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Internal change.

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PiperOrigin-RevId: 501136760
This commit is contained in:
Nikolay Chirkov 2023-01-10 17:35:57 -08:00 committed by Copybara-Service
parent e869e57cb4
commit 54268594dd
2 changed files with 522 additions and 0 deletions
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240
mediapipe/framework/formats/tensor/cpu_buffer_converters.cc Normal file
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#include <algorithm>
#include <memory>
#include <vector>
#include "mediapipe/framework/formats/tensor/backend.h"
#include "mediapipe/framework/formats/tensor/tensor2.h"
#include "mediapipe/framework/formats/tensor/views/buffer.h"
#include "mediapipe/framework/formats/tensor/views/cpu_buffer.h"
#include "third_party/FP16/include/fp16.h"
namespace mediapipe {
namespace {
template <class SourceType, class DestinationType>
auto ConverterCheckFunction() {
return
[](const Tensor2& tensor, uint64_t source_descriptor_type_id,
const Tensor2::ViewDescriptor& source_base_descriptor,
uint64_t destination_descriptor_type_id,
const Tensor2::ViewDescriptor& destination_base_descriptor) -> bool {
if (source_descriptor_type_id != TensorCpuView::kId ||
destination_descriptor_type_id != TensorCpuView::kId)
return false;
auto source_descriptor =
static_cast<const TensorCpuViewDescriptor&>(source_base_descriptor);
auto destination_descriptor =
static_cast<const TensorCpuViewDescriptor&>(
destination_base_descriptor);
return source_descriptor.buffer.format ==
TensorTypeToFormat<SourceType>::value &&
destination_descriptor.buffer.format ==
TensorTypeToFormat<DestinationType>::value;
};
}
template <class SourceType, class DestinationType>
auto ConvertFunction() {
return [](const Tensor2& tensor, const Tensor2::View& source_base_view,
const Tensor2::View& destination_base_view) -> bool {
auto source = source_base_view.DownCast<TensorCpuView>();
auto destination = destination_base_view.DownCast<TensorCpuView>();
if (source->descriptor().buffer.format ==
destination->descriptor().buffer.format) {
std::memcpy(
destination->data<void>(), source->data<void>(),
TensorBufferSize(destination->descriptor().buffer, tensor.shape()));
} else {
auto source_pointer = source->data<SourceType>();
auto destination_pointer = destination->data<DestinationType>();
for (int i = 0; i < tensor.shape().NumElements(); i++) {
*destination_pointer++ =
GpuLikeTypeCast<DestinationType>(*source_pointer++);
}
}
return true;
};
}
#define REGISTER_CONVERTER(SourceType, DestinationType) \
TENSOR_REGISTER_CONVERTER( \
{ConverterCheckFunction<SourceType, DestinationType>(), \
ConvertFunction<SourceType, DestinationType>()});
REGISTER_CONVERTER(float, Float16);
REGISTER_CONVERTER(float, int8_t);
REGISTER_CONVERTER(float, uint8_t);
REGISTER_CONVERTER(float, int16_t);
REGISTER_CONVERTER(float, uint16_t);
REGISTER_CONVERTER(float, int32_t);
REGISTER_CONVERTER(float, uint32_t);
REGISTER_CONVERTER(Float16, float);
REGISTER_CONVERTER(Float16, int8_t);
REGISTER_CONVERTER(Float16, uint8_t);
REGISTER_CONVERTER(Float16, int16_t);
REGISTER_CONVERTER(Float16, uint16_t);
REGISTER_CONVERTER(Float16, int32_t);
REGISTER_CONVERTER(Float16, uint32_t);
REGISTER_CONVERTER(int8_t, float);
REGISTER_CONVERTER(int8_t, Float16);
REGISTER_CONVERTER(int8_t, uint8_t);
