5/5\n", + "164/164 [==============================] - 4s 22ms/step - loss: 0.5684 - accuracy: 0.8089 - val_loss: 0.5705 - val_accuracy: 0.8023\n" ] }, { "data": { - "image/png": "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\n", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAEdCAYAAABZtfMGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOzdeXxU5dnw8d+VyUZCFhLCDiZEAUH2CCG4YNXWfalLwUeFWmuxYqu2PtW+bfV9+vR5+lZtrSvuuFVqXanFva5AAmHfBRKWsJNAEkL2XO8f9xkchkkySWaSmeH+fj7zSeacc9/nnoGT65x7FVXFsizLskJNVFcXwLIsy7J8sQHKsizLCkk2QFmWZVkhyQYoy7IsKyTZAGVZlmWFJBugLMuyrJBkA5QV0kRkhoioiJzczP4oEfmhiCwWkTIRqRKRLSIyV0QmOMeoH6+tzrH3O++rRSSlhfK0VCa/z9fKZ58jIiVt+b4sK5JEd3UBLKuDHgR+BjwM3A/UA0OAK4GJwGJgkleat4GVzvFutV7H1ANXA895bb8RqASSWihTe85nWZYXG6CssCUi3YDbgEdV9Zceuz4GHheRKABVzfdKVwsc8N7u5S3gBjwClIgMBM4GXgJmNJewneezLMuLreKzwlkiEAvs8bVTVZs6kPdLwFkicpLHthuA7cCXHcgXABGZICKfiMhhp1ryU3eVZCvpfigi9SJyj8e2H4vIShGpEZEDIvKciKR5pVMR+W8R+ZmIFItIpYh8ISIjOvpZLCtYbICywpaqHgCKgV+KyEwRGRTA7L8CtgL/4bHtBuAVoEPzg4nIKOALoAfmSexGIBn4QkRGt5DuXuAp4Meq+kdn2x+BJ4BPgMuAu4ELgPdFxOWVxfXAxcDPgR8Cg4B3RcTWpFghyQaoCCMimc7dcqt/dJwG/687o1xBdB1QBTwJbBORnc4TRKtPI61QTDC6AcwTDzAM82TVUb/DtEGdq6pvqOqbwLlANXCf98FOR5BHgd8AV6rqHGd7JiYg/V5Vf6GqH6nqC8C1wATgUq+s6oFLVHWeqr7hpM12jo0YJ+A1ELFsgOpCIrJVROpEpKfX9hXOBZbZNSVr20XelZx2naHAhcBDmKee6cAiEbmxg9m/BAwTkdMxTzn5qrrJ+yAngER7vLyfXLydBbynqoc8PkcFMA/TxuUpGpiLCcTnqeq/PPadj7mGX/U8P1AAVDjn8fSxqtZ7vF/t/Azkk2ebhPI14FGWRKcqdn5Xl+VEYwNU1ysGprnfiMhIoFvXFSf8qGqtqn6gqr9U1cnAcEy71J87mO9mYBHwI2AqzT89/Q7zdOJ+fdpK1mnAbh/b92Cq/TwlY6rlFmJ6JHrq5fzc7HX+eiddutfxZV7v3T0J41spb7CF+jVwNea7+q6I9O3ME4f6DWKw2QDV9V7G3J27TcfrD6GIpIjISyKyX0S2ichv3D3URMQlIg86jeNFmD9m3mmfE5HdTvXXf/txh98iEeknIvPEjDvaLCI/9tg3QUQKRaRCRPaKyJ+d7fEi8oqIlIrIIRFZIiK9O1KO5qjqN8DfgXQR6dXa8a14Cfgxplv535s55mngdI/XT1rJswzo42N7H44PImWYf9NzgNe8/mCVOj+/63V+9+v+VsoRKkL9GpgOzAZWcWybJCJyhogsdP5P7xCRGc72biLykFPWchH52tk2RbzGtjlPkec5v98vIm8410oFMMO5phY559gtIo+JSKxH+hEi8rFzPe4VkV+LSB8ROSIi6R7HjXe+v5g2fPYuZQNU18sHkkXkVOei+QGm7cPTo0AKMBhTBXQjppEbzB/PS4CxQA7mbs/Ti0ADcLJzzHeBmztY5teAEqCfc77/EZFznX1/Bf6qqsmY9o3Xne3Tnc8wEHNnPxPT5tJuIhLTQpAb5uRf3pFzYILSPOCPquodPABQ1V2qWujx2thKnl8AF4vI0bFUzu+XOvu88/8cU4V5ITDXI0h9DDQBg7zO734Vt/GzdpWQvQbEdLyZArzqvG702ve+U7YMYAywwtn9IDAeyMM8Mf8n5t/KH5cDbwCpzjkbgTuBnpgxducCP3XKkITpIPMB5no8GfhUVfcAn2PaI92uB+Z6VfOGtBP68TGEuO8gvwA2ADvdOzwu2LGqWglUishDfDtG51rgYVXd4Rz/v5gLCueP94VAqqpWA1Ui8hfgFkxvsDYTMxboDExjew2wQkSedcrzKaZ66WQR6en0snOP/anHBKaTVXUVsLSNp75ARLy7kwvwioi8DszHBM10THXchcCfVLVDA2JV9SBm0G8g/R7zB/VTEfl/mA4ZvwISgP9qphxficgFmD+IfxeRqaq6xUn/mIgMxfz/qcHcBJwPPKuqnwW47MESqtfAjcAqVV0nIoeAP4nIWFVdjnma+kRVX3OOLQVKnSe7m4BcVXV/joVOefz5Lhap6jvO79Uce61sFZGnMEH6Ycz/oz2q+pCzvwbTBgkmMP8MeNL5DqdhenqGDRugQsPLmLE1WRzfztETM9Znm8e2bUB/5/d+wA6vfW4nATHAbo8LI8rr+LbqB5Q5fyg8z5nj/P4jzB/ZDSJSDPxfVX0P8xkHYp4AUjF3yP+nDXdzj/rYth7Ts+184AFMm0wNsBZTzfZMWz5YZ1HVVSIyBfgD5o+IYAL52aq6soV0C0Tke5i75X+IyLWq+msRWY8ZsHwbJtjtwNwsHNehI4SF6jVwI87/I1XdJSJfYGoDlmP+P2/xkaYnpl3P1z5/HFM2ERmCaU/NwdzERPNt0GquDADvArNFZDBmdpVyVfVuxwxtqmpfXfTC9Dg7z/n9c0zPq0TMf0AFMgEXUAcM90h3C/C58/tnwEyPfec7aaOBvpg7sOhmzj8D+LqZfZnufLy2D8RUOSR5bPsfYI7XcVGYqpYaINFH3uuAH3X1v4F9de0rxK+BPCefMkwHlj2YIQ17nbzvBd72kS7KOedoH/tOx9zgud+7nDzd38H9wCteaT7FVBkmOe/vcJcZ81S0vIXv9yngt5iqwt909b93W1+2DSp0/Aj4jqpWeW5U1UZMO84fRCRJzMwGd/FtHf3rwM9EZICI9ADu8Ui7G/gIeEhEksV0h84WEe+uzC2Jczo4xItIPKbqZSHwv862UU7ZXwUQketFJEPNLA7ubtSNInKOiIx0qhoqMFV+jW0ohxX5Qu0amI5p5xuOaV8aA5yGeYq5EPN//jwRuVZMF/90ERnj/N9/HvizmA5FLhGZJCJxwDdAvIhc7HRW+A0Q10o5kjDXzGERGQbc6rHvPaCPiNwhInHO9zPRY797Wq7LOL5dL+TZABUiVHWLqhY2s/t2zF1WEfA18DfMBQCm+uFDzGSkyzBzyHm6EVM9sg44iGl8bUtX2cOYu0H36zuYu7ZMYBdmItT7VPVj5/gLgLUichjTYWKqmraqPs65KzBVc18QhheMFTyhdA04N2PXYuZ53OPxKsZUR05X1e3ARcAvME9ZKwD3TCC/xIwzW+Ls+39AlKqWYzo4PIu52avCtJ225JeYcXCVzmc92ptUTVX7+ZgONnsw1brneOxfgOmcsUxVt7ZynpAjzmOgZVmWFYFE5N/A31T12a4uS1vZAGVZlhWhxMyC8jEwUI/t2BQWbBWfZVlWBBKRFzFjpO4Ix+AEfgYoEblARDaKmTXgHh/77xYzd9YKEVkjIo0ikiYiQz22rxAzu8AdTpr7xYzqdu+7KNAfzrIs60SlqtNVNUWdyYXDUatVfE6vq28wDXElmEa/aaq6rpnjLwXuVNXv+MhnJzBRVbeJyP3AYVV9sMOfwrIsy4o4/gzUnQBsVtUiABGZi5mKw2eAwvTwes3H9nOBLaq6zcc+v/Ts2VMzMzPbm9yygmbp0qUHVDWjq8vRHHvtWKGsuevHnwDVn2NHNpcAE30dKCIJmG7Gs3zsnsrxgWuWmCURCoFfqJlWxjvPWzCD8hg0aBCFhc31QrWsriMi7b7x6gyZmZn22rFCVnPXjz9tUL4mj2quXvBSYIF6TaopZubdy4B/eGx+EjOZ6BjM0gMP4YOqPq2qOaqak5ERsjeolmVZVoD5E6BKMNPbuA3ADND0xddTEphR18tUda97g6ruVdVGZ9T1M0TYqp6WZVlWx/gToJYAp4hIlvMkNBWz/MAxRCQFM8Puuz7yOK5dSo5d+OtKYI2/hbYsy7IiX6ttUKraICKzMFOJuIDnVXWtiMx09s92Dr0S+Mh7Hi2nXep8jl/E7U8iMgZTXbjVx36/1NfXU1JSQk1NTXuSWz7Ex8czYMAAYmLCZl0zqx3stRN49toJLL+W21DV+Zj1djy3zfZ6PweY4yPtEY5fehpVvaEN5WxWSUkJSUlJZGZm+rvWitUCVaW0tJSSkhKysrK6ujhWENlrJ7DstRN4YT+TRE1NDenp6fYCCxARIT093d5VnwDstRNY9toJvLAPUOD3KpWWn+z3eeKw/9aBZb/PwIqIAAWAnfTWsiwrokRGgGqso2n/Rqg93OmnLi0tZcyYMYwZM4Y+ffrQv3//o+/r6upaTFtYWMjPfvazTiqpZYUWe+2cGP7rn+v4/XvNTTzUMr86SYS6IzV1uOrriS3dhCb1Jap7b+ikR+309HRWrFgBwP3330/37t355S9/eXR/Q0MD0dG+v+acnBxycnI6pZyWFWrstRP5VJX3Vu0id/Bx/eT8EhFPUN0SEinvPphyTSSqcjeNB7ZAY32XlWfGjBncddddnHPOOfzqV79i8eLF5OXlMXbsWPLy8ti4cSMAn3/+OZdccglgLtCbbrqJKVOmMHjwYB555JEuK79ldRV77USW4gNV7KusZeLgtHalj4gnKBGhV0oiv/l3LWtLyonlALAVYuJBXB3Ke3i/ZO67dESb033zzTd88sknuFwuKioq+PLLL4mOjuaTTz7h17/+NW+++eZxaTZs2MBnn31GZWUlQ4cO5dZbb7XjKaxO8X//uZZ1uyoCmqe9dqyCYjPrXXufoCIiQLnFREcRExtHXb2LGK1F6qvBFWteneyaa67B5TLBsby8nOnTp7Np0yZEhPp63093F198MXFxccTFxdGrVy/27t3LgAEDOrPYltXl7LUTOQqKSunZPY7BPRPblT6iApT7bk1VKTtcg6tiB6lSRUNMd6LTMsHVeXdUiYnf/oP89re/5ZxzzuHtt99m69atTJkyxWeauLi4o7+7XC4aGhqCXUzLAmjXk06w2GsnMqgq+UVlTByc1u7u9xHRBuVNREhP6kZcxmD2SAZRdVU07tuA1nTNqsfl5eX0798fgDlz5nRJGSwrHNlrJ3xtLzvCnooacrPa1/4EERqg3LrFRpPRuz/740+ivkmgbDMN5bs6fczUf/7nf3LvvfcyefJkGhsbO/XclhXO7LUTvgqKOtb+BH4s+R5KcnJy1HvRtfXr13Pqqae2mra8qgYt30Eqh6mPTiQmPatTq/zCjb/fq2WIyFJVDdl+zx25dqy2sd+rcdffV/DFN/sp/M15rVbxNXf9RPQTlKeUxHgSeg1mX1QvXPVHaNy7nqaawPZasizLsoyC4jImZKUh6+fB5k/alccJE6AAYqNdZPTuR1lCFvUahZRtof7QTjtNktUlROQCEdkoIptF5B4f+1NE5J8islJE1orID/1Na1ldaUfZEXYeqiYvMxnevwcW/LVd+ZxQAQpMB4qePVJoSDuFcpKIObKPun3foI0tT61iWYEkIi7gccxq08OBaSIy3Ouw24B1qjoamAI8JCKxfqa1rC7jHv90buNXULkL8n7ernxOuADl1r1bHN17D+ZAdG+iG6pp3LuBxuryri6WdeKYAGxW1SJVrQPmApd7HaNAkpgK/O5AGdDgZ1rL6jL5RaWkdoum79pnoNcIOPncduVzwgYogGhXFOkZfanoPpgGjSLqYBF1ZSW2ys/qDP2BHR7vS5xtnh4DTgV2AauBn6tqk59pLavLFBSXclPvzci+dZB3e7vnRj2hAxSYKr/UlGS051AqSCK2Zj+1e7+hqcFW+VlB5euK9b4z+h6wAugHjAEeE5FkP9MiIreISKGIFO7fv7+j5bUsv+w8VM2Osmqurn0bkvrBaVe1Oy+/ApQfjbl3i8gK57VGRBpFJM3Zt1VEVjv7Cj3SpInIxyKyyfnZo92fIgC6xcXQvU82ZTF9iW6spmnfBuqPHGo13ZQpU/jwww+P2fbwww/z05/+tNnj3d19L7roIg4dOv4c999/Pw8++GCL533nnXdYt+7bKex/97vf8ckn7espY3WJEmCgx/sBmCclTz8E3lJjM1AMDPMzLar6tKrmqGpORkZGQAsfCPbaiUwFRaWcJkX0O7gEcm+F6PZPNddqgPKnQVZVH1DVMao6BrgX+EJVyzwOOcfZ79nP/R7gU1U9BfjUed+lXFFCWkYfjiRn04CLmEPF1JS2XOU3bdo05s6de8y2uXPnMm3atFbPN3/+fFJTU9tVVu+L7L/+678477zz2pWX1SWWAKeISJaIxAJTgXlex2wHzgUQkd7AUKDIz7Qhz147kamgqIxZcfPRuGQYP6NDefnzBNXWBtlpwGt+5Hs58KLz+4vAFX6k6RRJSUlEZQyhQpKJr91P7d6NNNXX+jz26quv5r333qO21uzfunUru3bt4m9/+xs5OTmMGDGC++67z2fazMxMDhw4AMAf/vAHhg4dynnnnXd0SQGAZ555htNPP53Ro0dz1VVXceTIERYuXMi8efO4++67GTNmDFu2bGHGjBm88cYbAHz66aeMHTuWkSNHctNNNx0tW2ZmJvfddx/jxo1j5MiRbNiwIWDfmdU2qtoAzAI+BNYDr6vqWhGZKSIzncN+D+SJyGrMTdyvVPVAc2k7/1N0jL12ItO2Lev4LvlIzg8hPrlDefkzWayvBtmJvg4UkQTgAszF46bARyKiwFOq+rSzvbeq7gZQ1d0i0quZPG8BbgEYNGhQyyV9/x7Ys7q1z+OXWCAGpTb1ZKIn3ETT/g3UJw8irvuxNZHp6elMmDCBDz74gMsvv5y5c+fygx/8gHvvvZe0tDQaGxs599xzWbVqFaNGjfJ5rqVLlzJ37lyWL19OQ0MD48aNY/z48QB8//vf58c//jEAv/nNb3juuee4/fbbueyyy7jkkku4+uqrj8mrpqaGGTNm8OmnnzJkyBBuvPFGnnzySe644w4AevbsybJly3jiiSd48MEHefbZZwPyfVltp6rzgfle22Z7/L4L+K6/aTskgNfOUX1GwoV/bHa3vXYiz57yGr5X+RYaEwUTb+1wfv48QfnVIOu4FFjgVb03WVXHYaoIbxORs9pSwK6sRxeEuPgEalJPoYFo4iq2cuTADkxHqm95VlW4qyhef/11xo0bx9ixY1m7du0xVQrevvrqK6688koSEhJITk7msssuO7pvzZo1nHnmmYwcOZJXX32VtWtbvlHeuHEjWVlZDBkyBIDp06fz5ZdfHt3//e9/H4Dx48ezdevWNn0flhVo9tqJLMs2buEHrs+pOOVKSO7b4fz8eYLyq0HWMRWv6j3nLhBV3Scib2OqDL8E9opIX+fpqS+wr62FP04Ld2sdkQg0xA2l8sB2kuoOULPnMNHpg4mONVP8X3HFFdx1110sW7aM6upqevTowYMPPsiSJUvo0aMHM2bMoKampsVzNDdX1YwZM3jnnXcYPXo0c+bM4fPPP28xn9bmVnQvS2CXJLCOEaRrpzX22oksMUufJ0FqifvOXQHJz58nKL8aZEUkBTgbeNdjW6KIJLl/x1RXrHF2zwOmO79P90wXiqKjo+neO4vK+P7ENNXCgQ1UV5oHxe7duzNlyhRuuukmpk2bRkVFBYmJiaSkpLB3717ef//9FvM+66yzePvtt6murqayspJ//vOfR/dVVlbSt29f6uvrefXVV49uT0pKorLy+OVDhg0bxtatW9m8eTMAL7/8MmeffXYgvgLLCjh77USQ+mpy9v2Dld0m4OoTmIlNWg1QfjbmAlwJfKSqVR7begNfi8hKYDHwL1X9wNn3R+B8EdkEnO+8D2kiQlJaL+rThtBANN0qt1G1fxtNTU1MmzaNlStXMnXqVEaPHs3YsWMZMWIEN910E5MnT24x33HjxvGDH/yAMWPGcNVVV3HmmWce3ff73/+eiRMncv755zNs2LCj26dOncoDDzzA2LFj2bJly9Ht8fHxvPDCC1xzzTWMHDmSqKgoZs6ciWWFKnvtRIaKgpfpoeVsG3pzwPI8YZbbCLTGxkaqD2yne+MhqonHlZ5FbFx8p5cjWOySAW1jl9uw3E7I77WpkcMPjWVLpQtu/jejB7VtWOsJv9xGoLlcLrr3zqIqYQCxWkdU6Uaqyku7uliWZVmdb+N8uldt40W5nBH9UwKWrQ1QHZSYmkFjzyE0EENi1XYq922lscmu/GlZ1glCFRb8lV3Sh7JB3yPaFbiwEhEBqqurKWPjuhHbZyhV0T1IajhI3Z6N1NRUd2mZOqKrv0+r89h/68A6Ib/P7flQsoQn6y5gYrbP4aztFvYBKj4+ntLS0i7/jxEV5SKxVybV3QcRSz3Rpd9QcfBAl5errVSV0tJS4uMjpz3N8i1Urp1IccJeOwsfoS42lX80ns3EwWkBzdqfcVAhbcCAAZSUlBBKszU3NQhNVQeI1j1URyWgccm4XNFERwlRIu2deb7TxMfHM2DAgK4uhhVkoXjthLsT7trZ/w1snM+CPj8kqiaBkQFsf4IICFAxMTFkZWV1dTGOo/U1rHvpDsbteI06dfFl0yjmNebxOTmkpvZgQI9uzivhmJ+9k+NxRYV4BLMiQqheO1YYWfQoRMfzZNW5jD+pBzEBbH+CCAhQoUpi4hnxo9nU7vgJ1Utf48yN73Be9ePUR8WxypXHR4fP4L29I9h5+Nhpk2JcQr9UJ3ilOsEr7dsA1ivJBjDLskJA5V5YOZea065jcUEUd49LD/gpbIAKsriBY4kbOBaa/gjbFxGz5g3Gr32H8dWfcW98Cg0TL2H/SZewKWEcJeV1lBw8QsnBanYcPMK/N+5jf+Wxs6i3FMAG9kigV1IcUTaAWZYVbIufgsZ6FvedBpQyMSuw7U9gA1TniYqCzMnmdeGfoOhzWPMm0evn0Xflq/RN7AUjroDTroaBE44ukVxT38jOQ9WUHKw+GrzcvzcXwPqnelYdHluNaAOYZVkdVlsJS56FUy/l3/uSiI85yKgB7VufqyU2QHUFVwyccr55XVINmz6C1W/A0hdh8dOQMghO+z6MvJr43qeRndGd7IzuPrPyDmA7yr4NZJ+s38eBw8cGsFhXFP1S4zkpPZE7zx/CmIGB/09lWVaEW/Yy1JTD5J9T8GYZ40/qQWx04DuF2wDV1WK6wfDLzaumAjb8C9a8AQsfhQUPQ8+hMPJqOO0qSM8+Lnl8jKvFAFZd5w5gxz59LdlaxrVPLeJ/rxzJVeNPoF5HlmV1TGM95D8Bg/I4lDaKDXs+5s7zhgTlVDZAhZL4ZBgzzbyqDsC6d2D1m/DZH8yr31hTBXja9yG5n19Zdot1cXKv7pzc69gAVlZVx22vLuMX/1jJut0V3HvhsICOALcsK0KtfQfKd8BFD7C4uAxVgtL+BBEwUDdiJfaE02+Gm96HO9fC+b8HbYKP/g/8eTi8cDEUPg9HylrPy4e0xFhe+tEEZuRl8tzXxcx4YQmHjtQF+ENYlhVRVGHhX6HnEDjlexQUlxEXHcXoIDUV2AAVDlIGwOSfwU++hFlLYco9cHgvvHcnPHgKvHoNrPy7abhsgxhXFPdfNoI/XTWKxcVlXPbYAjbuaVselmWdQIo+hz2rIe9nEBVFflEpYwelEh/jCsrpbIAKNz1PNgFq1hITsHJ/CnvXwdu3wAMnw+vTYd08qG95FVJP154+kNduyaW6vpErn1jAB2v2BPEDWJYVthY+At37wKhrKa+uZ93uCiZmBX78k5sNUOFKBPqOhu/+Hu5YDTd9CGNvgK1fw+s3mCert2+FzZ9AY+vLU48/qQf/nHUGp/ROYuYrS/nLx9/Q1GTnaAsmEblARDaKyGYRucfH/rtFZIXzWiMijSKS5uy7U0TWOttfE5ETbAI4q9PtXgVb/g0TfwLRcRRuNe1PuYNtgLJaEhUFg3Lh4gfhFxvh+rfg1Ethw3vwylXw0FD41y9g2yJoamo2mz4p8fz9llyuGjeAv366iZmvLOVwbevBzWo7EXEBjwMXAsOBaSJyzDrZqvqAqo5R1THAvcAXqlomIv2BnwE5qnoa4AKmdu4nsE44Cx+F2O6QcxMA+UWlxLqiGDsoeENVbICKNK5oOPlcuOIJ+OUm+MErkHkGLH8FXrgA/joKPvqtqUf2IT7GxYPXjOK3lwzn0w37+P4TC9hWWtXJH+KEMAHYrKpFqloHzAUub+H4acBrHu+jgW4iEg0kALuCVlLLOrQD1rwJ46ZDNxOQCorLGDMweO1P4GeAam9VhIgMFJHPRGS9Ux3xc48094vITo90FwXyg1lATLx5krr2Rbh7M1z5NPQ61YxhmH0GbHzfZzIR4UdnZPHSTRPYV1nLZY8t4KtNdsbrAOsP7PB4X+JsO46IJAAXAG8CqOpO4EFgO7AbKFfVj3yku0VECkWk0M5YbnVI/pPmZ+6tAFTW1LNmZzm5AV5ew1urAaojVRFAA/ALVT0VyAVu80r7F3c6VZ0foM9k+RKXBKN/AP/xD/Nk1SMTvn64xSSTT+7JvNvOoE9yPNOfX8yzXxXZtYMCx9d8U819uZcCC5xrChHpgXnaygL6AYkicv1xmak+rao5qpqTkZERoGJbJ5zqQ7DsRTNZQOpAAAq3HaRJYWIQ25/AvyeodldFqOpuVV3m/F4JrKeZu0SrEyWkwYRbYEc+7Fre4qGD0hN466d5fHd4H/77X+v5xesrqam3S9oHQAkw0OP9AJqvppvKsdV75wHFqrpfVeuBt4C8oJTSsgqfh7rDZqiLI7+olBiXMG5Qj6Ce2p8A1e6qCK99mcBYoMBj8ywRWSUizzt3hb7ytNUUwTD2etPgmT+71UMT46J54j/Gcdf5Q3hr+U6ufWoRu8vDd0n7ELEEOEVEskQkFhOE5nkfJCIpwNnAux6btwO5IpIgIgKci7n5s6zAaqiFgtmQ/R3oM/Lo5oKiMqjmnBkAACAASURBVEYPSKVbbPDan8C/ANXuqoijGYh0xwStO1S1wtn8JJANjMHUoz/kK0NbTREk8Skw5jrT8Fm5t9XDo6KEn517Ck/fMJ4t+w5z6aMLWLqtfbNYWKCqDcAs4ENMcHldVdeKyEwRmelx6JXAR6pa5ZG2AHgDWAasxlzHT3da4a0Tx6q/m0kB8r59eqqqbWD1zvKAL+/uiz8BqiNVEYhIDCY4vaqqb7m3q+peVW1U1SbgGUxVotWZJvwEmurNI7yfvjuiD2/fNpnEOBdTn85n7uLtQSxgZFPV+ao6RFWzVfUPzrbZqjrb45g5qnpcF3JVvU9Vh6nqaap6g6rWeh9jWR3S1GS6lvcZCYOnHN1cuO0gjU0a1AG6bv4EqHZXRTjVD88B61X1z17H9/V4eyWwpu3Ftzqk58lwyneh8DnzKO+nIb2TePe2yeQOTueet1bzu3fXUN/Y/Pgqy7LC0KYP4cA3kPfzo+vTARQUlRIdJYw/KbjtT+BHgOpIVQQwGbgB+I6P7uR/EpHVIrIKOAe4MxAfyGqjiTOhaj+seav1Yz2kJsTywozTueWswby0aBvXP1tA6WF7E29ZEWPBI5Ay0Cyk6qGguIyRA1JIjAv+Yhh+ncHpAj7fa9tsr/dzgDle277GdxsWqnpDG8ppBUv2d8yaUwVPwuipx9wptSbaFcWvLzqV4X2T+dWbq7jssQU8feN4RvRLCWKBLcsKupJC2L4Qvve/ZoFVx5G6BlbuOMTNZw7ulGLYmSROdCJmbq3dK2F7fruyuGJsf/4xcxJNqlz15EL+udJOamBZYW3BXyE+FcbdeMzmZdsO0dCkndJBAmyAssA8OcWnmKeodho1IJV3Z03mtH4p3P7acv70wQYa7WSzlhV+SrfA+n/C6T+CuGMXOi0oLsUVJeR0QvsT2ABlAcQmmjm21r9n5txqp15J8fztx7lMmzCIJz7fws0vLqGipj6ABbUsK+gWPWaq9Sb85Lhd+UWlnNYvmaT4GB8JA88GKMuY8GNAYckzHcomNjqK//3+SP77itP4atMBrnh8AVv2Hw5MGS3LCq7D+2HF30ytSlLvY3bV1Deyckd50Kc38mQDlGWkDoJhl8DSF6Gu47OXX597Eq/ePJHyI/Vc8dgCPtuwLwCFtCwrqJY8Aw01MOn243Yt236QusamoE8Q68kGKOtbubdCzSEzejwAJg5OZ97tZzAoPYGbXlzCE59vtpPNWlaoqjsCi5+BoRdBxpDjdhcUlRElkJNpA5TVFQZNgj6joOApCFAg6Z/ajTdm5nHJqH786YON3P7acqrr7GSzlhVyVrwK1WXHTGvkKb+olOH9kknupPYnsAHK8iRinqL2b4CizwKWbbdYF49MHcM9Fw7jX6t3c9WTCyk5eCRg+VuW1UGNDaZzxIAJZnVuLzX1jSzfcYjcTpjeyJMNUNaxTrsKEjP8muW8LUSEmWdn8/z009lx8AiXPbaA/KLSgJ7Dsqx2Wj8PDm41S2r4GKy/csch6hqaOrWDBNgAZXmLjoOcm8w8XKVbAp79OcN68e5tk+mREMP1zxbw8qKttl3KsrqSKix8BNKyTfuTD/lFZYjAhE5sfwIboCxfcn4EUTGmLSoIBmd05+3bJnPWkAx+++5a7n1rNbUNtl3KsrrE1q/NwqV5syDK9/pOBcWlnNonmZSEzmt/AhugLF+SepuqvhWvQk15UE6RHB/DMzfmcNs52cxdsoPrnilgX2VNUM5lWVYLFj4CCT1h9DSfu2sbGlm2/WCnTW/kyQYoy7fcmWaZ5+WvBu0Urijh7u8N4/HrxrFuVwWXPbqAVSWHgnY+y7K87FsPmz4y83HGdPN5yKqScmrqmzpl/SdvNkBZvvUbCwNzYfFT0BTc6reLR/XlzVvzcEUJV89exNpdwXlqsyzLy8JHISYBTr+52UMKnM5ME7LsE5QVSnJnmp4933wY9FMN75fMO7dNprFJeX/1nqCfz7JOeBW7YNXrMPYGSGg++BQUlzGsTxJpibGdWDjDBiirecMuheQBHZrlvC0ykuIYNSCFhVsOdMr5LOuElv8kaCNM+mmzh9Q3NlG49SATu+DpCWyAslriioYJN0Pxl7B3baecMi87nVUl5RyubeiU83UlEblARDaKyGYRucfH/rs9VqJeIyKNIpLm7EsVkTdEZIOIrBeRSZ3/CaywVVMBS+fA8CugR2azh60qKae6vrHTxz+5+RWgOngh+UwrImki8rGIbHJ+ds4CI1bbjJsO0d2gILADd5szaXBPGpqUJVvLOuV8XUVEXMDjwIXAcGCaiAz3PEZVH1DVMao6BrgX+EJV3V/MX4EPVHUYMBpY33mlt8Le0jlQW2EG5ragoLjr2p/AjwDVkQuplbT3AJ+q6inAp857K9QkpMHoH5i66qrgz/ww/qQexLqiyN8S8bNMTAA2q2qRqtYBc4HLWzh+GvAagIgkA2cBzwGoap2q2u6Pln8a6kz1XuaZpjNUC/KLyjilV3d6do/rpMIdy58nqHZfSK2kvRx40fn9ReCKthbe6iQTZ5op+JfNCfqpusW6GDMolYWRH6D6A56rQ5Y4244jIgnABcCbzqbBwH7gBRFZLiLPikiij3S3iEihiBTu378/sKW3wteaN6FyF0z+eYuHNTQ2sXRrWZeMf3LzJ0B15EJqKW1vVd0N4Pzs5X+xrU7V61QYPAUWPwuNwV8hNy87nTW7yik/EtGr8R4/4Rk0N+fTpcACj+q9aGAc8KSqjgWq8FEDoapPq2qOquZkZGQEosxWuHNPa9RrOJx8XouHrtlVQVVdI7ld1P4E/gWojlxIbUnr++T2LjA0TLzV3HWtezfop8rL7onqt/XfEaoEGOjxfgCwq5ljp/JtrYQ7bYmqFjjv38AELMtq2eZPYN86s6SGj0lhPXXl+Cc3fwJURy+k5tLuFZG+AM5Pn0uu2rvAEHHKdyFtcKd0lhg9MIX4mKhIr+ZbApwiIlkiEou5duZ5HyQiKcDZwNE7A1XdA+wQkaHOpnOBdcEvshX2FvwVkvqZqcxakV9UyuCMRHolxXdCwXzzJ0C1+0JqJe08YLrz+3SvdFaoiYqCCT+BkiVQsjSop4qLdnF6ZlpEL8ehqg3ALOBDTA+811V1rYjMFJGZHodeCXykqlVeWdwOvCoiq4AxwP90RrmtMLZrOWz9yqz5Ft3yoNvGJqVw68Eurd4DPwJURy6k5tI6u/8InC8im4DznfdWKBtzHcQmdcrA3dzB6WzYU8mBw7VBP1dXUdX5qjpEVbNV9Q/OttmqOtvjmDmqOtVH2hVOzcIoVb1CVQ92ZtmtMLTgEYhLhvEzWj103a4KKmsbumyArlu0Pwep6nxgvte22V7v5wBz/EnrbC/FVE1Y4SI+GcZeD0uegfN/D8l9g3aqvGxz55ZfVMolo/oF7TyWdUI4uBXWvQOTZpnruBXu2ouQf4KyrGNMvMVMHlv4XFBPM7J/Ct3jolkU2e1QltU5Fj0B4jLVe34oKC4lq2civZO7rv0JbICy2iptMAy5AApfgPrgrd8U7YpiQlaaDVCW1VFHymD5yzDyGkhuvTaisUlZXFzW5dV7YAOU1R65M+HIAVjzRlBPk5edTtGBKvaU24UMLavdljwL9Ucg73a/Dl+/u4KKmoYuHaDrZgOU1XZZZ5uBfvmzzcC/IHHXfy8qsrObW1a71FdDwVNmmEjv4a0fj1leA+iSBQq92QBltZ2IWYFz72rYtiBopxneN5mUbjEs3Gyr+SyrXVa+Zmo78lqeFNZTQVEpg9IS6Jfqe4XdzmQDlNU+I6+Fbj3MpJNBEhUlTBqczqIIHg9lWUHT1AgLHzMTwmae4V+SJmXx1tBofwIboKz2ik0w4yk2zoeD24J2mknZ6ZQcrGZH2ZGgncOyItLG+VC2xa9pjY4m2VvJoSP1Xbb+kzcboKz2O/1mQGDx00E7hXs8lO3NZ1ltoGqmNUo9CU69zO9k7vn37BOUFf5SBsDwy2DZy1B7OCinONlZi8YuA29ZbbA930xLNmmWWRnbTwXFZfRP7cbAtIQgFs5/NkBZHTPxVqgtN42xQSAiTMpOZ+GWUjSIPQYtK6IsfAS6pcHY//A7iapSUNy16z95swHK6piBE0wjbMFT0NQUlFPkZaezr7KWogPe86ValnWc/d+Y9qcJP4bY49axbNamfYcpq6rr8umNPNkAZXWMiHmKKt0EW/4dlFNMci6YCF9+w7ICY9GjEB0PE25pUzJ3+1NuCIx/crMByuq4EVdC995Bm+X8pPQE+qXEk28DlGW1rHIvrJxrVh5I7NmmpPlFZfRNiWdgWtePf3KzAcrquOhYyPmRWa1z/zcBz15EyM0246Gammw7lGU1a/FT0FhvOke0gWl/KiV3cDriZ5f0zmADlBUYOTeBK9ZcIEGQl92Tsqo6Nu6tDEr+lhX2aivNvHunXgLp2W1KumV/FQcO14VM93I3G6CswOieYWZLXvEaVB8KePaT7Hgoy2rZspehphwm39HmpO71n0JlgK6bDVBW4EycCfVVZmr/AOuf2o2T0hNsRwnL8qWxwUw7NmgSDMhpc/KC4jJ6JcWRmR4a45/cbICyAqfvKDhpsplZoqkx4NnnZadTUFxKo22HsqxjrZ8H5dv9XlLDk6pSUBR67U/gZ4ASkQtEZKOIbBaRe5o5ZoqIrBCRtSLyhbNtqLPN/aoQkTucffeLyE6PfRcF7mNZXWbiTDi03YzDCLDcwelU1jSwdld5wPO2rLClCose+3Yx0TYqPlDFvsrakBqg69ZqgBIRF/A4cCEwHJgmIsO9jkkFngAuU9URwDUAqrpRVceo6hhgPHAEeNsj6V/c+1U18H/RrM437GJIGWTWigowdztUpFTztXbjJyJ3e9zArRGRRhFJ89jvEpHlIvJe55bcCik7FsPOpZD7U4hytTl5KK3/5M2fJ6gJwGZVLVLVOmAucLnXMdcBb6nqdgBV3ecjn3OBLaoavKmvra4X5TIj2Ld9DbtXBTTrXknxnNyre0R0lPDnxk9VH/C4wbsX+EJVyzwO+TmwvrPKbIWoRY9BfKoZ+9QOBUWl9OweR3aG/7NOdBZ/AlR/YIfH+xJnm6chQA8R+VxElorIjT7ymQp4T9g2S0RWicjzItLD18lF5BYRKRSRwv379/tRXKvLjbsBYhLM9EcBlpedzpKtZdQ3BmdapU7kz42fp2l4XD8iMgC4GHg2qKW0QltZMWx4zwzzaMO0Rm6qSn6RmX8v1NqfwL8A5avU3q3U0ZgqvIuB7wG/FZEhRzMQiQUuA/7hkeZJIBsYA+wGHvJ1clV9WlVzVDUnIyPDj+JaXa5bDxg9DVb/A6oCOwt5XnY6R+oaWVUS+K7sncyfGz8ARCQBuAB402Pzw8B/As1GantzdwIomA3iavO0Rm7by46wp6KG3BAb/+TmT4AqAQZ6vB8A7PJxzAeqWqWqB4AvgdEe+y8ElqnqXvcGVd2rqo2q2gQ8g7mjtCLFxJnQWAuFLwQ226x0RIiEZeD9ufFzuxRY4K7eE5FLgH2qurSlE9ibuwhXfciMfTrtKkju264sCopMjXEoTRDryZ8AtQQ4RUSynCehqcA8r2PeBc4UkWjnbm8ix9aNH1M9ASAint/olcCathbeCmEZQyD7XDOyvaEuYNn2SIzl1D7JkdBRwp8bPzfv6vHJwGUishVTNfgdEXklGIW0QtjSOWbc4aTb2p1FfnEp6YmxnNyre+DKFUCtBihVbQBmAR9igs7rqrpWRGaKyEznmPXAB8AqYDHwrKqugaPVE+cDb3ll/ScRWS0iq4BzgDsD9JmsUJF7KxzeA+veDWi2k7LTWbr9IDX1gR9r1Yn8ufFDRFKAszE3gQCo6r2qOkBVM510/1bV6zun2FZIaKw3bbxZZ5nxh+1UUFTGhKzQbH8C03bUKqcL+HyvbbO93j8APOAj7RHguOdHVb2hTSW1wk/2uZB+spnlfNQ1Acs2Lzud574uZtn2g+Rlt23G5lChqg0i4r7xcwHPu2/8nP3u6+tK4CNVtYthWd9a+w5U7oJLH253FjvKjrDzUDW3nDU4gAULLDuThBU8UVGmLWrnUtixJGDZTshKwxUlYb/8hqrOV9Uhqpqtqn9wts32vPlT1TmqOrWFPD5X1Us6o7xWiFA1az71HAInn9/ubI6OfwrBAbpuNkBZwTV6GsSlQP4TAcsyKT6G0/qnREI7lGW13bYFsHulMzC3/X/C84tKSU2IYUivpAAWLrBsgLKCK667GRe17l0o3xmwbPOy01mx4xBVtQ0By9OywsKix6FbGoxu9sHaLwXFpUzMSiMqKjTbn8AGKKszTPgxoKZHX4BMGpxOQ5NSuO1gwPK0rJB3YDNsfB9Ovxli2r/y7c5D1ewoqw7J6Y082QBlBV+PTBh6kdMttjogWeZk9iDGJSzcEtiBwJYV0vKfAFeMc9PXfgVH138K3fYnsAHK6iwTZ0J1Gax6PSDZJcRGM3Zgj7DvKGFZfjtSBiv+BqOuhe69OpRVQVEZyfHRDOuTHKDCBYcNUFbnyDwDep9mpmbRwKznlJudzuqd5ZRX1wckP8sKaYXPQ0M15LZ/YK5bQXEpE7LScYVw+xPYAGV1FhHzFLVvHRR/GZAs87LTaVJYXFzW+sGWFc4aas1CoNnfgd7DWz++BXvKa9haeoTcEK/eAxugrM408hpISDdPUQEwdlAqcdFREbH8hmW1aM2bcHgvTJrV4awKip32pxDvIAE2QFmdKSYexv/Q9EIqK+pwdnHRLnIye9iOElZkUzVdyzNONU9QHZRfVEZSXDTD+4V2+xPYAGV1ttNvNosaLn4mINnlZfdkw55KyqoCNyGtZYWU4i9g7xozKWwA5swrKCrldGc2llBnA5TVuZL7wvArYPkrUFvZ4ezcywTkF9lqPitCLXocEnuZ3nsdtK+ihqIDVUwM0fWfvNkAZXW+3FuhtsJ0me2gUQNSSIx12Wo+KzLt3wibPjLjnqLjOpyde/69UF3/yZsNUFbnG5AD/XPMcgFNHVu6PcYVxelZabajhBWZFj0O0fFmSfcAKCgupXtcNCPCoP0JbICyukrurVC2BTZ/3OGs8rLT2bK/ir0VNQEomGWFiKoDsHKumXMvMTDLyuQXlTH+pB5Eu8LjT394lNKKPMMvh6S+kP9kh7Nyrwll26GsiLLkWWisDcjAXIADh2vZvO9w2FTvgQ1QVldxxcDpP4Kiz2Dfhg5ldWrfZJLjo1m42QYoK0LU15ierqd8DzKGBCTLxWGw/pM3G6CsrjP+h+CK6/DAXVeUkDs4nYVFtqOEFSFWvw5HDpiu5QGSX1RKQqyLkf1TApZnsPkVoETkAhHZKCKbReSeZo6ZIiIrRGStiHzhsX2riKx29hV6bE8TkY9FZJPzs0fHP44VVhJ7mq6zK+eaiTA7YFJ2OjvKqtlRdiRAhbOsLuIemNt7JGSdFbBsC5z2p5gwaX8CPwKUiLiAx4ELgeHANBEZ7nVMKvAEcJmqjgCu8crmHFUdo6o5HtvuAT5V1VOAT5331okm91YzAeaylzqUjbsdapFth7LC3eZPYf8GyJsVkIG5AGVVdWzcWxlW7U/g3xPUBGCzqhapah0wF7jc65jrgLdUdTuAqu7zI9/LgRed318ErvCvyFZE6T0CMs809e2N7V8dd0jv7qQnxobV8hut1UyIyN1OzcMKEVkjIo1OzcNAEflMRNY7NRY/74ryW0Gy6DHo3gdGfD9gWS4+Ov9e+LQ/gX8Bqj+ww+N9ibPN0xCgh4h8LiJLReRGj30KfORsv8Vje29V3Q3g/PS5wImI3CIihSJSuH//fj+Ka4Wd3FuhogQ2vNfuLESE3Ox0Fm4pRQO0nEcw+VMzoaoPODUPY4B7gS9UtQxoAH6hqqcCucBt3mmtMLV3rek4NPEWiI4NWLb5RWXEx0QxakBqwPLsDP4EKF/PmN5/AaKB8cDFwPeA34qIu+vJZFUdh7kQbxORNlWqqurTqpqjqjkZGRltSWqFiyEXQOpJHe4skZedzp6KGooPVAWoYEHlT82Ep2nAa2Bu6FR1mfN7JbCe428arXC06HGISTAdiAKooNi0P8VGh0/7E/gXoEqAgR7vBwC7fBzzgapWqeoB4EtgNICq7nJ+7gPexlyYAHtFpC+A89OfakErEkW5YOJPYPsi2LWi3dlMcurXw6Qdyp+aCQBEJAG4AHjTx75MYCxQ4GOfrX0IJ5V7zIrTY/4DEgJXFXfoSB0b9lSExfIa3vwJUEuAU0QkS0RiganAPK9j3gXOFJFo52KaCKwXkUQRSQIQkUTgu8AaJ808YLrz+3QnD+tENfZ6iO3eoaeorJ6J9EmOZ2F4tEP5UzPhdimwwKne+zYDke6YoHWHqlYcl5mtfQgvS56FpgZT5R1Ai4vLUA2/9ifwI0CpagMwC/gQU5XwuqquFZGZIjLTOWY98AGwClgMPKuqa4DewNcistLZ/i9V/cDJ+o/A+SKyCTjfeW+dqOJTYMx1ZmG2yr3tykJEyMtOJz882qH8qZlwm4pTvecmIjGY4PSqqr4VlBJanafuCCx5DoZeBOnZAc26oLiMuOgoRg8Mr/YnMG1HrVLV+cB8r22zvd4/ADzgta0Ip6rPR56lwLltKawV4SbONL35Fj8N5/62XVnkZqfz1vKdfLP3MEP7JAW4gAF1tGYC2IkJQtd5HyQiKcDZwPUe2wR4Dlivqn/unOJaQbXyNaguM13LA6yguJSxg1KJj3EFPO9gC68WMyuypWfDqZeaIFVzXI2VX/KyTT17qC+/4U/NhONK4CNV9ez5MRm4AfiORzf0izqt8FZgNTVB/hPQbywMmhTQrMur61m7Kzzbn8AGKCvUnHEn1JZD4fPtSj6gRwID07qFxfIbqjpfVYeoaraq/sHZNtuzdkJV56jqVK90X6uqqOoodzd0p5bDCkebPoLSzTApcANz3Qq3mvancBug62YDlBVa+o+DwVPMHWV9+5bPyBvck/yiUhqbQr4dyrLMwNzk/maG/wArKC4j1hXF2EHh1/4ENkBZoeiMu+DwXljZvhV3805Op6KmgfW721dNaFmdZtcK2PqVaX91xQQ8+/yiUsYMDM/2J7ABygpFWWdBv3Gw4K/tmv7IPR4q1NuhLIv8J8zwinE3tn5sG1XW1LNmZzm5YbS8hjcboKzQIwJn3gUHt8K6d9qcvFdyPNkZieEyHso6UVXsMsMqxt4A3QJfBVe47SBNChPDtP0JbICyQtXQi6HnEPj6YbP8QBtNyk5nSXEZ9Y1NQSicZQVAwVOgTZA7s/Vj2yG/qJQYlzBuUPiuZGQDlBWaoqJg8h2wdzVs/qTNyfOye1JV18iqkvIgFM6yOqj2MCx9wQyr6JEZlFMUFJUxakAq3WLDs/0JbICyQtnIayB5AHzV9rGo7m61+eExL591olnxN6gpN13Lg6CqtoHVYd7+BDZAWaEsOtaMrN++ELbntylpWmIsw/ok2Y4SVuhpaoT8x2HA6TBwQuvHt0PhtoM0NmnYDtB1swHKCm3jboRuafD1X9qcNC+7J4VbD1Lb0BiEgllWO22cbzoABenpCaCgqBRXlDD+pPBtfwIboKxQF5toZnf+5gOzmFsbTMpOp7ahieXbDwWpcJbVDoseh9RBMOySoJ2ioLiMUQNSSIzza7rVkGUDlBX6Tr/ZjBX5+uE2JZuQlUaUYLubW6GjZKlZ92zireAKTvA4UtfAyh2Hwr56D2yAssJBQhqMn2HGjBzc6neylG4xnNY/hXwboKxQsegxiEuGcTcE7RTLth2ioUmZGOYdJMAGKCtcTJplVt5d8EjbkmWns3zHQarrbDuU1cUObYd178L46RAXvKVgCopN+1NOmLc/gQ1QVrhI7gujp8LyV+DwPr+T5WX3pL5RKdxW1vrBlhVMBU+ZnxN+EtzTFJVxWr9kkuIDP7dfZ7MBygofk++Axjozf5mfck7qQXSU2HYoq2vVVMCyl2DEFZA6sPXj23ua+kZW7DgU1tMbebIBygof6dlmSYIlz5lBjn5IjItmzMBUG6CsrrX8ZaitCGrXcoBl2w9S19gU9gN03fwKUCJygYhsFJHNInJPM8dMcVb2XCsiXzjbBorIZyKy3tn+c4/j7xeRnXZFUKtNzrzLXOhLnvM7yaTsdFaXHKKipj6IBbOsZjQ2QP5sGJRn1jsLooKiMqIEcjJPkAAlIi7gceBCYDgwTUSGex2TCjwBXKaqI4BrnF0NwC9U9VQgF7jNK+1f7IqgVpv0HQ3Z5zoLGlb7lWRSdjpNCkuKbTuU1QU2/BPKt8Ok24J+qvyiUob3SyY5AtqfwL8nqAnAZlUtUtU6YC7gvfTjdcBbqrodQFX3OT93q+oy5/dKYD3QP1CFt05QZ9wJVfthxat+HT5uUA9io6PCYhl4K8KowsLHoEcWDL0wqKeqqW9keYSMf3LzJ0D1B3Z4vC/h+CAzBOghIp+LyFIROW71LRHJBMYCBR6bZ4nIKhF5XkR89okUkVtEpFBECvfv3+9Hca2Il3mGmcdswSN+LWgYH+Ni/KAeIdcO1VrVuYjc7VEFvkZEGkUkzZ+0VojYsRh2Fpqnp6jgziq+csch6hqajk6UHAn8CVDiY5v3Aj3RwHjgYuB7wG9FZMjRDES6A28Cd6iqex3uJ4FsYAywG3jI18lV9WlVzVHVnIyMDD+Ka0U8EbMs/KFtsPYtv5LkZaezbncFB6vqglw4//hTda6qD7irwIF7gS9UtcyftFaIWPQYxKfCmOuCfqr8ojJEYEKEtD+BfwGqBPDsFzkA2OXjmA9UtUpVDwBfAqMBRCQGE5xeVdWjf01Uda+qNqpqE/AMpirRsvwz5ALIGGYmkfVjQcNJ2eausqA4ZJ6i/Kk69zQNeK2daa2uUFYMG96DnB+aOSWDaEfZEd5cVsKpfZJJSYiM9ifwL0AtAU4RkSwRiQWmAvO8jnkXOFNEokUkAZgIviQ7YgAAGM1JREFUrBcRAZ4D1qvqMYv6iEhfj7dXAmva+yGsE1BUlGmL2rcOvvmw1cNHDUglIdYVStV8/lSdA+BcUxdgbvT8Tmurx7tYwWwQV9AH5i7dVsYVjy/g0JE67rs0sh6kWw1QqtoAzAI+xHRyeF1V14rITBGZ6RyzHvgAWAUsBp5V1TXAZOAG4Ds+upP/SURWi8gq4BzgzkB/OCvCnXYVpAzyaymO2OgoTs9MC6WOEv5UnbtdCixQVXc3RL/S2urxLlR9CJa9bP6PJvdt/fh2emf5TqY9XUBSfDRv3zY5Ygbouvk1na7TBXy+17bZXu8fAB7w2vY1vi8mVDV4syVaJwZXDOTdDu/fDdsWwkl5LR4+KTudP76/gX2VNfRKiu+kQjbLn6pzt6l8W73X1rRWV1j2ItRXwaSfBiX7pibl4U++4ZF/b2ZiVhqzrx9Pj8TYoJyrK9mZJKzwNvZ6SOjp17LweU47VIg8RflTdY6IpABn8//bu/PwqMrrgePfk42ELYEEghDCEtYEBCQQEuCHG4pKBSq2aMV9oYoLtv3VLta2tn1abVUqKj