Fuse more ops & Simplify token mapping (#1758)
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@@ -337,7 +337,7 @@ class FlashInferIndicesUpdaterDecode:
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def update(
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self, req_pool_indices, seq_lens, seq_lens_sum, decode_wrappers, encoder_lens
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):
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# Keep the signature for type checking, will be initialized during runtime
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# Keep the signature for type checking. It will be assigned during runtime.
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raise NotImplementedError()
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def update_single_wrapper(
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@@ -432,8 +432,8 @@ class FlashInferIndicesUpdaterDecode:
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kv_start_idx,
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):
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bs = len(req_pool_indices)
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kv_indptr[1 : bs + 1] = torch.cumsum(paged_kernel_lens, dim=0)
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kv_indptr = kv_indptr[: bs + 1]
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kv_indptr[1:] = torch.cumsum(paged_kernel_lens, dim=0)
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kv_indices = torch.empty(
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paged_kernel_lens_sum, dtype=torch.int32, device="cuda"
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)
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@@ -497,7 +497,7 @@ class FlashInferIndicesUpdaterPrefill:
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self.update = self.update_single_wrapper
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def update(self, req_pool_indices, seq_lens, prefix_lens, use_ragged, encoder_lens):
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# Keep the signature for type checking, will be initialized during runtime
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# Keep the signature for type checking. It will be assigned during runtime.
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raise NotImplementedError()
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def update_single_wrapper(
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@@ -589,8 +589,8 @@ class FlashInferIndicesUpdaterPrefill:
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use_ragged,
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):
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bs = len(req_pool_indices)
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kv_indptr[1 : bs + 1] = torch.cumsum(paged_kernel_lens, dim=0)
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kv_indptr = kv_indptr[: bs + 1]
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kv_indptr[1:] = torch.cumsum(paged_kernel_lens, dim=0)
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kv_indices = torch.empty(kv_indptr[-1], dtype=torch.int32, device="cuda")
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create_flashinfer_kv_indices_triton[(bs,)](
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self.req_to_token,
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@@ -602,8 +602,8 @@ class FlashInferIndicesUpdaterPrefill:
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self.max_context_len,
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)
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qo_indptr[1 : bs + 1] = torch.cumsum(seq_lens - prefix_lens, dim=0)
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qo_indptr = qo_indptr[: bs + 1]
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qo_indptr[1:] = torch.cumsum(seq_lens - prefix_lens, dim=0)
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# extend part
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if use_ragged:
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