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# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Script to test TF-TensorRT integration."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.contrib.tensorrt.test import tf_trt_integration_test_base as trt_test
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import nn
from tensorflow.python.platform import test
class ConstBroadcastTest(trt_test.TfTrtIntegrationTestBase):
def GetParams(self):
"""Test for Constant broadcasting in TF-TRT."""
dtype = dtypes.float32
input_name = 'input'
input_dims = [5, 12, 12, 2]
g = ops.Graph()
with g.as_default():
x = array_ops.placeholder(dtype=dtype, shape=input_dims, name=input_name)
filt1 = constant_op.constant(
0.3, shape=(3, 3, 2, 1), dtype=dtype, name='filt1')
y1 = nn.conv2d(x, filt1, strides=[1, 1, 1, 1], padding='SAME', name='y1')
z1 = nn.relu(y1, name='z1')
filt2 = constant_op.constant(
np.random.randn(9), shape=(3, 3, 1, 1), dtype=dtype, name='filt2')
y2 = nn.conv2d(z1, filt2, strides=[1, 1, 1, 1], padding='SAME', name='y2')
z2 = nn.relu(y2, name='z')
filt3 = constant_op.constant(
np.random.randn(3, 3, 1, 1),
shape=(3, 3, 1, 1),
dtype=dtype,
name='filt3')
y3 = nn.conv2d(z2, filt3, strides=[1, 1, 1, 1], padding='SAME', name='y3')
nn.relu(y3, name='output')
return trt_test.TfTrtIntegrationTestParams(
gdef=g.as_graph_def(),
input_names=[input_name],
input_dims=[input_dims],
num_expected_engines=1,
expected_output_dims=(5, 12, 12, 1),
allclose_atol=1.e-02,
allclose_rtol=1.e-02)
if __name__ == '__main__':
test.main()
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