+qVK1WinWBKiqoCAIJEHYCooEACZCNJWzZc35/3MEnDYFMyCQzmZzP8/Bk5s5775zhyTsn997zvq9zGb1e+xovqSx35t3rOdYZt+dhxWWVPPjWJv76eSbfS4zhH3cl+WVyAktQprkLaQ2jZkDmMsjddt6mCV3DaRcaRNoe7ycody6du0wBlqrqqbr2bbrozXllvA/HDzhn9x6Wf7yEafNSWbL9ED+/dgB/uuFiQoL892u8eS+3aAzAiHtg1WznXtTU+edsFhggJPWK9JlCCTcvnb8KvOrOvsYHqELq8xDZF/qM9+ihMw4Wcfdr6RQVlzNveiLj46M9enxf5L+p17QcYREw4k7IeA8O7z5v05S4SPYdPs2BY+5Nk2RMvexbA4e2OPeeAjz39bo0I5cb56YC8PaM5BaRnMASlPEXo+6HgGBY8/x5myX71n0o429S50BYR7h4mkcOp6rMW7mb+97YQN/ObVn0wGgSuoZ75NjNgSUo4x/adXFG629+E07knrNZ/+h2dGwTwprdhU0YnGkRCjNh10cw4m7n3mgDlVVU8dg72/jDkq+4dvBF/Ou+ZDq393r1aZOyBGX8x+iHoKrivAsaBgQIo3p3JG33YdSNGSiMcdval5yhDyPubvChjp4qY/ora/lXejYPXdGX56cNIzS4cefy80WWoIz/6NgbEqbA+vnOQMlzSI6L4mBRCfsOn27C4IxfO30ENr0Jg78H7Rp2f2h3wUmmvLiaTfuP8dz3h/Lo+H4EBNQ6nNTvWYIy/mXMLCg7Aev/ds4m346H8oFyc+Mn0udDRXGD13xanVnIlBdWc6KkgrfuTWLysJa9OpElKONfugx2ynvT5kJZ7WdIvaPa0LldK58pNzfNXEUprJsHcZdD9IXPhffm2n3cOn8dXcJDef+B0Qzv4T+zkl8oS1DG/4x9FE4XwqY3an1ZREiJiyTV7kMZT9j+LpzMu+Czp8oq5bf/2cEv3tvO2L5RvPPDFLp3bHiRhT+wBGX8T48U6D4K1vzVmXamFslxkRSeLCUz/2QTB2f8iqpTWt5pIMRdUe/dT5SUc8/r6cxfncUdo3vy8q2JtPOT5do9wRKU8U9jZkFRNmx/p9aXU+KiAOwyn2mYrBWQt905e5L6FTJkHznN1JdSWfF1Ab+bPIgnvpNAUKB9JVdn/xvGP/W7GjrHO9MfVVWd9XL3jq2J6RBmA3ZNw6S+AG06weAb67Xbhn1HmfLiag4WFfPaHSO5ZVSPRgqwebMEZfyTiHMWVfAVfP1xrU2Se0eSuucwVVV2H8pcgIJd8M1SZy7IYPcH0C7afICb/pZGm1ZBvHf/aMb0jWrEIJs3S1DGfyV8FyJ6wKpnal0WPqVPJEXF5ew4dNwLwZlmL/UFCAqFEXe51byqSnlm6S4eXrCZod0jeP/+0fTp3LaRg2zeLEEZ/xUY5MwukbMe9q466+Xk3s5frr6w/IZpZk4VwpYFMGQatKn7DKikvJIHFzhrON04PIY3/HgNJ0+yBGX829AfOPcIalkWvkt4KL2j2lihhKm/9a9AZakzSXEd8k+U8P15aSzZdojHrhnAU1P9ew0nT3Lrf0lEJojILhHJFJHHztHmUhHZLCIZIrKirn1FpKOILBORb1w/OzT84xhTQ3CY8yWy+zM4uPmsl5PjIlmXdYSKyrMLKYypVXmJM1NJ36ugU//zNt1x8DiT56zm69wTzL1lODPGxSH1rPZryepMUCISCLwAXAPEAzeJSHyNNhHAi8D1qpoA3OjGvo8Bn6lqX+Az13NjPG/EXdCqfa1nUclxkZwsrWDbgSIvBGaapW0L4VQBJM88b7NPd+Qxde4aqtRZw+nqhC5NFKD/cOcMaiSQqap7VLUMWABMqtHmZuBdVd0PoKr5buw7CXjN9fg1YPKFfwxjziM03ElSOxadtaDhqN7OvHx2mc/UqbwYVjwNH/3UmVKr1//U2kxV+dvKPdzzj3T6dG7LopmjGdSt5azh5EnuJKhuQHa15zmubdX1AzqIyBciskFEbnVj32hVPQTg+tm5tjcXkXtFJF1E0gsKCtwI15hajLofAkNg9XP/tTmqbSv6R7ezQglzbqqwYzG8MBKW/w76XAk3Lah1YO6ZNZx+v2Qn1wzqwr/uTSa6ha3h5ElBbrSp7YJpzZrdIGA4cAUQBqSKSJqb+56Xqs4D5gEkJibagBVzYdp2hmG3wMbX4dKfQfuu376UHBfJgvX7Ka2opFVQy1tzx5xH3g74+KeQtdIZ+H3rYug9rtamx06XMeONDaTtOcKDl/dh1pUtd5kMT3HnDCoH6F7teQxwsJY2H6vqKVUtBFYCQ+rYN09ELgJw/czHmMY0+iHQKmf8SjUpcZGUlFexJbtp70M1sPholmvbdhF5S0Tsz3RPOn0ElvwE5o6BQ1vh2j/DfV+eMzntKTjJlBfXsHHfMZ79/hB+dFV/S04e4E6CWg/0FZFeIhICTAMW12izCBgrIkEi0hpIAnbWse9i4DbX49tcxzCm8XToCYNugPS/O19ALkm9IhGhSZeBb2DxUTfgISBRVQcBgTh9yzRUVSWsfxmeH+78HH47PLQJRt7jjKurxerMQia/sJqi4nL+eU8SU4bFNG3MfqzOBKWqFcBM4BOcpLNQVTNEZIaIzHC12Ql8DGwF1gEvq+r2c+3rOvQfgfEi8g0w3vXcmMY15hEoP+V8+biEtw5mUNfwpi6UaEjxETiX1cNEJAhozdlXNUx97V0N/zcOPvyRcznvvpUw8Rlofe51mf65dj+3zV9HdPtQFj0wmsSetoaTJ7lzDwpVXQIsqbFtbo3nTwNPu7Ova/thnHtWxjSd6AToNwHSXnJmoA5pAzj3oV5dvZfiskrCQprkPlRtBURJNdr0A4JF5AugHTBbVV9X1QMi8mdgP1AMLFXVpTXfQETuBe4FiI2N9fwn8BfHsmHZ45DxHoR3hxtfhfjJ552dvLJK+cOSnbyyKotx/Trx/M3DaG/LZHicDWc2Lc+YR6H4iFMw4ZIcF0lZZRUb9h1tqijqU3x0HXA18LiI9HMNap8E9AK6Am1E5JazDqY6T1UTVTWxU6dOno3eH5QXwxd/gjkjYNdHMO4xeGAdJEw5b3I6WVrBPa+n88qqLG5P6ckrtyVacmokbp1BGeNXYpMgNgXWzIHEuyAohBE9OxIYIKTuKWyq2aXdLT4qVNVTwCkROVN8BJClqgUAIvIukALUvoSw+W+qzpi4pY9D0X7nbOmqJyHi3GeZJeWVrPqmkKU7cvl0Zz5FxeU8OSmB6ck9my7uFsgSlGmZxj4Kb06FbW/DsB/QtlUQQ2Ka9D7UtwVEwAGcIoeba7RZBMxx3WcKwbkE+CzQBhjlKkgqxrlUnt5UgTdreRnOQNu9X0L0IJj8AfQaW2vTotPlLN+VzycZuaz4uoDTZZW0axXEZQM6Mz25ByPsflOjswRlWqY+V0L0YGfg7pCbICCAlLgoXlqxm5OlFbRt1bhdQ1UrRORMAVEgMP9M8ZHr9bmqulNEzhQfVeEqPgIQkX8DG4EKYBOusYLmHE4fgeV/gPRXnJlFrvsLXHL7WZV5uUUlLNuRyycZeaTtOUxFldK5XSumDOvG1QldGNU70iZ6bUKWoEzLJOJU9L1zF+z6EAZ+h+S4SOYsz2R91hEuG1DrxCYe1cDioyeAJxo1QH9QWQEb/g7Lfw8lRc4l3ct+/l+VeZn5J/kkI5elO/LYkn0MgN5Rbbh7bG+uSohmaEyEjWnyEktQpuWKnwyf/w6+fAYGTGR4jw6EBAawZndhkyQo08iyvnQu5+VnQM+xcM2fIDqBqiply/6jLN2RxycZuewpOAXAkJhwfnJ1f65OiKZP53ZeDt6AJSjTkp1Z0PCDWZC1ktDe4xgWG0GqzcvXvB3bD0t/6RRChMfC916nrO9E0rKOsDR1G8t25JF3vJSgAGFU70huT+nJ+PhoLgoP83bkpgZLUKZlG3IzfPFHZ1n43uNIiYviuc++5tjpMiJa24qnzUrZaVg92zUhsFA29jE+j5zGR1uP8fnCTzlRUkFYcCCX9u/EVQnRXN4/mvDWVh7uyyxBmZYtONQZsLvsV3BgIyl9evLsp5C25wgTBtn6Pc2CqjPIdtmvoCib/RdN4PnA6SxaHkhZxQ46tA5mQkIXrk7owpi+UYQG24TAzYUlKGOG3wFf/gVWPcuQG14jLDiQtD2HLUE1B7nbKPnPTwg9kMreoN78tOxx1mYNpFtEGLckdeGqhGgSe3QgKNAq75ojS1DGhLaHEffAl38h5GgmiT07NOnEsaZ+VJVdWfsoXfpbBuW+x2ltzZMVd7Ip/HrGJ3XjVwnRxF/U3pZW9wOWoIwBSJoBqXNgzWyS42bx1Me7KDhRSqd2rbwdmcGZ+y597xGWbj9Am22vc2fZP2lLMUvbTKQw8VHuG9Kf2MjW3g7TeJglKGMA2naCS26F9L8z7nszeQpI23OY7wzpWueupnHUnF6of/Emfh38Ov0lm9yoJHTiU1zTa6i3wzSNyBKUMWekPAjrX2Fg1mu0a3UZa3ZbgmpqqsrWnCIWpmezeMtBTpRU0D/0CPPbLWRo5UqqwmNhwht0GTDxvBO6Gv9gCcqYMyJiYfCNBGx8jctiryTNxkM1mcMnS3lv0wHeTs9hV94JWgUFMDkhgvuDPyD2q5eRkgC47JcEpMyEYBuv1FJYgjKmujGPwNYF3B60lO8WjuNQUbEN4GwkFZVVrPymgIXrc/h0Zx4VVcrImDBeSykguXQVIZmfQOlxGDQVxv8Gwm2l2pbGEpQx1XUeCP2v4+K9C2hNEqm7D/PdS+yL0ZP2FJzk7Q05vLMhh/wTpXRrXcUfB+7nKllL+/2fwcaTEBoBA6937gvG1lzH0bQUlqCMqWnMLIJ2fcidYStYs7uPJSgPOFlawZKth1iYnk36vqO0DyjhgW67mdQ5nei8lcjuYmgdCYOnQvwkZ+68QJvloaVzK0GJyARgNs6yAC+r6h9rvH4pzto1Wa5N76rqb0WkP/Cvak17A79S1edE5NfAPUCB67Wfu2Z3Nsa7uo+AnmO5K/tDpmReh+rFNqbmAqgq6fuOsnB9Nh9uO0Rg2Qluisjg6ZhN9DyaihSUQttoGPYDJynFppy1/IVp2er8bRCRQOAFYDzOCp/rRWSxqu6o0fRLVZ1YfYOq7gKGVjvOAeC9ak2eVdU/NyB+YxrHmEfo8MYNjCj5lOwjY22MTT3kHS/hnY05vJ2ew5HCPCaGbOKd8M30P7WBgJIyCO4KiXc4Sal7EgTY1EOmdu78uTISyFTVPQAisgCYBNRMUHW5AtitqvvquZ8xTS/uCkqiBjEj/z+kZt5PbGQvb0fk08oqqvj8qzwWpuewZVcmVwZs4Nm2G7k4bAsBWgEBsZB0r5OUuiVCgE09ZOrmToLqBmRXe56Ds/R0TckisgU4CPxYVTNqvD4NeKvGtpkicivOctU/UtWjNQ8qIvcC9wLExsa6Ea4xHiBCq0t/TNy/b2fFlvchaZa3I/JJX+Ue5+30HFZszCCpdA0zQtaT2GoHAVRC656QONNJSl2H2bglU2/uJKjafqu0xvONQA9VPSki1wLvA32/PYBICHA98LNq+7wEPOk61pPAX4A7z3oj1Xm4lrNOTEys+b7GNBqJv5784BhGHfoHWvUwYn/1A1BUXM7iLQf5bO0meuR/znWBa/lFwC4CghXt2AeJn+UkpS6