1# Copyright (c) Qualcomm Innovation Center, Inc. 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 executorch.backends.qualcomm.python.PyQnnWrapperAdaptor as PyQnnWrapper 10 11import numpy as np 12import torch 13from executorch.backends.qualcomm.utils.constants import QCOM_DATA 14 15from .node_visitor import NodeVisitor, register_node_visitor 16from .qnn_constants import OpReluMinMax, QNN_OP_PACKAGE_NAME_QTI_AISW 17 18 19@register_node_visitor 20class HardTanhVisitor(NodeVisitor): 21 target = ["aten.hardtanh.default"] 22 23 def __init__(self, *args) -> None: 24 super().__init__(*args) 25 26 def define_node( 27 self, 28 node: torch.fx.Node, 29 nodes_to_wrappers: Dict[torch.fx.Node, PyQnnWrapper.TensorWrapper], 30 ) -> PyQnnWrapper.PyQnnOpWrapper: 31 input_node = node.args[0] 32 input_tensor = self.get_tensor(input_node, node) 33 input_tensor_wrapper = self.define_tensor( 34 input_node, 35 input_tensor, 36 PyQnnWrapper.Qnn_TensorType_t.QNN_TENSOR_TYPE_NATIVE, 37 nodes_to_wrappers, 38 is_input_tensor=True, 39 ) 40 41 # default value of output_min and output_max 42 output_min = -1 43 output_max = 1 44 45 if len(node.args) > 1: 46 # update output_min 47 output_min = cast(float, node.args[1]) 48 # update output_max 49 output_max = cast(float, node.args[2]) 50 51 output_tensor = self.get_tensor(node, node) 52 output_tensor_wrapper = self.define_tensor( 53 node, 54 output_tensor, 55 PyQnnWrapper.Qnn_TensorType_t.QNN_TENSOR_TYPE_NATIVE, 56 nodes_to_wrappers, 57 is_input_tensor=False, 58 ) 59 60 hardtanh_op = PyQnnWrapper.PyQnnOpWrapper( 61 node.name, 62 QNN_OP_PACKAGE_NAME_QTI_AISW, 63 OpReluMinMax.op_name, 64 ) 65 hardtanh_op.AddInputTensors([input_tensor_wrapper]) 66 hardtanh_op.AddOutputTensors([output_tensor_wrapper]) 67 hardtanh_op.AddScalarParam( 68 OpReluMinMax.param_max_value, 69 PyQnnWrapper.Qnn_DataType_t.QNN_DATATYPE_FLOAT_32, 70 {QCOM_DATA: np.float32(output_max)}, 71 ) 72 hardtanh_op.AddScalarParam( 73 OpReluMinMax.param_min_value, 74 PyQnnWrapper.Qnn_DataType_t.QNN_DATATYPE_FLOAT_32, 75 {QCOM_DATA: np.float32(output_min)}, 76 ) 77 78 return hardtanh_op 79