[KERNEL_GEN][CPU] Generalize binary tests to support CPU platform.
PiperOrigin-RevId: 355365017 Change-Id: Ia73d3f7dc8a1e0db93415272d1c1cc4ae1471dd6
This commit is contained in:
Alexander Belyaev
TensorFlower Gardener
parent
0e30543810
commit
59fcbe5e28
@ -305,13 +305,10 @@ tf_cuda_cc_test(
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],
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],
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)
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)
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tf_cuda_cc_test(
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cc_library(
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name = "gpu_binary_ops_test",
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name = "base_binary_ops_test",
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size = "medium",
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testonly = 1,
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srcs = if_mlir_generated_gpu_kernels_enabled(["gpu_binary_ops_test.cc"]),
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hdrs = ["base_binary_ops_test.h"],
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tags = tf_cuda_tests_tags() + [
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"no_cuda_asan", # b/173033461
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],
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deps = [
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deps = [
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":base_ops_test",
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":base_ops_test",
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"//tensorflow/core:framework",
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"//tensorflow/core:framework",
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@ -332,6 +329,21 @@ tf_cuda_cc_test(
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],
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],
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)
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)
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tf_cuda_cc_test(
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name = "gpu_binary_ops_test",
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size = "medium",
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srcs = if_mlir_generated_gpu_kernels_enabled(["gpu_binary_ops_test.cc"]),
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tags = tf_cuda_tests_tags() + [
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"no_cuda_asan", # b/173033461
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],
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deps = [
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":base_binary_ops_test",
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":base_ops_test",
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"//tensorflow/core/common_runtime:device",
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"//tensorflow/core/common_runtime:device_factory",
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],
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)
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# TODO(b/160731748): Re-enable when it works again.
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# TODO(b/160731748): Re-enable when it works again.
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# gen_kernel_library(
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# gen_kernel_library(
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# name = "bias_add",
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# name = "bias_add",
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370
tensorflow/core/kernels/mlir_generated/base_binary_ops_test.h
Normal file
370
tensorflow/core/kernels/mlir_generated/base_binary_ops_test.h
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@ -0,0 +1,370 @@
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/* Copyright 2021 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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#ifndef TENSORFLOW_CORE_KERNELS_MLIR_GENERATED_BASE_BINARY_OPS_TEST_H_
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#define TENSORFLOW_CORE_KERNELS_MLIR_GENERATED_BASE_BINARY_OPS_TEST_H_
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#include "absl/container/inlined_vector.h"
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#include "absl/strings/string_view.h"
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#include "llvm/ADT/STLExtras.h"
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#include "tensorflow/core/common_runtime/device.h"
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#include "tensorflow/core/common_runtime/device_factory.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/tensor.h"
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#include "tensorflow/core/framework/tensor_shape.h"
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#include "tensorflow/core/kernels/mlir_generated/base_ops_test.h"
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#include "tensorflow/core/kernels/ops_testutil.h"
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#include "tensorflow/core/lib/core/status_test_util.h"
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#include "tensorflow/core/platform/test.h"
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namespace tensorflow {
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// Base class for `BinaryOpsTest` fixture that has to be defined with a custom
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// TF device if you want to use the test macros in this file.
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class BinaryOpsTestBase : public OpsTestBase {
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protected:
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// This method should set the TF device, e.g. DEVICE_CPU, DEVICE_GPU.
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void SetUp() override = 0;
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template <typename T, typename OutT>
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void SetOpKernel(const std::string& op_name, const TensorShape& lhs_shape,
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const absl::InlinedVector<T, 10>& lhs_input,
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const TensorShape& rhs_shape,
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const absl::InlinedVector<T, 10>& rhs_input, bool add_t,
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bool add_tout) {
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auto builder = NodeDefBuilder("some_name", op_name)
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.Input(FakeInput(DataTypeToEnum<T>::v()))
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.Input(FakeInput(DataTypeToEnum<T>::v()));
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if (add_t) {
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builder.Attr("T", DataTypeToEnum<T>::v());
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}
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if (add_tout) {
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builder.Attr("Tout", DataTypeToEnum<OutT>::v());
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}
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TF_ASSERT_OK(builder.Finalize(node_def()));
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TF_ASSERT_OK(InitOp());
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AddInputFromArray<T>(lhs_shape, lhs_input);
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AddInputFromArray<T>(rhs_shape, rhs_input);
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}
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// Run fully specified tests.
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template <typename T, typename OutT>
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void RunAndExpectResult(const std::string& op_name,
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const TensorShape& lhs_shape,
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const absl::InlinedVector<T, 10>& lhs_input,
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const TensorShape& rhs_shape,
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const absl::InlinedVector<T, 10>& rhs_input,
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const TensorShape& expected_shape,
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const absl::InlinedVector<OutT, 10>& expected_output,
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const test::OpsTestConfig& config) {
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SetOpKernel<T, OutT>(op_name, lhs_shape, lhs_input, rhs_shape, rhs_input,
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config.add_t, config.add_tout);
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TF_ASSERT_OK(RunOpKernel());
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// Compare output to expectation.
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Tensor expected_tensor(allocator(), DataTypeToEnum<OutT>::value,
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expected_shape);
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test::FillValues<OutT>(&expected_tensor, expected_output);
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if (config.expect_strictly_equal) {
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test::ExpectEqual(expected_tensor, *GetOutput(0));
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} else {
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test::ExpectClose(expected_tensor, *GetOutput(0));
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}
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}
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template <typename T, typename OutT>
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void RunAndExpectInvalidArgument(const std::string& op_name,
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const TensorShape& lhs_shape,
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const absl::InlinedVector<T, 10>& lhs_input,
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const TensorShape& rhs_shape,
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const absl::InlinedVector<T, 10>& rhs_input,
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const test::OpsTestConfig& config) {
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SetOpKernel<T, OutT>(op_name, lhs_shape, lhs_input, rhs_shape, rhs_input,
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config.add_t, config.add_tout);
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auto status = RunOpKernel();
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EXPECT_FALSE(status.ok());
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EXPECT_EQ(status.code(), error::INVALID_ARGUMENT);
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}
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// Run common test cases.
