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https://github.com/ROCm/composable_kernel.git
synced 2026-07-18 17:48:06 +00:00
bugfix for varlen fmha
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@@ -62,9 +62,9 @@ using fmha_trait_{F_idx} = ck_tile::TileFmhaTraits<{F_spad},
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{F_lse},
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{F_dropout},
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{F_squant},
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{F_occupancy},
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{F_sglang_layout},
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{F_chunked},
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{F_occupancy}>;
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{F_chunked}>;
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using fmha_variant_{F_idx} = ck_tile::ComposedAttention<{F_logits} * ck_tile::LOGITS_SOFT_CAP, CK_TILE_FMHA_FWD_FAST_EXP2>;
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@@ -275,8 +275,8 @@ class FmhaFwdPipeline:
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if self.F_squant == 't' : n += '_squant'
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else: n += '_nsquant'
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# if self.F_sglang_layout == 't' : n += '_sglang'
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# else: n += '_vllm'
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if self.F_sglang_layout == 't' : n += '_sglang'
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else: n += '_vllm'
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if self.F_chunked == 't' : n += '_chunked'
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else: n += '_nchunked'
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@@ -302,6 +302,7 @@ class FmhaFwdApiPool:
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per_dtypes=str()
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for i, dtype in enumerate(self.pool.keys()):
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per_hdim_case=str()
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for j, hdim in enumerate(self.pool[dtype].keys()):
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traits=self.pool[dtype][hdim]
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inners=str()
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@@ -475,31 +476,31 @@ def get_fwd_blobs(kernel_filter : Optional[str], receipt, optdim_list, mask_impl
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squant = 't' if dtype == 'fp8' else 'f'
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pipelines = []
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if dtype in ['fp16', 'bf16']:
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for logits, mask, bias, lse, dropout, chunked in itertools.product(["t", "f"], get_mask_map(mask_impl).keys(), BIAS_MAP.keys(), ["t", "f"], ["t", "f"], ["t", "f"]):
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for logits, mask, bias, lse, dropout, sglang, chunked in itertools.product(["t", "f"], get_mask_map(mask_impl).keys(), BIAS_MAP.keys(), ["t", "f"], ["t", "f"], ["t", "f"], ["t", "f"]):
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if hdim == 256:
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# if True:
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pipelines.append(FmhaFwdPipeline('qr', 'row', 'f', 'f', 'f', 'f', logits, bias, lse, dropout, squant, mask, 'f', chunked))
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pipelines.append(FmhaFwdPipeline('qr', 'col', 'f', 'f', 'f', 'f', logits, bias, lse, dropout, squant, mask, 'f', chunked))
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pipelines.append(FmhaFwdPipeline('qr', 'row', 'f', 'f', 'f', 'f', logits, bias, lse, dropout, squant, mask, sglang, chunked))
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pipelines.append(FmhaFwdPipeline('qr', 'col', 'f', 'f', 'f', 'f', logits, bias, lse, dropout, squant, mask, sglang, chunked))
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# the below two is used for hdim vectorize load
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pipelines.append(FmhaFwdPipeline('qr', 'row', 't', 't', 'f', 'f', logits, bias, lse, dropout, squant, mask, 'f', chunked))
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pipelines.append(FmhaFwdPipeline('qr', 'col', 't', 't', 'f', 'f', logits, bias, lse, dropout, squant, mask, 'f', chunked))
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pipelines.append(FmhaFwdPipeline('qr', 'row', 't', 't', 'f', 'f', logits, bias, lse, dropout, squant, mask, sglang, chunked))
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pipelines.append(FmhaFwdPipeline('qr', 'col', 't', 't', 'f', 'f', logits, bias, lse, dropout, squant, mask, sglang, chunked))
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pipelines.append(FmhaFwdPipeline('qr', 'row', 't', 't', 't', 't', logits, bias, lse, dropout, squant, mask, 'f', chunked))
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pipelines.append(FmhaFwdPipeline('qr', 'col', 't', 't', 't', 't', logits, bias, lse, dropout, squant, mask, 'f', chunked))
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pipelines.append(FmhaFwdPipeline('qr', 'row', 't', 't', 't', 't', logits, bias, lse, dropout, squant, mask, sglang, chunked))
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pipelines.append(FmhaFwdPipeline('qr', 'col', 't', 't', 't', 't', logits, bias, lse, dropout, squant, mask, sglang, chunked))
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else:
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if bias == "bias":
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pipelines.append(FmhaFwdPipeline('qr_async', 'row', 'f', 'f', 'f', 'f', logits, bias, lse, dropout, squant, mask, 'f', chunked))
