Support qmatmul with different dims tensors

Summary:
MobileBERT exposes an issue in our kernel, where tensors have compatible (for PyTorch) but different batch dimensions.

This diff changes the meta kernel to support that (the kernel can already do it).

Differential Revision: D60314979

backends/cadence/aot/ops_registrations.py

@@ -4,6 +4,7 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+from math import prod
 from typing import Optional, Tuple
 
 import torch
@@ -186,28 +187,29 @@ def quantized_matmul_meta(
     X_size = list(X.size())
     Y_size = list(Y.size())
 
-    assert len(X_size) == len(
-        Y_size
-    ), "quantized matmul not supported for tensors of different dimensions"
-
-    if len(X_size) == 3:
-        assert (
-            X_size[0] == Y_size[0]
-        ), "quantized matmul only supported for batch dimension of same size"
-        if transposed:
-            assert X_size[2] == Y_size[2], "matrices cannot be multiplied"
-            out_size = X_size[:2] + [Y_size[1]]
-        else:
-            assert X_size[2] == Y_size[1], "matrices cannot be multiplied"
-            out_size = X_size[:2] + [Y_size[2]]
-    elif len(X_size) == 2:
-        if transposed:
-            assert X_size[1] == Y_size[1], "matrices cannot be multiplied"
-            out_size = [X_size[0], Y_size[0]]
-        else:
-            assert X_size[1] == Y_size[0], "matrices cannot be multiplied"
-            out_size = [X_size[0], Y_size[1]]
+    # Get the batch dimensions for both tensors
+    X_batch_dims = X_size[:-2]
+    Y_batch_dims = Y_size[:-2]
+
+    # If they don't match, check that they're compatible
+    if X_batch_dims != Y_batch_dims:
+        assert prod(X_batch_dims) == prod(
+            Y_batch_dims
+        ), f"Batch dimensions of X and Y do not match: {X_batch_dims} vs {Y_batch_dims}"
+
+    # Get the matmul output size
+    if transposed:
+        assert X_size[-1] == Y_size[-1], "matrices cannot be multiplied"
+        mat_size = [X_size[-2], Y_size[-2]]
     else:
-        raise AssertionError("quantized matmul only supported for 2D or 3D tensors")
+        assert X_size[-1] == Y_size[-2], "matrices cannot be multiplied"
+        mat_size = [X_size[-2], Y_size[-1]]
+
+    # Combine the larger batch dimensions with the matmul output size
+    out_size = (
+        X_batch_dims + mat_size
+        if len(X_batch_dims) > len(Y_batch_dims)
+        else Y_batch_dims + mat_size
+    )
 
     return X.new_empty(out_size, dtype=X.dtype)