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[record-hessian] Introduce HessianComputer (#14265)
This commit introduce gessian computer and hessian vector. ONE-DCO-1.0-Signed-off-by: Banseok Lee <[email protected]>
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file(GLOB_RECURSE SOURCES "src/*.cpp") | ||
file(GLOB_RECURSE TESTS "src/*.test.cpp") | ||
list(REMOVE_ITEM SOURCES ${TESTS}) | ||
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add_library(record-hessian STATIC ${SOURCES}) | ||
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target_include_directories(record-hessian PUBLIC include) | ||
target_include_directories(record-hessian PRIVATE src) | ||
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target_link_libraries(record-hessian luci_import) | ||
target_link_libraries(record-hessian luci_env) | ||
target_link_libraries(record-hessian luci_export) | ||
target_link_libraries(record-hessian luci_interpreter) | ||
target_link_libraries(record-hessian luci_log) | ||
target_link_libraries(record-hessian dio_hdf5) | ||
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install(TARGETS record-hessian DESTINATION lib) | ||
install(DIRECTORY include/ DESTINATION include | ||
FILES_MATCHING PATTERN "*.h") | ||
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if(NOT ENABLE_TEST) | ||
return() | ||
endif(NOT ENABLE_TEST) | ||
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nnas_find_package(GTest REQUIRED) | ||
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GTest_AddTest(record_hessian_tests ${TESTS}) | ||
target_include_directories(record_hessian_tests PRIVATE include) | ||
target_include_directories(record_hessian_tests PRIVATE src) | ||
target_link_libraries(record_hessian_tests luci_lang) | ||
target_link_libraries(record_hessian_tests luci_pass) | ||
target_link_libraries(record_hessian_tests loco) | ||
target_link_libraries(record_hessian_tests dio_hdf5) | ||
target_link_libraries(record_hessian_tests nncc_coverage) | ||
target_link_libraries(record_hessian_tests luci_interpreter) | ||
target_link_libraries(record_hessian_tests record-hessian) |
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# record-hessian | ||
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_record-hessian_ calculates hessian metrix of activations for quantization. |
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compiler/record-hessian/include/record-hessian/HessianComputer.h
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/* | ||
* Copyright (c) 2024 Samsung Electronics Co., Ltd. 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. | ||
*/ | ||
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#ifndef __RECORD_HESSIAN_HESSIANCOMPUTER_H__ | ||
#define __RECORD_HESSIAN_HESSIANCOMPUTER_H__ | ||
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#include "record-hessian/HessianVector.h" | ||
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#include <luci/IR/CircleNode.h> | ||
#include <luci_interpreter/Interpreter.h> | ||
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#include <memory> | ||
#include <vector> | ||
#include <unordered_map> | ||
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namespace record_hessian | ||
{ | ||
/** | ||
* @brief Record approximated hessian matrix from | ||
* GPTQ paper(https://arxiv.org/abs/2210.17323). | ||
*/ | ||
using HessianMap = std::unordered_map<const luci::CircleNode *, std::vector<float>>; | ||
using HessianVectorMap = std::unordered_map<const luci::CircleNode *, HessianVector>; | ||
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class HessianComputer | ||
{ | ||
public: | ||
// Record min/max of node | ||
void recordHessian(const luci::CircleNode *node, const luci_interpreter::Tensor *input_tensor); | ||
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std::unique_ptr<HessianMap> getMap(); | ||
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private: | ||
HessianVectorMap _hessian_map; | ||
const luci_interpreter::Tensor *_input_tensor = nullptr; | ||
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void recordHessianForConv2D(const luci::CircleNode *node); | ||
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void recordHessianForFullyConnected(const luci::CircleNode *node); | ||
}; | ||
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void unfold(std::vector<float> &buf, uint32_t input_n, uint32_t input_h, uint32_t input_w, | ||
uint32_t input_c, uint32_t stride_h, uint32_t stride_w, uint32_t dilation_h, | ||
uint32_t dilation_w, uint32_t kernel_oc, uint32_t kernel_h, uint32_t kernel_w, | ||
uint32_t kernel_ic); | ||
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} // namespace record_hessian | ||
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#endif // __RECORD_HESSIAN_HESSIANCOMPUTER_H__ |
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compiler/record-hessian/include/record-hessian/HessianVector.h
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/* | ||
* Copyright (c) 2024 Samsung Electronics Co., Ltd. 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. | ||
*/ | ||
