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Fix ONNX test_quantize unittest (#6716)

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Funtowicz Morgan 2020-08-25 19:24:40 +02:00 committed by GitHub
parent 074340339a
commit ac9702c284
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4 changed files with 22 additions and 24 deletions
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2
.github/workflows/self-push.yml vendored
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@ -45,7 +45,7 @@ jobs:
source .env/bin/activate
pip install --upgrade pip
pip install torch!=1.6.0
pip install .[sklearn,testing]
pip install .[sklearn,testing,onnxruntime]
- name: Are GPUs recognized by our DL frameworks
run: |

2
.github/workflows/self-scheduled.yml vendored
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@ -42,7 +42,7 @@ jobs:
source .env/bin/activate
pip install --upgrade pip
pip install torch!=1.6.0
pip install .[sklearn,testing]
pip install .[sklearn,testing,onnxruntime]
- name: Are GPUs recognized by our DL frameworks
run: |

5
setup.py
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@ -74,16 +74,17 @@ extras["tf"] = [
# "onnxconverter-common",
# "keras2onnx"
"onnxconverter-common @ git+git://github.com/microsoft/onnxconverter-common.git@f64ca15989b6dc95a1f3507ff6e4c395ba12dff5#egg=onnxconverter-common",
"keras2onnx @ git+git://github.com/onnx/keras-onnx.git@cbdc75cb950b16db7f0a67be96a278f8d2953b48#egg=keras2onnx"
"keras2onnx @ git+git://github.com/onnx/keras-onnx.git@cbdc75cb950b16db7f0a67be96a278f8d2953b48#egg=keras2onnx",
]
extras["tf-cpu"] = [
"tensorflow-cpu",
# "onnxconverter-common",
# "keras2onnx"
"onnxconverter-common @ git+git://github.com/microsoft/onnxconverter-common.git@f64ca15989b6dc95a1f3507ff6e4c395ba12dff5#egg=onnxconverter-common",
"keras2onnx @ git+git://github.com/onnx/keras-onnx.git@cbdc75cb950b16db7f0a67be96a278f8d2953b48#egg=keras2onnx"
"keras2onnx @ git+git://github.com/onnx/keras-onnx.git@cbdc75cb950b16db7f0a67be96a278f8d2953b48#egg=keras2onnx",
]
extras["torch"] = ["torch"]
extras["onnxruntime"] = ["onnxruntime>=1.4.0", "onnxruntime-tools>=1.4.2"]
extras["serving"] = ["pydantic", "uvicorn", "fastapi", "starlette"]
extras["all"] = extras["serving"] + ["tensorflow", "torch"]

37
src/transformers/convert_graph_to_onnx.py
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@ -364,32 +364,29 @@ def quantize(onnx_model_path: Path) -> Path:
Returns: The Path generated for the quantized
"""
try:
import onnx
from onnxruntime.quantization import QuantizationMode, quantize
import onnx
from onnxruntime.quantization import QuantizationMode, quantize
onnx_model = onnx.load(onnx_model_path.as_posix())
onnx_model = onnx.load(onnx_model_path.as_posix())
# Discussed with @yufenglee from ONNX runtime, this will be address in the next release of onnxruntime
print(
"As of onnxruntime 1.4.0, models larger than 2GB will fail to quantize due to protobuf constraint.\n"
"This limitation will be removed in the next release of onnxruntime."
)
# Discussed with @yufenglee from ONNX runtime, this will be address in the next release of onnxruntime
print(
"As of onnxruntime 1.4.0, models larger than 2GB will fail to quantize due to protobuf constraint.\n"
"This limitation will be removed in the next release of onnxruntime."
)
quantized_model = quantize(
model=onnx_model, quantization_mode=QuantizationMode.IntegerOps, force_fusions=True, symmetric_weight=True,
)
quantized_model = quantize(
model=onnx_model, quantization_mode=QuantizationMode.IntegerOps, force_fusions=True, symmetric_weight=True,
)
# Append "-quantized" at the end of the model's name
quantized_model_path = generate_identified_filename(onnx_model_path, "-quantized")
# Append "-quantized" at the end of the model's name
quantized_model_path = generate_identified_filename(onnx_model_path, "-quantized")
# Save model
print(f"Quantized model has been written at {quantized_model_path}: \N{heavy check mark}")
onnx.save_model(quantized_model, quantized_model_path.as_posix())
# Save model
print(f"Quantized model has been written at {quantized_model_path}: \N{heavy check mark}")
onnx.save_model(quantized_model, quantized_model_path.as_posix())
return quantized_model_path
except Exception as ie:
print(f"Error while quantizing the model:\n{str(ie)}")
return quantized_model_path
def verify(path: Path):