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darienmtdarienmt
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Adding a few very simple notebooks
1 parent f7f4c24 commit d21c8bf

4 files changed

+367
-2
lines changed

‎001 - Hello World.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"b'Hello World!'\n"
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]
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}
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],
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"source": [
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"import tensorflow as tf\n",
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"\n",
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"hello_constant = tf.constant('Hello World!')\n",
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"\n",
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"with tf.Session() as sess:\n",
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" output = sess.run(hello_constant)\n",
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"\n",
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"print(output)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.0"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎002 - Hello World with placeholder.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Hello World with Placeholder\n"
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]
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}
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],
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"source": [
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"import tensorflow as tf\n",
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"\n",
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"x = tf.placeholder(tf.string)\n",
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"\n",
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"with tf.Session() as sess:\n",
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" output = sess.run(x, feed_dict={x: 'Hello World with Placeholder'})\n",
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"\n",
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"print(output)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Placeholders have types"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"y = tf.placeholder(tf.int32)\n",
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"z = tf.placeholder(tf.float32)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"123\n"
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]
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}
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],
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"source": [
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"with tf.Session() as sess:\n",
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" output = sess.run(y, feed_dict={x: 'Test String', y: 123, z: 45.67})\n",
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"\n",
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"print(output)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## and if you pass the wrong type you get an error"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"ename": "ValueError",
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"evalue": "invalid literal for int() with base 10: 'Hello'",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m<ipython-input-8-e2d3ac5f480b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSession\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0msess\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0moutput\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msess\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfeed_dict\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'Hello'\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/Users/darienmt/miniconda3/envs/IntroToTensorFlow/lib/python3.6/site-packages/tensorflow/python/client/session.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, fetches, feed_dict, options, run_metadata)\u001b[0m\n\u001b[1;32m 765\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 766\u001b[0m result = self._run(None, fetches, feed_dict, options_ptr,\n\u001b[0;32m--> 767\u001b[0;31m run_metadata_ptr)\n\u001b[0m\u001b[1;32m 768\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mrun_metadata\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 769\u001b[0m \u001b[0mproto_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtf_session\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTF_GetBuffer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrun_metadata_ptr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/Users/darienmt/miniconda3/envs/IntroToTensorFlow/lib/python3.6/site-packages/tensorflow/python/client/session.py\u001b[0m in \u001b[0;36m_run\u001b[0;34m(self, handle, fetches, feed_dict, options, run_metadata)\u001b[0m\n\u001b[1;32m 936\u001b[0m ' to a larger type (e.g. int64).')\n\u001b[1;32m 937\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 938\u001b[0;31m \u001b[0mnp_val\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msubfeed_val\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msubfeed_dtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 939\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 940\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0msubfeed_t\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_shape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_compatible_with\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp_val\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/Users/darienmt/miniconda3/envs/IntroToTensorFlow/lib/python3.6/site-packages/numpy/core/numeric.py\u001b[0m in \u001b[0;36masarray\u001b[0;34m(a, dtype, order)\u001b[0m\n\u001b[1;32m 480\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 481\u001b[0m \"\"\"\n\u001b[0;32m--> 482\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morder\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 483\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 484\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0masanyarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;31mValueError\u001b[0m: invalid literal for int() with base 10: 'Hello'"
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]
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}
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],
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"source": [
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"with tf.Session() as sess:\n",
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" output = sess.run(y, feed_dict={y: 'Hello'})\n",
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"\n",
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"print(output)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.0"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎003 - Doing some math.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Add : 44\n",
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"Subtract: 42\n",
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"Multiply: 126\n"
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]
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}
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],
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"source": [
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"import tensorflow as tf\n",
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"\n",
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"with tf.Session() as sess:\n",
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" add = sess.run( tf.add(4, 40) )\n",
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" print( f'Add : {add}' )\n",
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" \n",
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" subtract = sess.run( tf.subtract(add, 2 ) )\n",
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" print( f'Subtract: {subtract}' )\n",
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" \n",
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" mult = sess.run( tf.multiply(subtract, 3) )\n",
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" print( f'Multiply: {mult}' )"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## both side of the operation should be of the same type"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"ename": "TypeError",