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template <typename T, typename OutT>
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void TestIncompatibleShapes(const std::string& op_name,
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const absl::InlinedVector<T, 10>& lhs_input,
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const absl::InlinedVector<T, 10>& rhs_input,
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const test::OpsTestConfig& config) {
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// Prepare incompatibly shaped inputs.
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TensorShape lhs_shape{3};
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TensorShape rhs_shape{2};
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auto repeated_lhs_input =
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test::RepeatInputToMatchShape(lhs_input, lhs_shape.num_elements());
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auto repeated_rhs_input =
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test::RepeatInputToMatchShape(rhs_input, rhs_shape.num_elements());
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RunAndExpectInvalidArgument<T, OutT>(op_name, lhs_shape, repeated_lhs_input,
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rhs_shape, repeated_rhs_input, config);
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}
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template <typename T, typename BaselineT, typename OutT,
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typename BaselineOutT>
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void TestEqualShapes(const std::string& op_name, const TensorShape& shape,
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const absl::InlinedVector<T, 10>& lhs_input,
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const absl::InlinedVector<T, 10>& rhs_input,
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BaselineOutT (*baseline_callback)(BaselineT, BaselineT),
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const test::OpsTestConfig& config) {
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// Prepare inputs.
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int input_size = shape.num_elements();
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CHECK(lhs_input.size() <= input_size && rhs_input.size() <= input_size &&
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"expect input shape to hold all input values");
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auto repeated_lhs_input =
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test::RepeatInputToMatchShape(lhs_input, input_size);
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auto repeated_rhs_input =
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test::RepeatInputToMatchShape(rhs_input, input_size);
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// Compute expected results.
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absl::InlinedVector<OutT, 10> expected_output;
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for (auto it_lhs = repeated_lhs_input.begin(),
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it_rhs = repeated_rhs_input.begin(),
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end = repeated_lhs_input.end();
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it_lhs != end; ++it_lhs, ++it_rhs) {
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auto lhs = static_cast<BaselineT>(*it_lhs);
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auto rhs = static_cast<BaselineT>(*it_rhs);
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auto result = static_cast<OutT>(baseline_callback(lhs, rhs));
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expected_output.push_back(result);
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}
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RunAndExpectResult<T, OutT>(op_name, shape, repeated_lhs_input, shape,
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repeated_rhs_input, shape, expected_output,
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config);
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}
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template <typename T, typename BaselineT, typename OutT,
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typename BaselineOutT>
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void TestOneScalar(const std::string& op_name, T scalar_input,
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const TensorShape& other_shape,
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const absl::InlinedVector<T, 10>& other_input,
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BaselineOutT (*baseline_callback)(BaselineT, BaselineT),
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const test::OpsTestConfig& config) {
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// Prepare inputs.
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TensorShape scalar_shape{};
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CHECK(other_input.size() <= other_shape.num_elements() &&
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"expect other input shape to hold all input values");
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auto repeated_other_input =
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test::RepeatInputToMatchShape(other_input, other_shape.num_elements());
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// Compute expected results.
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absl::InlinedVector<OutT, 10> expected_output;
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for (auto it = repeated_other_input.begin(),
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end = repeated_other_input.end();
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it != end; ++it) {
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auto scalar = static_cast<BaselineT>(scalar_input);
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auto other_value = static_cast<BaselineT>(*it);
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auto result = static_cast<OutT>(baseline_callback(scalar, other_value));
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expected_output.push_back(result);
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}
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auto scalar_input_vector = test::InputAsVector<T>({scalar_input});
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RunAndExpectResult<T, OutT>(op_name, scalar_shape, scalar_input_vector,
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other_shape, repeated_other_input,
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/*expected_shape=*/other_shape, expected_output,
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config);
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}
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template <typename T, typename BaselineT, typename OutT,
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typename BaselineOutT>
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void TestBroadcastingExpand(const std::string& op_name,
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const absl::InlinedVector<T, 10>& lhs_input,
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const absl::InlinedVector<T, 10>& rhs_input,
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BaselineOutT (*baseline_callback)(BaselineT,
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BaselineT),
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const test::OpsTestConfig& config) {
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// Prepare inputs.
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TensorShape lhs_shape{1};
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TensorShape rhs_shape{6};
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auto repeated_lhs_input =
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test::RepeatInputToMatchShape(lhs_input, lhs_shape.num_elements());
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auto repeated_rhs_input =
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test::RepeatInputToMatchShape(rhs_input, rhs_shape.num_elements());
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// Compute expected results.
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std::vector<int> lhs_indices = {0, 0, 0, 0, 0, 0};
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std::vector<int> rhs_indices = {0, 1, 2, 3, 4, 5};
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auto expected_output =
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ComputeExpectedOutput<T, BaselineT, OutT, BaselineOutT>(
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lhs_indices, repeated_lhs_input, rhs_indices, repeated_rhs_input,
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baseline_callback);
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RunAndExpectResult<T, OutT>(
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op_name, lhs_shape, repeated_lhs_input, rhs_shape, repeated_rhs_input,
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/*expected_shape=*/rhs_shape, expected_output, config);
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}
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template <typename T, typename BaselineT, typename OutT,
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typename BaselineOutT>
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void TestBroadcastingInDim(const std::string& op_name,
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const absl::InlinedVector<T, 10>& lhs_input,
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const absl::InlinedVector<T, 10>& rhs_input,
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BaselineOutT (*baseline_callback)(BaselineT,
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BaselineT),
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const test::OpsTestConfig& config) {
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// Prepare inputs.
