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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.
# ==============================================================================
"""Model 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 gen_array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test
class BinaryTensorWeightBroadcastTest(trt_test.TfTrtIntegrationTestBase):
def GetParams(self):
"""Tests for scale & elementwise layers in TF-TRT."""
dtype = dtypes.float32
input_name = "input"
input_dims = [10, 24, 24, 20]
g = ops.Graph()
with g.as_default():
x = array_ops.placeholder(dtype=dtype, shape=input_dims, name=input_name)
# scale
a = constant_op.constant(np.random.randn(1), dtype=dtype)
f = x + a
x = math_ops.sigmoid(f)
# scale
a = constant_op.constant(np.random.randn(1), dtype=dtype)
f = a + x
x = math_ops.sigmoid(f)
# scale
a = constant_op.constant(np.random.randn(24, 1, 1), dtype=dtype)
f = x + a
x = math_ops.sigmoid(f)
# scale
a = constant_op.constant(np.random.randn(24, 1, 1), dtype=dtype)
f = a + x
x = math_ops.sigmoid(f)
# scale
a = constant_op.constant(np.random.randn(24, 24, 20), dtype=dtype)
f = a + x
x = math_ops.sigmoid(f)
# scale
a = constant_op.constant(np.random.randn(24, 24, 20), dtype=dtype)
f = x + a
x = math_ops.sigmoid(f)
# elementwise
a = constant_op.constant(np.random.randn(20), dtype=dtype)
f = x + a
x = math_ops.sigmoid(f)
# elementwise
a = constant_op.constant(np.random.randn(20), dtype=dtype)
f = a + x
x = math_ops.sigmoid(f)
# elementwise
a = constant_op.constant(np.random.randn(1, 24, 1, 1), dtype=dtype)
f = a + x
x = math_ops.sigmoid(f)
# elementwise
a = constant_op.constant(np.random.randn(1, 24, 1, 1), dtype=dtype)
f = x + a
x = math_ops.sigmoid(f)
# elementwise
a = constant_op.constant(np.random.randn(1, 24, 24, 1), dtype=dtype)
f = a + x
x = math_ops.sigmoid(f)
# elementwise
a = constant_op.constant(np.random.randn(1, 24, 24, 1), dtype=dtype)
f = x + a
x = math_ops.sigmoid(f)
# elementwise
a = constant_op.constant(np.random.randn(1, 24, 24, 20), dtype=dtype)
f = a + x
x = math_ops.sigmoid(f)
# elementwise
a = constant_op.constant(np.random.randn(1, 24, 24, 20), dtype=dtype)
f = x + a
x = math_ops.sigmoid(f)
# elementwise
a = constant_op.constant(np.random.randn(24, 20), dtype=dtype)
f = a + x
x = math_ops.sigmoid(f)
# elementwise
a = constant_op.constant(np.random.randn(24, 20), dtype=dtype)
f = x + a
x = math_ops.sigmoid(f)
gen_array_ops.reshape(x, [5, -1], name=self.output_name)
return trt_test.TfTrtIntegrationTestParams(
gdef=g.as_graph_def(),
input_names=[input_name],
input_dims=[input_dims],
num_expected_engines=16,
expected_output_dims=(5, 23040),
allclose_atol=1.e-03,
allclose_rtol=1.e-03)
if __name__ == "__main__":
test.main()
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