REGISTER_CONVERTER(int8_t, int16_t);
REGISTER_CONVERTER(int8_t, uint16_t);
REGISTER_CONVERTER(int8_t, int32_t);
REGISTER_CONVERTER(int8_t, uint32_t);
REGISTER_CONVERTER(uint8_t, float);
REGISTER_CONVERTER(uint8_t, Float16);
REGISTER_CONVERTER(uint8_t, int8_t);
REGISTER_CONVERTER(uint8_t, int16_t);
REGISTER_CONVERTER(uint8_t, uint16_t);
REGISTER_CONVERTER(uint8_t, int32_t);
REGISTER_CONVERTER(uint8_t, uint32_t);
REGISTER_CONVERTER(int16_t, float);
REGISTER_CONVERTER(int16_t, Float16);
REGISTER_CONVERTER(int16_t, int8_t);
REGISTER_CONVERTER(int16_t, uint8_t);
REGISTER_CONVERTER(int16_t, uint16_t);
REGISTER_CONVERTER(int16_t, uint32_t);
REGISTER_CONVERTER(int16_t, uint32_t);
REGISTER_CONVERTER(uint16_t, float);
REGISTER_CONVERTER(uint16_t, Float16);
REGISTER_CONVERTER(uint16_t, int8_t);
REGISTER_CONVERTER(uint16_t, uint8_t);
REGISTER_CONVERTER(uint16_t, int16_t);
REGISTER_CONVERTER(uint16_t, int32_t);
REGISTER_CONVERTER(uint16_t, uint32_t);
REGISTER_CONVERTER(int32_t, float);
REGISTER_CONVERTER(int32_t, Float16);
REGISTER_CONVERTER(int32_t, int8_t);
REGISTER_CONVERTER(int32_t, uint8_t);
REGISTER_CONVERTER(int32_t, int16_t);
REGISTER_CONVERTER(int32_t, uint16_t);
REGISTER_CONVERTER(int32_t, uint32_t);
REGISTER_CONVERTER(uint32_t, float);
REGISTER_CONVERTER(uint32_t, Float16);
REGISTER_CONVERTER(uint32_t, int8_t);
REGISTER_CONVERTER(uint32_t, uint8_t);
REGISTER_CONVERTER(uint32_t, int16_t);
REGISTER_CONVERTER(uint32_t, uint16_t);
REGISTER_CONVERTER(uint32_t, int32_t);
template <class DestinationType>
auto DequantizationCheckFunction() {
return
[](const Tensor2& tensor, uint64_t source_descriptor_type_id,
const Tensor2::ViewDescriptor& source_base_descriptor,
uint64_t destination_descriptor_type_id,
const Tensor2::ViewDescriptor& destination_base_descriptor) -> bool {
if (source_descriptor_type_id != TensorCpuView::kId ||
destination_descriptor_type_id != TensorCpuView::kId)
return false;
auto source_descriptor =
static_cast<const TensorCpuViewDescriptor&>(source_base_descriptor);
auto destination_descriptor =
static_cast<const TensorCpuViewDescriptor&>(
destination_base_descriptor);
return source_descriptor.buffer.format ==
TensorBufferDescriptor::Format::kQuantizedInt8 &&
destination_descriptor.buffer.format ==
TensorTypeToFormat<DestinationType>::value;
};
}
template <class DestinationType>
auto DequantizationConvertFunction() {
return [](const Tensor2& tensor, const Tensor2::View& source_base_view,
const Tensor2::View& destination_base_view) -> bool {
auto source = source_base_view.DownCast<TensorCpuView>();
auto destination = destination_base_view.DownCast<TensorCpuView>();
auto source_pointer = source->data<int8_t>();
auto destination_pointer = destination->data<DestinationType>();
int zero_point =
source->descriptor().buffer.quantization_parameters.zero_point;
float scale = source->descriptor().buffer.quantization_parameters.scale;
for (int i = 0; i < tensor.shape().NumElements(); i++) {
*destination_pointer++ = static_cast<DestinationType>(
(*source_pointer++ - zero_point) * scale);
}
return true;
};
}
#define REGISTER_DEQUANTIZATION_CONVERTER(DestinationType) \
TENSOR_REGISTER_CONVERTER( \
{DequantizationCheckFunction<DestinationType>(), \
DequantizationConvertFunction<DestinationType>()});
REGISTER_DEQUANTIZATION_CONVERTER(float);
REGISTER_DEQUANTIZATION_CONVERTER(Float16);
REGISTER_DEQUANTIZATION_CONVERTER(int8_t);
