-
Notifications
You must be signed in to change notification settings - Fork 74k
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Retain model metadata for 'reduced_precision_support' when sparsifying.
PiperOrigin-RevId: 495775017
- Loading branch information
1 parent
0d19180
commit cb23291
Showing
4 changed files
with
124 additions
and
4 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
87 changes: 87 additions & 0 deletions
87
tensorflow/compiler/mlir/lite/sparsity/sparsify_model_test.cc
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,87 @@ | ||
| /* Copyright 2022 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/compiler/mlir/lite/sparsity/sparsify_model.h" | ||
|
|
||
| #include <stdint.h> | ||
|
|
||
| #include <cstdarg> | ||
| #include <map> | ||
| #include <memory> | ||
| #include <string> | ||
| #include <utility> | ||
| #include <vector> | ||
|
|
||
| #include <gmock/gmock.h> | ||
| #include <gtest/gtest.h> | ||
| #include "flatbuffers/flatbuffer_builder.h" // from @flatbuffers | ||
| #include "tensorflow/lite/core/api/error_reporter.h" | ||
| #include "tensorflow/lite/core/c/c_api_types.h" | ||
| #include "tensorflow/lite/core/model_builder.h" | ||
| #include "tensorflow/lite/schema/schema_generated.h" | ||
| #include "tensorflow/lite/tools/optimize/reduced_precision_support.h" | ||
|
|
||
| namespace mlir { | ||
| namespace lite { | ||
| namespace { | ||
|
|
||
| class NoopErrorReporter : public ::tflite::ErrorReporter { | ||
| public: | ||
| int Report(const char* format, std::va_list args) override { return 0; } | ||
| }; | ||
|
|
||
| TEST(SparsifyModelTest, MetadataIsAddedToOutputModel) { | ||
| std::string expected_key = tflite::optimize::kTfLiteReducedPrecisionKey; | ||
| std::string expected_value = "test_data"; | ||
|
|
||
| // Load input model | ||
| auto input_fbm = tflite::FlatBufferModel::BuildFromFile( | ||
| "tensorflow/lite/testdata/sparse_tensor.bin"); | ||
| tflite::ModelT input_model; | ||
| input_fbm->GetModel()->UnPackTo(&input_model); | ||
|
|
||
| // Populate input metadata | ||
| auto model_metadata_buffer = std::make_unique<tflite::BufferT>(); | ||
| model_metadata_buffer->data = | ||
| std::vector<uint8_t>(expected_value.begin(), expected_value.end()); | ||
| input_model.buffers.push_back(std::move(model_metadata_buffer)); | ||
| auto metadata_t = std::make_unique<tflite::MetadataT>(); | ||
| metadata_t->name = tflite::optimize::kTfLiteReducedPrecisionKey; | ||
| metadata_t->buffer = input_model.buffers.size() - 1; | ||
| input_model.metadata.push_back(std::move(metadata_t)); | ||
|
|
||
| // Sparsify and create output model | ||
| flatbuffers::FlatBufferBuilder output_builder; | ||
| NoopErrorReporter reporter; | ||
| ASSERT_EQ(SparsifyModel(input_model, &output_builder, &reporter), kTfLiteOk); | ||
| auto output_fbm = tflite::FlatBufferModel::BuildFromBuffer( | ||
| reinterpret_cast<const char*>(output_builder.GetCurrentBufferPointer()), | ||
| output_builder.GetSize()); | ||
| tflite::ModelT output_model; | ||
| output_fbm->GetModel()->UnPackTo(&output_model); | ||
|
|
||
| // Extract output metadata | ||
| std::map<std::string, std::string> output_metadata; | ||
| for (const auto& metadata : output_model.metadata) { | ||
| const auto& data = output_model.buffers[metadata->buffer]->data; | ||
| output_metadata[metadata->name] = std::string(data.begin(), data.end()); | ||
| } | ||
|
|
||
| EXPECT_THAT(output_metadata, | ||
| testing::Contains(testing::Pair(expected_key, expected_value))); | ||
| } | ||
|
|
||
| } // namespace | ||
| } // namespace lite | ||
| } // namespace mlir |