VLLM Workaround

stack-info: PR: #2165, branch: drisspg/stack/52

Author: drisspg

torchao/prototype/mx_formats/utils.py

@@ -35,13 +35,14 @@ def to_blocked(input_matrix) -> Tensor:
     padded_cols = n_col_blocks * 4
 
     padded = input_matrix
-    # if (rows, cols) != (padded_rows, padded_cols):
-    padded = torch.zeros(
-        (padded_rows, padded_cols),
-        device=input_matrix.device,
-        dtype=input_matrix.dtype,
-    )
-    padded[:rows, :cols] = input_matrix
+    # TODO This is to work around VLLM's usage of compile w/ dynamic shapes
+    if torch.compiler.is_compiling() or (rows, cols) != (padded_rows, padded_cols):
+        padded = torch.zeros(
+            (padded_rows, padded_cols),
+            device=input_matrix.device,
+            dtype=input_matrix.dtype,
+        )
+        padded[:rows, :cols] = input_matrix
 
     # Rearrange the blocks
     blocks = padded.view(n_row_blocks, 128, n_col_blocks, 4).permute(0, 2, 1, 3)