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[BugFix] Fix import error on non-blackwell machines #21020

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Merged
merged 4 commits into from
Jul 16, 2025
Merged

[BugFix] Fix import error on non-blackwell machines #21020

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f489caa
fix linking error on non-blackwell devices
LucasWilkinson Jul 16, 2025
4bb6e6e
format
LucasWilkinson Jul 16, 2025
7bfe032
fix build
LucasWilkinson Jul 16, 2025
a41432f
no tensor args so use catchall
LucasWilkinson Jul 16, 2025
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6 changes: 6 additions & 0 deletions csrc/attention/mla/sm100_cutlass_mla_kernel.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -270,4 +270,10 @@ int64_t sm100_cutlass_mla_get_workspace_size(int64_t max_seq_len, int64_t num_ba
}

#endif

TORCH_LIBRARY_IMPL_EXPAND(TORCH_EXTENSION_NAME, CUDA, m) {
m.impl("sm100_cutlass_mla_decode", &sm100_cutlass_mla_decode);
m.impl("sm100_cutlass_mla_get_workspace_size", &sm100_cutlass_mla_get_workspace_size);
}
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high

The function sm100_cutlass_mla_get_workspace_size is a host-side function that calculates a workspace size and does not involve any GPU operations. Registering it only for the CUDA dispatch key is incorrect and can lead to runtime errors if called in a context where the PyTorch dispatcher selects a different backend. Host-only functions like this should be registered for the CPU dispatch key to ensure they can be called correctly regardless of the context.

TORCH_LIBRARY_IMPL_EXPAND(TORCH_EXTENSION_NAME, CUDA, m) {
  m.impl("sm100_cutlass_mla_decode", &sm100_cutlass_mla_decode);
}

TORCH_LIBRARY_IMPL_EXPAND(TORCH_EXTENSION_NAME, CPU, m) {
  m.impl("sm100_cutlass_mla_get_workspace_size", &sm100_cutlass_mla_get_workspace_size);
}


// clang-format on
13 changes: 0 additions & 13 deletions csrc/ops.h
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Expand Up @@ -167,19 +167,6 @@ void cutlass_mla_decode(torch::Tensor const& out, torch::Tensor const& q_nope,
torch::Tensor const& seq_lens,
torch::Tensor const& page_table, double scale);

void sm100_cutlass_mla_decode(
torch::Tensor const& out, torch::Tensor const& q_nope,
torch::Tensor const& q_pe, torch::Tensor const& kv_c_and_k_pe_cache,
torch::Tensor const& seq_lens, torch::Tensor const& page_table,
torch::Tensor const& workspace, double sm_scale,
int64_t num_kv_splits =
1 /* Set to 1 to avoid cuda_graph issue by default. */);

int64_t sm100_cutlass_mla_get_workspace_size(
int64_t max_seq_len, int64_t num_batches, int64_t sm_count = 0,
int64_t num_kv_splits =
1 /* Set to 1 to avoid cuda_graph issue by default. */);

torch::Tensor get_cuda_view_from_cpu_tensor(torch::Tensor& cpu_tensor);

#ifndef USE_ROCM
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5 changes: 2 additions & 3 deletions csrc/torch_bindings.cpp
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Expand Up @@ -521,15 +521,14 @@ TORCH_LIBRARY_EXPAND(TORCH_EXTENSION_NAME, ops) {
" Tensor page_table, Tensor workspace, float "
"scale,"
" int num_kv_splits) -> ()");
ops.impl("sm100_cutlass_mla_decode", torch::kCUDA, &sm100_cutlass_mla_decode);
// conditionally compiled so impl in source file

// SM100 CUTLASS MLA workspace
ops.def(
"sm100_cutlass_mla_get_workspace_size(int max_seq_len, int num_batches,"
" int sm_count, int num_kv_splits) "
"-> int");
ops.impl("sm100_cutlass_mla_get_workspace_size",
&sm100_cutlass_mla_get_workspace_size);
// conditionally compiled so impl in source file

// Compute NVFP4 block quantized tensor.
ops.def(
Expand Down