Arm backend: Add docstrings for operator_support/ethos_u55_support.py

backends/arm/operator_support/ethos_u55_support.py

@@ -2,6 +2,13 @@
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
+"""Provide Ethos-U55 specific operator support checks.
+
+Contains dtype validation, explicit unsupported-op filtering, and shape/
+permutation constraints for view and permute operations when targeting the
+Ethos-U55 subset of TOSA.
+
+"""
 
 # pyre-unsafe
 
@@ -21,6 +28,19 @@
 
 
 def _try_determine_dtype(node: fx.Node) -> torch.dtype | None:
+    """Return an inferred dtype for a node when possible.
+
+    Uses fake tensor metadata and nearby quantize/dequantize nodes to infer the
+    integer dtype used by the operator. Returns ``None`` when the dtype cannot
+    be determined reliably.
+
+    Args:
+        node (fx.Node): FX node to inspect.
+
+    Returns:
+        torch.dtype | None: Inferred dtype or ``None`` if unknown.
+
+    """
     dtype = get_first_fake_tensor(node).dtype
     if not dtype.is_floating_point:
         return dtype
@@ -34,8 +54,23 @@ def _try_determine_dtype(node: fx.Node) -> torch.dtype | None:
 
 
 class EthosU55DtypeSupport(OperatorSupportBase):
+    """Validate dtypes for U55-supported operators.
+
+    Ensures operators use a supported integer dtype according to U55
+    constraints, with specific rules for convolution, matmul, and table ops.
+
+    Attributes:
+        reporter (WhyNoPartitionReporter): Reporter for rejection reasons.
+
+    """
 
     def __init__(self, reporter: WhyNoPartitionReporter):
+        """Initialize the check with a reporter.
+
+        Args:
+            reporter (WhyNoPartitionReporter): Reporter for rejection reasons.
+
+        """
         super().__init__()
         self.reporter = reporter
 
@@ -52,7 +87,20 @@ def __init__(self, reporter: WhyNoPartitionReporter):
     def is_node_supported(  # noqa: C901
         self, submodules: typing.Mapping[str, torch.nn.Module], node: fx.Node
     ) -> bool:
+        """Return True if the node uses supported dtypes.
 
+        Applies per-operator dtype rules for U55, including specialized input
+        and weight constraints for convolution and int8-only checks for table
+        operations and matmul variants.
+
+        Args:
+            submodules (typing.Mapping[str, torch.nn.Module]): Exported modules.
+            node (fx.Node): FX node to check.
+
+        Returns:
+            bool: True if supported; otherwise, False.
+
+        """
         dtype = _try_determine_dtype(node)
         if dtype is None:
             # If we couldn't determine dtype, just return ok.
@@ -112,10 +160,12 @@ def is_node_supported(  # noqa: C901
 
 
 class EthosU55NotSupported(OperatorSupportBase):
-    """
-    Certain operators are not supported on U55. These are listed in `unsupported_ops`.
-    The comment mentions the unsupported TOSA operator that the aten operator maps to where it is not obvious.
-    For unimplemented operators, this is the anticipated mapping, and it might be incorrect.
+    """Reject operators not supported by Ethos-U55.
+
+    The ``unsupported_ops`` list contains aten ops that either map to TOSA
+    operators the U55 cannot run or remain unimplemented. The mapping comments
+    capture expected TOSA equivalents when not obvious.
+
     """
 
     unsupported_ops = [
@@ -165,12 +215,27 @@ class EthosU55NotSupported(OperatorSupportBase):
     ]
 
     def __init__(self, reporter: WhyNoPartitionReporter):
+        """Initialize the check with a reporter.
+
+        Args:
+            reporter (WhyNoPartitionReporter): Reporter for rejection reasons.
+
+        """
         self.reporter = reporter
 
     def is_node_supported(
         self, submodules: typing.Mapping[str, torch.nn.Module], node: fx.Node
     ) -> bool:
+        """Return False for nodes explicitly unsupported on U55.
 
+        Args:
+            submodules (typing.Mapping[str, torch.nn.Module]): Exported modules.
+            node (fx.Node): FX node to check.
+
+        Returns:
+            bool: False if ``node.target`` is in ``unsupported_ops``; else True.
+
+        """
         if node.target in self.unsupported_ops:
             self.reporter.report_reject(node, "Op is not supported on U55.")
             return False
@@ -182,12 +247,37 @@ def is_node_supported(
 
 
 class EthosU55ViewCheck(OperatorSupportBase):
+    """Validate view/select shapes and dtypes for U55.
+
+    Performs lightweight checks on output shape rank and product constraints,
+    with awareness that transposes may be inserted around view/select during
+    lowering to channels-last.
+
+    Attributes:
+        reporter (WhyNoPartitionReporter): Reporter for rejection reasons.
+
+    """
 
     def __init__(self, reporter: WhyNoPartitionReporter):
+        """Initialize the check with a reporter.
+
+        Args:
+            reporter (WhyNoPartitionReporter): Reporter for rejection reasons.
+
+        """
         super().__init__()
         self.reporter = reporter
 
     def axes_product(self, nhwc_shape: shape_t) -> int:
+        """Return the product of all axes in ``nhwc_shape``.
+
+        Args:
+            nhwc_shape (list[int]): Shape in NHWC order.
+
+        Returns:
+            int: Product of the axis sizes.
+
+        """
         product = 1
         for axes in nhwc_shape:
             product *= axes
@@ -197,26 +287,27 @@ def axes_product(self, nhwc_shape: shape_t) -> int:
     def is_node_supported(
         self, submodules: typing.Mapping[str, torch.nn.Module], node: fx.Node
     ) -> bool:
-        """
-        Check whether a given view node is supported on U55.
+        """Check whether a given view/select node is U55-supported.
 