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TensorShape lhs_shape{3};
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TensorShape rhs_shape{2, 3};
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auto repeated_lhs_input =
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test::RepeatInputToMatchShape(lhs_input, lhs_shape.num_elements());
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auto repeated_rhs_input =
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test::RepeatInputToMatchShape(rhs_input, rhs_shape.num_elements());
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// Compute expected results.
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std::vector<int> lhs_indices = {0, 1, 2, 0, 1, 2};
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std::vector<int> rhs_indices = {0, 1, 2, 3, 4, 5};
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auto expected_output =
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ComputeExpectedOutput<T, BaselineT, OutT, BaselineOutT>(
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lhs_indices, repeated_lhs_input, rhs_indices, repeated_rhs_input,
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baseline_callback);
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RunAndExpectResult<T, OutT>(
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op_name, lhs_shape, repeated_lhs_input, rhs_shape, repeated_rhs_input,
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/*expected_shape=*/rhs_shape, expected_output, config);
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}
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template <typename T, typename BaselineT, typename OutT,
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typename BaselineOutT>
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void TestBroadcasting(const std::string& op_name,
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const absl::InlinedVector<T, 10>& lhs_input,
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const absl::InlinedVector<T, 10>& rhs_input,
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BaselineOutT (*baseline_callback)(BaselineT, BaselineT),
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const test::OpsTestConfig& config) {
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// Prepare inputs.
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TensorShape lhs_shape{2, 1};
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TensorShape rhs_shape{3};
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auto repeated_lhs_input =
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test::RepeatInputToMatchShape(lhs_input, lhs_shape.num_elements());
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auto repeated_rhs_input =
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test::RepeatInputToMatchShape(rhs_input, rhs_shape.num_elements());
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// Compute expected results.
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TensorShape expected_shape{2, 3};
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std::vector<int> lhs_indices = {0, 0, 0, 1, 1, 1};
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std::vector<int> rhs_indices = {0, 1, 2, 0, 1, 2};
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auto expected_output =
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ComputeExpectedOutput<T, BaselineT, OutT, BaselineOutT>(
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lhs_indices, repeated_lhs_input, rhs_indices, repeated_rhs_input,
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baseline_callback);
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RunAndExpectResult<T, OutT>(op_name, lhs_shape, repeated_lhs_input,
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rhs_shape, repeated_rhs_input, expected_shape,
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expected_output, config);
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}
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template <typename T, typename BaselineT, typename OutT,
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typename BaselineOutT>
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void TestEmptyShapeBroadcasting(const std::string& op_name,
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const absl::InlinedVector<T, 10>& lhs_input,
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const absl::InlinedVector<T, 10>& rhs_input,
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const test::OpsTestConfig& config) {
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// Prepare inputs.
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TensorShape lhs_shape{2, 0, 1};
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TensorShape rhs_shape{2, 0, 5};
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absl::InlinedVector<T, 10> empty_input = {};
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// Define expected result.
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TensorShape expected_shape{2, 0, 5};
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absl::InlinedVector<OutT, 10> expected_output = {};
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RunAndExpectResult<T, OutT>(op_name, lhs_shape, empty_input, rhs_shape,
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empty_input, expected_shape, expected_output,
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config);
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}
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private:
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template <typename T, typename BaselineT, typename OutT,
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typename BaselineOutT>
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absl::InlinedVector<OutT, 10> ComputeExpectedOutput(
|
||||||
|
std::vector<int> lhs_indices, absl::InlinedVector<T, 10> lhs_input,
|
||||||
|
std::vector<int> rhs_indices, absl::InlinedVector<T, 10> rhs_input,
|
||||||
|
BaselineOutT (*baseline_callback)(BaselineT, BaselineT)) {
|
||||||
|
absl::InlinedVector<OutT, 10> expected_output;
|
||||||
|
for (int i = 0; i < lhs_indices.size(); i++) {
|
||||||
|
auto lhs = static_cast<BaselineT>(lhs_input[lhs_indices[i]]);
|
||||||
|
auto rhs = static_cast<BaselineT>(rhs_input[rhs_indices[i]]);
|
||||||
|
auto result = static_cast<OutT>(baseline_callback(lhs, rhs));
|
||||||
|
expected_output.push_back(result);
|
||||||
|
}
|
||||||
|
return expected_output;
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
// Macros to easily generate common test cases. The macros use `BinaryOpsTest`
|
||||||
|
// fixture in order to share implementation across GPU and CPU platform tests.
|
||||||
|
// For specific inputs, please define your own test fixtures.
