/* Copyright 2016 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 "tensorflow/core/framework/allocator.h"
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#include "tensorflow/core/framework/fake_input.h"
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#include "tensorflow/core/framework/node_def_builder.h"
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#include "tensorflow/core/framework/op_kernel.h"
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#include "tensorflow/core/framework/tensor.h"
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#include "tensorflow/core/framework/tensor_testutil.h"
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#include "tensorflow/core/framework/types.h"
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#include "tensorflow/core/kernels/ops_testutil.h"
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#include "tensorflow/core/platform/test.h"
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namespace tensorflow {
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namespace {
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class SparseReduceSumOpTest : public OpsTestBase {
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protected:
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template <typename T>
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void MakeOp() {
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DataType value_type = tensorflow::DataTypeToEnum<T>::value;
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TF_ASSERT_OK(NodeDefBuilder("sparse_reduce_sum", "SparseReduceSum")
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.Input(FakeInput(DT_INT64))
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.Input(FakeInput(value_type))
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.Input(FakeInput(DT_INT64))
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.Input(FakeInput(DT_INT32))
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.Attr("T", value_type)
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.Finalize(node_def()));
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TF_ASSERT_OK(InitOp());
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}
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};
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TEST_F(SparseReduceSumOpTest, SimpleReduce) {
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MakeOp<float>();
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// [ 1]
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// [2 ]
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// [3 4]
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const auto indices_shape = TensorShape({4, 2});
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std::initializer_list<int64> in{0, 1, 1, 0, 2, 0, 2, 1};
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const gtl::ArraySlice<int64> indices(in);
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std::initializer_list<int64> sh{3, 2};
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const gtl::ArraySlice<int64> shape(sh);
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AddInputFromArray<int64>(indices_shape, indices);
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AddInputFromArray<float>(TensorShape({4}), {1, 2, 3, 4});
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AddInputFromArray<int64>(TensorShape({2}), shape);
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AddInputFromArray<int32>(TensorShape({1}), {0}); // reduction axes
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TF_ASSERT_OK(RunOpKernel());
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Tensor expected_by_0(allocator(), DT_FLOAT, TensorShape({2}));
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test::FillValues<float>(&expected_by_0, {5, 5});
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test::ExpectTensorEqual<float>(expected_by_0, *GetOutput(0));
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}
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class SparseReduceSumSparseOpTest : public OpsTestBase {
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protected:
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template <typename T>
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void MakeOp() {
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DataType value_type = tensorflow::DataTypeToEnum<T>::value;
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TF_ASSERT_OK(
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NodeDefBuilder("sparse_reduce_sum_sparse", "SparseReduceSumSparse")
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.Input(FakeInput(DT_INT64))
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.Input(FakeInput(value_type))
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.Input(FakeInput(DT_INT64))
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.Input(FakeInput(DT_INT32))
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.Attr("T", value_type)
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.Finalize(node_def()));
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TF_ASSERT_OK(InitOp());
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}
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};
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TEST_F(SparseReduceSumSparseOpTest, SimpleReduce) {
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MakeOp<float>();
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// [ 2]
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// [2 ]
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// [3 4]
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const auto indices_shape = TensorShape({4, 2});
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std::initializer_list<int64> in{0, 1, 1, 0, 2, 0, 2, 1};
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const gtl::ArraySlice<int64> indices(in);
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std::initializer_list<int64> sh{3, 2};
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const gtl::ArraySlice<int64> shape(sh);
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AddInputFromArray<int64>(indices_shape, indices);
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AddInputFromArray<float>(TensorShape({4}), {2, 2, 3, 4});
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AddInputFromArray<int64>(TensorShape({2}), shape);
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AddInputFromArray<int32>(TensorShape({1}), {0}); // reduction axes
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TF_ASSERT_OK(RunOpKernel());
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const int expected_nnz = 2;
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Tensor expected_indices(allocator(), DT_INT64,
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TensorShape({expected_nnz, 1}));
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test::FillValues<int64>(&expected_indices, {0, 1});
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test::ExpectTensorEqual<int64>(expected_indices, *GetOutput(0));
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Tensor expected_values(allocator(), DT_FLOAT, TensorShape({2}));
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test::FillValues<float>(&expected_values, {5, 6});
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test::ExpectTensorEqual<float>(expected_values, *GetOutput(1));
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Tensor expected_shape(allocator(), DT_INT64, {1});
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test::FillValues<int64>(&expected_shape, {2});
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test::ExpectTensorEqual<int64>(expected_shape, *GetOutput(2));
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}
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} // namespace
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} // namespace tensorflow
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