mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-07-24 19:43:35 +00:00
6cdd2b4934
* add dml gpu pipelines
* add x86 to the gpu dml dev build pipeline
* Enable DML x86 builds
* Fix uint64_t -> size_t warning
* fix warnings
* enable dml on x86 ci builds
* operatorHelper 773 error uint32_t vs uint64_t
* operatorHelper 773 error uint32_t vs uint64_t
* make x86 pipeline use the gpu pool
* more warnings
* fix x86 directml path
* make dml nuget package
* disable tf_pnasnet_large
* disable zfnet512
* make validation use wildcards
* disable x86 dml gpu tests
* add args.
* update gpu.yml
* change nupkg wildcard
* add debug statements
* package x86 dml nupkg
* dont drop managed nuget again from dml pipeline build
* Add DML EULA
* directml license should be renamed to not clobber the existing license
* casing on dml package....
* {} to ()
* fix license name
* disable dml from x86 ci
* typo and cr feedback
* remove featurizers
* ship the dml pdb as well
236 lines
No EOL
14 KiB
Python
236 lines
No EOL
14 KiB
Python
# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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import argparse
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import sys
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import os
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def parse_arguments():
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parser = argparse.ArgumentParser(description="ONNX Runtime create nuget spec script (for hosting native shared library artifacts)",
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usage='')
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# Main arguments
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parser.add_argument("--package_name", required=True, help="ORT package name. Eg: Microsoft.ML.OnnxRuntime.Gpu")
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parser.add_argument("--package_version", required=True, help="ORT package version. Eg: 1.0.0")
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parser.add_argument("--target_architecture", required=True, help="Eg: x64")
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parser.add_argument("--build_config", required=True, help="Eg: RelWithDebInfo")
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parser.add_argument("--ort_build_path", required=True, help="ORT build directory.")
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parser.add_argument("--native_build_path", required=True, help="Native build output directory.")
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parser.add_argument("--packages_path", required=True, help="Nuget packages output directory.")
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parser.add_argument("--sources_path", required=True, help="OnnxRuntime source code root.")
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parser.add_argument("--commit_id", required=True, help="The last commit id included in this package.")
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parser.add_argument("--is_release_build", required=False, default=None, type=str, help="Flag indicating if the build is a release build. Accepted values: true/false.")
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return parser.parse_args()
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def generate_id(list, package_name):
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list.append('<id>' + package_name + '</id>')
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def generate_version(list, package_version):
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list.append('<version>' + package_version + '</version>')
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def generate_authors(list, authors):
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list.append('<authors>' + authors + '</authors>')
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def generate_owners(list, owners):
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list.append('<owners>' + owners + '</owners>')
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def generate_description(list, description):
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list.append('<description>' + description + '</description>')
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def generate_copyright(list, copyright):
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list.append('<copyright>' + copyright + '</copyright>')
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def generate_tags(list, tags):
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list.append('<tags>' + tags + '</tags>')
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def generate_icon_url(list, icon_url):
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list.append('<iconUrl>' + icon_url + '</iconUrl>')
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def generate_license(list):
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list.append('<license type="file">LICENSE.txt</license>')
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def generate_project_url(list, project_url):
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list.append('<projectUrl>' + project_url + '</projectUrl>')
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def generate_repo_url(list, repo_url, commit_id):
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list.append('<repository type="git" url="' + repo_url + '"' + ' commit="' + commit_id + '" />')
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def generate_dependencies(list, version):
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list.append('<dependencies>')
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# Support .Net Core
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list.append('<group targetFramework="NETCOREAPP">')
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list.append('<dependency id="Microsoft.ML.OnnxRuntime.Managed"' + ' version="' + version + '"/>')
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list.append('</group>')
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# Support .Net Standard
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list.append('<group targetFramework="NETSTANDARD">')
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list.append('<dependency id="Microsoft.ML.OnnxRuntime.Managed"' + ' version="' + version + '"/>')
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list.append('</group>')
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# Support .Net Framework
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list.append('<group targetFramework="NETFRAMEWORK">')
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list.append('<dependency id="Microsoft.ML.OnnxRuntime.Managed"' + ' version="' + version + '"/>')
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list.append('</group>')
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list.append('</dependencies>')
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def get_env_var(key):
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return os.environ.get(key)
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def generate_release_notes(list):
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list.append('<releaseNotes>')
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list.append('Release Def:')
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branch = get_env_var('BUILD_SOURCEBRANCH')
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list.append('\t' + 'Branch: ' + (branch if branch != None else ''))
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version = get_env_var('BUILD_SOURCEVERSION')
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list.append('\t' + 'Commit: ' + (version if version != None else ''))
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build_id = get_env_var('BUILD_BUILDID')
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list.append('\t' + 'Build: https://aiinfra.visualstudio.com/Lotus/_build/results?buildId=' + (build_id if build_id != None else ''))
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list.append('</releaseNotes>')
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def generate_metadata(list, args):
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metadata_list = ['<metadata>']
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generate_id(metadata_list, args.package_name)
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generate_version(metadata_list, args.package_version)
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generate_authors(metadata_list, 'Microsoft')
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generate_owners(metadata_list, 'Microsoft')
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generate_description(metadata_list, 'This package contains native shared library artifacts for all supported platforms of ONNX Runtime.')