|
||||||
|
#define GENERATE_DEFAULT_TESTS_2(op_name, test_name, T, BaselineT, OutT, \
|
||||||
|
BaselineOutT, lhs_input, rhs_input, \
|
||||||
|
baseline_callback, config) \
|
||||||
|
TEST_F(BinaryOpsTest, op_name##EqShapes##test_name) { \
|
||||||
|
TestEqualShapes<T, BaselineT, OutT, BaselineOutT>( \
|
||||||
|
#op_name, /*shape=*/test::DefaultInputShape(), lhs_input, rhs_input, \
|
||||||
|
baseline_callback, config); \
|
||||||
|
} \
|
||||||
|
\
|
||||||
|
TEST_F(BinaryOpsTest, op_name##OneScalar##test_name) { \
|
||||||
|
TestOneScalar<T, BaselineT, OutT, BaselineOutT>( \
|
||||||
|
#op_name, /*scalar_input=*/lhs_input.front(), \
|
||||||
|
/*other_shape=*/test::DefaultInputShape(), /*other_input=*/rhs_input, \
|
||||||
|
baseline_callback, config); \
|
||||||
|
} \
|
||||||
|
\
|
||||||
|
TEST_F(BinaryOpsTest, op_name##IncompatibleShapes##test_name) { \
|
||||||
|
TestIncompatibleShapes<T, OutT>(#op_name, lhs_input, rhs_input, config); \
|
||||||
|
} \
|
||||||
|
\
|
||||||
|
TEST_F(BinaryOpsTest, op_name##BroadcastingExpand##test_name) { \
|
||||||
|
TestBroadcastingExpand<T, BaselineT, OutT, BaselineOutT>( \
|
||||||
|
#op_name, lhs_input, rhs_input, baseline_callback, config); \
|
||||||
|
} \
|
||||||
|
\
|
||||||
|
TEST_F(BinaryOpsTest, op_name##BroadcastingInDim##test_name) { \
|
||||||
|
TestBroadcastingInDim<T, BaselineT, OutT, BaselineOutT>( \
|
||||||
|
#op_name, lhs_input, rhs_input, baseline_callback, config); \
|
||||||
|
} \
|
||||||
|
\
|
||||||
|
TEST_F(BinaryOpsTest, op_name##Broadcasting##test_name) { \
|
||||||
|
TestBroadcasting<T, BaselineT, OutT, BaselineOutT>( \
|
||||||
|
#op_name, lhs_input, rhs_input, baseline_callback, config); \
|
||||||
|
} \
|
||||||
|
\
|
||||||
|
TEST_F(BinaryOpsTest, op_name##EmptyShapeBroadcasting##test_name) { \
|
||||||
|
TestEmptyShapeBroadcasting<T, BaselineT, OutT, BaselineOutT>( \
|
||||||
|
#op_name, lhs_input, rhs_input, config); \
|
||||||
|
}
|
||||||
|
|
||||||
|
#define GENERATE_DEFAULT_TESTS(op_name, test_name, T, OutT, baseline_callback) \
|
||||||
|
GENERATE_DEFAULT_TESTS_2(op_name, test_name, T, T, OutT, OutT, \
|
||||||
|
test::DefaultInput<T>(), test::DefaultInput<T>(), \
|
||||||
|
baseline_callback, \
|
||||||
|
test::OpsTestConfig().ExpectStrictlyEqual())
|
||||||
|
|
||||||
|
#define GENERATE_DEFAULT_TESTS_WITH_SPECIFIC_INPUT_VALUES( \
|
||||||
|
op_name, test_name, T, OutT, lhs_input, rhs_input, baseline_callback) \
|
||||||
|
GENERATE_DEFAULT_TESTS_2(op_name, test_name, T, T, OutT, OutT, lhs_input, \
|
||||||
|
rhs_input, baseline_callback, \
|
||||||
|
test::OpsTestConfig().ExpectStrictlyEqual())
|
||||||
|
|
||||||
|
} // namespace tensorflow
|
||||||
|
|
||||||
|
#endif // TENSORFLOW_CORE_KERNELS_MLIR_GENERATED_BASE_BINARY_OPS_TEST_H_
|
||||||
@ -13,29 +13,17 @@ See the License for the specific language governing permissions and
|
|||||||
limitations under the License.
|
limitations under the License.
|
||||||
==============================================================================*/
|
==============================================================================*/
|
||||||
|
|
||||||
#include <initializer_list>
|
|
||||||
#include <limits>
|
|
||||||
#include <memory>
|
|
||||||
#include <vector>
|
|
||||||
|
|
||||||
#include "absl/container/inlined_vector.h"
|
|
||||||
#include "absl/strings/string_view.h"
|
|
||||||
#include "llvm/ADT/STLExtras.h"
|
|
||||||
#include "tensorflow/core/common_runtime/device.h"
|
#include "tensorflow/core/common_runtime/device.h"
|
||||||
#include "tensorflow/core/common_runtime/device_factory.h"
|
#include "tensorflow/core/common_runtime/device_factory.h"
|
||||||
#include "tensorflow/core/framework/fake_input.h"
|
#include "tensorflow/core/kernels/mlir_generated/base_binary_ops_test.h"
|
||||||
#include "tensorflow/core/framework/node_def_builder.h"
|
|
||||||
#include "tensorflow/core/framework/tensor.h"
|
|
||||||
#include "tensorflow/core/framework/tensor_shape.h"
|
|
||||||
#include "tensorflow/core/kernels/mlir_generated/base_ops_test.h"
|
#include "tensorflow/core/kernels/mlir_generated/base_ops_test.h"
|
||||||
#include "tensorflow/core/kernels/ops_testutil.h"
|
|
||||||
#include "tensorflow/core/lib/core/status_test_util.h"
|
|
||||||
#include "tensorflow/core/platform/test.h"
|
|
||||||
|
|
||||||
namespace tensorflow {
|
namespace tensorflow {
|
||||||
namespace {
|
namespace {
|
||||||
|
|
||||||
class GpuBinaryOpTest : public OpsTestBase {
|
// Test fixture `BinaryOpsTest` that sets the TF device is expected by the TEST
|
||||||
|
// macros below.