REGISTER_DEQUANTIZATION_CONVERTER(uint8_t);
REGISTER_DEQUANTIZATION_CONVERTER(int16_t);
REGISTER_DEQUANTIZATION_CONVERTER(uint16_t);
REGISTER_DEQUANTIZATION_CONVERTER(int32_t);
REGISTER_DEQUANTIZATION_CONVERTER(uint32_t);
template <class SourceType>
auto QuantizationCheckFunction() {
return
[](const Tensor2& tensor, uint64_t source_descriptor_type_id,
const Tensor2::ViewDescriptor& source_base_descriptor,
uint64_t destination_descriptor_type_id,
const Tensor2::ViewDescriptor& destination_base_descriptor) -> bool {
if (source_descriptor_type_id != TensorCpuView::kId ||
destination_descriptor_type_id != TensorCpuView::kId)
return false;
auto source_descriptor =
static_cast<const TensorCpuViewDescriptor&>(source_base_descriptor);
auto destination_descriptor =
static_cast<const TensorCpuViewDescriptor&>(
destination_base_descriptor);
bool same = source_descriptor.buffer.format ==
TensorTypeToFormat<SourceType>::value &&
destination_descriptor.buffer.format ==
TensorBufferDescriptor::Format::kQuantizedInt8;
return same;
};
}
template <class SourceType>
auto QuantizationConvertFunction() {
return [](const Tensor2& tensor, const Tensor2::View& source_base_view,
const Tensor2::View& destination_base_view) -> bool {
auto source = source_base_view.DownCast<TensorCpuView>();
auto destination = destination_base_view.DownCast<TensorCpuView>();
auto source_pointer = source->data<SourceType>();
auto destination_pointer = destination->data<int8_t>();
int zero_point =
destination->descriptor().buffer.quantization_parameters.zero_point;
float scale =
destination->descriptor().buffer.quantization_parameters.scale;
for (int i = 0; i < tensor.shape().NumElements(); i++) {
*destination_pointer++ =
static_cast<int8_t>(*source_pointer++ / scale + zero_point);
}
return true;
};
}
#define REGISTER_QUANTIZATION_CONVERTER(SourceType) \
TENSOR_REGISTER_CONVERTER({QuantizationCheckFunction<SourceType>(), \
QuantizationConvertFunction<SourceType>()});
REGISTER_QUANTIZATION_CONVERTER(float);
REGISTER_QUANTIZATION_CONVERTER(Float16);
REGISTER_QUANTIZATION_CONVERTER(int8_t);
REGISTER_QUANTIZATION_CONVERTER(uint8_t);
REGISTER_QUANTIZATION_CONVERTER(int16_t);
REGISTER_QUANTIZATION_CONVERTER(uint16_t);
REGISTER_QUANTIZATION_CONVERTER(int32_t);
REGISTER_QUANTIZATION_CONVERTER(uint32_t);
} // namespace
} // namespace mediapipe

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mediapipe/framework/formats/tensor/cpu_buffer_converters_test.cc Normal file
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#include <cstdint>
#include "mediapipe/framework/formats/tensor/tensor2.h"
#include "mediapipe/framework/formats/tensor/views/buffer.h"
#include "mediapipe/framework/formats/tensor/views/cpu_buffer.h"
#include "testing/base/public/gmock.h"
#include "testing/base/public/gunit.h"
MATCHER_P(NearWithPrecision, precision, "") {
return std::abs(std::get<0>(arg) - std::get<1>(arg)) < precision;
}
MATCHER_P(IntegerEqual, precision, "") {
return std::get<0>(arg) == std::get<1>(arg);
}
namespace mediapipe {
TEST(TensorCpuViewTest, TestWrite32ThenRead16) {
Tensor2 tensor{Tensor2::Shape({1})};
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kWriteOnly>(
TensorCpuViewDescriptor{
.buffer = {.format =
TensorBufferDescriptor::Format::kFloat32}}));
ASSERT_NE(view->data<void>(), nullptr);
*view->data<float>() = 1234.0f;
}