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#ifndef __RECORD_HESSIAN_HESSIANVECTOR_H__ | ||
#define __RECORD_HESSIAN_HESSIANVECTOR_H__ | ||
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#include <luci/IR/CircleNodes.h> | ||
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#include <cstddef> | ||
#include <vector> | ||
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namespace record_hessian | ||
{ | ||
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struct HessianVector | ||
{ | ||
std::vector<float> hessian; | ||
size_t count; | ||
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HessianVector() : count(0) {} | ||
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void update(const std::vector<float> &new_hessian) | ||
{ | ||
if (count == 0) | ||
{ | ||
hessian.resize(new_hessian.size()); | ||
} | ||
else if (hessian.size() != new_hessian.size()) | ||
{ | ||
hessian.resize(new_hessian.size()); | ||
} | ||
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size_t numel = new_hessian.size(); | ||
float alpha = 1.f / static_cast<float>(count + 1); | ||
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for (size_t i = 0; i < numel; ++i) | ||
{ | ||
hessian[i] = (hessian[i] * count + new_hessian[i]) * alpha; | ||
} | ||
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count++; | ||
}; | ||
}; | ||
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} // namespace record_hessian | ||
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#endif // __RECORD_HESSIAN_HESSIANVECTOR_H__ |
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require("luci") | ||
require("luci-interpreter") | ||
require("dio-hdf5") |
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/* | ||
* Copyright (c) 2024 Samsung Electronics Co., Ltd. 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. | ||
*/ | ||
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#include "record-hessian/HessianComputer.h" | ||
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#include <luci/IR/CircleQuantParam.h> | ||
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namespace record_hessian | ||
{ | ||
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/** | ||
* @brief unfold the vector with NHWC shape, inherently acting in an in-place manner. | ||
* @note (N, H, W, C) -> (N, L, K_h * K_w * C). | ||
* See details(https://pytorch.org/docs/stable/generated/torch.nn.Unfold.html). | ||
*/ | ||
void unfold(std::vector<float> &buf, uint32_t input_n, uint32_t input_h, uint32_t input_w, | ||
uint32_t input_c, uint32_t stride_h, uint32_t stride_w, uint32_t dilation_h, | ||
uint32_t dilation_w, uint32_t kernel_oc, uint32_t kernel_h, uint32_t kernel_w, | ||
uint32_t kernel_ic) | ||
{ | ||
assert(input_n > 0 && input_h > 0 && input_w > 0 && input_c > 0); | ||
assert(stride_h > 0 && stride_w > 0); | ||
assert(kernel_oc > 0 && kernel_h > 0 && kernel_w > 0 && kernel_ic > 0); | ||
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if (input_c != kernel_ic) | ||
throw std::runtime_error("RecordHessian: Input channels do not match kernel channels."); | ||
int out_height = (input_h - dilation_h * (kernel_h - 1) - 1) / stride_h + 1; | ||
int out_width = (input_w - dilation_w * (kernel_w - 1) - 1) / stride_w + 1; | ||
int patch_size = kernel_h * kernel_w * kernel_ic; | ||
std::vector<float> unfolded_buf(input_n * out_height * out_width * patch_size, 0.0f); | ||
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int index = 0; | ||
int in_y, in_x; | ||
for (int n = 0; n < input_n; ++n) | ||
{ | ||
for (int y = 0; y < out_height; ++y) | ||
{ | ||
for (int x = 0; x < out_width; ++x) | ||
{ | ||
for (int in_c = 0; in_c < input_c; ++in_c) | ||
{ | ||
for (int ky = 0; ky < kernel_h; ++ky) | ||
{ | ||
for (int kx = 0; kx < kernel_w; ++kx) | ||
{ | ||
in_y = y * stride_h + ky * dilation_h; | ||
in_x = x * stride_w + kx * dilation_w; | ||
if (in_y < input_h && in_x < input_w) | ||
{ | ||
unfolded_buf[index] = buf[((n * input_h + in_y) * input_w + in_x) * input_c + in_c]; | ||
} | ||
index++; | ||
} | ||
} | ||
} | ||
} | ||
} | ||
} | ||
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buf.swap(unfolded_buf); | ||
} | ||
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void HessianComputer::recordHessianForFullyConnected(const luci::CircleNode *node) | ||
{ | ||
assert(_input_tensor->shape().num_dims() < 4); | ||
assert(_input_tensor->element_type() == luci_interpreter::DataType::FLOAT32); | ||
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uint32_t size_in_ch; | ||
uint32_t length; | ||
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const auto data = _input_tensor->data<float>(); | ||
const auto num_elements = _input_tensor->shape().num_elements(); | ||
std::vector<float> buf(data, data + num_elements); | ||
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if (_input_tensor->shape().num_dims() == 3) | ||
{ | ||
size_in_ch = _input_tensor->shape().dim(2); // input_tensor [batch, length, channel] | ||
} | ||
else if (_input_tensor->shape().num_dims() == 2) | ||
{ | ||
size_in_ch = _input_tensor->shape().dim(1); // input_tensor [length, channel] | ||
} | ||
else | ||
{ | ||
