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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,75 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 5, | ||
| "metadata": { | ||
| "collapsed": false | ||
| }, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "30\n", | ||
| "10\n", | ||
| "200\n", | ||
| "2\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "import tensorflow as tf\n", | ||
| "\n", | ||
| "sess = tf.Session()\n", | ||
| "x = tf.Variable(20,name='x')\n", | ||
| "y = tf.Variable(10,name='y')\n", | ||
| "\n", | ||
| "za = tf.add(x,y)\n", | ||
| "zb = tf.subtract(x,y)\n", | ||
| "zc = tf.multiply(x,y)\n", | ||
| "zd = tf.div(x,y)\n", | ||
| "\n", | ||
| "sess.run(tf.global_variables_initializer())\n", | ||
| "\n", | ||
| "print(sess.run(za))\n", | ||
| "print(sess.run(zb))\n", | ||
| "print(sess.run(zc))\n", | ||
| "print(sess.run(zd))\n", | ||
| "\n", | ||
| "sess.close()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "collapsed": true | ||
| }, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "anaconda-cloud": {}, | ||
| "kernelspec": { | ||
| "display_name": "Python [conda root]", | ||
| "language": "python", | ||
| "name": "conda-root-py" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.5.2" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 1 | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,69 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 1, | ||
| "metadata": { | ||
| "collapsed": false | ||
| }, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "[[ 0. 0.]\n", | ||
| " [ 0. 0.]]\n", | ||
| "[[ 0. 0. 0. 0.]]\n", | ||
| "[[ 0. 0.]\n", | ||
| " [ 0. 0.]]\n", | ||
| "[[ 0. 0. 0. 0.]]\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "import tensorflow as tf\n", | ||
| "import numpy as np\n", | ||
| "\n", | ||
| "a = np.zeros([2,2])\n", | ||
| "print(a)\n", | ||
| "print(a.reshape([1,4]))\n", | ||
| "\n", | ||
| "t = tf.zeros([2,2])\n", | ||
| "sess = tf.Session()\n", | ||
| "print(sess.run(t))\n", | ||
| "print(sess.run(tf.reshape(t,[1,4])))\n", | ||
| "sess.close()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "collapsed": true | ||
| }, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python [conda root]", | ||
| "language": "python", | ||
| "name": "conda-root-py" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.5.2" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 1 | ||
| } |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,95 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 1, | ||
| "metadata": { | ||
| "collapsed": false | ||
| }, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "[[[[ 0. 0.]]\n", | ||
| "\n", | ||
| " [[ 0. 0.]]\n", | ||
| "\n", | ||
| " [[ 0. 0.]]]]\n", | ||
| "[[ 0. 0.]\n", | ||
| " [ 0. 0.]\n", | ||
| " [ 0. 0.]]\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "import numpy as np\n", | ||
| "a = np.zeros((1,3,1,2))\n", | ||
| "print(a)\n", | ||
| "print(np.squeeze(a))" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 3, | ||
| "metadata": { | ||
| "collapsed": false | ||
| }, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "[[[[ 0. 0.]]\n", | ||
| "\n", | ||
| " [[ 0. 0.]]\n", | ||
| "\n", | ||
| " [[ 0. 0.]]]]\n", | ||
| "[[ 0. 0.]\n", | ||
| " [ 0. 0.]\n", | ||
| " [ 0. 0.]]\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "import tensorflow as tf\n", | ||
| "ta = tf.zeros((1,3,1,2))\n", | ||
| "\n", | ||
| "with tf.Session() as sess:\n", | ||
| " print(sess.run(ta))\n", | ||
| " print(sess.run(tf.squeeze(ta)))" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "collapsed": true | ||
| }, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "anaconda-cloud": {}, | ||
| "kernelspec": { | ||
| "display_name": "Python [conda root]", | ||
| "language": "python", | ||
| "name": "conda-root-py" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.5.2" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 1 | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,90 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 2, | ||
| "metadata": { | ||
| "collapsed": false | ||
| }, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "()\n", | ||
| "(5,)\n", | ||
| "(2, 3)\n", | ||
| "(3, 3, 1)\n", | ||
| "10000\n", | ||
| "[[[1]\n", | ||
| " [2]\n", | ||
| " [3]]\n", | ||
| "\n", | ||
| " [[4]\n", | ||
| " [5]\n", | ||
| " [6]]\n", | ||
| "\n", | ||
| " [[7]\n", | ||
| " [8]\n", | ||
| " [9]]]\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "import tensorflow as tf\n", | ||
| "\n", | ||
| "scalar1 = tf.constant(10000)\n", | ||
| "\n", | ||
| "vector1 = tf.constant([1,2,3,4,5])\n", | ||
| "\n", | ||
| "matrix1 = tf.constant([[1,2,3],[4,5,6]])\n", | ||
| "\n", | ||
| "cube1 = tf.constant([[[1],[2],[3]],[[4],[5],[6]],[[7],[8],[9]]])\n", | ||
| "\n", | ||
| "print(scalar1.get_shape())\n", | ||
| "print(vector1.get_shape())\n", | ||
| "print(matrix1.get_shape())\n", | ||
| "print(cube1.get_shape())\n", | ||
| "\n", | ||
| "init = tf.global_variables_initializer()\n", | ||
| "\n", | ||
| "sess = tf.Session()\n", | ||
| "sess.run(init)\n", | ||
| "print(sess.run(scalar1))\n", | ||
| "print(sess.run(cube1))\n", | ||
| "sess.close()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "collapsed": true | ||
| }, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "anaconda-cloud": {}, | ||
| "kernelspec": { | ||
| "display_name": "Python [conda root]", | ||
| "language": "python", | ||
| "name": "conda-root-py" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.5.2" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 1 | ||
| } |
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