| /* Copyright 2015 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 <functional> |
| #include <memory> |
| |
| #include "tensorflow/core/framework/allocator.h" |
| #include "tensorflow/core/framework/fake_input.h" |
| #include "tensorflow/core/framework/node_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/framework/types.pb.h" |
| #include "tensorflow/core/kernels/ops_testutil.h" |
| #include "tensorflow/core/kernels/ops_util.h" |
| #include "tensorflow/core/lib/core/status_test_util.h" |
| #include "tensorflow/core/lib/histogram/histogram.h" |
| #include "tensorflow/core/lib/strings/str_util.h" |
| #include "tensorflow/core/lib/strings/strcat.h" |
| #include "tensorflow/core/platform/env.h" |
| #include "tensorflow/core/platform/logging.h" |
| #include "tensorflow/core/platform/protobuf.h" |
| #include "tensorflow/core/platform/test.h" |
| |
| namespace tensorflow { |
| namespace { |
| |
| static void EXPECT_SummaryMatches(const Summary& actual, |
| const string& expected_str) { |
| Summary expected; |
| CHECK(protobuf::TextFormat::ParseFromString(expected_str, &expected)); |
| EXPECT_EQ(expected.DebugString(), actual.DebugString()); |
| } |
| |
| class SummaryScalarOpTest : public OpsTestBase { |
| protected: |
| void MakeOp(DataType dt) { |
| TF_ASSERT_OK(NodeDefBuilder("myop", "ScalarSummary") |
| .Input(FakeInput()) |
| .Input(FakeInput(dt)) |
| .Finalize(node_def())); |
| TF_ASSERT_OK(InitOp()); |
| } |
| }; |
| |
| TEST_F(SummaryScalarOpTest, SimpleFloat) { |
| MakeOp(DT_FLOAT); |
| |
| // Feed and run |
| AddInputFromArray<string>(TensorShape({3}), {"tag1", "tag2", "tag3"}); |
| AddInputFromArray<float>(TensorShape({3}), {1.0f, -0.73f, 10000.0f}); |
| TF_ASSERT_OK(RunOpKernel()); |
| |
| // Check the output size. |
| Tensor* out_tensor = GetOutput(0); |
| ASSERT_EQ(0, out_tensor->dims()); |
| Summary summary; |
| ParseProtoUnlimited(&summary, out_tensor->scalar<string>()()); |
| EXPECT_SummaryMatches(summary, R"( |
| value { tag: 'tag1' simple_value: 1.0 } |
| value { tag: 'tag2' simple_value: -0.73 } |
| value { tag: 'tag3' simple_value: 10000.0 } |
| )"); |
| } |
| |
| TEST_F(SummaryScalarOpTest, SimpleDouble) { |
| MakeOp(DT_DOUBLE); |
| |
| // Feed and run |
| AddInputFromArray<string>(TensorShape({3}), {"tag1", "tag2", "tag3"}); |
| AddInputFromArray<double>(TensorShape({3}), {1.0, -0.73, 10000.0}); |
| TF_ASSERT_OK(RunOpKernel()); |
| |
| // Check the output size. |
| Tensor* out_tensor = GetOutput(0); |
| ASSERT_EQ(0, out_tensor->dims()); |
| Summary summary; |
| ParseProtoUnlimited(&summary, out_tensor->scalar<tstring>()()); |
| EXPECT_SummaryMatches(summary, R"( |
| value { tag: 'tag1' simple_value: 1.0 } |
| value { tag: 'tag2' simple_value: -0.73 } |
| value { tag: 'tag3' simple_value: 10000.0 } |
| )"); |
| } |
| |
| TEST_F(SummaryScalarOpTest, SimpleHalf) { |
| MakeOp(DT_HALF); |
| |
| // Feed and run |
| AddInputFromList<tstring>(TensorShape({3}), {"tag1", "tag2", "tag3"}); |
| AddInputFromList<Eigen::half>(TensorShape({3}), {1.0, -2.0, 10000.0}); |
| TF_ASSERT_OK(RunOpKernel()); |
| |
| // Check the output size. |
