saymrwulf/onnxruntime
1
0
Fork 0
mirror of https://github.com/saymrwulf/onnxruntime.git synced 2026-07-24 19:43:35 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

Support u8u8 in quantization tool (#3140)

Browse source
This commit is contained in:
Yufeng Li 2020-03-05 14:42:46 -08:00 committed by GitHub
parent ade4fa108f
commit 1d2b8115e2
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
1 changed files with 9 additions and 6 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

15
onnxruntime/python/tools/quantization/quantize.py
View file

@ -1221,7 +1221,7 @@ def check_opset_version(org_model, force_fusions):
return fuse_dynamic_quant
def quantize(model, per_channel=False, nbits=8, quantization_mode=QuantizationMode.IntegerOps,
static=False, force_fusions=False, asymmetric_input_types=False,
static=False, force_fusions=False, symmetric_activation=False, symmetric_weight=False,
quantization_params=None, nodes_to_quantize=None):
'''
Given an onnx model, create a quantized onnx model and save it into a file
@ -1243,9 +1243,12 @@ def quantize(model, per_channel=False, nbits=8, quantization_mode=QuantizationMo
True: Fuses nodes added for dynamic quantization
False: No fusion is applied for nodes which are added for dynamic quantization.
Should be only used in cases where backends want to apply special fusion routines
:param asymmetric_input_types:
True: Weights are quantized into signed integers and inputs/activations into unsigned integers.
False: Weights and inputs/activations are quantized into unsigned integers.
:param symmetric_activation:
True: activations are quantized into signed integers.
False: activations are quantized into unsigned integers.
:param symmetric_weight:
True: weights are quantized into signed integers.
False: weights are quantized into unsigned integers.
:param quantization_params:
Dictionary to specify the zero point and scale values for inputs to conv and matmul nodes.
Should be specified when static is set to True.
@ -1270,8 +1273,8 @@ def quantize(model, per_channel=False, nbits=8, quantization_mode=QuantizationMo
]
'''
if nbits == 8:
input_qType = onnx_proto.TensorProto.UINT8
weight_qType = onnx_proto.TensorProto.INT8 if asymmetric_input_types else onnx_proto.TensorProto.UINT8
input_qType = onnx_proto.TensorProto.INT8 if symmetric_activation else onnx_proto.TensorProto.UINT8
weight_qType = onnx_proto.TensorProto.INT8 if symmetric_weight else onnx_proto.TensorProto.UINT8
mode = quantization_mode
copy_model = onnx_proto.ModelProto()
copy_model.CopyFrom(model)