|
||||||
|
class BinaryOpsTest : public BinaryOpsTestBase {
|
||||||
protected:
|
protected:
|
||||||
void SetUp() override {
|
void SetUp() override {
|
||||||
std::unique_ptr<tensorflow::Device> device_gpu(
|
std::unique_ptr<tensorflow::Device> device_gpu(
|
||||||
@ -43,333 +31,8 @@ class GpuBinaryOpTest : public OpsTestBase {
|
|||||||
"/job:a/replica:0/task:0"));
|
"/job:a/replica:0/task:0"));
|
||||||
SetDevice(tensorflow::DEVICE_GPU, std::move(device_gpu));
|
SetDevice(tensorflow::DEVICE_GPU, std::move(device_gpu));
|
||||||
}
|
}
|
||||||
|
|
||||||
template <typename T, typename OutT>
|
|
||||||
void SetOpKernel(const std::string& op_name, const TensorShape& lhs_shape,
|
|
||||||
const absl::InlinedVector<T, 10>& lhs_input,
|
|
||||||
const TensorShape& rhs_shape,
|
|
||||||
const absl::InlinedVector<T, 10>& rhs_input, bool add_t,
|
|
||||||
bool add_tout) {
|
|
||||||
auto builder = NodeDefBuilder("some_name", op_name)
|
|
||||||
.Input(FakeInput(DataTypeToEnum<T>::v()))
|
|
||||||
.Input(FakeInput(DataTypeToEnum<T>::v()));
|
|
||||||
if (add_t) {
|
|
||||||
builder.Attr("T", DataTypeToEnum<T>::v());
|
|
||||||
}
|
|
||||||
if (add_tout) {
|
|
||||||
builder.Attr("Tout", DataTypeToEnum<OutT>::v());
|
|
||||||
}
|
|
||||||
TF_ASSERT_OK(builder.Finalize(node_def()));
|
|
||||||
|
|
||||||
TF_ASSERT_OK(InitOp());
|
|
||||||
AddInputFromArray<T>(lhs_shape, lhs_input);
|
|
||||||
AddInputFromArray<T>(rhs_shape, rhs_input);
|
|
||||||
}
|
|
||||||
|
|
||||||
// Run fully specified tests.
|
|
||||||
|
|
||||||
template <typename T, typename OutT>
|
|
||||||
void RunAndExpectResult(const std::string& op_name,
|
|
||||||
const TensorShape& lhs_shape,
|
|
||||||
const absl::InlinedVector<T, 10>& lhs_input,
|
|
||||||
const TensorShape& rhs_shape,
|
|
||||||
const absl::InlinedVector<T, 10>& rhs_input,
|
|
||||||
const TensorShape& expected_shape,
|
|
||||||
const absl::InlinedVector<OutT, 10>& expected_output,
|
|
||||||
const test::OpsTestConfig& config) {
|
|
||||||
SetOpKernel<T, OutT>(op_name, lhs_shape, lhs_input, rhs_shape, rhs_input,
|
|
||||||
config.add_t, config.add_tout);
|
|
||||||
TF_ASSERT_OK(RunOpKernel());
|
|
||||||
|
|
||||||
// Compare output to expectation.
|
|
||||||
Tensor expected_tensor(allocator(), DataTypeToEnum<OutT>::value,
|
|
||||||
expected_shape);
|
|
||||||
test::FillValues<OutT>(&expected_tensor, expected_output);
|
|
||||||
if (config.expect_strictly_equal) {
|
|
||||||
test::ExpectEqual(expected_tensor, *GetOutput(0));
|
|
||||||
} else {
|
|
||||||
test::ExpectClose(expected_tensor, *GetOutput(0));
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
template <typename T, typename OutT>
|
|
||||||
void RunAndExpectInvalidArgument(const std::string& op_name,
|
|
||||||
const TensorShape& lhs_shape,
|
|
||||||
const absl::InlinedVector<T, 10>& lhs_input,
|
|
||||||
const TensorShape& rhs_shape,
|
|
||||||
const absl::InlinedVector<T, 10>& rhs_input,
|
|
||||||
const test::OpsTestConfig& config) {
|
|
||||||
SetOpKernel<T, OutT>(op_name, lhs_shape, lhs_input, rhs_shape, rhs_input,
|
|
||||||
config.add_t, config.add_tout);
|
|
||||||
auto status = RunOpKernel();
|
|
||||||
EXPECT_FALSE(status.ok());
|
|
||||||
EXPECT_EQ(status.code(), error::INVALID_ARGUMENT);
|
|
||||||
}
|
|
||||||
|
|
||||||
// Run common test cases.
|
|
||||||
|
|
||||||
template <typename T, typename OutT>
|
|
||||||
void TestIncompatibleShapes(const std::string& op_name,
|
|
||||||
const absl::InlinedVector<T, 10>& lhs_input,
|
|
||||||
const absl::InlinedVector<T, 10>& rhs_input,
|
|
||||||
const test::OpsTestConfig& config) {
|
|
||||||
// Prepare incompatibly shaped inputs.
|
|
||||||
TensorShape lhs_shape{3};
|
|
||||||
TensorShape rhs_shape{2};
|
|
||||||
auto repeated_lhs_input =
|
|
||||||
test::RepeatInputToMatchShape(lhs_input, lhs_shape.num_elements());
|
|
||||||
auto repeated_rhs_input =
|
|
||||||
test::RepeatInputToMatchShape(rhs_input, rhs_shape.num_elements());
|
|
||||||
|
|
||||||
RunAndExpectInvalidArgument<T, OutT>(op_name, lhs_shape, repeated_lhs_input,
|
|
||||||
rhs_shape, repeated_rhs_input, config);
|
|
||||||
}
|
|
||||||
|
|
||||||
template <typename T, typename BaselineT, typename OutT,
|
|
||||||
typename BaselineOutT>
|
|
||||||
void TestEqualShapes(const std::string& op_name, const TensorShape& shape,
|
|
||||||
const absl::InlinedVector<T, 10>& lhs_input,
|
|
||||||
const absl::InlinedVector<T, 10>& rhs_input,
|
|
||||||
BaselineOutT (*baseline_callback)(BaselineT, BaselineT),
|
|
||||||
const test::OpsTestConfig& config) {
|
|
||||||
// Prepare inputs.
|
|
||||||
int input_size = shape.num_elements();
|
|
||||||
CHECK(lhs_input.size() <= input_size && rhs_input.size() <= input_size &&
|
|
||||||
"expect input shape to hold all input values");
|
|
||||||
auto repeated_lhs_input =
|
|
||||||
test::RepeatInputToMatchShape(lhs_input, input_size);
|
|
||||||
auto repeated_rhs_input =
|
|
||||||
test::RepeatInputToMatchShape(rhs_input, input_size);
|
|
||||||
|
|
||||||
// Compute expected results.