throw std::runtime_error("RecordHessian: Unsupported node rank"); | ||
} | ||
assert(size_in_ch != 0); | ||
length = num_elements / size_in_ch; | ||
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std::vector<float> hessian(size_in_ch * size_in_ch, 0); | ||
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for (int i = 0; i < size_in_ch; ++i) | ||
{ | ||
for (int j = 0; j < size_in_ch; ++j) | ||
{ | ||
float sum = 0; | ||
for (int k = 0; k < length; ++k) | ||
{ | ||
sum += buf[i + k * size_in_ch] * buf[j + k * size_in_ch]; | ||
} | ||
hessian[i * size_in_ch + j] = 2 * sum; | ||
} | ||
} | ||
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HessianVector &vector = _hessian_map[node]; | ||
vector.update(hessian); | ||
} | ||
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void HessianComputer::recordHessianForConv2D(const luci::CircleNode *node) | ||
{ | ||
assert(_input_tensor->shape().num_dims() == 4); | ||
assert(_input_tensor->element_type() == luci_interpreter::DataType::FLOAT32); | ||
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const auto circle_conv2d = loco::must_cast<const luci::CircleConv2D *>(node); | ||
const auto node_filter = loco::must_cast<luci::CircleConst *>((circle_conv2d)->filter()); | ||
assert(circle_conv2d->rank() >= 4); | ||
assert(node_filter->dtype() == loco::DataType::FLOAT32); | ||
assert(node_filter->rank() == 4); | ||
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uint32_t size_filter = node_filter->size<loco::DataType::FLOAT32>(); | ||
uint32_t size_in_ch = | ||
node_filter->size<loco::DataType::FLOAT32>() / circle_conv2d->dim(3).value(); | ||
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uint32_t input_n = _input_tensor->shape().dim(0); | ||
uint32_t input_h = _input_tensor->shape().dim(1); | ||
uint32_t input_w = _input_tensor->shape().dim(2); | ||
uint32_t input_c = _input_tensor->shape().dim(3); | ||
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uint32_t stride_h = circle_conv2d->stride()->h(); | ||
uint32_t stride_w = circle_conv2d->stride()->w(); | ||
uint32_t dilation_h = circle_conv2d->dilation()->h(); | ||
uint32_t dilation_w = circle_conv2d->dilation()->w(); | ||
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uint32_t kernel_oc = node_filter->dim(0).value(); | ||
uint32_t kernel_h = node_filter->dim(1).value(); | ||
uint32_t kernel_w = node_filter->dim(2).value(); | ||
uint32_t kernel_ic = node_filter->dim(3).value(); | ||
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const auto data = _input_tensor->data<float>(); | ||
const auto num_elements = _input_tensor->shape().num_elements(); | ||
assert(data != 0); | ||
assert(num_elements != 0); | ||
std::vector<float> buf(data, data + num_elements); | ||
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unfold(buf, input_n, input_h, input_w, input_c, stride_h, stride_w, dilation_h, dilation_w, | ||
kernel_oc, kernel_h, kernel_w, kernel_ic); | ||
assert(size_in_ch != 0); | ||
uint32_t length = buf.size() / size_in_ch; | ||
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std::vector<float> hessian(size_in_ch * size_in_ch, 0); | ||
for (int i = 0; i < size_in_ch; ++i) | ||
{ | ||
for (int j = 0; j < size_in_ch; ++j) | ||
{ | ||
float sum = 0; | ||
for (int k = 0; k < length; ++k) | ||
{ | ||
sum += buf[i + k * size_in_ch] * buf[j + k * size_in_ch]; | ||
} | ||
hessian[i * size_in_ch + j] = 2 * sum; | ||
} | ||
} | ||
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HessianVector &vector = _hessian_map[node]; | ||
vector.update(hessian); | ||
} | ||
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void HessianComputer::recordHessian(const luci::CircleNode *node, | ||
const luci_interpreter::Tensor *input_tensor) | ||
{ | ||
if (node == nullptr || input_tensor == nullptr) | ||
throw std::invalid_argument("RecordHessian: node or input_tensor is null."); | ||
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if (input_tensor->element_type() != luci_interpreter::DataType::FLOAT32) | ||
throw std::runtime_error("RecordHessian: Unsupported dtype: only FLOAT32 is supported."); | ||
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_input_tensor = input_tensor; | ||
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switch (node->opcode()) | ||
{ | ||
case luci::CircleOpcode::FULLY_CONNECTED: | ||
recordHessianForFullyConnected(node); | ||
break; | ||
case luci::CircleOpcode::CONV_2D: | ||
recordHessianForConv2D(node); | ||
break; | ||
default: | ||
throw std::runtime_error("RecordHessian: " + node->name() + " is unsupported op."); | ||
} | ||
} | ||
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std::unique_ptr<HessianMap> HessianComputer::getMap() | ||
{ | ||
auto hessian_map = std::make_unique<HessianMap>(); | ||
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for (auto item : _hessian_map) | ||
{ | ||
auto &vec = (*hessian_map)[item.first]; | ||
vec = item.second.hessian; | ||
} | ||
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return hessian_map; | ||
} | ||
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} // namespace record_hessian |
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