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braingineer/july_10_example.ipynb

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getting values from expressions in keras
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july_10_example.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Using Theano backend.\n",
"Using gpu device 0: GeForce GTX 980 (CNMeM is disabled, cuDNN 5004)\n"
]
}
],
"source": [
"import keras.backend as K\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([ 0., 0., 0., 0., 0.], dtype=float32)"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"## this work because x is a variable\n",
"x = K.variable(np.zeros(5,))\n",
"K.get_value(x)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"ename": "Exception",
"evalue": "'get_value() can only be called on a variable. If you have an expression instead, use eval().",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mException\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-3-9d401c25f7f5>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[1;31m## this fails because y is an expression\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mx\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m5\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mK\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_value\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;32m/home/cogniton/research/code/keras/keras/backend/theano_backend.py\u001b[0m in \u001b[0;36mget_value\u001b[1;34m(x)\u001b[0m\n\u001b[0;32m 546\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'get_value'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 547\u001b[0m raise Exception(\"'get_value() can only be called on a variable. \" +\n\u001b[1;32m--> 548\u001b[1;33m \"If you have an expression instead, use eval().\")\n\u001b[0m\u001b[0;32m 549\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_value\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 550\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mException\u001b[0m: 'get_value() can only be called on a variable. If you have an expression instead, use eval()."
]
}
],
"source": [
"## this fails because y is an expression\n",
"y = x + 5\n",
"K.get_value(y)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"ename": "ValueError",
"evalue": "setting an array element with a sequence.",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-4-fca89c8203fe>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[1;31m## this will also fail.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvariable\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzeros\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m5\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[1;32m----> 3\u001b[1;33m \u001b[0mK\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_value\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mx\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[0;32m 4\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_value\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/research/code/keras/keras/backend/theano_backend.py\u001b[0m in \u001b[0;36mset_value\u001b[1;34m(x, value)\u001b[0m\n\u001b[0;32m 558\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 559\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mset_value\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 560\u001b[1;33m \u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_value\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdtype\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 561\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 562\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/numpy/core/numeric.py\u001b[0m in \u001b[0;36masarray\u001b[1;34m(a, dtype, order)\u001b[0m\n\u001b[0;32m 480\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 481\u001b[0m \"\"\"\n\u001b[1;32m--> 482\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0marray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0morder\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0morder\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 483\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 484\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0masanyarray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0morder\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mValueError\u001b[0m: setting an array element with a sequence."
]
}
],
"source": [
"## this will also fail. \n",
"y = K.variable(np.zeros(5,))\n",
"K.set_value(y, x+5)\n",
"K.get_value(y)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([ 5., 5., 5., 5., 5.], dtype=float32)"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"## y shouldn't be initialized a variable. instead, use eval\n",
"y = K.variable(np.zeros(5,))\n",
"y *= 10\n",
"y = x + 5 ## y is gone\n",
"K.eval(y)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"ename": "MissingInputError",
"evalue": "(\"An input of the graph, used to compute Elemwise{add,no_inplace}(<TensorType(float32, vector)>, DimShuffle{x}.0), was not provided and not given a value.Use the Theano flag exception_verbosity='high',for more information on this error.\", <TensorType(float32, vector)>)",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mMissingInputError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-6-2cf4c1d4495e>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplaceholder\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m5\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[0;32m 2\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mx\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m5\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mK\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0meval\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;32m/home/cogniton/research/code/keras/keras/backend/theano_backend.py\u001b[0m in \u001b[0;36meval\u001b[1;34m(x)\u001b[0m\n\u001b[0;32m 69\u001b[0m '''Run a graph.