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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 29, | ||
"metadata": { | ||
"collapsed": true | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"import tensorflow as tf\n", | ||
"import numpy as np" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 7, | ||
"metadata": { | ||
"collapsed": false | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"t = tf.random_normal((4,3))" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 8, | ||
"metadata": { | ||
"collapsed": false | ||
}, | ||
"outputs": [ | ||
{ | ||
"name": "stderr", | ||
"output_type": "stream", | ||
"text": [ | ||
"Exception AssertionError: AssertionError() in <bound method InteractiveSession.__del__ of <tensorflow.python.client.session.InteractiveSession object at 0x7f8d1448e150>> ignored\n" | ||
] | ||
} | ||
], | ||
"source": [ | ||
"sess = tf.InteractiveSession()" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 15, | ||
"metadata": { | ||
"collapsed": false | ||
}, | ||
"outputs": [ | ||
{ | ||
"data": { | ||
"text/plain": [ | ||
"[array([[ 0.72746545, -0.68051934, 0.21055566],\n", | ||
" [ 0.85468984, -1.73917162, -1.21599209],\n", | ||
" [ 0.58213192, -0.90190017, -0.64913821],\n", | ||
" [-0.86752349, 0.16742691, 0.84491307]], dtype=float32),\n", | ||
" array([0, 0, 0, 2])]" | ||
] | ||
}, | ||
"execution_count": 15, | ||
"metadata": {}, | ||
"output_type": "execute_result" | ||
} | ||
], | ||
"source": [ | ||
"sess.run([t, tf.arg_max(t, dimension=1)])" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 12, | ||
"metadata": { | ||
"collapsed": true | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"?tf.arg_max" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 18, | ||
"metadata": { | ||
"collapsed": false | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"c = tf.constant(0.5)" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 19, | ||
"metadata": { | ||
"collapsed": false | ||
}, | ||
"outputs": [ | ||
{ | ||
"data": { | ||
"text/plain": [ | ||
"[array([[ 0.34724277, 0.6608656 , 0.43116933],\n", | ||
" [-0.48315111, 0.892003 , 0.60531151],\n", | ||
" [ 0.17994949, 0.13526289, -0.71118593],\n", | ||
" [ 0.2168636 , -0.0341404 , -1.04781568]], dtype=float32),\n", | ||
" array([[ 0.17362139, 0.3304328 , 0.21558467],\n", | ||
" [-0.24157555, 0.4460015 , 0.30265576],\n", | ||
" [ 0.08997475, 0.06763145, -0.35559297],\n", | ||
" [ 0.1084318 , -0.0170702 , -0.52390784]], dtype=float32)]" | ||
] | ||
}, | ||
"execution_count": 19, | ||
"metadata": {}, | ||
"output_type": "execute_result" | ||
} | ||
], | ||
"source": [ | ||
"sess.run([t, c*t])" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 21, | ||
"metadata": { | ||
"collapsed": false | ||
}, | ||
"outputs": [ | ||
{ | ||
"data": { | ||
"text/plain": [ | ||
"[array([[ 0.46160161, -2.05513716, -2.90273142],\n", | ||
" [-1.03117085, -0.45882538, -0.44779259],\n", | ||
" [-0.61726028, -0.33546519, 0.38373214],\n", | ||
" [ 0.83618456, -0.21057898, 2.06498384]], dtype=float32),\n", | ||
" array([-4.49626684, -1.93778872, -0.56899333, 2.69058943], dtype=float32)]" | ||
] | ||
}, | ||
"execution_count": 21, | ||
"metadata": {}, | ||
"output_type": "execute_result" | ||
} | ||
], | ||
"source": [ | ||
"sess.run([t, tf.reduce_sum(t, reduction_indices=[1,])])" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 34, | ||
"metadata": { | ||
"collapsed": false | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"i = tf.placeholder(tf.int32, (4,))" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 36, | ||
"metadata": { | ||
"collapsed": false | ||
}, | ||
"outputs": [ | ||
{ | ||
"ename": "TypeError", | ||
"evalue": "Bad slice index Tensor(\"Placeholder_1:0\", shape=TensorShape([Dimension(4)]), dtype=int32) of type <class 'tensorflow.python.framework.ops.Tensor'>", | ||
"output_type": "error", | ||
"traceback": [ | ||
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", | ||
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", | ||
