Support exp op in XNNPACK backend

Author: leafs1

backends/xnnpack/operators/__init__.py

@@ -19,6 +19,7 @@
     op_dynamic_dequantize_ops,
     op_dynamic_quantize_ops,
     op_elu,
+    op_exp,
     op_floor,
     op_gelu,
     op_hardswish,

backends/xnnpack/operators/op_exp.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 (
+    XNNExp,
+    XNNGraph,
+    XNode,
+)
+from executorch.backends.xnnpack.utils.utils import get_input_node
+
+
+@register_node_visitor
+class ExpVisitor(NodeVisitor):
+    target = "aten.exp.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=XNNExp(
+                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

@@ -25,10 +25,11 @@
     ConstantPadConfig,
     DeQuantizedPerTensorConfig,
     DivConfig,
+    # EluConfig,
+    ExpConfig,
     FloorConfig,
     GeluConfig,
     HardswishConfig,
-    # EluConfig,
     HardtanhConfig,
     LeakyReLUConfig,
     LogConfig,
@@ -79,6 +80,7 @@
     ClampConfig,
     DivConfig,
     # EluConfig, # Waiting for PyTorch Pin Update
+    ExpConfig,
     FloorConfig,
     GeluConfig,
     HardtanhConfig,

backends/xnnpack/partition/config/generic_node_configs.py

@@ -336,6 +336,13 @@ def get_original_aten(self) -> Optional[torch._ops.OpOverload]:
         return torch.ops.aten.upsample_bilinear2d.vec
 
 
+class ExpConfig(GenericNodePartitionerConfig):
+    target_name = "exp.default"
+
+    def supported_precision_types(self) -> List[ConfigPrecisionType]:
+        return [ConfigPrecisionType.FP32]
+
+
 class FloorConfig(GenericNodePartitionerConfig):
     target_name = "floor.default"
 

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.exp.default,
 ]
 
 SUPPORTED_MODULES = [