|
|
||||||
absl::InlinedVector<OutT, 10> expected_output;
|
|
||||||
for (auto it_lhs = repeated_lhs_input.begin(),
|
|
||||||
it_rhs = repeated_rhs_input.begin(),
|
|
||||||
end = repeated_lhs_input.end();
|
|
||||||
it_lhs != end; ++it_lhs, ++it_rhs) {
|
|
||||||
auto lhs = static_cast<BaselineT>(*it_lhs);
|
|
||||||
auto rhs = static_cast<BaselineT>(*it_rhs);
|
|
||||||
auto result = static_cast<OutT>(baseline_callback(lhs, rhs));
|
|
||||||
expected_output.push_back(result);
|
|
||||||
}
|
|
||||||
|
|
||||||
RunAndExpectResult<T, OutT>(op_name, shape, repeated_lhs_input, shape,
|
|
||||||
repeated_rhs_input, shape, expected_output,
|
|
||||||
config);
|
|
||||||
}
|
|
||||||
|
|
||||||
template <typename T, typename BaselineT, typename OutT,
|
|
||||||
typename BaselineOutT>
|
|
||||||
void TestOneScalar(const std::string& op_name, T scalar_input,
|
|
||||||
const TensorShape& other_shape,
|
|
||||||
const absl::InlinedVector<T, 10>& other_input,
|
|
||||||
BaselineOutT (*baseline_callback)(BaselineT, BaselineT),
|
|
||||||
const test::OpsTestConfig& config) {
|
|
||||||
// Prepare inputs.
|
|
||||||
TensorShape scalar_shape{};
|
|
||||||
CHECK(other_input.size() <= other_shape.num_elements() &&
|
|
||||||
"expect other input shape to hold all input values");
|
|
||||||
auto repeated_other_input =
|
|
||||||
test::RepeatInputToMatchShape(other_input, other_shape.num_elements());
|
|
||||||
|
|
||||||
// Compute expected results.
|
|
||||||
absl::InlinedVector<OutT, 10> expected_output;
|
|
||||||
for (auto it = repeated_other_input.begin(),
|
|
||||||
end = repeated_other_input.end();
|
|
||||||
it != end; ++it) {
|
|
||||||
auto scalar = static_cast<BaselineT>(scalar_input);
|
|
||||||
auto other_value = static_cast<BaselineT>(*it);
|
|
||||||
auto result = static_cast<OutT>(baseline_callback(scalar, other_value));
|
|
||||||
expected_output.push_back(result);
|
|
||||||
}
|
|
||||||
|
|
||||||
auto scalar_input_vector = test::InputAsVector<T>({scalar_input});
|
|
||||||
RunAndExpectResult<T, OutT>(op_name, scalar_shape, scalar_input_vector,
|
|
||||||
other_shape, repeated_other_input,
|
|
||||||
/*expected_shape=*/other_shape, expected_output,
|
|
||||||
config);
|
|
||||||
}
|
|
||||||
|
|
||||||
template <typename T, typename BaselineT, typename OutT,
|
|
||||||
typename BaselineOutT>
|
|
||||||
void TestBroadcastingExpand(const std::string& op_name,
|
|
||||||
const absl::InlinedVector<T, 10>& lhs_input,
|
|
||||||
const absl::InlinedVector<T, 10>& rhs_input,
|
|
||||||
BaselineOutT (*baseline_callback)(BaselineT,
|
|
||||||
BaselineT),
|
|
||||||
const test::OpsTestConfig& config) {
|
|
||||||
// Prepare inputs.
|
|
||||||
TensorShape lhs_shape{1};
|
|
||||||
TensorShape rhs_shape{6};
|
|
||||||
auto repeated_lhs_input =
|
|
||||||
test::RepeatInputToMatchShape(lhs_input, lhs_shape.num_elements());
|
|
||||||
auto repeated_rhs_input =
|
|
||||||
test::RepeatInputToMatchShape(rhs_input, rhs_shape.num_elements());
|
|
||||||
|
|
||||||
// Compute expected results.
|
|
||||||
std::vector<int> lhs_indices = {0, 0, 0, 0, 0, 0};
|
|
||||||
std::vector<int> rhs_indices = {0, 1, 2, 3, 4, 5};
|
|
||||||
auto expected_output =
|
|
||||||
ComputeExpectedOutput<T, BaselineT, OutT, BaselineOutT>(
|
|
||||||
lhs_indices, repeated_lhs_input, rhs_indices, repeated_rhs_input,
|
|
||||||
baseline_callback);
|
|
||||||
|
|
||||||
RunAndExpectResult<T, OutT>(
|
|
||||||
op_name, lhs_shape, repeated_lhs_input, rhs_shape, repeated_rhs_input,
|
|
||||||
/*expected_shape=*/rhs_shape, expected_output, config);
|
|
||||||
}
|
|
||||||
|
|
||||||
template <typename T, typename BaselineT, typename OutT,
|
|
||||||
typename BaselineOutT>
|
|
||||||
void TestBroadcastingInDim(const std::string& op_name,
|
|
||||||
const absl::InlinedVector<T, 10>& lhs_input,
|
|
||||||
const absl::InlinedVector<T, 10>& rhs_input,
|
|
||||||
BaselineOutT (*baseline_callback)(BaselineT,
|
|
||||||
BaselineT),
|
|
||||||
const test::OpsTestConfig& config) {
|
|
||||||
// Prepare inputs.
|
|
||||||
TensorShape lhs_shape{3};
|
|
||||||
TensorShape rhs_shape{2, 3};
|
|
||||||
auto repeated_lhs_input =
|
|
||||||
test::RepeatInputToMatchShape(lhs_input, lhs_shape.num_elements());
|
|
||||||
auto repeated_rhs_input =
|
|
||||||
test::RepeatInputToMatchShape(rhs_input, rhs_shape.num_elements());
|
|
||||||
|
|
||||||
// Compute expected results.