| Tensor* out_tensor = GetOutput(0); |
| ASSERT_EQ(0, out_tensor->dims()); |
| Summary summary; |
| ParseProtoUnlimited(&summary, out_tensor->scalar<tstring>()()); |
| EXPECT_SummaryMatches(summary, R"( |
| value { tag: 'tag1' simple_value: 1.0 } |
| value { tag: 'tag2' simple_value: -2.0 } |
| value { tag: 'tag3' simple_value: 10000.0 } |
| )"); |
| } |
| |
| TEST_F(SummaryScalarOpTest, Error_MismatchedSize) { |
| MakeOp(DT_FLOAT); |
| |
| // Feed and run |
| AddInputFromArray<string>(TensorShape({2}), {"tag1", "tag2"}); |
| AddInputFromArray<float>(TensorShape({3}), {1.0f, -0.73f, 10000.0f}); |
| Status s = RunOpKernel(); |
| EXPECT_TRUE(absl::StrContains(s.ToString(), "not the same shape")) << s; |
| } |
| |
| TEST_F(SummaryScalarOpTest, Error_WrongDimsTags) { |
| MakeOp(DT_FLOAT); |
| |
| // Feed and run |
| AddInputFromArray<string>(TensorShape({2, 1}), {"tag1", "tag2"}); |
| AddInputFromArray<float>(TensorShape({2}), {1.0f, -0.73f}); |
| Status s = RunOpKernel(); |
| EXPECT_TRUE( |
| absl::StrContains(s.ToString(), "tags and values not the same shape")) |
| << s; |
| } |
| |
| TEST_F(SummaryScalarOpTest, Error_WrongDimsValues) { |
| MakeOp(DT_FLOAT); |
| |
| // Feed and run |
| AddInputFromArray<string>(TensorShape({2}), {"tag1", "tag2"}); |
| AddInputFromArray<float>(TensorShape({2, 1}), {1.0f, -0.73f}); |
| Status s = RunOpKernel(); |
| EXPECT_TRUE( |
| absl::StrContains(s.ToString(), "tags and values not the same shape")) |
| << s; |
| } |
| |
| // -------------------------------------------------------------------------- |
| // SummaryHistoOp |
| // -------------------------------------------------------------------------- |
| class SummaryHistoOpTest : public OpsTestBase { |
| protected: |
| void MakeOp(DataType dt) { |
| TF_ASSERT_OK(NodeDefBuilder("myop", "HistogramSummary") |
| .Input(FakeInput()) |
| .Input(FakeInput(dt)) |
| .Finalize(node_def())); |
| TF_ASSERT_OK(InitOp()); |
| } |
| }; |
| |
| TEST_F(SummaryHistoOpTest, SimpleFloat) { |
| MakeOp(DT_FLOAT); |
| |
| // Feed and run |
| AddInputFromArray<string>(TensorShape({}), {"taghisto"}); |
| AddInputFromArray<float>(TensorShape({3, 2}), |
| {0.1f, -0.7f, 4.1f, 4., 5.f, 4.f}); |
| TF_ASSERT_OK(RunOpKernel()); |
| |
| // Check the output size. |
| Tensor* out_tensor = GetOutput(0); |
| ASSERT_EQ(0, out_tensor->dims()); |
| Summary summary; |
| ParseProtoUnlimited(&summary, out_tensor->scalar<tstring>()()); |
| ASSERT_EQ(summary.value_size(), 1); |
| EXPECT_EQ(summary.value(0).tag(), "taghisto"); |
| histogram::Histogram histo; |
| EXPECT_TRUE(histo.DecodeFromProto(summary.value(0).histo())); |
| EXPECT_EQ( |
| "Count: 6 Average: 2.7500 StdDev: 2.20\n" |
| "Min: -0.7000 Median: 3.9593 Max: 5.0000\n" |
| "------------------------------------------------------\n" |
| "[ -0.76, -0.69 ) 1 16.667% 16.667% ###\n" |
| "[ 0.093, 0.1 ) 1 16.667% 33.333% ###\n" |
| "[ 3.8, 4.2 ) 3 50.000% 83.333% ##########\n" |
| "[ 4.6, 5.1 ) 1 16.667% 100.000% ###\n", |
| histo.ToString()); |
| } |
| |
| TEST_F(SummaryHistoOpTest, SimpleDouble) { |
| MakeOp(DT_DOUBLE); |
| |
| // Feed and run |