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generate_copyright(metadata_list, '\xc2\xa9 ' + 'Microsoft Corporation. All rights reserved.')
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generate_tags(metadata_list, 'ONNX ONNX Runtime Machine Learning')
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generate_icon_url(metadata_list, 'https://go.microsoft.com/fwlink/?linkid=2049168')
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generate_license(metadata_list)
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generate_project_url(metadata_list, 'https://github.com/Microsoft/onnxruntime')
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generate_repo_url(metadata_list, 'https://github.com/Microsoft/onnxruntime.git', args.commit_id)
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generate_dependencies(metadata_list, args.package_version)
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generate_release_notes(metadata_list)
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metadata_list.append('</metadata>')
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list += metadata_list
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def generate_files(list, args):
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files_list = ['<files>']
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# Process headers
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files_list.append('<file src=' + '"' + os.path.join(args.sources_path, 'include\\onnxruntime\\core\\session\\onnxruntime_*.h') + '" target="build\\native\\include" />')
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files_list.append('<file src=' + '"' + os.path.join(args.sources_path, 'include\\onnxruntime\\core\\providers\\cpu\\cpu_provider_factory.h') + '" target="build\\native\\include" />')
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if (args.package_name != 'Microsoft.ML.OnnxRuntime.DirectML'):
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files_list.append('<file src=' + '"' + os.path.join(args.sources_path, 'include\\onnxruntime\\core\\providers\\cuda\\cuda_provider_factory.h') + '" target="build\\native\\include" />')
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else: # it is a DirectML package
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files_list.append('<file src=' + '"' + os.path.join(args.sources_path, 'include\\onnxruntime\\core\\providers\\dml\\dml_provider_factory.h') + '" target="build\\native\\include" />')
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# Process DirectML dll
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if os.path.exists(os.path.join(args.native_build_path, 'DirectML.dll')):
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files_list.append('<file src=' + '"' + os.path.join(args.native_build_path, 'DirectML.dll') + '" target="runtimes\\win-' + args.target_architecture + '\\native" />')
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files_list.append('<file src=' + '"' + os.path.join(args.native_build_path, 'DirectML.pdb') + '" target="runtimes\\win-' + args.target_architecture + '\\native" />')
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files_list.append('<file src=' + '"' + os.path.join(args.packages_path, 'DirectML.0.0.1\\LICENSE.txt') + '" target="DirectML_LICENSE.txt" />')
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# Process onnxruntime import lib, dll, and pdb
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files_list.append('<file src=' + '"' + os.path.join(args.native_build_path, 'onnxruntime.lib') + '" target="runtimes\\win-' + args.target_architecture + '\\native" />')
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files_list.append('<file src=' + '"' + os.path.join(args.native_build_path, 'onnxruntime.dll') + '" target="runtimes\\win-' + args.target_architecture + '\\native" />')
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files_list.append('<file src=' + '"' + os.path.join(args.native_build_path, 'onnxruntime.pdb') + '" target="runtimes\\win-' + args.target_architecture + '\\native" />')
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# Process Windows.AI.MachineLearning lib, dll, and pdb
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if (args.package_name == 'Microsoft.ML.OnnxRuntime.DirectML' or args.package_name == 'Microsoft.ML.OnnxRuntime') and os.path.exists(os.path.join(args.native_build_path, 'windows.ai.machinelearning.lib')):
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files_list.append('<file src=' + '"' + os.path.join(args.native_build_path, 'windows.ai.machinelearning.lib') + '" target="runtimes\\win-' + args.target_architecture + '\\native\\Windows.AI.MachineLearning.lib" />')
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if (args.package_name == 'Microsoft.ML.OnnxRuntime.DirectML' or args.package_name == 'Microsoft.ML.OnnxRuntime') and os.path.exists(os.path.join(args.native_build_path, 'windows.ai.machinelearning.dll')):