DLSmZBnEnQeUA3as9j8E5S/qWqh6v9niJiLwoIlGqembGzWuAjaqaV63dt49F5G/ABxcQvzGNJyCQvQPuZuS2X3Ng00d0G36dtyPymqoqJXXPYZalphPy9QdcJWuZHvA1BENF1AACEn4K8ZOQzgMtKRmPcSdBrQf6ikgvnCKHacDN1RuISBcgT1VVREYCAUD1Yfg3UePynohcpKqHXE+nANsv7CMY03iix95G7tbZBKx+DjycoOqqjnW1uRR4DggGClV1nGt7BPAyMAjnKsSdqprq0QCB7COnWbYmjeLN7zG6bDW/DtgNgVAcmYBe/EskfhJBnfp5+m2NAdxIUKpaISIzgU9wOtJ8Vc0QkRmu1+cCU4EfikgFUAxMU1UFEJHWOBWA99U49FMiMhSnc+2t5XVjvC62UwfmBE/iwSOvQs4GiBnukeO6Ux3rSkIvAhNUdb+IdK52iNnAx6o61XUJ3WNlhiXllaxam8bhdW8Tf2w5dwbsBeBox0GUD3uC4EGTCIuM89TbGXNObg06cI1PWlJj29xqj+cAc86x72kgspbt0+sVqTFeICIciptG2q4NjKwsx4N3odypjr0ZZ0zhfgBVzXe1bQ/8D3C7a3sZUNaQYFSVr7evJ2f1ArrnLuNK9gNwKHwwx4Y+QcQlN9ChQ4+GvIUx9Waj4oypw/B+3Zm25WcsCY4n3nOHdac6th8QLCJfAO2A2ar6Os6A9wLg7yIyBNgAPKyqp6rv7E4FrKqy8Y1fEJW1mP5V2fRVIav1ILISfkmP0dO4qEP3WvczpilYgjKmDslxkYQGB7D38Cniu7b31GHdqY4NAobjjCEMA1JFJM21/RLgQVVdKyKzgceAx//rYG5UwIoIcmADRYEdWDdgOgMuu5m4TpaUjG+wBGVMHbpGhLH1iasJCfJomXmd1bGuNoWuM6NTIrISGAJ8CeSo6lpXu3/jJKgLMvCR/xAWGnKhuxvTaGxghzFu8HBygmrVsa4ih2nA4hptFgFjRSTIVWyUBOxU1Vwg2zXXJThnWPWd2eVblpyMr7IzKGO8wJ3qWFXdKSIfA1uBKpxS9DPDMR4E3nQltz3AHU3/KYxpXJagjPGSuqpjXc+fBp6uZd/NQGKjBmiMl9klPmOMMT7JEpQxxhifZAnKGGOMT7IEZYwxxidZgjLGGOOTLEEZY4zxSeKadLxZEJEC4HxLxkcBhed53VssrvppjnH1UNVOTRlMfVjf8TiLq37qiqvW/tOsElRdRCRdVX1ubIjFVT8WV9Pz1c9mcdWPv8Vll/iMMcb4JEtQxhhjfJK/Jah53g7gHCyu+rG4mp6vfjaLq378Ki6/ugdljDHGf/jbGZQxxhg/YQnKGGOMT/KLBCUiE0Rkl4hkisgFryzqSSIyX0TyRWR73a2bjoh0F5HlIrJTRDJE5GFvxwQgIqEisk5Etrji+o23Y6pORAJFZJOIfODtWDzJF/sOWP+pL1/uPw3pO80+QYlIIPACcA0QD9wkIvHejQqAV4EJ3g6iFhXAj1R1IDAKeMBH/r9KgctVdQgwFJggIqO8HFN1DwM7vR2EJ/lw3wHrP/Xly/3ngvtOs09QwEggU1X3qGoZsACY5OWYUNWVwBFvx1GTqh5S1Y2uxydwfnG6eTcqUMdJ19Ng1z+fqOARkRjgOuBlb8fiYT7Zd8D6T335av9paN/xhwTVDciu9jwHH/iFaQ5EpCcwDFjr3UgcrksBm4F8YJmq+kRcwHPA/+Isu+5PrO80gPUftzSo7/hDgpJatnn9LwdfJyJtgXeAR1T1uLfjAVDVSlUdCsQAI0VkkLdjEpGJQL6qbvB2LI3A+s4Fsv5TN0/0HX9IUDlA92rPY4CDXoqlWRCRYJzO9aaqvuvteGpS1WPAF/jGPYjRwPUishfnEtjlIvKGd0PyGOs7F8D6j9sa3Hf8IUGtB/qKSC8RCQGmAYu9HJPPEhEBXgF2quoz3o7nDBHpJCIRrsdhwJXAV96NClT1Z6oao6o9cX63PlfVW7wclqdY36kn6z/u80TfafYJSlUrgJnAJzg3LBeqaoZ3owIReQtIBfqLSI6I3OXtmFxGA9Nx/prZ7Pp3rbeDAi4ClovIVpwvzmWq6lcl3b7GV/sOWP+5AH7Zf2yqI2OMMT6p2Z9BGWOM8U+WoIwxxvgkS1DGGGN8kiUoY4wxPskSlDHGGJ9kCcoYY4xPsgRljDHGJ/0/6i4DSGi8S68AAAAASUVORK5CYII=\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ - "2560/2560 [==============================] - 12s 5ms/step\n", + "52/52 [==============================] - 0s 7ms/step - loss: 0.5426 - accuracy: 0.8152\n", "\n", - "Accurancy: 0.852\n" + "Accuracy: 0.8152\n" ] } ], "source": [ - "num_epochs = 7\n", - "lstm_units = 93\n", - "\n", - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Embedding(vocabulary_size, embedding_size)(text_input)\n", - "x = LSTM(units=lstm_units, return_sequences=True)(x)\n", - "x = LSTM(units=lstm_units)(x)\n", - "x = Dense(128, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_token_train, y_token_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_token_test, y_token_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.3f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('word_saved_models/LSTM-Token-{:.3f}.h5'.format((scores[1] * 100)))\n" + "run_experiment(construct_lstm(), token_dataset, num_epochs=5)" ] }, { @@ -778,262 +687,127 @@ }, { "cell_type": "code", - "execution_count": 108, + "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Train on 8195 samples, validate on 2049 samples\n", - "Epoch 1/7\n", - "8195/8195 [==============================] - 99s 12ms/step - loss: 0.8054 - acc: 0.6630 - val_loss: 0.7406 - val_acc: 0.6593\n", - "Epoch 2/7\n", - "8195/8195 [==============================] - 100s 12ms/step - loss: 0.7322 - acc: 0.6671 - val_loss: 0.7363 - val_acc: 0.6593\n", - "Epoch 3/7\n", - "8195/8195 [==============================] - 99s 12ms/step - loss: 0.7283 - acc: 0.6748 - val_loss: 0.7326 - val_acc: 0.6911\n", - "Epoch 4/7\n", - "8195/8195 [==============================] - 96s 12ms/step - loss: 0.7148 - acc: 0.6941 - val_loss: 0.7277 - val_acc: 0.6984\n", - "Epoch 5/7\n", - "8195/8195 [==============================] - 96s 12ms/step - loss: 0.5452 - acc: 0.7980 - val_loss: 0.4492 - val_acc: 0.8277\n", - "Epoch 6/7\n", - "8195/8195 [==============================] - 99s 12ms/step - loss: 0.3767 - acc: 0.8709 - val_loss: 0.4376 - val_acc: 0.8375\n", - "Epoch 7/7\n", - "8195/8195 [==============================] - 96s 12ms/step - loss: 0.3036 - acc: 0.9054 - val_loss: 0.4061 - val_acc: 0.8619\n" + "Epoch 1/4\n", + "164/164 [==============================] - 5s 28ms/step - loss: 0.7567 - accuracy: 0.6710 - val_loss: 0.7291 - val_accuracy: 0.6891- los - ETA: 1s - los - ETA: 1s\n", + "Epoch 2/4\n", + "164/164 [==============================] - 4s 23ms/step - loss: 0.7210 - accuracy: 0.6962 - val_loss: 0.7057 - val_accuracy: 0.6989\n", + "Epoch 3/4\n", + "164/164 [==============================] - 4s 23ms/step - loss: 0.5711 - accuracy: 0.7979 - val_loss: 0.4634 - val_accuracy: 0.8214\n", + "Epoch 4/4\n", + "164/164 [==============================] - 4s 23ms/step - loss: 0.3806 - accuracy: 0.8790 - val_loss: 0.3902 - val_accuracy: 0.8599\n" ] }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ - "2560/2560 [==============================] - 8s 3ms/step\n", + "52/52 [==============================] - 0s 7ms/step - loss: 0.3703 - accuracy: 0.8766\n", "\n", - "Accurancy: 0.862\n" + "Accuracy: 0.8766\n" ] } ], "source": [ - "num_epochs = 7\n", - "\n", - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Embedding(vocabulary_size, embedding_size)(text_input)\n", - "x = LSTM(units=lstm_units, return_sequences=True)(x)\n", - "x = LSTM(units=lstm_units)(x)\n", - "x = Dense(128, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_morph_train, y_morph_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_morph_test, y_morph_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.3f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('word_saved_models/LSTM-Morph-{:.3f}.h5'.format((scores[1] * 100)))" + "run_experiment(construct_lstm(), morph_dataset, num_epochs=4)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## BiLSTM" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def construct_bilstm(units=93):\n", + " return Sequential([\n", + " layers.Embedding(vocabulary_size, embedding_size, input_length=max_document_length),\n", + " layers.Bidirectional(layers.LSTM(units, return_sequences=True)),\n", + " layers.Bidirectional(layers.LSTM(units)),\n", + " layers.Dense(128, activation='relu'),\n", + " layers.Dropout(dropout_keep_prob),\n", + " layers.Dense(3, activation='softmax'),\n", + " ], name=\"BiLSTM\") " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## BiLSTM - Token" + "### BiLSTM - Token" ] }, { "cell_type": "code", - "execution_count": 109, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Train on 8195 samples, validate on 2049 samples\n", - "Epoch 1/3\n", - "8195/8195 [==============================] - 219s 27ms/step - loss: 0.7574 - acc: 0.6876 - val_loss: 0.6579 - val_acc: 0.7272\n", - "Epoch 2/3\n", - "8195/8195 [==============================] - 212s 26ms/step - loss: 0.5360 - acc: 0.7993 - val_loss: 0.4653 - val_acc: 0.8253\n", - "Epoch 3/3\n", - "8195/8195 [==============================] - 212s 26ms/step - loss: 0.3556 - acc: 0.8819 - val_loss: 0.4067 - val_acc: 0.8536\n" - ] - }, - { - "data": { - "image/png": "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\n", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2560/2560 [==============================] - 16s 6ms/step\n", - "\n", - "Accurancy: 0.874\n" - ] - } - ], + "outputs": [], "source": [ - "num_epochs = 3\n", - "\n", - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Embedding(vocabulary_size, embedding_size)(text_input)\n", - "x = Bidirectional(LSTM(units=lstm_units, return_sequences=True))(x)\n", - "x = Bidirectional(LSTM(units=lstm_units))(x)\n", - "x = Dense(128, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_token_train, y_token_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_token_test, y_token_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.3f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('word_saved_models/BiLSTM-Token-{:.3f}.h5'.format((scores[1] * 100)))" + "run_experiment(construct_bilstm(), token_dataset, num_epochs=4)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## BiLSTM - Morph" + "### BiLSTM - Morph" ] }, { "cell_type": "code", - "execution_count": 110, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Train on 8195 samples, validate on 2049 samples\n", - "Epoch 1/3\n", - "8195/8195 [==============================] - 217s 26ms/step - loss: 0.7777 - acc: 0.6633 - val_loss: 0.6716 - val_acc: 0.7052\n", - "Epoch 2/3\n", - "8195/8195 [==============================] - 210s 26ms/step - loss: 0.5638 - acc: 0.7790 - val_loss: 0.4487 - val_acc: 0.8350\n", - "Epoch 3/3\n", - "8195/8195 [==============================] - 211s 26ms/step - loss: 0.3663 - acc: 0.8722 - val_loss: 0.3792 - val_acc: 0.8638\n" - ] - }, - { - "data": { - "image/png": "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\n", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2560/2560 [==============================] - 16s 6ms/step\n", - "\n", - "Accurancy: 0.875\n" - ] - } - ], + "outputs": [], "source": [ - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Embedding(vocabulary_size, embedding_size)(text_input)\n", - "x = Bidirectional(LSTM(units=lstm_units, return_sequences=True))(x)\n", - "x = Bidirectional(LSTM(units=lstm_units))(x)\n", - "x = Dense(128, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_morph_train, y_morph_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_morph_test, y_morph_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.3f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('word_saved_models/BiLSTM-Morph-{:.3f}.h5'.format((scores[1] * 100)))" + "run_experiment(construct_bilstm(), morph_dataset, num_epochs=4)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## MLP" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "def construct_mlp():\n", + " return Sequential([\n", + " layers.Embedding(vocabulary_size, embedding_size, input_length=max_document_length),\n", + " layers.Flatten(),\n", + " layers.Dense(256, activation='relu'), layers.Dropout(dropout_keep_prob),\n", + " layers.Dense(128, activation='relu'), layers.Dropout(dropout_keep_prob),\n", + " layers.Dense(64, activation='relu'), layers.Dropout(dropout_keep_prob),\n", + " layers.Dense(3, activation='softmax')\n", + " ], name=\"MLP\")" ] }, { @@ -1045,91 +819,51 @@ }, { "cell_type": "code", - "execution_count": 111, + "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Train on 8195 samples, validate on 2049 samples\n", "Epoch 1/6\n", - "8195/8195 [==============================] - 56s 7ms/step - loss: 0.8829 - acc: 0.5907 - val_loss: 0.7232 - val_acc: 0.6950\n", + "164/164 [==============================] - 3s 15ms/step - loss: 0.7707 - accuracy: 0.6570 - val_loss: 0.6525 - val_accuracy: 0.7301\n", "Epoch 2/6\n", - "8195/8195 [==============================] - 55s 7ms/step - loss: 0.7718 - acc: 0.6595 - val_loss: 0.6982 - val_acc: 0.7135\n", + "164/164 [==============================] - 2s 15ms/step - loss: 0.5863 - accuracy: 0.7668 - val_loss: 0.4506 - val_accuracy: 0.8272\n", "Epoch 3/6\n", - "8195/8195 [==============================] - 56s 7ms/step - loss: 0.7250 - acc: 0.6948 - val_loss: 0.6528 - val_acc: 0.7243\n", + "164/164 [==============================] - 2s 15ms/step - loss: 0.3912 - accuracy: 0.8661 - val_loss: 0.3603 - val_accuracy: 0.8668\n", "Epoch 4/6\n", - "8195/8195 [==============================] - 55s 7ms/step - loss: 0.6569 - acc: 0.7300 - val_loss: 0.5763 - val_acc: 0.7672\n", + "164/164 [==============================] - 2s 15ms/step - loss: 0.2804 - accuracy: 0.9121 - val_loss: 0.3306 - val_accuracy: 0.8780\n", "Epoch 5/6\n", - "8195/8195 [==============================] - 56s 7ms/step - loss: 0.5388 - acc: 0.7971 - val_loss: 0.4485 - val_acc: 0.8321\n", + "164/164 [==============================] - 2s 15ms/step - loss: 0.2036 - accuracy: 0.9375 - val_loss: 0.3197 - val_accuracy: 0.8907\n", "Epoch 6/6\n", - "8195/8195 [==============================] - 56s 7ms/step - loss: 0.4014 - acc: 0.8664 - val_loss: 0.3789 - val_acc: 0.8638\n" + "164/164 [==============================] - 2s 15ms/step - loss: 0.1563 - accuracy: 0.9502 - val_loss: 0.3335 - val_accuracy: 0.8931\n" ] }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ - "2560/2560 [==============================] - 2s 702us/step\n", + "52/52 [==============================] - 0s 4ms/step - loss: 0.3171 - accuracy: 0.8992\n", "\n", - "Accurancy: 0.868\n" + "Accuracy: 0.8992\n" ] } ], "source": [ - "num_epochs = 6\n", - "\n", - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Embedding(vocabulary_size, embedding_size)(text_input)\n", - "x = Flatten()(x)\n", - "x = Dense(256, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "x = Dense(128, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "x = Dense(64, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_token_train, y_token_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_token_test, y_token_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.3f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('word_saved_models/MLP-Token-{:.3f}.h5'.format((scores[1] * 100)))" + "run_experiment(construct_mlp(), token_dataset, num_epochs=6)" ] }, { @@ -1141,89 +875,51 @@ }, { "cell_type": "code", - "execution_count": 112, + "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Train on 8195 samples, validate on 2049 samples\n", "Epoch 1/6\n", - "8195/8195 [==============================] - 57s 7ms/step - loss: 0.8336 - acc: 0.6349 - val_loss: 0.7146 - val_acc: 0.6940\n", + "164/164 [==============================] - 3s 16ms/step - loss: 0.7685 - accuracy: 0.6692 - val_loss: 0.6694 - val_accuracy: 0.7267\n", "Epoch 2/6\n", - "8195/8195 [==============================] - 56s 7ms/step - loss: 0.7561 - acc: 0.6727 - val_loss: 0.6825 - val_acc: 0.7101\n", + "164/164 [==============================] - 2s 15ms/step - loss: 0.6141 - accuracy: 0.7561 - val_loss: 0.4841 - val_accuracy: 0.8209\n", "Epoch 3/6\n", - "8195/8195 [==============================] - 56s 7ms/step - loss: 0.7124 - acc: 0.6981 - val_loss: 0.6535 - val_acc: 0.7194\n", + "164/164 [==============================] - 2s 15ms/step - loss: 0.4083 - accuracy: 0.8563 - val_loss: 0.3660 - val_accuracy: 0.8604\n", "Epoch 4/6\n", - "8195/8195 [==============================] - 56s 7ms/step - loss: 0.6369 - acc: 0.7389 - val_loss: 0.5678 - val_acc: 0.7579\n", + "164/164 [==============================] - 3s 15ms/step - loss: 0.2754 - accuracy: 0.9126 - val_loss: 0.3362 - val_accuracy: 0.8795\n", "Epoch 5/6\n", - "8195/8195 [==============================] - 55s 7ms/step - loss: 0.5140 - acc: 0.8088 - val_loss: 0.4434 - val_acc: 0.8253\n", + "164/164 [==============================] - 2s 15ms/step - loss: 0.1971 - accuracy: 0.9394 - val_loss: 0.3345 - val_accuracy: 0.8843\n", "Epoch 6/6\n", - "8195/8195 [==============================] - 56s 7ms/step - loss: 0.3832 - acc: 0.8663 - val_loss: 0.3724 - val_acc: 0.8580\n" + "164/164 [==============================] - 2s 15ms/step - loss: 0.1516 - accuracy: 0.9523 - val_loss: 0.3603 - val_accuracy: 0.8868\n" ] }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ - "2560/2560 [==============================] - 2s 717us/step\n", + "52/52 [==============================] - 0s 4ms/step - loss: 0.3593 - accuracy: 0.8918\n", "\n", - "Accurancy: 0.864\n" + "Accuracy: 0.8918\n" ] } ], "source": [ - "# Create new TF graph\n", - "K.clear_session()\n", - "\n", - "# Construct model\n", - "text_input = Input(shape=(max_document_length,))\n", - "x = Embedding(vocabulary_size, embedding_size)(text_input)\n", - "x = Flatten()(x)\n", - "x = Dense(256, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "x = Dense(128, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "x = Dense(64, activation='relu')(x)\n", - "x = Dropout(dropout_keep_prob)(x)\n", - "preds = Dense(3, activation='softmax')(x)\n", - "\n", - "model = Model(text_input, preds)\n", - "\n", - "adam = optimizers.Adam(lr=lr)\n", - "\n", - "model.compile(loss='categorical_crossentropy',\n", - " optimizer=adam,\n", - " metrics=['accuracy'])\n", - "\n", - "# Train the model\n", - "history = model.fit(x_morph_train, y_morph_train,\n", - " batch_size=batch_size,\n", - " epochs=num_epochs,\n", - " verbose=1,\n", - " validation_split=dev_size)\n", - "\n", - "# Plot training accuracy and loss\n", - "plot_loss_and_accuracy(history)\n", - "\n", - "# Evaluate the model\n", - "scores = model.evaluate(x_morph_test, y_morph_test,\n", - " batch_size=batch_size, verbose=1)\n", - "print('\\nAccurancy: {:.3f}'.format(scores[1]))\n", - "\n", - "# Save the model\n", - "model.save('word_saved_models/MLP-Morph-{:.3f}.h5'.format((scores[1] * 100)))" + "run_experiment(construct_mlp(), morph_dataset, num_epochs=6)" ] }, { @@ -1250,9 +946,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.3" + "version": "3.8.2" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 }