wehub-resource-sync
92 lines
3.2 KiB
C++
92 lines
3.2 KiB
C++
/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include <initializer_list>
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#include <vector>
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#include <gtest/gtest.h>
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#include "tensorflow/cc/framework/grad_op_registry.h"
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#include "tensorflow/cc/framework/gradient_checker.h"
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#include "tensorflow/cc/framework/ops.h"
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#include "tensorflow/cc/framework/testutil.h"
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#include "tensorflow/cc/gradients/grad_testutil.h"
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#include "tensorflow/cc/ops/array_ops.h"
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#include "tensorflow/cc/ops/functional_ops.h"
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#include "tensorflow/cc/ops/standard_ops.h"
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#include "tensorflow/core/framework/attr_value.pb.h"
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#include "tensorflow/core/framework/function.pb.h"
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#include "tensorflow/core/framework/function_testlib.h"
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#include "tensorflow/core/framework/tensor_testutil.h"
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#include "tensorflow/core/framework/types.pb.h"
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#include "tensorflow/core/lib/core/status_test_util.h"
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namespace tensorflow {
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namespace ops {
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namespace {
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class FunctionGradTest : public ::testing::Test {
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protected:
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FunctionGradTest() : scope_(Scope::NewRootScope()) {}
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void RunTest(const Output& x, const TensorShape& x_shape, const Output& y,
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const TensorShape& y_shape) {
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TF_ASSERT_OK(scope_.status());
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float max_error;
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auto result = (ComputeGradientError<float, float, float>(
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scope_, {x}, {x_shape}, {y}, {y_shape}, &max_error));
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TF_CHECK_OK(result);
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TF_ASSERT_OK(result);
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EXPECT_LT(max_error, 1e-3);
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}
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void RunTest(const OutputList& xs, const std::vector<TensorShape>& x_shapes,
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const OutputList& ys, const std::vector<TensorShape>& y_shapes) {
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TF_ASSERT_OK(scope_.status());
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float max_error;
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TF_ASSERT_OK((ComputeGradientError<float, float, float>(
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scope_, xs, x_shapes, ys, y_shapes, &max_error)));
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EXPECT_LT(max_error, 1e-3);
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}
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Scope scope_;
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};
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TEST_F(FunctionGradTest, PartitionedCallGrad) {
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FunctionDefLibrary f_lib_proto;
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*(f_lib_proto.add_function()) = test::function::XTimesTwo();
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// Construct a graph:
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// A = Placeholder[dtype=int32]
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// B = XTimesTwo[_tpu_replicate="cluster"](A)
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// C = XTimesTwo[_xla_compile_id="cluster"](A)
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TF_ASSERT_OK(scope_.graph()->AddFunctionLibrary(f_lib_proto));
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Output x = Placeholder(scope_, DT_FLOAT);
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NameAttrList f;
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f.set_name("XTimesTwo");
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(*f.mutable_attr())["T"].set_type(DT_FLOAT);
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auto results =
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PartitionedCall(scope_, std::initializer_list<Input>{x}, {DT_FLOAT}, f);
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RunTest(x, {}, results[0], {});
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auto stateful_results = StatefulPartitionedCall(
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scope_, std::initializer_list<Input>{x}, {DT_FLOAT}, f);
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RunTest(x, {}, stateful_results[0], {});
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}
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} // namespace
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} // namespace ops
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} // namespace tensorflow
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