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kReadOnly>(
TensorCpuViewDescriptor{
.buffer = {.format =
TensorBufferDescriptor::Format::kFloat16}}));
ASSERT_NE(view->data<void>(), nullptr);
EXPECT_EQ(*view->data<Float16>(), 1234.0f);
}
}
TEST(TensorCpuViewTest, TestWrite16ThenRead32) {
Tensor2 tensor{Tensor2::Shape({1})};
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kWriteOnly>(
TensorCpuViewDescriptor{
.buffer = {.format =
TensorBufferDescriptor::Format::kFloat16}}));
ASSERT_NE(view->data<void>(), nullptr);
*view->data<Float16>() = 1234.0f;
}
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kReadOnly>(
TensorCpuViewDescriptor{
.buffer = {.format =
TensorBufferDescriptor::Format::kFloat32}}));
ASSERT_NE(view->data<void>(), nullptr);
EXPECT_EQ(*view->data<float>(), 1234.0f);
}
}
TEST(TensorCpuViewTest, TestWriteFloat32ThenReadInt8) {
Tensor2 tensor{Tensor2::Shape({1})};
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kWriteOnly>(
TensorCpuViewDescriptor{
.buffer = {.format =
TensorBufferDescriptor::Format::kFloat32}}));
ASSERT_NE(view->data<void>(), nullptr);
*view->data<float>() = 0.121569f;
}
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kReadOnly>(
TensorCpuViewDescriptor{
.buffer = {.format = TensorBufferDescriptor::Format::kUInt8}}));
ASSERT_NE(view->data<void>(), nullptr);
EXPECT_EQ(
*view->data<uint8_t>(),
static_cast<uint8_t>(0.121569f * std::numeric_limits<uint8_t>::max()));
}
}
TEST(TensorCpuViewTest, TestWriteInt8ThenReadFloat32) {
Tensor2 tensor{Tensor2::Shape({1})};
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kWriteOnly>(
TensorCpuViewDescriptor{
.buffer = {.format = TensorBufferDescriptor::Format::kUInt8}}));
ASSERT_NE(view->data<void>(), nullptr);
*view->data<uint8_t>() =
static_cast<uint8_t>(0.123f * std::numeric_limits<uint8_t>::max());
}
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kReadOnly>(
TensorCpuViewDescriptor{
.buffer = {.format =
TensorBufferDescriptor::Format::kFloat32}}));
ASSERT_NE(view->data<void>(), nullptr);
EXPECT_NEAR(*view->data<float>(), 0.123f,
1.0f / std::numeric_limits<uint8_t>::max());
}
}
TEST(TensorCpuViewTest, TestWriteUInt8ThenReadUInt16) {
Tensor2 tensor{Tensor2::Shape({1})};
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kWriteOnly>(
TensorCpuViewDescriptor{
.buffer = {.format = TensorBufferDescriptor::Format::kUInt8}}));
ASSERT_NE(view->data<void>(), nullptr);
*view->data<uint8_t>() = 123;
}
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kReadOnly>(
TensorCpuViewDescriptor{
.buffer = {.format =
TensorBufferDescriptor::Format::kUInt16}}));
ASSERT_NE(view->data<void>(), nullptr);
EXPECT_EQ(*view->data<uint16_t>(), uint16_t{123} << 8);
}
}
TEST(TensorCpuViewTest, TestWriteUInt16ThenReadUInt8) {
Tensor2 tensor{Tensor2::Shape({1})};
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kWriteOnly>(
TensorCpuViewDescriptor{
.buffer = {.format =
TensorBufferDescriptor::Format::kUInt16}}));
ASSERT_NE(view->data<void>(), nullptr);
*view->data<uint16_t>() = uint16_t{123} << 8;
}
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kReadOnly>(
TensorCpuViewDescriptor{
.buffer = {.format = TensorBufferDescriptor::Format::kUInt8}}));
ASSERT_NE(view->data<void>(), nullptr);
EXPECT_EQ(*view->data<uint8_t>(), 123);
}
}
TEST(TensorCpuViewTest, TestWriteNegativeInt8ThenReadUInt8) {
Tensor2 tensor{Tensor2::Shape({1})};
