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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 gen_math_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test
class UnaryTest(trt_test.TfTrtIntegrationTestBase):
def GetParams(self):
"""Test for unary operations in TF-TRT."""
dtype = dtypes.float32
input_name = "input"
input_dims = [12, 5, 8, 1, 1, 12]
input2_name = "input_2"
input2_dims = [12, 5, 8, 1, 12, 1, 1]
g = ops.Graph()
with g.as_default():
x = array_ops.placeholder(dtype=dtype, shape=input_dims, name=input_name)
q = math_ops.abs(x)
q = q + 1.0
q = gen_math_ops.exp(q)
q = gen_math_ops.log(q)
q = array_ops.squeeze(q, axis=-2)
q = math_ops.abs(q)
q = q + 2.2
q = gen_math_ops.sqrt(q)
q = gen_math_ops.rsqrt(q)
q = math_ops.negative(q)
q = array_ops.squeeze(q, axis=3)
q = math_ops.abs(q)
q = q + 3.0
a = gen_math_ops.reciprocal(q)
x = constant_op.constant(np.random.randn(5, 8, 12), dtype=dtype)
q = math_ops.abs(x)
q = q + 2.0
q = gen_math_ops.exp(q)
q = gen_math_ops.log(q)
q = math_ops.abs(q)
q = q + 2.1
q = gen_math_ops.sqrt(q)
q = gen_math_ops.rsqrt(q)
q = math_ops.negative(q)
q = math_ops.abs(q)
q = q + 4.0
b = gen_math_ops.reciprocal(q)
# TODO(jie): this one will break, broadcasting on batch.
x = array_ops.placeholder(
dtype=dtype, shape=input2_dims, name=input2_name)
q = math_ops.abs(x)
q = q + 5.0
q = gen_math_ops.exp(q)
q = array_ops.squeeze(q, axis=[-1, -2, 3])
q = gen_math_ops.log(q)
q = math_ops.abs(q)
q = q + 5.1
q = gen_array_ops.reshape(q, [12, 5, 1, 1, 8, 1, 12])
q = array_ops.squeeze(q, axis=[5, 2, 3])
q = gen_math_ops.sqrt(q)
q = math_ops.abs(q)
q = q + 5.2
q = gen_math_ops.rsqrt(q)
q = math_ops.negative(q)
q = math_ops.abs(q)
q = q + 5.3
c = gen_math_ops.reciprocal(q)
q = a * b
q = q / c
array_ops.squeeze(q, name=self.output_name)
return trt_test.TfTrtIntegrationTestParams(
gdef=g.as_graph_def(),
input_names=[input_name, input2_name],
input_dims=[input_dims, input2_dims],
num_expected_engines=5,
expected_output_dims=(12, 5, 8, 12),
allclose_atol=1.e-03,
allclose_rtol=1.e-03)
if __name__ == "__main__":
test.main()
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