Add cadence.where_Scalar op

Differential Revision: D70539497

Pull Request resolved: #9764

Author: mcremon-meta

backends/cadence/aot/ops_registrations.py

@@ -162,6 +162,10 @@
     "quantized_fully_connected.per_tensor(Tensor src, Tensor weight, Tensor bias, int src_zero_point, "
     "int weight_zero_point, int out_multiplier, int out_shift, int out_zero_point, Tensor? offset) -> (Tensor Z)"
 )
+lib.define("where_Scalar(Tensor condition, float self, float other) -> (Tensor Z)")
+lib.define(
+    "where_Scalar.out(Tensor condition, float self, float other, *, Tensor(a!) out) -> Tensor(a!)"
+)
 
 # ------------------------------------ #
 #   Migrated from custom_ops.yaml      #
@@ -935,3 +939,12 @@ def transposed_im2row_meta(
     output_size = torch.Size((batch_size, output_length, n_output_plane))
 
     return input.new_empty(output_size, dtype=input.dtype)
+
+
+@register_fake("cadence::where_Scalar")
+def where_Scalar_meta(
+    condition: torch.Tensor,
+    self: float,
+    other: float,
+) -> torch.Tensor:
+    return condition.new_empty(condition.size(), dtype=torch.float32)

backends/cadence/aot/replace_ops.py

@@ -2062,6 +2062,54 @@ def call(self, graph_module: torch.fx.GraphModule) -> PassResult:
         return PassResult(ret.graph_module, modified)
 
 
+@register_cadence_pass(CadencePassAttribute(opt_level=1))
+class ReplaceWhereWithFullArgsWithWhereScalar(ExportPass):
+    """Replaces where ops using two full ops as tensors with a scalar
+    version.
+    """
+
+    def call_operator(
+        self,
+        op,
+        args: Tuple[Argument, ...],
+        kwargs: Dict[str, Argument],
+        meta: NodeMetadata,
+    ) -> ProxyValue:
+        if op not in {
+            exir_ops.edge.aten.where.self,
+        }:
+            return super().call_operator(op, args, kwargs, meta)
+
+        # If the args are not full ops, bail
+        # pyre-ignore[16]: `ProxyValue` has no attribute `node`.
+        if (args[1].node.target != exir_ops.edge.aten.full.default) or (
+            args[2].node.target != exir_ops.edge.aten.full.default
+        ):
+            return super().call_operator(op, args, kwargs, meta)
+
+        # If one of the full ops is a different size than than the cond tensor, we need to broadcast. Bail.
+        if (
+            # pyre-ignore[16]: `ProxyValue` has no attribute `node`.
+            list(args[0].to_tensor().shape) != args[1].node.args[0]
+            or list(args[0].to_tensor().shape) != args[2].node.args[0]
+        ):
+            return super().call_operator(op, args, kwargs, meta)
+
+        # Get the scalar values from the full ops
+        scalar_value_1 = args[1].node.args[1]
+        scalar_value_2 = args[2].node.args[1]
+
+        # Replace the where op with a scalar where op
+        return super().call_operator(
+            exir_ops.edge.cadence.where_Scalar.default,
+            (args[0], scalar_value_1, scalar_value_2),
+            kwargs,
+            meta,
+        )
+
+        return super().call_operator(op, args, kwargs, meta)
+
+
 # This class encapsulates all the functions that replace/switch one op in the
 # graph with another.
 class CadenceReplaceOpsInGraph:
@@ -2100,4 +2148,5 @@ class CadenceReplaceOpsInGraph:
         ReplaceSingleElementTensorArgumentsFromFullOpWithScalarPass,
         ReplaceAtenAvgPoolWithJarvisAvgPoolPass,
         ReplaceAtenLinalgVectorNormWithCadenceLinalgVectorNormPass,
+        ReplaceWhereWithFullArgsWithWhereScalar,
     ]

backends/cadence/aot/tests/test_replace_ops_passes.py

@@ -44,6 +44,7 @@
     ReplaceTCopyWithTransposePass,
     ReplaceTransposedConvWithLinearPass,
     ReplaceTrivialConvWithLinear,
+    ReplaceWhereWithFullArgsWithWhereScalar,
 )
 from executorch.exir.dialects._ops import ops as exir_ops
 from executorch.exir.pass_base import ExportPass
@@ -1217,6 +1218,89 @@ def forward(self, x: torch.Tensor):
             1,
         )
 
+    def test_replace_aten_where_with_cadence_where_Scalar(self):
+        class WhereScalarModel(torch.nn.Module):
+            def forward(self, cond: torch.Tensor):
+                a = torch.ops.aten.full.default(a_shape, val1)
+                b = torch.ops.aten.full.default(b_shape, val2)
+                return torch.where(cond > 0, a, b)
+
+        cond_shape, a_shape, b_shape, val1, val2 = [(4, 8), (4, 8), (4, 8), 0.0, 1.0]
+        cond = torch.randn(cond_shape)
+
+        graph_module = (
+            export_to_edge(WhereScalarModel(), (cond,)).exported_program().graph_module
+        )
+
+        p = ReplaceWhereWithFullArgsWithWhereScalar()
+        graph_after_passes = cast(PassResult, p(graph_module)).graph_module
+
+        # Assert that aten.where op was replaced by a
+        # cadence.where_Scalar op
+        self.assertEqual(
+            count_node(
+                graph_after_passes,
+                exir_ops.edge.aten.where.self,
+            ),
+            0,
+        )
+        self.assertEqual(
+            count_node(graph_after_passes, exir_ops.edge.cadence.where_Scalar.default),
+            1,
+        )
+
+        class WhereBroadcastModel(torch.nn.Module):
+            def forward(self, cond: torch.Tensor):
+                a = torch.ops.aten.full.default(a_shape, val1)
+                b = torch.ops.aten.full.default(b_shape, val2)
+                return torch.where(cond > 0, a, b)
+
+        # a tensor bigger than cond and b
+        cond_shape, a_shape, b_shape, val1, val2 = [(8,), (4, 8), (8,), 0.0, 1.0]
+        cond = torch.randn(cond_shape)
+
+        graph_module = (
+            export_to_edge(WhereBroadcastModel(), (cond,))
+            .exported_program()
+            .graph_module
+        )
+
+        p = ReplaceWhereWithFullArgsWithWhereScalar()
+        graph_after_passes = cast(PassResult, p(graph_module)).graph_module
+
+        # Assert that aten.where op is still in the graph since where_Scalar does not
+        # support broadcast
+        self.assertEqual(
+            count_node(
+                graph_after_passes,
+                exir_ops.edge.aten.where.self,
+            ),
+            1,
+        )
+
+        # cond tensor bigger than a and b
+        cond_shape, a_shape, b_shape, val1, val2 = [(4, 8), (8,), (8,), 0.0, 1.0]
+        cond = torch.randn(cond_shape)
+
+        graph_module = (
+            export_to_edge(WhereBroadcastModel(), (cond,))
+            .exported_program()
+            .graph_module
+        )
+
+        p = ReplaceWhereWithFullArgsWithWhereScalar()
+        graph_after_passes = cast(PassResult, p(graph_module)).graph_module
+
+        # Assert that aten.where op is still in the graph since where_Scalar does not
+        # support broadcast
+        self.assertEqual(
+            count_node(
+                graph_after_passes,
+                exir_ops.edge.aten.where.self,
+            ),
+            1,
+        )
+
 
 class TestReplaceIm2rowWithViewPass(unittest.TestCase):
     def test_no_replacement_for_conv(self):