Arm backend: Add docstrings for operator_support/embedding_support.py

backends/arm/operator_support/embedding_support.py

@@ -2,7 +2,12 @@
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
+"""Declare operator support for ``aten.embedding`` in TOSA.
 
+Permit embeddings with int32 indices (TOSA lacks int64 support); other dtypes
+are rejected by this check.
+
+"""
 
 import torch
 
@@ -17,6 +22,8 @@
 
 @register_tosa_support_check
 class EmbeddingSupported(SupportedTOSAOperatorCheck):
+    """Provide TOSA support check for ``aten.embedding``."""
+
     targets = [exir_ops.edge.aten.embedding.default]
 
     tosa_specs = [
@@ -27,16 +34,20 @@ class EmbeddingSupported(SupportedTOSAOperatorCheck):
     def is_node_tosa_supported(
         self, node: fx.Node, tosa_spec: TosaSpecification
     ) -> bool:  # type: ignore[override, misc]
-        # Note aten.embedding.default requires int64 indices and TOSA does not
-        # support it. Int32 indices here for aten.embedding.default is ok since
-        # it will be decomposed into ops that can handle it.
+        """Return True if the node is supported by TOSA.
 
+        PyTorch's ``aten.embedding`` typically takes int64 indices, but for
+        TOSA we only allow int32 indices. The export path decomposes the op so
+        that int32 indices are ok.
+
+        """
         if len(node.all_input_nodes) != 2:
             self.reporter.report_reject(
                 node,
                 (f"Expected exactly two input nodes, got {len(node.all_input_nodes)}"),
             )
             return False
+
         indices_val = node.all_input_nodes[1].meta["val"]
         indices_dtype = indices_val.dtype