Unified Llama 4 Scout/Maverick BI-V150 deployment bundle

patches/01_fp8_quant.patch

@@ -0,0 +1,46 @@
+--- a/vllm/_custom_ops.py
++++ b/vllm/_custom_ops.py
+@@ -1933,14 +1933,28 @@
+     if scale is None:
+         if use_per_token_if_dynamic:
+             scale = torch.empty((shape[0], 1), device=input.device, dtype=torch.float32)
+-            torch.ops._C.dynamic_per_token_scaled_fp8_quant(
+-                output, input, scale, scale_ub
+-            )
++            # COREXX_FP8_QUANT_PATCH: native fallback (vLLM _C op missing on CoreX)
++            m = input.shape[0]
++            s = input.abs().amax(dim=1, keepdim=True).float().clamp_min(1e-12) / 448.0
++            if scale_ub is not None:
++                ub = torch.as_tensor(scale_ub, device=s.device, dtype=s.dtype)
++                s = torch.minimum(s, ub)
++            scale[:m].copy_(s)
++            if shape[0] > m:
++                scale[m:].fill_(1.0)
++                output[m:].zero_()
++            output[:m].copy_((input.float() / s).to(out_dtype))
+         else:
+             scale = torch.empty(1, device=input.device, dtype=torch.float32)
+-            torch.ops._C.dynamic_scaled_fp8_quant(output, input, scale)
++            # COREXX_FP8_QUANT_PATCH: native fallback
++            amax = input.abs().amax().float().clamp_min(1e-12)
++            scale.fill_(amax / 448.0)
++            output.copy_((input.float() / scale).to(out_dtype))
+     else:
+-        torch.ops._C.static_scaled_fp8_quant(output, input, scale, group_shape)
++        # COREXX_FP8_QUANT_PATCH: native fallback
++        if group_shape is not None and tuple(group_shape) not in ((-1, -1), (-1, 1), (1, -1)):
++            raise NotImplementedError(f"native fp8 static quant: unsupported group_shape {group_shape}")
++        output.copy_((input.float() / scale).to(out_dtype))
+ 
+     return output, scale
+ 
+@@ -3824,6 +3838,9 @@
+         mul_routed_weight,
+         top_k,
+         config['BLOCK_SIZE_M'],
++        # COREXX_FP8_MOE_PATCH: pass quant scales to ixformer kernel
++        w_scale=B_scale,
++        a_scale=A_scale,
+         bias=bias
+     )
+