Add tanh op to XNNPACK backend

Author: leafs1

backends/xnnpack/operators/__init__.py

@@ -50,5 +50,6 @@
     op_static_constant_pad,
     op_static_resize_bilinear_2d,
     op_sub,
+    op_tanh,
     op_to_copy,
 )

backends/xnnpack/operators/op_tanh.py

@@ -0,0 +1,52 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+from typing import Dict
+
+import torch
+from executorch.backends.xnnpack.operators.node_visitor import (
+    NodeVisitor,
+    register_node_visitor,
+)
+from executorch.backends.xnnpack.serialization.xnnpack_graph_schema import (
+    XNNGraph,
+    XNNTanh,
+    XNode,
+)
+from executorch.backends.xnnpack.utils.utils import get_input_node
+
+
+@register_node_visitor
+class TanhVisitor(NodeVisitor):
+    target = "aten.tanh.default"
+
+    def __init__(self, *args) -> None:
+        super().__init__(*args)
+
+    def define_node(
+        self,
+        node: torch.fx.Node,
+        xnn_graph: XNNGraph,
+        vals_to_ids: Dict[torch.fx.Node, int],
+        debug_handle: int,
+    ) -> None:
+        self.define_nodes_tensor_inputs_outputs(node, xnn_graph, vals_to_ids)
+
+        # input
+        input_id = vals_to_ids[get_input_node(node, 0)]
+
+        # output
+        output_id = vals_to_ids[node]
+
+        ser_node = XNode(
+            xnode_union=XNNTanh(
+                input_id=input_id,
+                output_id=output_id,
+                flags=0,
+            ),
+            debug_handle=debug_handle,
+        )
+        xnn_graph.xnodes.append(ser_node)

backends/xnnpack/partition/config/__init__.py

@@ -49,6 +49,7 @@
     SoftmaxConfig,
     SquareRootConfig,
     SubConfig,
+    TanhConfig,
     UpsampleBilinear2dConfig,
 )
 from executorch.backends.xnnpack.partition.config.node_configs import (
@@ -99,6 +100,7 @@
     PreluConfig,
     ReciprocalSquareRootConfig,
     ReLUConfig,
+    TanhConfig,
     # SDPAConfig, TODO: D60553559: preserving SDPA for fairseq fails
     SigmoidConfig,
     SliceCopyConfig,

backends/xnnpack/partition/config/generic_node_configs.py

@@ -371,6 +371,13 @@ def supported_precision_types(self) -> List[ConfigPrecisionType]:
         return [ConfigPrecisionType.FP32]
 
 
+class TanhConfig(GenericNodePartitionerConfig):
+    target_name = "tanh.default"
+
+    def supported_precision_types(self) -> List[ConfigPrecisionType]:
+        return [ConfigPrecisionType.FP32]
+
+
 class MeanDimConfig(GenericNodePartitionerConfig):
     target_name = "mean.dim"
 

backends/xnnpack/partition/configs.py

@@ -66,6 +66,7 @@
     exir_ops.edge.aten.rsqrt.default,
     exir_ops.edge.aten.log.default,
     exir_ops.edge.aten.gelu.default,
+    exir_ops.edge.aten.tanh.default,
 ]
 
 SUPPORTED_MODULES = [