|
|
||||||
std::vector<int> lhs_indices = {0, 1, 2, 0, 1, 2};
|
|
||||||
std::vector<int> rhs_indices = {0, 1, 2, 3, 4, 5};
|
|
||||||
auto expected_output =
|
|
||||||
ComputeExpectedOutput<T, BaselineT, OutT, BaselineOutT>(
|
|
||||||
lhs_indices, repeated_lhs_input, rhs_indices, repeated_rhs_input,
|
|
||||||
baseline_callback);
|
|
||||||
|
|
||||||
RunAndExpectResult<T, OutT>(
|
|
||||||
op_name, lhs_shape, repeated_lhs_input, rhs_shape, repeated_rhs_input,
|
|
||||||
/*expected_shape=*/rhs_shape, expected_output, config);
|
|
||||||
}
|
|
||||||
|
|
||||||
template <typename T, typename BaselineT, typename OutT,
|
|
||||||
typename BaselineOutT>
|
|
||||||
void TestBroadcasting(const std::string& op_name,
|
|
||||||
const absl::InlinedVector<T, 10>& lhs_input,
|
|
||||||
const absl::InlinedVector<T, 10>& rhs_input,
|
|
||||||
BaselineOutT (*baseline_callback)(BaselineT, BaselineT),
|
|
||||||
const test::OpsTestConfig& config) {
|
|
||||||
// Prepare inputs.
|
|
||||||
TensorShape lhs_shape{2, 1};
|
|
||||||
TensorShape rhs_shape{3};
|
|
||||||
auto repeated_lhs_input =
|
|
||||||
test::RepeatInputToMatchShape(lhs_input, lhs_shape.num_elements());
|
|
||||||
auto repeated_rhs_input =
|
|
||||||
test::RepeatInputToMatchShape(rhs_input, rhs_shape.num_elements());
|
|
||||||
|
|
||||||
// Compute expected results.
|
|
||||||
TensorShape expected_shape{2, 3};
|
|
||||||
std::vector<int> lhs_indices = {0, 0, 0, 1, 1, 1};
|
|
||||||
std::vector<int> rhs_indices = {0, 1, 2, 0, 1, 2};
|
|
||||||
auto expected_output =
|
|
||||||
ComputeExpectedOutput<T, BaselineT, OutT, BaselineOutT>(
|
|
||||||
lhs_indices, repeated_lhs_input, rhs_indices, repeated_rhs_input,
|
|
||||||
baseline_callback);
|
|
||||||
|
|
||||||
RunAndExpectResult<T, OutT>(op_name, lhs_shape, repeated_lhs_input,
|
|
||||||
rhs_shape, repeated_rhs_input, expected_shape,
|
|
||||||
expected_output, config);
|
|
||||||
}
|
|
||||||
|
|
||||||
template <typename T, typename BaselineT, typename OutT,
|
|
||||||
typename BaselineOutT>
|
|
||||||
void TestEmptyShapeBroadcasting(const std::string& op_name,
|
|
||||||
const absl::InlinedVector<T, 10>& lhs_input,
|
|
||||||
const absl::InlinedVector<T, 10>& rhs_input,
|
|
||||||
const test::OpsTestConfig& config) {
|
|
||||||
// Prepare inputs.
|
|
||||||
TensorShape lhs_shape{2, 0, 1};
|
|
||||||
TensorShape rhs_shape{2, 0, 5};
|
|
||||||
absl::InlinedVector<T, 10> empty_input = {};
|
|
||||||
|
|
||||||
// Define expected result.
|
|
||||||
TensorShape expected_shape{2, 0, 5};
|
|
||||||
absl::InlinedVector<OutT, 10> expected_output = {};
|
|
||||||
|
|
||||||
RunAndExpectResult<T, OutT>(op_name, lhs_shape, empty_input, rhs_shape,
|
|
||||||
empty_input, expected_shape, expected_output,
|
|
||||||
config);
|
|
||||||
}
|
|
||||||
|
|
||||||
private:
|
|
||||||
template <typename T, typename BaselineT, typename OutT,
|
|
||||||
typename BaselineOutT>
|
|
||||||
absl::InlinedVector<OutT, 10> ComputeExpectedOutput(
|
|
||||||
std::vector<int> lhs_indices, absl::InlinedVector<T, 10> lhs_input,
|
|
||||||
std::vector<int> rhs_indices, absl::InlinedVector<T, 10> rhs_input,
|
|
||||||
BaselineOutT (*baseline_callback)(BaselineT, BaselineT)) {
|
|
||||||
absl::InlinedVector<OutT, 10> expected_output;
|
|
||||||
for (int i = 0; i < lhs_indices.size(); i++) {
|
|
||||||
auto lhs = static_cast<BaselineT>(lhs_input[lhs_indices[i]]);
|
|
||||||
auto rhs = static_cast<BaselineT>(rhs_input[rhs_indices[i]]);
|
|
||||||
auto result = static_cast<OutT>(baseline_callback(lhs, rhs));
|
|
||||||
expected_output.push_back(result);
|
|
||||||
}
|
|
||||||
return expected_output;
|
|
||||||
}
|
|
||||||
};
|
};
|
||||||
|
|
||||||
// Macros to easily generate common test cases. For specific inputs, please
|
|
||||||
// define your own test fixtures.