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files_list.append('<file src=' + '"' + os.path.join(args.native_build_path, 'windows.ai.machinelearning.dll') + '" target="runtimes\\win-' + args.target_architecture + '\\native\\Windows.AI.MachineLearning.dll" />')
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if (args.package_name == 'Microsoft.ML.OnnxRuntime.DirectML' or args.package_name == 'Microsoft.ML.OnnxRuntime') and os.path.exists(os.path.join(args.native_build_path, 'windows.ai.machinelearning.pdb')):
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files_list.append('<file src=' + '"' + os.path.join(args.native_build_path, 'windows.ai.machinelearning.pdb') + '" target="runtimes\\win-' + args.target_architecture + '\\native\\Windows.AI.MachineLearning.pdb" />')
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# Process windows.ai.machinelearning.winmd
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if (args.package_name == 'Microsoft.ML.OnnxRuntime.DirectML' or args.package_name == 'Microsoft.ML.OnnxRuntime') and os.path.exists(os.path.join(args.ort_build_path, args.build_config, 'windows.ai.machinelearning.winmd')):
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files_list.append('<file src=' + '"' + os.path.join(args.ort_build_path, args.build_config, 'windows.ai.machinelearning.winmd') + '" target="build\\native\\metadata\\Windows.AI.MachineLearning.winmd" />')
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# Process windows.ai.machinelearning headers
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if (args.package_name == 'Microsoft.ML.OnnxRuntime.DirectML' or args.package_name == 'Microsoft.ML.OnnxRuntime') and os.path.exists(os.path.join(args.ort_build_path, args.build_config, 'windows.ai.machinelearning.h')):
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files_list.append('<file src=' + '"' + os.path.join(args.ort_build_path, args.build_config, 'windows.ai.machinelearning.h') + '" target="build\\native\\include\\Windows.AI.MachineLearning.h" />')
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if (args.package_name == 'Microsoft.ML.OnnxRuntime.DirectML' or args.package_name == 'Microsoft.ML.OnnxRuntime') and os.path.exists(os.path.join(args.ort_build_path, args.build_config, 'windows.ai.machinelearning.native.h')):
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files_list.append('<file src=' + '"' + os.path.join(args.ort_build_path, args.build_config, 'windows.ai.machinelearning.native.h') + '" target="build\\native\\include\\Windows.AI.MachineLearning.Native.h" />')
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# Process dnll.dll
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if os.path.exists(os.path.join(args.native_build_path, 'dnnl.dll')):
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files_list.append('<file src=' + '"' + os.path.join(args.native_build_path, 'dnnl.dll') + '" target="runtimes\\win-' + args.target_architecture + '\\native" />')
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# Process mklml.dll
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if os.path.exists(os.path.join(args.native_build_path, 'mklml.dll')):
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files_list.append('<file src=' + '"' + os.path.join(args.native_build_path, 'mklml.dll') + '" target="runtimes\\win-' + args.target_architecture + '\\native" />')
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# Process libiomp5md.dll
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if os.path.exists(os.path.join(args.native_build_path, 'libiomp5md.dll')):
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files_list.append('<file src=' + '"' + os.path.join(args.native_build_path, 'libiomp5md.dll') + '" target="runtimes\\win-' + args.target_architecture + '\\native" />')
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# Process tvm.dll
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if os.path.exists(os.path.join(args.native_build_path, 'tvm.dll')):
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files_list.append('<file src=' + '"' + os.path.join(args.native_build_path, 'tvm.dll') + '" target="runtimes\\win-' + args.target_architecture + '\\native" />')
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# Process License, ThirdPartyNotices, Privacy, README
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files_list.append('<file src=' + '"' + os.path.join(args.sources_path, 'LICENSE.txt') + '" target="LICENSE.txt" />')
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files_list.append('<file src=' + '"' + os.path.join(args.sources_path, 'ThirdPartyNotices.txt') + '" target="ThirdPartyNotices.txt" />')
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files_list.append('<file src=' + '"' + os.path.join(args.sources_path, 'docs', 'Privacy.md') + '" target="Privacy.md" />')
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files_list.append('<file src=' + '"' + os.path.join(args.sources_path, 'docs', 'C_API.md') + '" target="README.md" />')
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# Process props file
