xref: /aosp_15_r20/external/executorch/backends/xnnpack/operators/op_clamp.py (revision 523fa7a60841cd1ecfb9cc4201f1ca8b03ed023a) 
1# Copyright (c) Meta Platforms, Inc. and affiliates.
2# All rights reserved.
3#
4# This source code is licensed under the BSD-style license found in the
5# LICENSE file in the root directory of this source tree.
6
7from typing import cast, Dict
8
9import torch
10from executorch.backends.xnnpack.operators.node_visitor import (
11    NodeVisitor,
12    register_node_visitor,
13)
14from executorch.backends.xnnpack.serialization.xnnpack_graph_schema import (
15    OutputMinMax,
16    XNNClamp,
17    XNNGraph,
18    XNode,
19)
20
21
22@register_node_visitor
23class ReluVisitor(NodeVisitor):
24    target = "aten.clamp.default"
25
26    def __init__(self, *args) -> None:
27        super().__init__(*args)
28
29    def define_node(
30        self,
31        node: torch.fx.Node,
32        xnn_graph: XNNGraph,
33        vals_to_ids: Dict[torch.fx.Node, int],
34        debug_handle: int,
35    ) -> None:
36        self.define_nodes_tensor_inputs_outputs(node, xnn_graph, vals_to_ids)
37
38        min_val = "-inf"
39        max_val = "inf"
40
41        if len(node.args) >= 2 and node.args[1] is not None:
42            min_val = cast(float, node.args[1])
43
44        if len(node.args) >= 3 and node.args[2] is not None:
45            max_val = cast(float, node.args[2])
46
47        # input_id
48        input_id = vals_to_ids[node.all_input_nodes[0]]
49
50        # output
51        output_id = vals_to_ids[node]
52
53        output_min_max = OutputMinMax(output_min=min_val, output_max=max_val)
54
55        ser_node = XNode(
56            xnode_union=XNNClamp(
57                input_id=input_id,
58                output_id=output_id,
59                flags=0,
60            ),
61            debug_handle=debug_handle,
62            output_min_max=output_min_max,
63        )
64        xnn_graph.xnodes.append(ser_node)
65