/* Copyright 2020 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. ==============================================================================*/ #include "tensorflow/c/kernels.h" #include "tensorflow/core/framework/allocator.h" #include "tensorflow/core/framework/attr_value.pb.h" #include "tensorflow/core/framework/attr_value_util.h" #include "tensorflow/core/framework/device_base.h" #include "tensorflow/core/framework/node_def.pb.h" #include "tensorflow/core/framework/op.h" #include "tensorflow/core/framework/op_def_builder.h" #include "tensorflow/core/framework/op_kernel.h" #include "tensorflow/core/framework/summary.pb.h" #include "tensorflow/core/framework/tensor.h" #include "tensorflow/core/framework/types.h" #include "tensorflow/core/lib/gtl/inlined_vector.h" #include "tensorflow/core/platform/env.h" #include "tensorflow/core/platform/protobuf.h" #include "tensorflow/core/platform/status.h" #include "tensorflow/core/platform/strcat.h" #include "tensorflow/core/platform/test.h" #include "tensorflow/core/protobuf/error_codes.pb.h" namespace tensorflow { namespace { class DummyDevice : public DeviceBase { public: explicit DummyDevice(Env* env) : DeviceBase(env) {} Allocator* GetAllocator(AllocatorAttributes /*attr*/) override { return cpu_allocator(); } }; // Helper for comparing output and expected output void ExpectSummaryMatches(const Summary& actual, const std::string& expected_str) { Summary expected; ASSERT_TRUE(protobuf::TextFormat::ParseFromString(expected_str, &expected)); EXPECT_EQ(expected.DebugString(), actual.DebugString()); } void TestScalarSummaryOp(Tensor* tags, Tensor* values, std::string expected_output, error::Code expected_code) { // Initialize node used to fetch OpKernel absl::Status status; NodeDef def; def.set_op("ScalarSummary"); def.set_device(DEVICE_CPU); AttrValue valuesTypeAttr; SetAttrValue(values->dtype(), &valuesTypeAttr); (*def.mutable_attr())["T"] = valuesTypeAttr; def.add_input(absl::StrCat("input1: ", DataTypeString(tags->dtype()))); def.add_input(absl::StrCat("input2: ", DataTypeString(values->dtype()))); std::unique_ptr kernel = CreateOpKernel(DeviceType(DEVICE_CPU), nullptr, nullptr, def, 1, &status); ASSERT_TRUE(status.ok()) << status.ToString(); OpKernelContext::Params params; DummyDevice dummy_device(nullptr); params.device = &dummy_device; params.op_kernel = kernel.get(); AllocatorAttributes alloc_attrs; params.output_attr_array = &alloc_attrs; absl::InlinedVector inputs; inputs.emplace_back(tags); inputs.emplace_back(values); params.inputs = inputs; OpKernelContext ctx(¶ms, 1); kernel->Compute(&ctx); ASSERT_EQ(expected_code, ctx.status().code()); if (expected_code == error::OK) { Summary summary; ASSERT_TRUE(ParseProtoUnlimited( &summary, ctx.mutable_output(0)->scalar()())); ExpectSummaryMatches(summary, expected_output); } else { EXPECT_TRUE(absl::StrContains(ctx.status().ToString(), expected_output)) << ctx.status(); } } TEST(ScalarSummaryOpTest, SimpleFloat) { int vectorSize = 3; Tensor tags(DT_STRING, {vectorSize}); Tensor values(DT_FLOAT, {vectorSize}); tags.vec()(0) = "tag1"; tags.vec()(1) = "tag2"; tags.vec()(2) = "tag3"; values.vec()(0) = 1.0f; values.vec()(1) = -0.73f; values.vec()(2) = 10000.0f; TestScalarSummaryOp(&tags, &values, R"( value { tag: 'tag1' simple_value: 1.0 } value { tag: 'tag2' simple_value: -0.73} value { tag: 'tag3' simple_value: 10000.0})", error::OK); } TEST(ScalarSummaryOpTest, SimpleDouble) { int vectorSize = 3; Tensor tags(DT_STRING, {vectorSize}); Tensor values(DT_DOUBLE, {vectorSize}); tags.vec()(0) = "tag1"; tags.vec()(1) = "tag2"; tags.vec()(2) = "tag3"; values.vec()(0) = 1.0; values.vec()(1) = -0.73; values.vec()(2) = 10000.0; TestScalarSummaryOp(&tags, &values, R"( value { tag: 'tag1' simple_value: 1.0 } value { tag: 'tag2' simple_value: -0.73} value { tag: 'tag3' simple_value: 10000.0})", error::OK); } TEST(ScalarSummaryOpTest, SimpleHalf) { int vectorSize = 3; Tensor tags(DT_STRING, {vectorSize}); Tensor values(DT_HALF, {vectorSize}); tags.vec()(0) = "tag1"; tags.vec()(1) = "tag2"; tags.vec()(2) = "tag3"; values.vec()(0) = Eigen::half(1.0); values.vec()(1) = Eigen::half(-2.0); values.vec()(2) = Eigen::half(10000.0); TestScalarSummaryOp(&tags, &values, R"( value { tag: 'tag1' simple_value: 1.0 } value { tag: 'tag2' simple_value: -2.0} value { tag: 'tag3' simple_value: 10000.0})", error::OK); } TEST(ScalarSummaryOpTest, Error_WrongDimsTags) { Tensor tags(DT_STRING, {2, 1}); Tensor values(DT_FLOAT, {2}); tags.matrix()(0, 0) = "tag1"; tags.matrix()(1, 0) = "tag2"; values.vec()(0) = 1.0f; values.vec()(1) = -2.0f; TestScalarSummaryOp(&tags, &values, "tags and values are not the same shape", error::INVALID_ARGUMENT); } TEST(ScalarSummaryOpTest, Error_WrongValuesTags) { Tensor tags(DT_STRING, {2}); Tensor values(DT_FLOAT, {2, 1}); tags.vec()(0) = "tag1"; tags.vec()(1) = "tag2"; values.matrix()(0, 0) = 1.0f; values.matrix()(1, 0) = -2.0f; TestScalarSummaryOp(&tags, &values, "tags and values are not the same shape", error::INVALID_ARGUMENT); } TEST(ScalarSummaryOpTest, Error_WrongWithSingleTag) { Tensor tags(DT_STRING, {1}); Tensor values(DT_FLOAT, {2, 1}); tags.vec()(0) = "tag1"; values.matrix()(0, 0) = 1.0f; values.matrix()(1, 0) = -2.0f; TestScalarSummaryOp(&tags, &values, "tags and values are not the same shape", error::INVALID_ARGUMENT); } TEST(ScalarSummaryOpTest, IsRegistered) { const OpRegistrationData* reg; TF_CHECK_OK(OpRegistry::Global()->LookUp("ScalarSummary", ®)); } } // namespace } // namespace tensorflow