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Modifying the text_generation.ipynb #1313

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28 changes: 15 additions & 13 deletions docs/tutorials/text_generation.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -160,7 +160,9 @@
"\n",
"import numpy as np\n",
"import os\n",
"import time"
"import time",
"!pip install tf-keras",
"import tf_keras as keras"
]
},
{
Expand All @@ -182,7 +184,7 @@
},
"outputs": [],
"source": [
"path_to_file = tf.keras.utils.get_file('shakespeare.txt', 'https://storage.googleapis.com/download.tensorflow.org/data/shakespeare.txt')"
"path_to_file = keras.utils.get_file('shakespeare.txt', 'https://storage.googleapis.com/download.tensorflow.org/data/shakespeare.txt')"
]
},
{
Expand Down Expand Up @@ -288,7 +290,7 @@
},
"outputs": [],
"source": [
"ids_from_chars = tf.keras.layers.StringLookup(\n",
"ids_from_chars = keras.layers.StringLookup(\n",
" vocabulary=list(vocab), mask_token=None)"
]
},
Expand Down Expand Up @@ -339,7 +341,7 @@
},
"outputs": [],
"source": [
"chars_from_ids = tf.keras.layers.StringLookup(\n",
"chars_from_ids = keras.layers.StringLookup(\n",
" vocabulary=ids_from_chars.get_vocabulary(), invert=True, mask_token=None)"
]
},
Expand Down Expand Up @@ -671,14 +673,14 @@
},
"outputs": [],
"source": [
"class MyModel(tf.keras.Model):\n",
"class MyModel(keras.Model):\n",
" def __init__(self, vocab_size, embedding_dim, rnn_units):\n",
" super().__init__(self)\n",
" self.embedding = tf.keras.layers.Embedding(vocab_size, embedding_dim)\n",
" self.gru = tf.keras.layers.GRU(rnn_units,\n",
" self.embedding = keras.layers.Embedding(vocab_size, embedding_dim)\n",
" self.gru = keras.layers.GRU(rnn_units,\n",
" return_sequences=True,\n",
" return_state=True)\n",
" self.dense = tf.keras.layers.Dense(vocab_size)\n",
" self.dense = keras.layers.Dense(vocab_size)\n",
"\n",
" def call(self, inputs, states=None, return_state=False, training=False):\n",
" x = inputs\n",
Expand Down Expand Up @@ -974,7 +976,7 @@
"# Name of the checkpoint files\n",
"checkpoint_prefix = os.path.join(checkpoint_dir, \"ckpt_{epoch}\")\n",
"\n",
"checkpoint_callback = tf.keras.callbacks.ModelCheckpoint(\n",
"checkpoint_callback = keras.callbacks.ModelCheckpoint(\n",
" filepath=checkpoint_prefix,\n",
" save_weights_only=True)"
]
Expand Down Expand Up @@ -1058,7 +1060,7 @@
},
"outputs": [],
"source": [
"class OneStep(tf.keras.Model):\n",
"class OneStep(keras.Model):\n",
" def __init__(self, model, chars_from_ids, ids_from_chars, temperature=1.0):\n",
" super().__init__()\n",
" self.temperature = temperature\n",
Expand Down Expand Up @@ -1306,8 +1308,8 @@
},
"outputs": [],
"source": [
"model.compile(optimizer = tf.keras.optimizers.Adam(),\n",
" loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True))"
"model.compile(optimizer = keras.optimizers.Adam(),\n",
" loss=keras.losses.SparseCategoricalCrossentropy(from_logits=True))"
]
},
{
Expand Down Expand Up @@ -1345,7 +1347,7 @@
"for epoch in range(EPOCHS):\n",
" start = time.time()\n",
"\n",
" mean.reset_states()\n",
" mean.reset_state()\n",
" for (batch_n, (inp, target)) in enumerate(dataset):\n",
" logs = model.train_step([inp, target])\n",
" mean.update_state(logs['loss'])\n",
Expand Down