| AddInputFromArray<string>(TensorShape({}), {"taghisto"}); |
| AddInputFromArray<double>(TensorShape({3, 2}), {0.1, -0.7, 4.1, 4., 5., 4.}); |
| TF_ASSERT_OK(RunOpKernel()); |
| |
| // Check the output size. |
| Tensor* out_tensor = GetOutput(0); |
| ASSERT_EQ(0, out_tensor->dims()); |
| Summary summary; |
| ParseProtoUnlimited(&summary, out_tensor->scalar<tstring>()()); |
| ASSERT_EQ(summary.value_size(), 1); |
| EXPECT_EQ(summary.value(0).tag(), "taghisto"); |
| histogram::Histogram histo; |
| EXPECT_TRUE(histo.DecodeFromProto(summary.value(0).histo())); |
| EXPECT_EQ( |
| "Count: 6 Average: 2.7500 StdDev: 2.20\n" |
| "Min: -0.7000 Median: 3.9593 Max: 5.0000\n" |
| "------------------------------------------------------\n" |
| "[ -0.76, -0.69 ) 1 16.667% 16.667% ###\n" |
| "[ 0.093, 0.1 ) 1 16.667% 33.333% ###\n" |
| "[ 3.8, 4.2 ) 3 50.000% 83.333% ##########\n" |
| "[ 4.6, 5.1 ) 1 16.667% 100.000% ###\n", |
| histo.ToString()); |
| } |
| |
| TEST_F(SummaryHistoOpTest, SimpleHalf) { |
| MakeOp(DT_HALF); |
| |
| // Feed and run |
| AddInputFromList<string>(TensorShape({}), {"taghisto"}); |
| AddInputFromList<Eigen::half>(TensorShape({3, 2}), |
| {0.1, -0.7, 4.1, 4., 5., 4.}); |
| TF_ASSERT_OK(RunOpKernel()); |
| |
| // Check the output size. |
| Tensor* out_tensor = GetOutput(0); |
| ASSERT_EQ(0, out_tensor->dims()); |
| Summary summary; |
| ParseProtoUnlimited(&summary, out_tensor->scalar<tstring>()()); |
| ASSERT_EQ(summary.value_size(), 1); |
| EXPECT_EQ(summary.value(0).tag(), "taghisto"); |
| histogram::Histogram histo; |
| EXPECT_TRUE(histo.DecodeFromProto(summary.value(0).histo())); |
| EXPECT_EQ( |
| "Count: 6 Average: 2.7502 StdDev: 2.20\n" |
| "Min: -0.7002 Median: 3.9593 Max: 5.0000\n" |
| "------------------------------------------------------\n" |
| "[ -0.76, -0.69 ) 1 16.667% 16.667% ###\n" |
| "[ 0.093, 0.1 ) 1 16.667% 33.333% ###\n" |
| "[ 3.8, 4.2 ) 3 50.000% 83.333% ##########\n" |
| "[ 4.6, 5.1 ) 1 16.667% 100.000% ###\n", |
| histo.ToString()); |
| } |
| |
| TEST_F(SummaryHistoOpTest, Error_WrongDimsTags) { |
| MakeOp(DT_FLOAT); |
| |
| // Feed and run |
| AddInputFromArray<string>(TensorShape({2, 1}), {"tag1", "tag2"}); |
| AddInputFromArray<float>(TensorShape({2}), {1.0f, -0.73f}); |
| Status s = RunOpKernel(); |
| EXPECT_TRUE(absl::StrContains(s.ToString(), "tags must be scalar")) << s; |
| } |
| |
| TEST_F(SummaryHistoOpTest, Error_TooManyTagValues) { |
| MakeOp(DT_FLOAT); |
| |
| // Feed and run |
| AddInputFromArray<string>(TensorShape({2}), {"tag1", "tag2"}); |
| AddInputFromArray<float>(TensorShape({2, 1}), {1.0f, -0.73f}); |
| Status s = RunOpKernel(); |
| EXPECT_TRUE(absl::StrContains(s.ToString(), "tags must be scalar")) << s; |
| } |
| |
| // -------------------------------------------------------------------------- |
| // SummaryMergeOp |
| // -------------------------------------------------------------------------- |
| class SummaryMergeOpTest : public OpsTestBase { |
| protected: |
| void MakeOp(int num_inputs) { |
| TF_ASSERT_OK(NodeDefBuilder("myop", "MergeSummary") |
| .Input(FakeInput(num_inputs)) |
| .Finalize(node_def())); |