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kWriteOnly>(
TensorCpuViewDescriptor{
.buffer = {.format = TensorBufferDescriptor::Format::kInt8}}));
ASSERT_NE(view->data<void>(), nullptr);
*view->data<int8_t>() = -123;
}
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kReadOnly>(
TensorCpuViewDescriptor{
.buffer = {.format = TensorBufferDescriptor::Format::kUInt8}}));
ASSERT_NE(view->data<void>(), nullptr);
EXPECT_EQ(*view->data<uint8_t>(), 0);
}
}
TEST(TensorCpuViewTest, TestWritePositiveInt8ThenReadUInt8) {
Tensor2 tensor{Tensor2::Shape({1})};
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kWriteOnly>(
TensorCpuViewDescriptor{
.buffer = {.format = TensorBufferDescriptor::Format::kInt8}}));
ASSERT_NE(view->data<void>(), nullptr);
*view->data<int8_t>() = 123;
}
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kReadOnly>(
TensorCpuViewDescriptor{
.buffer = {.format = TensorBufferDescriptor::Format::kUInt8}}));
ASSERT_NE(view->data<void>(), nullptr);
EXPECT_EQ(*view->data<uint8_t>(), 123 * 2);
}
}
TEST(TensorCpuViewTest, TestDequantization) {
constexpr int num_elements = 20;
// Gives quantization values in range [-100, 90].
constexpr int zero_point = -100;
constexpr float scale = 2.0f;
Tensor2 tensor{Tensor2::Shape({num_elements})};
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kWriteOnly>(
TensorCpuViewDescriptor{
.buffer = {
.format = TensorBufferDescriptor::Format::kQuantizedInt8,
.quantization_parameters = {.scale = scale,
.zero_point = zero_point}}}));
ASSERT_NE(view->data<void>(), nullptr);
auto data = view->data<int8_t>();
for (int i = 0; i < num_elements; ++i) {
// Add some bias (+1) to make round-up take place.
data[i] = (i * 20 + 1) / scale + zero_point;
}
}
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kReadOnly>(
TensorCpuViewDescriptor{
.buffer = {.format =
TensorBufferDescriptor::Format::kFloat32}}));
ASSERT_NE(view->data<void>(), nullptr);
std::vector<float> reference(num_elements);
for (int i = 0; i < num_elements; ++i) {
reference[i] = i * 20.0f + 1.0f;
}
EXPECT_THAT(absl::Span<float>(view->data<float>(), num_elements),
testing::Pointwise(NearWithPrecision(1.001), reference));
}
}
TEST(TensorCpuViewTest, TestQuantization) {
constexpr int num_elements = 20;
// Gives quantization values in range [-100, 90].
constexpr int zero_point = -100;
constexpr float scale = 2.0f;
Tensor2 tensor{Tensor2::Shape({num_elements})};
{
MP_ASSERT_OK_AND_ASSIGN(
auto view,
tensor.GetView<Tensor2::View::Access::kWriteOnly>(
TensorCpuViewDescriptor{
.buffer = {.format =
TensorBufferDescriptor::Format::kFloat32}}));
ASSERT_NE(view->data<void>(), nullptr);
auto data = view->data<float>();
for (int i = 0; i < num_elements; ++i) {
// Add some bias (+1) to make round-up take place.
data[i] = i * 20 + 1;
}
}
{
TensorCpuViewDescriptor d{
.buffer = {.format = TensorBufferDescriptor::Format::kQuantizedInt8,
.quantization_parameters = {.scale = scale,
.zero_point = zero_point}}};
MP_ASSERT_OK_AND_ASSIGN(
auto view, tensor.GetView<Tensor2::View::Access::kReadOnly>(d));
ASSERT_NE(view->data<void>(), nullptr);
std::vector<int8_t> reference(num_elements);
for (int i = 0; i < num_elements; ++i) {
reference[i] = (i * 20 + 1) / scale + zero_point;
}
EXPECT_THAT(absl::Span<int8_t>(view->data<int8_t>(), num_elements),
testing::Pointwise(IntegerEqual(0), reference));
}
}
} // namespace mediapipe