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Upgrade version number for ORT in preparation for release (#1468)
* Update version number to 0.5.0 in preparation for release * Update to README.md to direct to Versioning doc * Resolve PR comment * Remove incorrect line generation * Minor updates to update version script * Minor comment update
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7 changed files with 20 additions and 8 deletions
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@ -6,7 +6,7 @@
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[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=12)
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[](https://dev.azure.com/onnxruntime/onnxruntime/_build/latest?definitionId=13)
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**ONNX Runtime** is a performance-focused complete scoring engine for Open Neural Network Exchange (ONNX) models, with an open extensible architecture to continually address the latest developments in AI and Deep Learning. ONNX Runtime stays up to date with the ONNX standard with complete implementation of **all** ONNX operators, and supports all ONNX releases (1.2+) with both future and backwards compatibility. **As of May 2019, ONNX Runtime supports up to ONNX 1.5 (Opset 10).**
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**ONNX Runtime** is a performance-focused complete scoring engine for Open Neural Network Exchange (ONNX) models, with an open extensible architecture to continually address the latest developments in AI and Deep Learning. ONNX Runtime stays up to date with the ONNX standard with complete implementation of **all** ONNX operators, and supports all ONNX releases (1.2+) with both future and backwards compatibility. Please refer to [this page](docs/Versioning.md) for ONNX opset compatibility details.
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[ONNX](https://onnx.ai) is an interoperable format for machine learning models supported by various ML and DNN frameworks and tools. The universal format makes it easier to interoperate between frameworks and maximize the reach of hardware optimization investments.
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@ -1 +1 @@
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0.4.0
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0.5.0
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@ -32,6 +32,7 @@ For more details on ONNX Release versions, see [this page](https://github.com/on
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| ONNX Runtime release version | ONNX release version | ONNX opset version | ONNX ML opset version | Supported ONNX IR version | [WinML compatibility](https://docs.microsoft.com/en-us/windows/ai/windows-ml/)|
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|------------------------------|--------------------|--------------------|----------------------|------------------|------------------|
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| 0.5.0 | 1.5 | 10 | 1 | 5 | -- |
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| 0.4.0 | 1.5 | 10 | 1 | 5 | -- |
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| 0.3.1<br>0.3.0 | 1.4 | 9 | 1 | 3 | -- |
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| 0.2.1<br>0.2.0 | 1.3 | 8 | 1 | 3 | 1903 (19H1)+ |
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@ -52,6 +52,11 @@ replaces *scikit-learn* to compute the predictions.
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Changes
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-------
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0.5.0
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^^^^^
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Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v0.5.0
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0.4.0
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^^^^^
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@ -12,7 +12,7 @@ community, it supports traditional ML models as well
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as Deep Learning algorithms in the
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`ONNX-ML format <https://github.com/onnx/onnx/blob/master/docs/IR.md>`_.
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"""
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__version__ = "0.4.0"
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__version__ = "0.5.0"
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__author__ = "Microsoft"
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from onnxruntime.capi import onnxruntime_validation
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@ -1,5 +1,5 @@
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Name: onnxruntime
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Version: 0.4.0
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Version: 0.5.0
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Release: 1%{?dist}
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Summary: onnxruntime
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@ -13,18 +13,23 @@ def update_version():
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for line in lines:
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if line.startswith('|'):
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sections = line.split('|')
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if len(sections) == 6 and sections[1].strip()[0].isdigit() :
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if len(sections) == 8 and sections[1].strip()[0].isdigit() :
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current_version = sections[1].strip()
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break
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print ('Current version of ORT seems to be: ' + current_version)
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if version != current_version:
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with open(file_path, 'w') as f:
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for i,line in enumerate(lines):
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f.write(line)
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if line.startswith('|--'):
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sections = lines[i+1].split('|')
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sections[1] = ' ' + version + ' '
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new_line = '|'.join(sections)
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f.write(new_line)
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# Make sure there are no 'False Positive' version additions
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# by making sure the line we are building a new line from
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# contains the current_version
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if len(sections) > 1 and sections[1].strip() == current_version:
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sections[1] = ' ' + version + ' '
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new_line = '|'.join(sections)
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f.write(new_line)
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lines = []
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current_version = ''
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file_path = os.path.join(cwd, '..', '..', 'docs', 'python', 'README.rst')
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@ -43,6 +48,7 @@ def update_version():
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if inserted == False and len(sections) == 3 and sections[0].isdigit() and sections[1].isdigit() and sections[2].isdigit():
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f.write(version + '\n')
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f.write('^^^^^\n\n')
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f.write('Release Notes : https://github.com/Microsoft/onnxruntime/releases/tag/v' + version.strip() + '\n\n')
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inserted = True
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f.write(line)
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lines = []
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