\n\u001b[0;32m 70\u001b[0m '''\n\u001b[1;32m---> 71\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0meval\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 72\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 73\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/gof/graph.py\u001b[0m in \u001b[0;36meval\u001b[1;34m(self, inputs_to_values)\u001b[0m\n\u001b[0;32m 518\u001b[0m \u001b[0minputs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtuple\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msorted\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minputs_to_values\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mid\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 519\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0minputs\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_fn_cache\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 520\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_fn_cache\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0minputs\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtheano\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfunction\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 521\u001b[0m \u001b[0margs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0minputs_to_values\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mparam\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mparam\u001b[0m \u001b[1;32min\u001b[0m \u001b[0minputs\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 522\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/compile/function.py\u001b[0m in \u001b[0;36mfunction\u001b[1;34m(inputs, outputs, mode, updates, givens, no_default_updates, accept_inplace, name, rebuild_strict, allow_input_downcast, profile, on_unused_input)\u001b[0m\n\u001b[0;32m 318\u001b[0m \u001b[0mon_unused_input\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mon_unused_input\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 319\u001b[0m \u001b[0mprofile\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mprofile\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 320\u001b[1;33m output_keys=output_keys)\n\u001b[0m\u001b[0;32m 321\u001b[0m \u001b[1;31m# We need to add the flag check_aliased inputs if we have any mutable or\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 322\u001b[0m \u001b[1;31m# borrowed used defined inputs\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/compile/pfunc.py\u001b[0m in \u001b[0;36mpfunc\u001b[1;34m(params, outputs, mode, updates, givens, no_default_updates, accept_inplace, name, rebuild_strict, allow_input_downcast, profile, on_unused_input, output_keys)\u001b[0m\n\u001b[0;32m 477\u001b[0m \u001b[0maccept_inplace\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0maccept_inplace\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 478\u001b[0m \u001b[0mprofile\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mprofile\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mon_unused_input\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mon_unused_input\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 479\u001b[1;33m output_keys=output_keys)\n\u001b[0m\u001b[0;32m 480\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 481\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/compile/function_module.py\u001b[0m in \u001b[0;36morig_function\u001b[1;34m(inputs, outputs, mode, accept_inplace, name, profile, on_unused_input, output_keys)\u001b[0m\n\u001b[0;32m 1774\u001b[0m \u001b[0mprofile\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mprofile\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1775\u001b[0m \u001b[0mon_unused_input\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mon_unused_input\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1776\u001b[1;33m \u001b[0moutput_keys\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0moutput_keys\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcreate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1777\u001b[0m defaults)\n\u001b[0;32m 1778\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/compile/function_module.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, inputs, outputs, mode, accept_inplace, function_builder, profile, on_unused_input, fgraph, output_keys)\u001b[0m\n\u001b[0;32m 1426\u001b[0m \u001b[1;31m# OUTPUT VARIABLES)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1427\u001b[0m fgraph, additional_outputs = std_fgraph(inputs, outputs,\n\u001b[1;32m-> 1428\u001b[1;33m accept_inplace)\n\u001b[0m\u001b[0;32m 1429\u001b[0m \u001b[0mfgraph\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mprofile\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mprofile\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1430\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/compile/function_module.py\u001b[0m in \u001b[0;36mstd_fgraph\u001b[1;34m(input_specs, output_specs, accept_inplace)\u001b[0m\n\u001b[0;32m 175\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 176\u001b[0m fgraph = gof.fg.FunctionGraph(orig_inputs, orig_outputs,\n\u001b[1;32m--> 177\u001b[1;33m update_mapping=update_mapping)\n\u001b[0m\u001b[0;32m 178\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 179\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mnode\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mfgraph\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply_nodes\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/gof/fg.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, inputs, outputs, features, clone, update_mapping)\u001b[0m\n\u001b[0;32m 169\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 170\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0moutput\u001b[0m \u001b[1;32min\u001b[0m \u001b[0moutputs\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 171\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__import_r__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreason\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"init\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 172\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moutput\u001b[0m \u001b[1;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0moutputs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 173\u001b[0m \u001b[0moutput\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclients\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'output'\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[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/gof/fg.py\u001b[0m in \u001b[0;36m__import_r__\u001b[1;34m(self, variable, reason)\u001b[0m\n\u001b[0;32m 358\u001b[0m \u001b[1;31m# Imports the owners of the variables\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 359\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mvariable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mowner\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mvariable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mowner\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply_nodes\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 360\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__import__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvariable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mowner\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreason\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mreason\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 361\u001b[0m if (variable.owner is None and\n\u001b[0;32m 362\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvariable\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mgraph\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mConstant\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mand\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/gof/fg.py\u001b[0m in \u001b[0;36m__import__\u001b[1;34m(self, apply_node, check, reason)\u001b[0m\n\u001b[0;32m 472\u001b[0m \u001b[1;34m\"for more information on this error.\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 473\u001b[0m % str(node)),\n\u001b[1;32m--> 474\u001b[1;33m r)\n\u001b[0m\u001b[0;32m 475\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 476\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mnode\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mnew_nodes\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mMissingInputError\u001b[0m: (\"An input of the graph, used to compute Elemwise{add,no_inplace}(<TensorType(float32, vector)>, DimShuffle{x}.0), was not provided and not given a value.Use the Theano flag exception_verbosity='high',for more information on this error.\", <TensorType(float32, vector)>)"
