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Revert "[Bugfix] Fix activation quantization dispatch for WNA4Int/WNA8Int" (#48785) #49032

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Revert "[Bugfix] Fix activation quantization dispatch for WNA4Int/WNA8Int" (#48785) #49032

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4 changes: 2 additions & 2 deletions .../model_executor/layers/quantization/compressed_tensors/schemes/compressed_tensors_wNa4.py
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Original file line number Diff line number Diff line change
Expand Up @@ -96,7 +96,7 @@ def get_min_capability(cls) -> int:
return 75

def _build_input_quant_config(self) -> dict | None:
"""Build the config dict that BaseInputSchema.from_config expects."""
"""Build the config dict that HummingInputSchema.from_config expects."""
if self.input_quant is None:
return None
iq = self.input_quant
Expand All @@ -112,7 +112,7 @@ def _build_input_quant_config(self) -> dict | None:
"dynamic": iq.dynamic,
"group_size": iq.group_size or 0,
"quant_method": "compressed-tensors",
"format": "int-quantized",
"format": self.quant_format,
}

def create_weights(
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4 changes: 2 additions & 2 deletions .../model_executor/layers/quantization/compressed_tensors/schemes/compressed_tensors_wNa8.py
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Original file line number Diff line number Diff line change
Expand Up @@ -96,7 +96,7 @@ def get_min_capability(cls) -> int:
return 75

def _build_input_quant_config(self) -> dict | None:
"""Build the config dict that BaseInputSchema.from_config expects."""
"""Build the config dict that HummingInputSchema.from_config expects."""
if self.input_quant is None:
return None
iq = self.input_quant
Expand All @@ -112,7 +112,7 @@ def _build_input_quant_config(self) -> dict | None:
"dynamic": iq.dynamic,
"group_size": iq.group_size or 0,
"quant_method": "compressed-tensors",
"format": "int-quantized",
"format": self.quant_format,
}

def create_weights(
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11 changes: 2 additions & 9 deletions vllm/model_executor/layers/quantization/utils/humming_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -441,15 +441,14 @@ def prepare_humming_layer(
input_quant_config: dict | None = None,
):
from vllm.utils.humming import (
BaseInputSchema,
BaseWeightSchema,
HummingInputSchema,
HummingMethod,
)

weight_schema = BaseWeightSchema.from_config(quant_config)
if input_quant_config is not None:
input_schema = BaseInputSchema.from_config(input_quant_config)
input_schema = HummingInputSchema.from_config(input_quant_config)
else:
input_schema = HummingInputSchema()

Expand All @@ -464,19 +463,13 @@ def prepare_humming_layer(
shape_k_stacks = [input_size_per_partition]
shape_n_stacks = layer.output_partition_sizes

# Step 1: convert weight and input schemas to humming standard format
# Step 1: convert weight to humming standard format
weight_schema, tensors = weight_schema.convert_humming(
tensors=dict(layer.named_parameters()),
shape_n_stacks=shape_n_stacks,
shape_k_stacks=shape_k_stacks,
param_dtype=layer.params_dtype,
)
input_schema, _ = input_schema.convert_humming(
tensors={},
shape_n_stacks=shape_n_stacks,
shape_k_stacks=shape_k_stacks,
param_dtype=layer.params_dtype,
)

layer.weight_schema = weight_schema

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