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chore: import upstream snapshot with attribution

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wehub-resource-sync
2026-07-13 13:18:33 +08:00
commit 4ececc111a
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csrc/includes/quantization.h
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// Copyright (c) Microsoft Corporation.
// SPDX-License-Identifier: Apache-2.0
// DeepSpeed Team
#pragma once
#include <cuda_fp16.h>
#include "ds_kernel_utils.h"
namespace quantize {
enum class Type { Symmetric, Asymmetric };
struct PackedInt4 {
int8_t high : 4;
int8_t low : 4;
};
DS_HD_INLINE bool requires_offset(Type qType) { return qType == Type::Asymmetric; }
} // namespace quantize
void launch_quant(int8_t* output_data,
float* params,
const __half* input_data,
const int groups,
const int elems_per_group,
const int num_bits,
const quantize::Type quant_type,
cudaStream_t stream);
template <typename T>
void launch_dequantize_kernel(T* dequant_data,
const int8_t* q_data,
const float* q_params,
quantize::Type q_type,
int num_bits,
int elems_per_group,
int total_elems,
cudaStream_t stream);
void launch_swizzled_quant(int8_t* q_data,
float* q_scales,
const __half* input_data,
int num_bits,
quantize::Type q_type,
int groups,
int elems_per_group,
int pipelining,
int nodes,
int devices_per_node,
cudaStream_t stream);
void launch_loco_swizzled_quant(int8_t* quantized_data,
float* quantized_scales,
const __half* uncompressed_data,
__half* error_feedback,
const float err_beta,
int num_bits,
quantize::Type quant_type,
int groups,
int elems_per_group,
int pipelining,
int nodes,
int devices_per_node,
cudaStream_t stream);
void launch_loco_dequant_reduce(int8_t* reduced_data,
float* reduced_scales,
const int8_t* input_data,
const float* input_scales,
int num_gpus,
int num_bits,
quantize::Type quant_type,
int out_groups,
int elems_per_out_group,
int elems_per_in_tensor,
int groups_per_in_tensor,
int elems_per_in_group,
__half2* error_feedback,
const float err_beta,
cudaStream_t stream);
void launch_dequant_reduce(int8_t* reduced_data,
float* reduced_scales,
const int8_t* input_data,
const float* input_scales,
int num_gpus,
int num_bits,
quantize::Type quant_type,
int out_groups,
int elems_per_out_group,
int elems_per_in_tensor,
int groups_per_in_tensor,
int elems_per_in_group,
cudaStream_t stream);
template <typename T>
void launch_fake_quantize_kernel(T* vals,
int total_count,
int group_num,
int num_bits,
cudaStream_t stream);
template <typename T>
void launch_sr_fake_quantize_kernel(T* vals,
int total_count,
int group_num,
int num_bits,
cudaStream_t stream);
template <typename T>
void launch_fake_quantize_kernel_asym(T* vals,
int total_count,
int group_num,
int num_bits,
cudaStream_t stream);
template <typename T>
void launch_sr_fake_quantize_kernel_asym(T* vals,
int total_count,
int group_num,
int num_bits,
cudaStream_t stream);
void launch_dequantize_int4_to_half_experimental(uint8_t* data_in,
half* data_out,
half* scale_buffer,
half* min_val_buffer,
int num_group,
int group_size,
cudaStream_t stream);
void launch_dequantize_int8_to_half_experimental(uint8_t* data_in,
half* data_out,
half* scale_buffer,
half* min_val_buffer,
int num_group,
int group_size,
cudaStream_t stream);