]
}
],
"source": [
"x = K.placeholder((5,))\n",
"y = x + 5\n",
"K.eval(y)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[ 5. 5. 5. 5. 5.]\n"
]
}
],
"source": [
"x = K.placeholder((5,))\n",
"y = x + 5\n",
"F = K.Function([x], y)\n",
"print(F([np.zeros(5)]))\n",
"#K.eval(y)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([ 5., 5., 5., 5., 5.], dtype=float32)"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# this is the same thing as above\n",
"import theano\n",
"import theano.tensor as T\n",
"x = T.vector()\n",
"y = x + 5\n",
"F = theano.function([x], y)\n",
"F(np.zeros(5, dtype=np.float32))"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"collapsed": false
},
"outputs": [
{
"ename": "MissingInputError",
"evalue": "(\"An input of the graph, used to compute Elemwise{add,no_inplace}(<TensorType(float32, vector)>, DimShuffle{x}.0), was not provided and not given a value.Use the Theano flag exception_verbosity='high',for more information on this error.\", <TensorType(float32, vector)>)",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mMissingInputError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-35-8e5fec318922>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0my\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0meval\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/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/gof/graph.py\u001b[0m in \u001b[0;36meval\u001b[1;34m(self, inputs_to_values)\u001b[0m\n\u001b[0;32m 518\u001b[0m \u001b[0minputs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtuple\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msorted\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minputs_to_values\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mid\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 519\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0minputs\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_fn_cache\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 520\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_fn_cache\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0minputs\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtheano\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfunction\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 521\u001b[0m \u001b[0margs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0minputs_to_values\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mparam\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mparam\u001b[0m \u001b[1;32min\u001b[0m \u001b[0minputs\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 522\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/compile/function.py\u001b[0m in \u001b[0;36mfunction\u001b[1;34m(inputs, outputs, mode, updates, givens, no_default_updates, accept_inplace, name, rebuild_strict, allow_input_downcast, profile, on_unused_input)\u001b[0m\n\u001b[0;32m 318\u001b[0m \u001b[0mon_unused_input\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mon_unused_input\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 319\u001b[0m \u001b[0mprofile\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mprofile\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 320\u001b[1;33m output_keys=output_keys)\n\u001b[0m\u001b[0;32m 321\u001b[0m \u001b[1;31m# We need to add the flag check_aliased inputs if we have any mutable or\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 322\u001b[0m \u001b[1;31m# borrowed used defined inputs\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/compile/pfunc.py\u001b[0m in \u001b[0;36mpfunc\u001b[1;34m(params, outputs, mode, updates, givens, no_default_updates, accept_inplace, name, rebuild_strict, allow_input_downcast, profile, on_unused_input, output_keys)\u001b[0m\n\u001b[0;32m 477\u001b[0m \u001b[0maccept_inplace\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0maccept_inplace\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 478\u001b[0m \u001b[0mprofile\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mprofile\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mon_unused_input\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mon_unused_input\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 479\u001b[1;33m output_keys=output_keys)\n\u001b[0m\u001b[0;32m 480\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 481\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/compile/function_module.py\u001b[0m in \u001b[0;36morig_function\u001b[1;34m(inputs, outputs, mode, accept_inplace, name, profile, on_unused_input, output_keys)\u001b[0m\n\u001b[0;32m 1774\u001b[0m \u001b[0mprofile\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mprofile\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1775\u001b[0m \u001b[0mon_unused_input\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mon_unused_input\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1776\u001b[1;33m \u001b[0moutput_keys\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0moutput_keys\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcreate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1777\u001b[0m defaults)\n\u001b[0;32m 1778\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/compile/function_module.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, inputs, outputs, mode, accept_inplace, function_builder, profile, on_unused_input, fgraph, output_keys)\u001b[0m\n\u001b[0;32m 1426\u001b[0m \u001b[1;31m# OUTPUT VARIABLES)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1427\u001b[0m fgraph, additional_outputs = std_fgraph(inputs, outputs,\n\u001b[1;32m-> 1428\u001b[1;33m accept_inplace)\n\u001b[0m\u001b[0;32m 1429\u001b[0m \u001b[0mfgraph\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mprofile\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mprofile\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1430\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/compile/function_module.py\u001b[0m in \u001b[0;36mstd_fgraph\u001b[1;34m(input_specs, output_specs, accept_inplace)\u001b[0m\n\u001b[0;32m 175\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 176\u001b[0m fgraph = gof.fg.FunctionGraph(orig_inputs, orig_outputs,\n\u001b[1;32m--> 177\u001b[1;33m update_mapping=update_mapping)\n\u001b[0m\u001b[0;32m 178\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 179\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mnode\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mfgraph\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply_nodes\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/gof/fg.