Minor speedup for infer_quantization_format when save_compressed=False

src/llmcompressor/transformers/compression/quantization_format.py

@@ -3,10 +3,7 @@
 from compressed_tensors import CompressionFormat
 from compressed_tensors.config import SparsityStructure
 from compressed_tensors.quantization import QuantizationStrategy, QuantizationType
-from compressed_tensors.quantization.utils import (
-    is_model_quantized,
-    is_module_quantized,
-)
+from compressed_tensors.quantization.utils import is_module_quantized
 
 __all__ = ["infer_quantization_format"]
 
@@ -47,57 +44,57 @@ def infer_quantization_format(
     :param save_compressed: used to infer a quantization format if None is provided
     :return compression format appropriate for model
     """
-    if not is_model_quantized(model):
-        return None
-
     if quantization_format is not None:
         return quantization_format
 
-    if save_compressed:
-        weight_args, input_args = _get_unique_quant_args(model)
-        is_24_structure = (
-            SparsityStructure(sparsity_structure) == SparsityStructure.TWO_FOUR
+    if not save_compressed:
+        # format will be inferred from config
+        return None
+
+    weight_args, input_args = _get_unique_quant_args(model)
+    if len(weight_args) <= 0:
+        return None
+
+    is_24_structure = (
+        SparsityStructure(sparsity_structure) == SparsityStructure.TWO_FOUR
+    )
+    is_weight_only = len(input_args) == 0 and len(weight_args) > 0
+
+    if (
+        weight_args[0].num_bits == 4
+        and weight_args[0].type == QuantizationType.FLOAT.value
+    ):
+        return CompressionFormat.nvfp4_pack_quantized
+
+    if is_weight_only:  # w4a16 and w8a16
+        is_valid_pack = all(
+            weight_arg.num_bits in [4, 8]
+            and weight_arg.type == QuantizationType.INT.value
+            for weight_arg in weight_args
         )
-        is_weight_only = len(input_args) == 0 and len(weight_args) > 0
-
-        if (
-            weight_args[0].num_bits == 4
-            and weight_args[0].type == QuantizationType.FLOAT.value
-        ):
-            return CompressionFormat.nvfp4_pack_quantized
-
-        if is_weight_only:  # w4a16 and w8a16
-            is_valid_pack = all(
-                weight_arg.num_bits in [4, 8]
-                and weight_arg.type == QuantizationType.INT.value
-                for weight_arg in weight_args
-            )
-            if not is_valid_pack:  # packing only valid for int4 and int 8
-                return CompressionFormat.naive_quantized
-            if is_24_structure:
-                for arg in weight_args:
-                    if (
-                        arg.strategy is not QuantizationStrategy.CHANNEL.value
-                        and arg.strategy is not QuantizationStrategy.GROUP.value
-                    ):
-                        # marlin24 kernel only applicable for channel/group quantization
-                        return CompressionFormat.pack_quantized
-                return CompressionFormat.marlin_24
-            return CompressionFormat.pack_quantized
-        else:  # w8a8 float and int
-            if len(weight_args) == 1:
+        if not is_valid_pack:  # packing only valid for int4 and int 8
+            return CompressionFormat.naive_quantized
+        if is_24_structure:
+            for arg in weight_args:
                 if (
-                    weight_args[0].type == QuantizationType.FLOAT.value
-                    and weight_args[0].num_bits == 8
+                    arg.strategy is not QuantizationStrategy.CHANNEL.value
+                    and arg.strategy is not QuantizationStrategy.GROUP.value
                 ):
-                    return CompressionFormat.float_quantized
-                if weight_args[0].type == QuantizationType.INT.value:
-                    return CompressionFormat.int_quantized
+                    # marlin24 kernel only applicable for channel/group quantization
+                    return CompressionFormat.pack_quantized
+            return CompressionFormat.marlin_24
+        return CompressionFormat.pack_quantized
+    else:  # w8a8 float and int
+        if len(weight_args) == 1:
+            if (
+                weight_args[0].type == QuantizationType.FLOAT.value
+                and weight_args[0].num_bits == 8
+            ):
+                return CompressionFormat.float_quantized
+            if weight_args[0].type == QuantizationType.INT.value:
+                return CompressionFormat.int_quantized
 
-            return CompressionFormat.naive_quantized
-    else:
-        # format will be inferred from config
-        return None
+        return CompressionFormat.naive_quantized
 
 
 def _get_unique_quant_args(model):