"\u001b[1;32m<ipython-input-36-39534c948248>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0msess\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mt\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m{\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", | ||
"\u001b[1;32m/usr/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.pyc\u001b[0m in \u001b[0;36m_SliceHelper\u001b[1;34m(tensor, slice_spec)\u001b[0m\n\u001b[0;32m 127\u001b[0m \u001b[1;32mraise\u001b[0m \u001b[0mNotImplementedError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Ellipsis is not currently supported\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 128\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 129\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Bad slice index %s of type %s\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 130\u001b[0m \u001b[0msliced\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mslice\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtensor\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindices\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msizes\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 131\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0msqueeze_dims\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", | ||
"\u001b[1;31mTypeError\u001b[0m: Bad slice index Tensor(\"Placeholder_1:0\", shape=TensorShape([Dimension(4)]), dtype=int32) of type <class 'tensorflow.python.framework.ops.Tensor'>" | ||
] | ||
} | ||
], | ||
"source": [ | ||
"sess.run(t[i], {i: np.array([0,1,1,1])})" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 45, | ||
"metadata": { | ||
"collapsed": false | ||
}, | ||
"outputs": [ | ||
{ | ||
"data": { | ||
"text/plain": [ | ||
"[array([[ 0.02137903, 1.23828769, 0.53914273],\n", | ||
" [-1.06534982, -0.21909024, -1.19062781],\n", | ||
" [-0.50089341, -1.03411007, 0.02972561],\n", | ||
" [ 1.17602372, 0.27990618, -1.23782802]], dtype=float32),\n", | ||
" array([ 1.23828769, -0.21909024, 0.02972561, 1.17602372], dtype=float32)]" | ||
] | ||
}, | ||
"execution_count": 45, | ||
"metadata": {}, | ||
"output_type": "execute_result" | ||
} | ||
], | ||
"source": [ | ||
"sess.run([t, tf.reduce_max(t, 1)])" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 39, | ||
"metadata": { | ||
"collapsed": true | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"?tf.train.RMSPropOptimizer" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 46, | ||
"metadata": { | ||
"collapsed": false | ||
}, | ||
"outputs": [ | ||
{ | ||
"ename": "ValueError", | ||
"evalue": "too many values to unpack", | ||
"output_type": "error", | ||
"traceback": [ | ||
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", | ||
"\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)", | ||
"\u001b[1;32m<ipython-input-46-4c110fc8efb5>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m4\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", | ||
"\u001b[1;31mValueError\u001b[0m: too many values to unpack" | ||
] | ||
} | ||
], | ||
"source": [ | ||
"a,b,c = [1,2,3,4,5]" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 47, | ||
"metadata": { | ||
"collapsed": true | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"x = tf.train.SummaryWriter(\"logs/\", sess.graph_def)" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 48, | ||
"metadata": { | ||
"collapsed": true | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"?x.add_summary" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": { | ||
"collapsed": true | ||
}, | ||
"outputs": [], | ||
"source": [] | ||
} | ||
], | ||
"metadata": { | ||
"kernelspec": { | ||
"display_name": "Python 2", | ||
"language": "python", | ||
"name": "python2" | ||
}, | ||
"language_info": { | ||
"codemirror_mode": { | ||
"name": "ipython", | ||
"version": 2 | ||
}, | ||
"file_extension": ".py", | ||
"mimetype": "text/x-python", | ||
"name": "python", | ||
"nbconvert_exporter": "python", | ||
"pygments_lexer": "ipython2", | ||
"version": "2.7.8" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 0 | ||
} |
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