|
|
||||||
|
|
||||||
#define GENERATE_DEFAULT_TESTS_2(op_name, test_name, T, BaselineT, OutT, \
|
|
||||||
BaselineOutT, lhs_input, rhs_input, \
|
|
||||||
baseline_callback, config) \
|
|
||||||
TEST_F(GpuBinaryOpTest, op_name##EqShapes##test_name) { \
|
|
||||||
TestEqualShapes<T, BaselineT, OutT, BaselineOutT>( \
|
|
||||||
#op_name, /*shape=*/test::DefaultInputShape(), lhs_input, rhs_input, \
|
|
||||||
baseline_callback, config); \
|
|
||||||
} \
|
|
||||||
\
|
|
||||||
TEST_F(GpuBinaryOpTest, op_name##OneScalar##test_name) { \
|
|
||||||
TestOneScalar<T, BaselineT, OutT, BaselineOutT>( \
|
|
||||||
#op_name, /*scalar_input=*/lhs_input.front(), \
|
|
||||||
/*other_shape=*/test::DefaultInputShape(), /*other_input=*/rhs_input, \
|
|
||||||
baseline_callback, config); \
|
|
||||||
} \
|
|
||||||
\
|
|
||||||
TEST_F(GpuBinaryOpTest, op_name##IncompatibleShapes##test_name) { \
|
|
||||||
TestIncompatibleShapes<T, OutT>(#op_name, lhs_input, rhs_input, config); \
|
|
||||||
} \
|
|
||||||
\
|
|
||||||
TEST_F(GpuBinaryOpTest, op_name##BroadcastingExpand##test_name) { \
|
|
||||||
TestBroadcastingExpand<T, BaselineT, OutT, BaselineOutT>( \
|
|
||||||
#op_name, lhs_input, rhs_input, baseline_callback, config); \
|
|
||||||
} \
|
|
||||||
\
|
|
||||||
TEST_F(GpuBinaryOpTest, op_name##BroadcastingInDim##test_name) { \
|
|
||||||
TestBroadcastingInDim<T, BaselineT, OutT, BaselineOutT>( \
|
|
||||||
#op_name, lhs_input, rhs_input, baseline_callback, config); \
|
|
||||||
} \
|
|
||||||
\
|
|
||||||
TEST_F(GpuBinaryOpTest, op_name##Broadcasting##test_name) { \
|
|
||||||
TestBroadcasting<T, BaselineT, OutT, BaselineOutT>( \
|
|
||||||
#op_name, lhs_input, rhs_input, baseline_callback, config); \
|
|
||||||
} \
|
|
||||||
\
|
|
||||||
TEST_F(GpuBinaryOpTest, op_name##EmptyShapeBroadcasting##test_name) { \
|
|
||||||
TestEmptyShapeBroadcasting<T, BaselineT, OutT, BaselineOutT>( \
|
|
||||||
#op_name, lhs_input, rhs_input, config); \
|
|
||||||
}
|
|
||||||
|
|
||||||
#define GENERATE_DEFAULT_TESTS(op_name, test_name, T, OutT, baseline_callback) \
|
|
||||||
GENERATE_DEFAULT_TESTS_2(op_name, test_name, T, T, OutT, OutT, \
|
|
||||||
test::DefaultInput<T>(), test::DefaultInput<T>(), \
|
|
||||||
baseline_callback, \
|
|
||||||
test::OpsTestConfig().ExpectStrictlyEqual())
|
|
||||||
|
|
||||||
#define GENERATE_DEFAULT_TESTS_WITH_SPECIFIC_INPUT_VALUES( \
|
|
||||||
op_name, test_name, T, OutT, lhs_input, rhs_input, baseline_callback) \
|
|
||||||
GENERATE_DEFAULT_TESTS_2(op_name, test_name, T, T, OutT, OutT, lhs_input, \
|
|
||||||
rhs_input, baseline_callback, \
|
|
||||||
test::OpsTestConfig().ExpectStrictlyEqual())
|
|
||||||
|
|
||||||
/// Test `tf.AddV2`.
|
/// Test `tf.AddV2`.
|
||||||
|
|
||||||
template <typename T>
|
template <typename T>
|
||||||
@ -410,14 +73,14 @@ GENERATE_DEFAULT_TESTS_WITH_SPECIFIC_INPUT_VALUES(
|
|||||||
std::atan2);
|
std::atan2);
|
||||||
|
|
||||||
// Test some particularly interesting cases.
|
// Test some particularly interesting cases.
|
||||||
TEST_F(GpuBinaryOpTest, Atan2FloatSpecialCases) {
|
TEST_F(BinaryOpsTest, Atan2FloatSpecialCases) {
|
||||||
TestEqualShapes<float, float, float, float>(
|
TestEqualShapes<float, float, float, float>(
|
||||||
"Atan2", /*shape=*/{20},
|
"Atan2", /*shape=*/{20},
|
||||||
test::InputAsVector<float>({1, 1, 1, 0, -1, -1, -1, 0}),
|
test::InputAsVector<float>({1, 1, 1, 0, -1, -1, -1, 0}),
|
||||||
test::InputAsVector<float>({1, 0, -1, -1, -1, 0, 1, 1}), std::atan2,
|
test::InputAsVector<float>({1, 0, -1, -1, -1, 0, 1, 1}), std::atan2,
|
||||||
test::OpsTestConfig().ExpectStrictlyEqual());
|
test::OpsTestConfig().ExpectStrictlyEqual());
|
||||||
}
|
}
|
||||||
TEST_F(GpuBinaryOpTest, Atan2DoubleSpecialCases) {
|
TEST_F(BinaryOpsTest, Atan2DoubleSpecialCases) {
|
||||||
TestEqualShapes<double, double, double, double>(
|
TestEqualShapes<double, double, double, double>(
|
||||||
"Atan2", /*shape=*/{20},
|
"Atan2", /*shape=*/{20},
|
||||||
test::InputAsVector<double>({1, 1, 1, 0, -1, -1, -1, 0}),
|
test::InputAsVector<double>({1, 1, 1, 0, -1, -1, -1, 0}),
|
||||||
|
|||||||
Loading…
Reference in New Issue
Block a user