[Minor] Remove unnecessary error message (#27115)

Signed-off-by: Zhuohan Li <zhuohan123@gmail.com>

vllm/model_executor/layers/linear.py

@@ -34,7 +34,6 @@ from vllm.model_executor.parameter import (
 )
 from vllm.model_executor.utils import set_weight_attrs
 from vllm.platforms import current_platform
-from vllm.utils import GiB_bytes
 
 logger = init_logger(__name__)
 
@@ -211,33 +210,17 @@ class UnquantizedLinearMethod(LinearMethodBase):
         # The weights are not quantized, and they are not sharded.
         # The amount of memory allocated for the weights is
         # sum(output_partition_sizes) * input_size_per_partition.
-        try:
-            weight_loader = extra_weight_attrs.pop("weight_loader")
-            weight = ModelWeightParameter(
-                data=torch.empty(
-                    sum(output_partition_sizes),
-                    input_size_per_partition,
-                    dtype=params_dtype,
-                ),
-                input_dim=1,
-                output_dim=0,
-                weight_loader=weight_loader,
-            )
-        except torch.cuda.OutOfMemoryError as e:
-            logger.error("Failed to create unquantized linear weights: %s", e)
-            if torch.cuda.is_available():
-                logger.debug("CUDA device: %s", torch.cuda.current_device())
-                logger.debug(
-                    "Allocated: %.2f GiB", torch.cuda.memory_allocated() / GiB_bytes
-                )
-                logger.debug(
-                    "Reserved: %.2f GiB", torch.cuda.memory_reserved() / GiB_bytes
-                )
-            raise RuntimeError(
-                "Failed to create unquantized linear weights. "
-                "This may be caused by insufficient memory to allocate "
-                "the weight."
-            ) from e
+        weight_loader = extra_weight_attrs.pop("weight_loader")
+        weight = ModelWeightParameter(
+            data=torch.empty(
+                sum(output_partition_sizes),
+                input_size_per_partition,
+                dtype=params_dtype,
+            ),
+            input_dim=1,
+            output_dim=0,
+            weight_loader=weight_loader,
+        )
 
         layer.register_parameter("weight", weight)
         set_weight_attrs(weight, extra_weight_attrs)