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pipelines.append(FmhaFwdPipeline('qr_async', 'row', 't', 't', 't', 't', logits, bias, lse, dropout, squant, mask, 'f', chunked))
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pipelines.append(FmhaFwdPipeline('qr_async', 'col', 'f', 'f', 'f', 'f', logits, bias, lse, dropout, squant, mask, 'f', chunked))
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pipelines.append(FmhaFwdPipeline('qr_async', 'col', 't', 't', 't', 't', logits, bias, lse, dropout, squant, mask, 'f', chunked))
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pipelines.append(FmhaFwdPipeline('qr_async', 'row', 'f', 'f', 'f', 'f', logits, bias, lse, dropout, squant, mask, sglang, chunked))
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pipelines.append(FmhaFwdPipeline('qr_async', 'row', 't', 't', 't', 't', logits, bias, lse, dropout, squant, mask, sglang, chunked))
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pipelines.append(FmhaFwdPipeline('qr_async', 'col', 'f', 'f', 'f', 'f', logits, bias, lse, dropout, squant, mask, sglang, chunked))
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pipelines.append(FmhaFwdPipeline('qr_async', 'col', 't', 't', 't', 't', logits, bias, lse, dropout, squant, mask, sglang, chunked))
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else:
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pipelines.append(FmhaFwdPipeline('qr_async', 'row', 't', 'f', 't', 't', logits, bias, lse, dropout, squant, mask, 'f', chunked))
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pipelines.append(FmhaFwdPipeline('qr_async', 'row', 't', 't', 't', 't', logits, bias, lse, dropout, squant, mask, 'f', chunked))
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pipelines.append(FmhaFwdPipeline('qr_async', 'col', 't', 'f', 't', 't', logits, bias, lse, dropout, squant, mask, 'f', chunked))
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pipelines.append(FmhaFwdPipeline('qr_async', 'col', 't', 't', 't', 't', logits, bias, lse, dropout, squant, mask, 'f', chunked))
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pipelines.append(FmhaFwdPipeline('qr_async', 'row', 't', 'f', 't', 't', logits, bias, lse, dropout, squant, mask, sglang, chunked))
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pipelines.append(FmhaFwdPipeline('qr_async', 'row', 't', 't', 't', 't', logits, bias, lse, dropout, squant, mask, sglang, chunked))
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pipelines.append(FmhaFwdPipeline('qr_async', 'col', 't', 'f', 't', 't', logits, bias, lse, dropout, squant, mask, sglang, chunked))
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pipelines.append(FmhaFwdPipeline('qr_async', 'col', 't', 't', 't', 't', logits, bias, lse, dropout, squant, mask, sglang, chunked))
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if receipt == 1 and bias != "bias":
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pipelines.append(FmhaFwdPipeline('qr', 'row', 't', 't', 't', 't', logits, bias, lse, dropout, squant, mask, 'f', chunked)) # TODO: cover arbitraty hdim
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pipelines.append(FmhaFwdPipeline('qr', 'col', 't', 'f', 't', 't', logits, bias, lse, dropout, squant, mask, 'f', chunked)) # TODO: cover arbitraty hdim
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pipelines.append(FmhaFwdPipeline('qr', 'row', 't', 't', 't', 't', logits, bias, lse, dropout, squant, mask, sglang, chunked)) # TODO: cover arbitraty hdim
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pipelines.append(FmhaFwdPipeline('qr', 'col', 't', 'f', 't', 't', logits, bias, lse, dropout, squant, mask, sglang, chunked)) # TODO: cover arbitraty hdim
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elif dtype in ['fp8', 'bf8']:
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# no need lse/dropout kernels
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for logits, mask, bias in itertools.product(["t", "f"], get_mask_map(mask_impl).keys(), BIAS_MAP.keys()):
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@@ -820,7 +820,6 @@ struct BlockFmhaBatchPrefillPipelineQRKSVSAsync
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}
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else
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{
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statically_indexed_array<index_t, NRepeat> k_offsets;
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static_for<0, NRepeat, 1>{}([&](auto n0) {
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int32_t seqlen_k_idx_per_repeat = k_coord[0] + kN0 / NRepeat * n0.value;
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int32_t i_page = seqlen_k_idx_per_repeat / page_block_size;
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@@ -19,9 +19,9 @@ template <bool kPadSeqLenQ_ /* padding for seqlen_q */,
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bool kStoreLSE_,
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bool kHasDropout_,
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bool kDoFp8StaticQuant_,
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index_t kBlockPerCu_ = -1, /* overwrite occupancy if not -1 */
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bool kIsSglangLayout_ = false,
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bool kIsChunkedPrefill_ = false,
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index_t kBlockPerCu_ = -1 /* overwrite occupancy if not -1 */>
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bool kIsChunkedPrefill_ = false>
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struct TileFmhaTraits
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{
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static constexpr bool kPadSeqLenQ = kPadSeqLenQ_;
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