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"evalue": "Input 'y' of 'Mul' Op has type int32 that does not match type float32 of argument 'x'.",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m/Users/darienmt/miniconda3/envs/IntroToTensorFlow/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py\u001b[0m in \u001b[0;36mapply_op\u001b[0;34m(self, op_type_name, name, **keywords)\u001b[0m\n\u001b[1;32m 490\u001b[0m \u001b[0mas_ref\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minput_arg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_ref\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 491\u001b[0;31m preferred_dtype=default_dtype)\n\u001b[0m\u001b[1;32m 492\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/Users/darienmt/miniconda3/envs/IntroToTensorFlow/lib/python3.6/site-packages/tensorflow/python/framework/ops.py\u001b[0m in \u001b[0;36minternal_convert_to_tensor\u001b[0;34m(value, dtype, name, as_ref, preferred_dtype)\u001b[0m\n\u001b[1;32m 715\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mret\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 716\u001b[0;31m \u001b[0mret\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconversion_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mas_ref\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mas_ref\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 717\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/Users/darienmt/miniconda3/envs/IntroToTensorFlow/lib/python3.6/site-packages/tensorflow/python/framework/ops.py\u001b[0m in \u001b[0;36m_TensorTensorConversionFunction\u001b[0;34m(t, dtype, name, as_ref)\u001b[0m\n\u001b[1;32m 588\u001b[0m \u001b[0;34m\"Tensor conversion requested dtype %s for Tensor with dtype %s: %r\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 589\u001b[0;31m % (dtype.name, t.dtype.name, str(t)))\n\u001b[0m\u001b[1;32m 590\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;31mValueError\u001b[0m: Tensor conversion requested dtype float32 for Tensor with dtype int32: 'Tensor(\"Const_1:0\", shape=(), dtype=int32)'",
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"\nDuring handling of the above exception, another exception occurred:\n",
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"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m<ipython-input-11-d43fc9661d0f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSession\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0msess\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mbadOperation\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msess\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m \u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmultiply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 6\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m \u001b[0;34m'Never here'\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/Users/darienmt/miniconda3/envs/IntroToTensorFlow/lib/python3.6/site-packages/tensorflow/python/ops/math_ops.py\u001b[0m in \u001b[0;36mmultiply\u001b[0;34m(x, y, name)\u001b[0m\n\u001b[1;32m 355\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 356\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mmultiply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 357\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mgen_math_ops\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_mul\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 358\u001b[0m \u001b[0mmultiply\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgen_math_ops\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_mul\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreplace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Mul\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"`tf.multiply`\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 359\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
63+
"\u001b[0;32m/Users/darienmt/miniconda3/envs/IntroToTensorFlow/lib/python3.6/site-packages/tensorflow/python/ops/gen_math_ops.py\u001b[0m in \u001b[0;36m_mul\u001b[0;34m(x, y, name)\u001b[0m\n\u001b[1;32m 1623\u001b[0m \u001b[0mA\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m`\u001b[0m\u001b[0mTensor\u001b[0m\u001b[0;31m`\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0mHas\u001b[0m \u001b[0mthe\u001b[0m \u001b[0msame\u001b[0m \u001b[0mtype\u001b[0m \u001b[0;32mas\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m`\u001b[0m\u001b[0mx\u001b[0m\u001b[0;31m`\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1624\u001b[0m \"\"\"\n\u001b[0;32m-> 1625\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_op_def_lib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply_op\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Mul\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1626\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1627\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
64+
"\u001b[0;32m/Users/darienmt/miniconda3/envs/IntroToTensorFlow/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py\u001b[0m in \u001b[0;36mapply_op\u001b[0;34m(self, op_type_name, name, **keywords)\u001b[0m\n\u001b[1;32m 520\u001b[0m \u001b[0;34m\"%s type %s of argument '%s'.\"\u001b[0m \u001b[0;34m%\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 521\u001b[0m (prefix, dtypes.as_dtype(attrs[input_arg.type_attr]).name,\n\u001b[0;32m--> 522\u001b[0;31m inferred_from[input_arg.type_attr]))\n\u001b[0m\u001b[1;32m 523\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 524\u001b[0m \u001b[0mtypes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;31mTypeError\u001b[0m: Input 'y' of 'Mul' Op has type int32 that does not match type float32 of argument 'x'."
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]
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}
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],
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"source": [
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"x = tf.constant(4.0)\n",
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"y = tf.constant(2)\n",
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"\n",
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"with tf.Session() as sess:\n",
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" badOperation = sess.run( tf.multiply(x, y))\n",
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" print( 'Never here' )"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## cast operation should be applied"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Everything ok : 8 \n"
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]
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}
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],
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"source": [
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"with tf.Session() as sess:\n",
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" notSobadOperation = sess.run( tf.multiply( tf.cast(x, tf.int32), y))\n",
103+
" print( f'Everything ok : {notSobadOperation} ' )"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.0"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎README.md

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# intro-to-tensorflow
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Tensorflow playground
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# Intro to Tensorflow
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Here you can read about my first interacion with [TensorFlow](https://www.tensorflow.org/). More or less, it is my playground to learn more about the library.
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# Prerequisites
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To run this project, you need [Miniconda](https://conda.io/miniconda.html) installed(please visit [this link](https://conda.io/docs/install/quick.html) for quick installation instructions.)
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# Installation
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To create an environment for this project use the following command:
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```
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conda create --name=IntroToTensorFlow python=3 anaconda
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```
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Activate your new environment:
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```
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source activate IntroToTensorFlow
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```
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And install TensorFlow:
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```
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conda install -c conda-forge tensorflow
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```
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Everything done, you can start Jupyter and start playing with it:
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```
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jupyter notebook
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```
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This will opens a browser with Jupyter on the current directory.

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