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, inputs, outputs, features, clone, update_mapping)\u001b[0m\n\u001b[0;32m 169\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 170\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0moutput\u001b[0m \u001b[1;32min\u001b[0m \u001b[0moutputs\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 171\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__import_r__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreason\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"init\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 172\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moutput\u001b[0m \u001b[1;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0moutputs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 173\u001b[0m \u001b[0moutput\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclients\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'output'\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[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/gof/fg.py\u001b[0m in \u001b[0;36m__import_r__\u001b[1;34m(self, variable, reason)\u001b[0m\n\u001b[0;32m 358\u001b[0m \u001b[1;31m# Imports the owners of the variables\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 359\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mvariable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mowner\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mvariable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mowner\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply_nodes\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 360\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__import__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvariable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mowner\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreason\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mreason\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 361\u001b[0m if (variable.owner is None and\n\u001b[0;32m 362\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvariable\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mgraph\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mConstant\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mand\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/gof/fg.py\u001b[0m in \u001b[0;36m__import__\u001b[1;34m(self, apply_node, check, reason)\u001b[0m\n\u001b[0;32m 472\u001b[0m \u001b[1;34m\"for more information on this error.\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 473\u001b[0m % str(node)),\n\u001b[1;32m--> 474\u001b[1;33m r)\n\u001b[0m\u001b[0;32m 475\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 476\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mnode\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mnew_nodes\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mMissingInputError\u001b[0m: (\"An input of the graph, used to compute Elemwise{add,no_inplace}(<TensorType(float32, vector)>, DimShuffle{x}.0), was not provided and not given a value.Use the Theano flag exception_verbosity='high',for more information on this error.\", <TensorType(float32, vector)>)"
]
}
],
"source": [
"y.eval()"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[ 5. 5. 5. 5. 5.]\n"
]
},
{
"ename": "MissingInputError",
"evalue": "(\"An input of the graph, used to compute Elemwise{add,no_inplace}(<TensorType(float32, vector)>, DimShuffle{x}.0), was not provided and not given a value.Use the Theano flag exception_verbosity='high',for more information on this error.\", <TensorType(float32, vector)>)",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mMissingInputError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-36-e57bb8fd2bd9>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[0mF\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mFunction\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mF\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzeros\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m5\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[1;32m----> 5\u001b[1;33m \u001b[0mK\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0meval\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;32m/home/cogniton/research/code/keras/keras/backend/theano_backend.py\u001b[0m in \u001b[0;36meval\u001b[1;34m(x)\u001b[0m\n\u001b[0;32m 69\u001b[0m '''Run a graph.\n\u001b[0;32m 70\u001b[0m '''\n\u001b[1;32m---> 71\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0meval\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 72\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 73\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/gof/graph.py\u001b[0m in \u001b[0;36meval\u001b[1;34m(self, inputs_to_values)\u001b[0m\n\u001b[0;32m 518\u001b[0m \u001b[0minputs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtuple\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msorted\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minputs_to_values\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mid\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 519\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0minputs\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_fn_cache\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 520\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_fn_cache\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0minputs\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtheano\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfunction\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 521\u001b[0m \u001b[0margs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0minputs_to_values\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mparam\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mparam\u001b[0m \u001b[1;32min\u001b[0m \u001b[0minputs\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 522\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/compile/function.py\u001b[0m in \u001b[0;36mfunction\u001b[1;34m(inputs, outputs, mode, updates, givens, no_default_updates, accept_inplace, name, rebuild_strict, allow_input_downcast, profile, on_unused_input)\u001b[0m\n\u001b[0;32m 318\u001b[0m \u001b[0mon_unused_input\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mon_unused_input\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 319\u001b[0m \u001b[0mprofile\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mprofile\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 320\u001b[1;33m output_keys=output_keys)\n\u001b[0m\u001b[0;32m 321\u001b[0m \u001b[1;31m# We need to add the flag check_aliased inputs if we have any mutable or\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 