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source_props = os.path.join(args.sources_path, 'csharp', 'src', 'Microsoft.ML.OnnxRuntime', 'props.xml')
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target_props = os.path.join(args.sources_path, 'csharp', 'src', 'Microsoft.ML.OnnxRuntime', args.package_name + '.props')
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os.system('copy ' + source_props + ' ' + target_props)
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files_list.append('<file src=' + '"' + target_props + '" target="build\\native" />')
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files_list.append('<file src=' + '"' + target_props + '" target="build\\netstandard1.1" />')
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# Process targets file
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source_targets = os.path.join(args.sources_path, 'csharp', 'src', 'Microsoft.ML.OnnxRuntime', 'targets.xml')
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target_targets = os.path.join(args.sources_path, 'csharp', 'src', 'Microsoft.ML.OnnxRuntime', args.package_name + '.targets')
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os.system('copy ' + source_targets + ' ' + target_targets)
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files_list.append('<file src=' + '"' + target_targets + '" target="build\\native" />')
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files_list.append('<file src=' + '"' + target_targets + '" target="build\\netstandard1.1" />')
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# Some tools to be packaged in nightly build only, should not be released
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# These are copied to the runtimes folder for convenience of loading with the dlls
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if args.is_release_build.lower() != 'true' and args.target_architecture == 'x64' and os.path.exists(os.path.join(args.native_build_path, 'onnxruntime_perf_test.exe')):
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files_list.append('<file src=' + '"' + os.path.join(args.native_build_path, 'onnxruntime_perf_test.exe') + '" target="runtimes\\win-' + args.target_architecture + '\\native" />')
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if args.is_release_build.lower() != 'true' and args.target_architecture == 'x64' and os.path.exists(os.path.join(args.native_build_path, 'onnx_test_runner.exe')):
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files_list.append('<file src=' + '"' + os.path.join(args.native_build_path, 'onnx_test_runner.exe') + '" target="runtimes\\win-' + args.target_architecture + '\\native" />')
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files_list.append('</files>')
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list += files_list
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def generate_nuspec(args):
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lines = ['<?xml version="1.0"?>']
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lines.append('<package>')
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generate_metadata(lines, args)
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generate_files(lines, args)
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lines.append('</package>')
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return lines
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def is_windows():
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return sys.platform.startswith("win")
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def main():
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if not is_windows():
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raise Exception('Native Nuget generation is currently supported only on Windows')
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# Parse arguments
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args = parse_arguments()
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if (args.is_release_build.lower() != 'true' and args.is_release_build.lower() != 'false'):
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raise Exception('Only valid options for IsReleaseBuild are: true and false')
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# Generate nuspec
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lines = generate_nuspec(args)
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# Create the nuspec needed to generate the Nuget
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with open(os.path.join(args.native_build_path, 'NativeNuget.nuspec'), 'w') as f:
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for line in lines:
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f.write(line)
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f.write('\n')
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if __name__ == "__main__":
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sys.exit(main()) |