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5f923cd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 | // Copyright 2025 The ODML Authors.
//
// 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 "runtime/components/preprocessor/audio_preprocessor.h"
#include <cstddef>
#include <memory>
#include <utility>
#include <vector>
#include <gmock/gmock.h>
#include <gtest/gtest.h>
#include "absl/status/statusor.h" // from @com_google_absl
#include "absl/types/span.h" // from @com_google_absl
#include "litert/cc/litert_layout.h" // from @litert
#include "litert/cc/litert_tensor_buffer.h" // from @litert
#include "litert/test/matchers.h" // from @litert
#include "runtime/engine/io_types.h"
#include "runtime/util/convert_tensor_buffer.h"
#include "runtime/util/test_utils.h" // NOLINT
namespace litert::lm {
namespace {
using ::litert::Dimensions;
using ::testing::Return;
// Mock implementation of AudioPreprocessor for testing.
class MockAudioPreprocessor : public AudioPreprocessor {
public:
MOCK_METHOD(absl::StatusOr<InputAudio>, Preprocess,
(const InputAudio& input_audio), (override));
MOCK_METHOD(void, Reset, (), (override));
};
TEST(AudioPreprocessorTest, Preprocess) {
auto mock_preprocessor = std::make_unique<MockAudioPreprocessor>();
// Create a dummy InputAudio for the input. The content doesn't matter for
// the mock.
std::vector<float> dummy_input_data(1 * 10 * 128, 0.0f);
LITERT_ASSERT_OK_AND_ASSIGN(
TensorBuffer dummy_input_tensor_buffer,
CopyToTensorBuffer<float>(dummy_input_data, {1, 10, 128}));
InputAudio test_input_audio(std::move(dummy_input_tensor_buffer));
// Create a dummy TensorBuffer to be returned *inside* the InputAudio.
// We'll use a float tensor of size {1, 100, 128} as a common audio feature
// shape (e.g., 100 time frames, 128 mel bins).
std::vector<float> dummy_data(1 * 100 * 128, 0.1f);
LITERT_ASSERT_OK_AND_ASSIGN(
TensorBuffer expected_tensor_buffer,
CopyToTensorBuffer<float>(dummy_data, {1, 100, 128}));
InputAudio expected_output_audio(std::move(expected_tensor_buffer));
// Set up the mock expectation.
EXPECT_CALL(*mock_preprocessor,
Preprocess(testing::Ref(
test_input_audio))) // Match the specific test_input_audio
.WillOnce(Return(std::move(expected_output_audio)));
// Call the Preprocess method.
absl::StatusOr<InputAudio> result =
mock_preprocessor->Preprocess(test_input_audio);
// Assert that the result is OK.
ASSERT_OK(result);
// Get the TensorBuffer from the result InputAudio.
LITERT_ASSERT_OK_AND_ASSIGN(auto result_tensor_buffer,
result->GetPreprocessedAudioTensor());
// Verify the dimensions and content of the returned TensorBuffer.
LITERT_ASSERT_OK_AND_ASSIGN(auto tensor_type,
result_tensor_buffer->TensorType());
EXPECT_EQ(tensor_type.Layout().Dimensions(), Dimensions({1, 100, 128}));
// Confirm the data in the result tensor buffer matches the dummy data.
auto output_tensor_lock_and_addr = ::litert::TensorBufferScopedLock::Create(
*result_tensor_buffer, TensorBuffer::LockMode::kRead);
ASSERT_TRUE(output_tensor_lock_and_addr.HasValue());
const float* result_data =
static_cast<const float*>(output_tensor_lock_and_addr->second);
ASSERT_NE(result_data, nullptr);
size_t num_elements = 1 * 100 * 128;
EXPECT_THAT(absl::MakeConstSpan(result_data, num_elements),
testing::ElementsAreArray(dummy_data));
}
} // namespace
} // namespace litert::lm
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