47 lines
1.9 KiB
Diff
47 lines
1.9 KiB
Diff
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--- a/vllm/_custom_ops.py
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+++ b/vllm/_custom_ops.py
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@@ -1933,14 +1933,28 @@
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if scale is None:
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if use_per_token_if_dynamic:
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scale = torch.empty((shape[0], 1), device=input.device, dtype=torch.float32)
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- torch.ops._C.dynamic_per_token_scaled_fp8_quant(
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- output, input, scale, scale_ub
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- )
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+ # COREXX_FP8_QUANT_PATCH: native fallback (vLLM _C op missing on CoreX)
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+ m = input.shape[0]
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+ s = input.abs().amax(dim=1, keepdim=True).float().clamp_min(1e-12) / 448.0
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+ if scale_ub is not None:
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+ ub = torch.as_tensor(scale_ub, device=s.device, dtype=s.dtype)
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+ s = torch.minimum(s, ub)
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+ scale[:m].copy_(s)
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+ if shape[0] > m:
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+ scale[m:].fill_(1.0)
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+ output[m:].zero_()
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+ output[:m].copy_((input.float() / s).to(out_dtype))
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else:
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scale = torch.empty(1, device=input.device, dtype=torch.float32)
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- torch.ops._C.dynamic_scaled_fp8_quant(output, input, scale)
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+ # COREXX_FP8_QUANT_PATCH: native fallback
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+ amax = input.abs().amax().float().clamp_min(1e-12)
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+ scale.fill_(amax / 448.0)
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+ output.copy_((input.float() / scale).to(out_dtype))
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else:
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- torch.ops._C.static_scaled_fp8_quant(output, input, scale, group_shape)
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+ # COREXX_FP8_QUANT_PATCH: native fallback
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+ if group_shape is not None and tuple(group_shape) not in ((-1, -1), (-1, 1), (1, -1)):
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+ raise NotImplementedError(f"native fp8 static quant: unsupported group_shape {group_shape}")
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+ output.copy_((input.float() / scale).to(out_dtype))
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return output, scale
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@@ -3824,6 +3838,9 @@
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mul_routed_weight,
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top_k,
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config['BLOCK_SIZE_M'],
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+ # COREXX_FP8_MOE_PATCH: pass quant scales to ixformer kernel
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+ w_scale=B_scale,
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+ a_scale=A_scale,
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bias=bias
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)
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