88 lines
4.2 KiB
C++
88 lines
4.2 KiB
C++
#pragma once
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#include <torch/csrc/stable/library.h>
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#include <torch/csrc/stable/tensor.h>
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#ifndef USE_ROCM
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torch::stable::Tensor permute_cols(torch::stable::Tensor const& A,
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torch::stable::Tensor const& perm);
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void per_token_group_quant_fp8(const torch::stable::Tensor& input,
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torch::stable::Tensor& output_q,
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torch::stable::Tensor& output_s,
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int64_t group_size, double eps, double fp8_min,
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double fp8_max, bool scale_ue8m0,
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bool dummy_is_scale_transposed,
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bool dummy_is_tma_aligned);
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// Fused activation quantisation + DeepGEMM-compatible UE8M0-packed scales.
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void per_token_group_quant_8bit_packed(const torch::stable::Tensor& input,
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torch::stable::Tensor& output_q,
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torch::stable::Tensor& output_s_packed,
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int64_t group_size, double eps,
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double min_8bit, double max_8bit);
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void per_token_group_quant_int8(const torch::stable::Tensor& input,
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torch::stable::Tensor& output_q,
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torch::stable::Tensor& output_s,
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int64_t group_size, double eps, double int8_min,
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double int8_max);
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bool cutlass_scaled_mm_supports_fp8(int64_t cuda_device_capability);
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bool cutlass_scaled_mm_supports_block_fp8(int64_t cuda_device_capability);
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bool cutlass_group_gemm_supported(int64_t cuda_device_capability);
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void cutlass_scaled_mm(torch::stable::Tensor& out,
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torch::stable::Tensor const& a,
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torch::stable::Tensor const& b,
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torch::stable::Tensor const& a_scales,
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torch::stable::Tensor const& b_scales,
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std::optional<torch::stable::Tensor> const& bias);
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void cutlass_moe_mm(torch::stable::Tensor& out_tensors,
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torch::stable::Tensor const& a_tensors,
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torch::stable::Tensor const& b_tensors,
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torch::stable::Tensor const& a_scales,
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torch::stable::Tensor const& b_scales,
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torch::stable::Tensor const& expert_offsets,
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torch::stable::Tensor const& problem_sizes,
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torch::stable::Tensor const& a_strides,
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torch::stable::Tensor const& b_strides,
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torch::stable::Tensor const& c_strides, bool per_act_token,
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bool per_out_ch);
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void cutlass_scaled_mm_azp(torch::stable::Tensor& out,
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torch::stable::Tensor const& a,
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torch::stable::Tensor const& b,
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torch::stable::Tensor const& a_scales,
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torch::stable::Tensor const& b_scales,
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torch::stable::Tensor const& azp_adj,
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std::optional<torch::stable::Tensor> const& azp,
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std::optional<torch::stable::Tensor> const& bias);
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void get_cutlass_moe_mm_data(
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const torch::stable::Tensor& topk_ids,
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torch::stable::Tensor& expert_offsets,
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torch::stable::Tensor& problem_sizes1,
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torch::stable::Tensor& problem_sizes2,
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torch::stable::Tensor& input_permutation,
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torch::stable::Tensor& output_permutation, const int64_t num_experts,
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const int64_t n, const int64_t k,
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const std::optional<torch::stable::Tensor>& blockscale_offsets,
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const bool is_gated);
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void get_cutlass_moe_mm_problem_sizes_from_expert_offsets(
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const torch::stable::Tensor& expert_first_token_offset,
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torch::stable::Tensor& problem_sizes1,
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torch::stable::Tensor& problem_sizes2, const int64_t n, const int64_t k,
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const bool swap_ab);
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void get_cutlass_batched_moe_mm_data(
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torch::stable::Tensor& expert_offsets,
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torch::stable::Tensor& problem_sizes1,
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torch::stable::Tensor& problem_sizes2,
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const torch::stable::Tensor& expert_num_tokens,
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const int64_t num_local_experts, const int64_t padded_m, const int64_t n,
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const int64_t k);
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#endif
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