         Currently only checks dtypes and product of axes.
 
-        It is not the view operator itself that is not supported on U55. In order for the
-        view operator to be compatible with the channels-last format of TosaBackend,
-        transposes may need to be inserted before and after the view op. If that happens
-        and that transpose operator does not adhere to the limitations then it will
-        result in the following error:
+        It is not the view operator itself that is not supported on U55. In
+        order for the view operator to be compatible with the channels-last
+        format of TosaBackend, transposes may need to be inserted before and
+        after the view op. If that happens and that transpose operator does not
+        adhere to the limitations then it will result in the following error:
 
             CPU performance estimation for "Transpose" not implemented.
             ...
             CPU operations are not supported for GraphAPI input
 
         Args:
-            node: The FX node representing the view_copy operator.
+            submodules (typing.Mapping[str, torch.nn.Module]): Exported modules.
+            node (fx.Node): FX node for ``view_copy`` or ``select``.
 
         Returns:
-            False if the operator is not support and True if it is supported.
+            bool: False if rejected by constraints; otherwise, True.
+
         """
         # Select decomposes into squeeze, which in turn becomes a view. Therefore,
         # perform the same check on select operators as view operators.
@@ -279,14 +370,40 @@ def is_node_supported(
 
 
 class EthosU55TransposeCheck(OperatorSupportBase):
+    """Validate permute nodes against U55 reshape/transpose limits.
+
+    Applies dtype- and rank-specific constraints to permutations. Tests both
+    NCHW and NHWC interpretations for rank-3/4 shapes since dim order is unknown
+    at partition time.
+
+    Attributes:
+        reporter (WhyNoPartitionReporter): Reporter for rejection reasons.
+
+    """
 
     def __init__(self, reporter: WhyNoPartitionReporter):
+        """Initialize the check with a reporter.
+
+        Args:
+            reporter (WhyNoPartitionReporter): Reporter for rejection reasons.
+
+        """
         super().__init__()
         self.reporter = reporter
 
     def _pad_to_rank_4(
         self, shape: shape_t, permutation: list[int]
     ) -> tuple[shape_t, shape_t]:
+        """Pad shape/permutation to rank 4 by prepending ones/indices.
+
+        Args:
+            shape (list[int]): Original shape.
+            permutation (list[int]): Original permutation indices.
+
+        Returns:
+            tuple[list[int], list[int]]: Padded shape and permutation.
+
+        """
         diff = 4 - len(shape)
         padded_shape = [1] * diff + shape
         for i in range(len(permutation)):
@@ -295,6 +412,15 @@ def _pad_to_rank_4(
         return padded_shape, padded_permutation
 
     def axes_product(self, nhwc_shape: shape_t) -> int:
+        """Return the product of all axes in ``nhwc_shape``.
+
+        Args:
+            nhwc_shape (list[int]): Shape in NHWC order.
+
+        Returns:
+            int: Product of the axis sizes.
+
+        """
         product = 1
         for axes in nhwc_shape:
             product *= axes
@@ -303,7 +429,7 @@ def axes_product(self, nhwc_shape: shape_t) -> int:
     def _permute_constraint_i8_i16(
         self, nhwc_shape: list[int], permutation: list[int]
     ) -> bool:
-        """Returns True if the constraints are ok."""
+        """Return True if permutation meets i8/i16 constraints."""
         N, H, W, C = nhwc_shape
         match permutation:
             case (0, 1, 2, 3):  # NHWC -> NHWC
@@ -316,7 +442,7 @@ def _permute_constraint_i8_i16(
     def _permute_constraint_i32(
         self, nhwc_shape: list[int], permutation: list[int]
     ) -> bool:
-        """Returns True if the constraints are ok."""
+        """Return True if permutation meets i32 constraints."""
         N, H, W, C = nhwc_shape
         match permutation:
             case (0, 1, 2, 3):  # NHWC -> NHWC
@@ -329,6 +455,7 @@ def _permute_constraint_i32(
                 return False
 
     def _permute_constraint(self, shape, permutation, dtype):
+        """Return True if permutation meets dtype-specific constraints."""
         if dtype in (torch.int8, torch.int16):
             return self._permute_constraint_i8_i16(shape, permutation)
         if dtype == torch.int32:
@@ -338,7 +465,19 @@ def _permute_constraint(self, shape, permutation, dtype):
     def is_node_supported(
         self, submodules: typing.Mapping[str, torch.nn.Module], node: fx.Node
     ) -> bool:
+        """Return True if a permute node satisfies U55 constraints.
+
+        Tests both NCHW and NHWC interpretations for rank-3/4 shapes, and
+        applies dtype-specific limits to shapes and permutations.
+
+        Args:
+            submodules (typing.Mapping[str, torch.nn.Module]): Exported modules.
+            node (fx.Node): FX node to check.
+
+        Returns:
+            bool: True if supported; otherwise, False.
 
+        """
         if not node.target == exir_ops.edge.aten.permute_copy.default:
             return True