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Fp8 cleanup #4

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Fp8 cleanup #4

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b0e78eb
cleanup
amogkam May 8, 2025
5375fc5
update
amogkam May 8, 2025
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24 changes: 22 additions & 2 deletions vllm/model_executor/layers/quantization/utils/w8a8_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -344,8 +344,28 @@
out_dtype = input.dtype

# cutlass_scaled_mm supports per tensor/channel W and per tensor/token A
input_scale = torch.tensor([1.0], dtype=torch.float32, device=input_2d.device)
qinput, x_scale = input_2d, input_scale
if self.cutlass_fp8_supported and input.dtype != current_platform.fp8_dtype():

Check failure on line 347 in vllm/model_executor/layers/quantization/utils/w8a8_utils.py

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Ruff (E501) 

vllm/model_executor/layers/quantization/utils/w8a8_utils.py:347:81: E501 Line too long (84 > 80)
assert input.dtype != current_platform.fp8_dtype(
), "FP8 input to cutlass is not currently implemented"
qinput, x_scale = ops.scaled_fp8_quant(
input_2d,
input_scale,
scale_ub=input_scale_ub,
use_per_token_if_dynamic=use_per_token_if_dynamic)
else:
if input.dtype != current_platform.fp8_dtype():
# Maybe apply padding to output, see comment in __init__
qinput, x_scale = ops.scaled_fp8_quant(
input_2d,
input_scale,
num_token_padding=self.output_padding,
use_per_token_if_dynamic=use_per_token_if_dynamic)
else:
if x_scale is not None:
qinput, x_scale = input_2d, input_scale
else:
qinput = input_2d
x_scale = torch.tensor([1.0], dtype=torch.float32, device=input_2d.device)

per_tensor_weights = (weight_scale.numel() == 1)
per_tensor_activations = (x_scale.numel() == 1)
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