322\u001b[0m \u001b[1;31m# borrowed used defined inputs\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/compile/pfunc.py\u001b[0m in \u001b[0;36mpfunc\u001b[1;34m(params, outputs, mode, updates, givens, no_default_updates, accept_inplace, name, rebuild_strict, allow_input_downcast, profile, on_unused_input, output_keys)\u001b[0m\n\u001b[0;32m 477\u001b[0m \u001b[0maccept_inplace\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0maccept_inplace\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 478\u001b[0m \u001b[0mprofile\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mprofile\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mon_unused_input\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mon_unused_input\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 479\u001b[1;33m output_keys=output_keys)\n\u001b[0m\u001b[0;32m 480\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 481\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/compile/function_module.py\u001b[0m in \u001b[0;36morig_function\u001b[1;34m(inputs, outputs, mode, accept_inplace, name, profile, on_unused_input, output_keys)\u001b[0m\n\u001b[0;32m 1774\u001b[0m \u001b[0mprofile\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mprofile\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1775\u001b[0m \u001b[0mon_unused_input\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mon_unused_input\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1776\u001b[1;33m \u001b[0moutput_keys\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0moutput_keys\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcreate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1777\u001b[0m defaults)\n\u001b[0;32m 1778\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/compile/function_module.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, inputs, outputs, mode, accept_inplace, function_builder, profile, on_unused_input, fgraph, output_keys)\u001b[0m\n\u001b[0;32m 1426\u001b[0m \u001b[1;31m# OUTPUT VARIABLES)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1427\u001b[0m fgraph, additional_outputs = std_fgraph(inputs, outputs,\n\u001b[1;32m-> 1428\u001b[1;33m accept_inplace)\n\u001b[0m\u001b[0;32m 1429\u001b[0m \u001b[0mfgraph\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mprofile\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mprofile\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1430\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/compile/function_module.py\u001b[0m in \u001b[0;36mstd_fgraph\u001b[1;34m(input_specs, output_specs, accept_inplace)\u001b[0m\n\u001b[0;32m 175\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 176\u001b[0m fgraph = gof.fg.FunctionGraph(orig_inputs, orig_outputs,\n\u001b[1;32m--> 177\u001b[1;33m update_mapping=update_mapping)\n\u001b[0m\u001b[0;32m 178\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 179\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mnode\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mfgraph\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply_nodes\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/gof/fg.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, inputs, outputs, features, clone, update_mapping)\u001b[0m\n\u001b[0;32m 169\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 170\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0moutput\u001b[0m \u001b[1;32min\u001b[0m \u001b[0moutputs\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 171\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__import_r__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreason\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"init\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 172\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moutput\u001b[0m \u001b[1;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0moutputs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 173\u001b[0m \u001b[0moutput\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclients\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'output'\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[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/gof/fg.py\u001b[0m in \u001b[0;36m__import_r__\u001b[1;34m(self, variable, reason)\u001b[0m\n\u001b[0;32m 358\u001b[0m \u001b[1;31m# Imports the owners of the variables\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 359\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mvariable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mowner\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mvariable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mowner\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply_nodes\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 360\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__import__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvariable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mowner\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreason\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mreason\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 361\u001b[0m if (variable.owner is None and\n\u001b[0;32m 362\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvariable\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mgraph\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mConstant\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mand\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m/home/cogniton/anaconda/envs/py3k/lib/python3.5/site-packages/Theano-0.8.2-py3.5.egg/theano/gof/fg.py\u001b[0m in \u001b[0;36m__import__\u001b[1;34m(self, apply_node, check, reason)\u001b[0m\n\u001b[0;32m 472\u001b[0m \u001b[1;34m\"for more information on this error.\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 473\u001b[0m % str(node)),\n\u001b[1;32m--> 474\u001b[1;33m r)\n\u001b[0m\u001b[0;32m 475\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 476\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mnode\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mnew_nodes\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mMissingInputError\u001b[0m: (\"An input of the graph, used to compute Elemwise{add,no_inplace}(<TensorType(float32, vector)>, DimShuffle{x}.0), was not provided and not given a value.Use the Theano flag exception_verbosity='high',for more information on this error.\", <TensorType(float32, vector)>)"
]
}
],
"source": [
"x = K.placeholder((5,))\n",
"y = x + 5\n",
"F = K.Function([x], y)\n",
"print(F([np.zeros(5)]))\n",
"K.eval(y)"
]
}
],
"metadata": {
"_draft": {
"nbviewer_url": "https://gist.github.com/ed71bcc289e31860762cfb4bcdf690fa"
},
"gist": {
"data": {
"description": "getting values from expressions in keras",
"public": true
},
"id": "ed71bcc289e31860762cfb4bcdf690fa"
},
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"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": 0
}
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