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December 20, 2015 07:08
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Script to test my GpuJoin.c_code for Theano. See https://github.com/shackenberg/Theano/compare/adding_GpuJoin.c_code
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#!/usr/bin/env python | |
""" | |
call this to run the code: | |
export CUDA_LAUNCH_BLOCKING=1 | |
THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32,exception_verbosity=high python jointest.py | |
""" | |
import theano | |
import theano.tensor as T | |
from numpy import * | |
axis = 0 | |
np_array1 = array(random.random([2]), dtype='float32') | |
np_array2 = array(random.random([5]), dtype='float32') | |
T_vector1 = T.vector('T_vector1') | |
T_vector2 = T.vector('T_vector2') | |
T_result = T.concatenate([T_vector1, T_vector2], axis) | |
f1 = theano.function([T_vector1, T_vector2], T_result , profile=True) | |
numpy_result = concatenate([np_array1, np_array2], axis) | |
theano_result = f1(np_array1, np_array2) | |
if not allclose(theano_result,numpy_result): | |
print numpy_result | |
print theano_result | |
axis = 1 | |
np_array1 = array(random.random([2, 3]), dtype='float32') | |
np_array2 = array(random.random([2, 11]), dtype='float32') | |
np_array3 = array(random.random([2, 3]), dtype='float32') | |
T_matrix1 = T.matrix('T_matrix1') | |
T_matrix2 = T.matrix('T_matrix2') | |
T_matrix3 = T.matrix('T_matrix3') | |
T_result = T.concatenate([T_matrix1, T_matrix2, T_matrix3], axis) | |
f1 = theano.function([T_matrix1, T_matrix2, T_matrix3], T_result , profile=True) | |
numpy_result = concatenate([np_array1, np_array2, np_array3], axis) | |
theano_result = f1(np_array1, np_array2, np_array3) | |
if not allclose(theano_result,numpy_result): | |
print numpy_result | |
print theano_result | |
axis = 2 | |
np_array1 = array(random.random([2, 3, 2, 4]), dtype='float32') | |
np_array2 = array(random.random([2, 3, 11, 4]), dtype='float32') | |
np_array3 = array(random.random([2, 3, 44, 4]), dtype='float32') | |
np_array4 = array(random.random([2, 3, 1, 4]), dtype='float32') | |
T_tensor_1 = T.tensor4('T_tensor3_1') | |
T_tensor_2 = T.tensor4('T_tensor3_2') | |
T_tensor_3 = T.tensor4('T_tensor3_3') | |
T_tensor_4 = T.tensor4('T_tensor3_4') | |
T_result = T.concatenate([T_tensor_1, T_tensor_2, T_tensor_3, T_tensor_4], axis) | |
f1 = theano.function([T_tensor_1, T_tensor_2, T_tensor_3, T_tensor_4], T_result , profile=True) | |
numpy_result = concatenate([np_array1, np_array2, np_array3, np_array4], axis) | |
theano_result = f1(np_array1, np_array2, np_array3, np_array4) | |
if not allclose(theano_result,numpy_result): | |
print numpy_result | |
print theano_result |
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