[microNPU] Add NHWC -> NHCWB16 layout transformation pass (apache#9561)

Adds a layout optimization pass that modifies the ifm/ofm layout
of an operation to NHCWB16 where possible. This can occur when the
producer or consumer of a tensor is also an NPU operator.

Author: lhutton1

python/tvm/relay/backend/contrib/ethosu/codegen.py

@@ -134,6 +134,134 @@ def transform_function(
         return OptimizeLUTs().visit(func)
 
 
+class LayoutOptimization(ExprMutator):
+    """A pass to optimize the layout of NPU operations. If both the
+    producer and consumer of a tensor are NPU operators, then the
+    layout is converted from NHWC to NHCWB16.
+
+    Attributes
+    ----------
+    children : Dict[tvm.relay.expr.Call, List[tvm.relay.expr.Call]]
+        A map from current call to a list of calls that rely on the current
+        call. This allows the graph to be traversed backwards, which is useful
+        for checking whether the output layouts can be rewritten.
+    optimize_op : Dict[str, Callable]
+        A map from NPU op name to function that creates NPU op.
+    """
+
+    def __init__(self):
+        self.children = {}
+        self.optimize_op = {
+            "contrib.ethosu.conv2d": op.ethosu_conv2d,
+            "contrib.ethosu.depthwise_conv2d": op.ethosu_depthwise_conv2d,
+            "contrib.ethosu.pooling": op.ethosu_pooling,
+            "contrib.ethosu.binary_elementwise": op.ethosu_binary_elementwise,
+            "contrib.ethosu.unary_elementwise": op.ethosu_unary_elementwise,
+        }
+
+        super().__init__()
+
+    def alter_ethosu_op_layout(self, call: tvm.relay.expr.Call) -> tvm.relay.expr.Call:
+        """Alter the input and output layouts of an NPU operation if needed.
+        Input layout is only altered if the producing operation is an NPU
+        operation. Likewise, the output layout is only altered if the consuming
+        operation is an NPU operation.
+
+        Parameters
+        ----------
+        call : tvm.relay.expr.Call
+            The call pointing to an NPU operation that will be checked if
+            the layout needs altering.
+
+        Returns
+        -------
+        new_call : tvm.relay.expr.Call
+            New call with altered layouts.
+        """
+        assert isinstance(call.attrs, tvm.ir.Attrs), (
+            f"The attributes for operator '{call.op.name}' could not be "
+            "found. Did you register the relay.attrs.Ethosu<opname>Attrs "
+            "object in python api?"
+        )
+
+        new_attrs = dict(call.attrs)
+        parents = []
+
+        # Check if we can rewrite the input layouts
+        input_count = 0
+        for arg in call.args:
+            input_count += 1
+            if not isinstance(arg, tvm.relay.expr.Call):
+                continue
+            if isinstance(arg.op, tvm.ir.op.Op) and arg.op.name in self.optimize_op:
+                layout_string = "ifm_layout" if input_count <= 1 else f"ifm{input_count}_layout"
+                new_attrs[layout_string] = "NHCWB16"
+            parents.append(arg)
+
+        # Check if we can rewrite the output layouts
+        if call in self.children:
+            children = self.children[call]
+            if all(
+                isinstance(child, tvm.relay.expr.Call)
+                and isinstance(child.op, tvm.ir.op.Op)
+                and child.op.name in self.optimize_op
+                and child.attrs["ifm_layout"] == "NHCWB16"
+                for child in children
+            ):
+                new_attrs["ofm_layout"] = "NHCWB16"
+
+        name = call.op.name
+        assert name in self.optimize_op, (
+            f"Could not create operator '{name}' as the creation function "
+            "is unknown. Please provide a mapping."
+        )
+        new_call = self.optimize_op[name](*call.args, **new_attrs)
+
+        # Update map of children
+        for input_arg in parents:
+            if input_arg in self.children:
+                self.children[input_arg].append(new_call)
+            else:
+                self.children[input_arg] = [new_call]
+
+        return super().visit_call(new_call)
+
+    def visit_call(self, call: tvm.relay.expr.Call) -> tvm.relay.expr.Call:
+        """Recursively visit call nodes in the input graph and alter the
+        layout of an op if needed.
+
+        Parameters
+        ----------
+        call : tvm.relay.expr.Call
+            The current call node being visited.
+
+        Returns
+        -------
+        tvm.relay.expr.Call
+            The input call node in the case the current call node does
+            not refer to an Op. Else, a new call node with altered Op
+            attributes.
+        """
+        if isinstance(call.op, tvm.ir.op.Op) and call.op.name in self.optimize_op:
+            return self.alter_ethosu_op_layout(call)
+        return super().visit_call(call)
+
+
+@relay.transform.function_pass(opt_level=1, name="LayoutOptimizer")
+class LayoutOptimizer(Pass):
+    """Register LayoutOptimizer as a Relay pass."""
+
+    def transform_function(
+        self, func: tvm.relay.function.Function, mod: tvm.IRModule, _
+    ) -> tvm.IRModule:
+        """A pass to optimize the layout of NPU operations. If both the
+        producer and consumer of a tensor are NPU operators, then the
+        layout is converted from NHWC to NHCWB16 as this is the layout NPU
+        uses internally."""
+        assert len(mod.functions.items()) == 1, "Module can only contain one function."
+        return LayoutOptimization().visit(func)
+
+
 @tvm._ffi.register_func("relay.ext.ethos-u.constant_updater")
 def constant_updater(expr, symbol):  # pylint: disable=unused-argument
     """

python/tvm/relay/backend/contrib/ethosu/op/op_attrs.py

@@ -37,3 +37,13 @@ class EthosuDepthwiseConv2DAttrs(Attrs):
 @tvm._ffi.register_object("relay.attrs.EthosuPoolingAttrs")
 class EthosuPooling2DAttrs(Attrs):
     """Attributes for contrib.ethosu.pooling."""
+
+
+@tvm._ffi.register_object("relay.attrs.EthosuBinaryElementwiseAttrs")
+class EthosuBinaryElementwiseAttrs(Attrs):
+    """Attributes for contrib.ethosu.binary_elementwise"""
+
+
+@tvm._ffi.register_object("relay.attrs.EthosuUnaryElementwiseAttrs")
+class EthosuUnaryElementwiseAttrs(Attrs):
+    """Attributes for contrib.ethosu.unary_elementwise"""