per_channel_group can't be dynamic

backends/xnnpack/utils/quant_utils.py

@@ -12,6 +12,7 @@
 from executorch.exir.backend.canonical_partitioners.config_partitioner import (
     format_target_name,
 )
+from torch.fx.experimental.symbolic_shapes import free_symbols, has_free_symbols
 
 _Q_OPS = {
     "quantize_per_tensor.tensor",
@@ -126,8 +127,8 @@ def is_affine_qdq(node: torch.fx.Node) -> bool:
 def _get_block_size_input_scale(node: torch.fx.Node):
     assert is_affine_qdq(node)
     block_size = node.args[1]
-    input_val = node.all_input_nodes[0].meta["val"]
-    scale_val = node.all_input_nodes[1].meta["val"]
+    input_val = cast(torch.fx.Node, node.args[0]).meta["val"]
+    scale_val = cast(torch.fx.Node, node.args[2]).meta["val"]
     return block_size, input_val, scale_val
 
 
@@ -145,7 +146,21 @@ def is_per_token(node: torch.fx.Node):
             flag &= block_size[i] == 1
             scale_numel_expected *= input_val.shape[i]
 
-        flag &= block_size[-1] == input_val.shape[-1]
+        ic_block_size = block_size[-1]
+        if isinstance(ic_block_size, torch.fx.Node):
+            ic_block_size = ic_block_size.meta["val"]
+            assert free_symbols(
+                ic_block_size
+            ), f"block_size: {block_size} given, but {block_size[-1]} is not a dynamic symint"
+
+        ic_dim = input_val.shape[-1]
+        if isinstance(ic_dim, torch.fx.Node):
+            ic_dim = ic_dim.meta["val"]
+            assert free_symbols(
+                ic_dim
+            ), f"input_shape: {input_val.shape} given, but {input_val.shape[-1]} is not a dynamic symint"
+
+        flag &= ic_dim == ic_block_size
         flag &= scale_val.numel() == scale_numel_expected
         return flag
 
@@ -160,6 +175,11 @@ def is_per_channel_group(node: torch.fx.Node):
         return True
     elif is_affine_qdq(node):
         block_size, input_val, scale_val = _get_block_size_input_scale(node)
+        # per channel group is only valid on static weights
+        # so scales and weights can't have dynamic shape
+        if has_free_symbols(input_val.shape) or has_free_symbols(scale_val.shape):
+            return False
+
         flag = True
         flag &= len(block_size) == 2
         flag &= block_size[0] == 1