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Add quantized value map after quantize input node added. (#7558)

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Zhang Lei 2021-05-04 15:27:56 -07:00 committed by GitHub
parent a647da3e1a
commit f6cefc92e2
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1 changed files with 20 additions and 29 deletions
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49
onnxruntime/python/tools/quantization/onnx_quantizer.py
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@ -409,47 +409,38 @@ class ONNXQuantizer:
'''
input_name = node.input[input_index]
output_name = input_name + "_quantized"
ql_node_name = input_name + "_QuantizeLinear"
if (given_scale_name is not None) and (given_zp_name is not None):
data_found, scale_name, zp_name = (True, given_scale_name, given_zp_name)
else:
data_found, scale_name, zp_name, _, _ = self._get_quantization_params(input_name)
if self.static:
if data_found == False:
nodes = []
if data_found == True:
qlinear_node = onnx.helper.make_node("QuantizeLinear", [input_name, scale_name, zp_name],
[output_name], ql_node_name)
else:
if self.static:
raise ValueError(
"Quantization parameters are not specified for param {}."
"In static mode quantization params for inputs and outputs of nodes to be quantized are required.".
format(input_name))
qlinear_node = onnx.helper.make_node("QuantizeLinear", [input_name, scale_name, zp_name], [output_name],
input_name + "_QuantizeLinear")
return [qlinear_node]
else:
if data_found == True:
qlinear_node = onnx.helper.make_node("QuantizeLinear", [input_name, scale_name, zp_name], [output_name],
input_name + "_QuantizeLinear")
return [qlinear_node]
# dynamic mode
# Scale and Zero Points not available for this input. Add nodes to dynamically compute it
if self.fuse_dynamic_quant and qType == onnx_proto.TensorProto.UINT8:
scale_name = input_name + "_scale"
zp_name = input_name + "_zero_point"
qlinear_node = onnx.helper.make_node("DynamicQuantizeLinear", [input_name],
[output_name, scale_name, zp_name], ql_node_name)
else:
# Scale and Zero Points not available for this input. Add nodes to dynamically compute it
if self.fuse_dynamic_quant and qType == onnx_proto.TensorProto.UINT8:
scale_name = input_name + "_scale"
zeropoint_name = input_name + "_zero_point"
qlinear_node = onnx.helper.make_node("DynamicQuantizeLinear", [input_name],
[output_name, scale_name, zeropoint_name],
input_name + "_QuantizeLinear")
return [qlinear_node]
scale_name, zp_name, scale_shape, zp_shape = \
self._get_dynamic_input_quantization_params(input_name, nodes, qType)
qlinear_node = onnx.helper.make_node("QuantizeLinear", [input_name, scale_name, zp_name],
[output_name], ql_node_name)
else:
nodes = []
scale_name, zp_name, scale_shape, zp_shape = \
self._get_dynamic_input_quantization_params(
input_name, nodes, qType)
qlinear_node = onnx.helper.make_node("QuantizeLinear", [input_name, scale_name, zp_name],
[output_name], input_name + "_QuantizeLinear")
return nodes + [qlinear_node]
self.quantized_value_map[input_name] = QuantizedValue(input_name, output_name, scale_name, zp_name, qType)
return nodes + [qlinear_node]
def get_bias_add_nodes(self, nodes, node, last_output, quantized_bias_name):
'''