| TF_ASSERT_OK(InitOp()); |
| } |
| }; |
| |
| TEST_F(SummaryMergeOpTest, Simple) { |
| MakeOp(1); |
| |
| // Feed and run |
| Summary s1; |
| ASSERT_TRUE(protobuf::TextFormat::ParseFromString( |
| "value { tag: \"tag1\" simple_value: 1.0 } " |
| "value { tag: \"tag2\" simple_value: -0.73 } ", |
| &s1)); |
| Summary s2; |
| ASSERT_TRUE(protobuf::TextFormat::ParseFromString( |
| "value { tag: \"tag3\" simple_value: 10000.0 }", &s2)); |
| Summary s3; |
| ASSERT_TRUE(protobuf::TextFormat::ParseFromString( |
| "value { tag: \"tag4\" simple_value: 11.0 }", &s3)); |
| |
| AddInputFromArray<string>( |
| TensorShape({3}), |
| {s1.SerializeAsString(), s2.SerializeAsString(), s3.SerializeAsString()}); |
| TF_ASSERT_OK(RunOpKernel()); |
| |
| // Check the output size. |
| Tensor* out_tensor = GetOutput(0); |
| ASSERT_EQ(0, out_tensor->dims()); |
| Summary summary; |
| ParseProtoUnlimited(&summary, out_tensor->scalar<tstring>()()); |
| |
| EXPECT_SummaryMatches(summary, |
| "value { tag: \"tag1\" simple_value: 1.0 } " |
| "value { tag: \"tag2\" simple_value: -0.73 } " |
| "value { tag: \"tag3\" simple_value: 10000.0 }" |
| "value { tag: \"tag4\" simple_value: 11.0 }"); |
| } |
| |
| TEST_F(SummaryMergeOpTest, Simple_MultipleInputs) { |
| MakeOp(3); |
| |
| // Feed and run |
| Summary s1; |
| ASSERT_TRUE(protobuf::TextFormat::ParseFromString( |
| "value { tag: \"tag1\" simple_value: 1.0 } " |
| "value { tag: \"tag2\" simple_value: -0.73 } ", |
| &s1)); |
| Summary s2; |
| ASSERT_TRUE(protobuf::TextFormat::ParseFromString( |
| "value { tag: \"tag3\" simple_value: 10000.0 }", &s2)); |
| Summary s3; |
| ASSERT_TRUE(protobuf::TextFormat::ParseFromString( |
| "value { tag: \"tag4\" simple_value: 11.0 }", &s3)); |
| |
| AddInputFromArray<string>(TensorShape({}), {s1.SerializeAsString()}); |
| AddInputFromArray<string>(TensorShape({}), {s2.SerializeAsString()}); |
| AddInputFromArray<string>(TensorShape({}), {s3.SerializeAsString()}); |
| TF_ASSERT_OK(RunOpKernel()); |
| |
| // Check the output size. |
| Tensor* out_tensor = GetOutput(0); |
| ASSERT_EQ(0, out_tensor->dims()); |
| Summary summary; |
| ParseProtoUnlimited(&summary, out_tensor->scalar<tstring>()()); |
| |
| EXPECT_SummaryMatches(summary, |
| "value { tag: \"tag1\" simple_value: 1.0 } " |
| "value { tag: \"tag2\" simple_value: -0.73 } " |
| "value { tag: \"tag3\" simple_value: 10000.0 }" |
| "value { tag: \"tag4\" simple_value: 11.0 }"); |
| } |
| |
| TEST_F(SummaryMergeOpTest, Error_MismatchedSize) { |
| MakeOp(1); |
| |
| // Feed and run |
| Summary s1; |
| ASSERT_TRUE(protobuf::TextFormat::ParseFromString( |
| "value { tag: \"tag1\" simple_value: 1.0 } " |
| "value { tag: \"tagduplicate\" simple_value: -0.73 } ", |
| &s1)); |
| Summary s2; |
| ASSERT_TRUE(protobuf::TextFormat::ParseFromString( |
| "value { tag: \"tagduplicate\" simple_value: 1.0 } ", &s2)); |
| AddInputFromArray<string>(TensorShape({2}), |
| {s1.SerializeAsString(), s2.SerializeAsString()}); |
| Status s = RunOpKernel(); |
| EXPECT_TRUE(absl::StrContains(s.ToString(), "Duplicate tag")) << s; |
| } |
| |
| } // namespace |
| } // namespace tensorflow |
