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introduction to tensorflow
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{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"provenance": [],
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"authorship_tag": "ABX9TyO0fxb6omsPqcaelthdhOlo",
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"include_colab_link": true
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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}
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},
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "view-in-github",
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"colab_type": "text"
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},
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"source": [
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"<a href=\"https://colab.research.google.com/github/iamanolive/code-harbor-hub/blob/main/tensorflow-tutorials/introduction.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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]
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},
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{
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"cell_type": "code",
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"source": [
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"import tensorflow as tf"
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],
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"metadata": {
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"id": "A2iC7nlsQ_tU"
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},
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"execution_count": 8,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"source": [
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"# creating tensors"
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],
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"metadata": {
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"id": "d3SLZ6TiR4Zw"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"string = tf.Variable(\"this is a string\", tf.string)\n",
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"number = tf.Variable(324, tf.int16)\n",
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"floating = tf.Variable(3.567, tf.float64)"
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],
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"metadata": {
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"id": "nW0NfMdPVmDo"
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},
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"execution_count": 9,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"source": [
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"# ranks or degrees of tensors"
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],
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"metadata": {
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"id": "njzcqxqsWDpc"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"rank1_tensor = tf.Variable([\"Test\", \"Ok\", \"Somebody\", \"Somebody\"], tf.string)\n",
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"rank2_tensor = tf.Variable([[\"test\", \"ok\"], [\"test\", \"yes\"], [\"ok\", \"ok\"]], tf.string)"
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],
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"metadata": {
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"id": "jY_yrAmUVxmp"
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},
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"execution_count": 27,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"tf.rank(rank1_tensor)"
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "JKhqMx7iWe7x",
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"outputId": "7f11b444-016e-4654-8436-6340e612def7"
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},
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"execution_count": 28,
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"<tf.Tensor: shape=(), dtype=int32, numpy=1>"
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]
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},
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"metadata": {},
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"execution_count": 28
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}
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]
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},
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{
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"cell_type": "code",
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"source": [
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"tf.rank(rank2_tensor)"
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "sw5Ns_2YWsEo",
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"outputId": "e96a3e35-d3b6-4056-e327-ca08c35c2795"
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},
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"execution_count": 29,
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"<tf.Tensor: shape=(), dtype=int32, numpy=2>"
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]
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},
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"metadata": {},
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"execution_count": 29
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}
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]
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},
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{
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"cell_type": "code",
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"source": [
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"tf.rank(number)"
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "4qSdqk-aXRO1",
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"outputId": "41573023-fe3c-44a9-8f15-4e119d58fec3"
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},
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"execution_count": 30,
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"<tf.Tensor: shape=(), dtype=int32, numpy=0>"
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]
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},
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"metadata": {},
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"execution_count": 30
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}
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"# shapes of tensors"
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],
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"metadata": {
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"id": "JSh-sGGtXFbd"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"rank1_tensor.shape"
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "lKeKVZ0DXXXo",
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"outputId": "9bdef519-f5b6-42fd-af37-93f0d86f51f8"
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},
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"execution_count": 31,
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"TensorShape([4])"
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]
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},
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"metadata": {},
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"execution_count": 31
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}
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]
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},
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{
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"cell_type": "code",
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"source": [
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"rank2_tensor.shape"
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "Nq55Y62_XH2C",
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"outputId": "d662fd43-8d3a-4ad5-e894-67e3e5d34557"
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},
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"execution_count": 32,
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"TensorShape([3, 2])"
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]
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},
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"metadata": {},
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"execution_count": 32
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}
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"# changing shapes"
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],
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"metadata": {
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"id": "fZq-ciAuX9nd"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"tensor1 = tf.ones([1, 2, 3])\n",
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"tensor2 = tf.reshape(tensor1, [2, 3, 1])\n",
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"tensor3 = tf.reshape(tensor2, [3, -1])"
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],
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"metadata": {
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"id": "6B220CYWYA-r"
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},
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"execution_count": 37,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"print(tensor1)"
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "yk7p22RyYS2I",
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"outputId": "c5d3f951-7ba4-4f10-f76f-508d7efadbff"
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},
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"execution_count": 38,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"tf.Tensor(\n",
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"[[[1. 1. 1.]\n",
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" [1. 1. 1.]]], shape=(1, 2, 3), dtype=float32)\n"
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]
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}
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]
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},
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{
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"cell_type": "code",
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"source": [
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"print(tensor2)"
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "121lHMJYYVG3",
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"outputId": "0b1d5684-ce45-4f6d-a108-1a54ba008f6d"
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},
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"execution_count": 39,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"tf.Tensor(\n",
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"[[[1.]\n",
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" [1.]\n",
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" [1.]]\n",
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"\n",
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" [[1.]\n",
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" [1.]\n",
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" [1.]]], shape=(2, 3, 1), dtype=float32)\n"
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]
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}
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]
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},
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{
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"cell_type": "code",
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"source": [
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"print(tensor3)"
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "UnbSuXgxYWiw",
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"outputId": "9c1f3139-6863-47a9-f95b-067fc158a914"
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},
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"execution_count": 44,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"tf.Tensor(\n",
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"[[1. 1.]\n",
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" [1. 1.]\n",
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" [1. 1.]], shape=(3, 2), dtype=float32)\n"
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]
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}
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]
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}
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]
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}

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