mirror of https://github.com/hpcaitech/ColossalAI
48 lines
1.8 KiB
Python
48 lines
1.8 KiB
Python
# adepted from https://github.com/ModelTC/lightllm/blob/ece7b43f8a6dfa74027adc77c2c176cff28c76c8/lightllm/models/llama/triton_kernel/flash_decoding.py
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import torch
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try:
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from lightllm.models.llama.triton_kernel.flash_decoding_stage1 import flash_decode_stage1
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from lightllm.models.llama.triton_kernel.flash_decoding_stage2 import flash_decode_stage2
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HAS_LIGHTLLM_KERNEL = True
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except:
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print("install lightllm from https://github.com/ModelTC/lightllm/blob/ece7b43f8a6dfa74027adc77c2c176cff28c76c8")
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HAS_LIGHTLLM_KERNEL = False
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if HAS_LIGHTLLM_KERNEL:
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def token_flash_decoding(q, o_tensor, infer_state, q_head_num, head_dim, cache_k, cache_v):
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BLOCK_SEQ = 256
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batch_size = infer_state.batch_size
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max_len_in_batch = infer_state.max_len_in_batch
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calcu_shape1 = (batch_size, q_head_num, head_dim)
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if getattr(infer_state, "mid_o", None) is None:
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infer_state.mid_o = torch.empty(
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[batch_size, q_head_num, max_len_in_batch // BLOCK_SEQ + 1, head_dim],
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dtype=torch.float32,
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device="cuda",
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)
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infer_state.mid_o_logexpsum = torch.empty(
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[batch_size, q_head_num, max_len_in_batch // BLOCK_SEQ + 1], dtype=torch.float32, device="cuda"
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)
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mid_o = infer_state.mid_o
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mid_o_logexpsum = infer_state.mid_o_logexpsum
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flash_decode_stage1(
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q.view(calcu_shape1),
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cache_k,
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cache_v,
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infer_state.block_loc,
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infer_state.seq_len,
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infer_state.max_len_in_batch,
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mid_o,
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mid_o_logexpsum,
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BLOCK_SEQ,
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)
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flash_decode_stage2(mid_o, mid_o_logexpsum, infer_state.seq_len, o_tensor.view(calcu_shape1), BLOCK_SEQ)
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