| import onnx |
| from onnx import onnx_pb as onnx_proto |
|
|
| from ..quant_utils import TENSOR_NAME_QUANT_SUFFIX, QuantizedValue, QuantizedValueType, attribute_to_kwarg, ms_domain |
| from .base_operator import QuantOperatorBase |
|
|
|
|
| class QLinearBinaryOp(QuantOperatorBase): |
| def __init__(self, onnx_quantizer, onnx_node): |
| super().__init__(onnx_quantizer, onnx_node) |
|
|
| def quantize(self): |
| node = self.node |
|
|
| ( |
| data_found, |
| output_scale_name, |
| output_zp_name, |
| _, |
| _, |
| ) = self.quantizer._get_quantization_params(node.output[0]) |
| ( |
| quantized_input_names, |
| zero_point_names, |
| scale_names, |
| nodes, |
| ) = self.quantizer.quantize_activation(node, [0, 1]) |
| if not data_found or quantized_input_names is None: |
| return super().quantize() |
|
|
| qlinear_binary_math_output = node.output[0] + TENSOR_NAME_QUANT_SUFFIX |
| qlinear_binary_math_name = node.name + "_quant" if node.name else "" |
|
|
| kwargs = {} |
| for attribute in node.attribute: |
| kwargs.update(attribute_to_kwarg(attribute)) |
| kwargs["domain"] = ms_domain |
|
|
| qlinear_binary_math_inputs = [] |
| |
| qlinear_binary_math_inputs.append(quantized_input_names[0]) |
| qlinear_binary_math_inputs.append(scale_names[0]) |
| qlinear_binary_math_inputs.append(zero_point_names[0]) |
| |
| qlinear_binary_math_inputs.append(quantized_input_names[1]) |
| qlinear_binary_math_inputs.append(scale_names[1]) |
| qlinear_binary_math_inputs.append(zero_point_names[1]) |
|
|
| |
| qlinear_binary_math_inputs.append(output_scale_name) |
| qlinear_binary_math_inputs.append(output_zp_name) |
|
|
| qlinear_binary_math_node = onnx.helper.make_node( |
| "QLinear" + node.op_type, |
| qlinear_binary_math_inputs, |
| [qlinear_binary_math_output], |
| qlinear_binary_math_name, |
| **kwargs, |
| ) |
| nodes.append(qlinear_binary_math_node) |
|
|
| |
| q_output = QuantizedValue( |
| node.output[0], |
| qlinear_binary_math_output, |
| output_scale_name, |
| output_zp_name, |
| QuantizedValueType.Input, |
| ) |
| self.quantizer.quantized_value_map[node.output[0]] = q_output |
|
|
| self.quantizer.new_nodes += nodes |
|
|
