| #!/usr/bin/env python3 |
| |
| from dataclasses import asdict, dataclass, field |
| from pathlib import Path |
| from typing import Set |
| |
| import jinja2 |
| from typing_extensions import Literal |
| |
| YamlShellBool = Literal["''", 1] |
| Arch = Literal["windows", "linux"] |
| |
| DOCKER_REGISTRY = "308535385114.dkr.ecr.us-east-1.amazonaws.com" |
| GITHUB_DIR = Path(__file__).resolve().parent.parent |
| |
| WINDOWS_CPU_TEST_RUNNER = "windows.4xlarge" |
| WINDOWS_CUDA_TEST_RUNNER = "windows.8xlarge.nvidia.gpu" |
| WINDOWS_RUNNERS = { |
| WINDOWS_CPU_TEST_RUNNER, |
| WINDOWS_CUDA_TEST_RUNNER, |
| } |
| |
| LINUX_CPU_TEST_RUNNER = "linux.2xlarge" |
| LINUX_CUDA_TEST_RUNNER = "linux.8xlarge.nvidia.gpu" |
| LINUX_RUNNERS = { |
| LINUX_CPU_TEST_RUNNER, |
| LINUX_CUDA_TEST_RUNNER, |
| } |
| |
| |
| # TODO: ------------- Remove the comment once fully rollout ------------------- |
| # Rollout Strategy: |
| # 1. Manual Phase |
| # step 1. Add 'ciflow/default' label to the PR |
| # step 2. Once there's an [unassigned] event from PR, it should rerun |
| # step 3. Remove 'ciflow/default' label |
| # step 4. Trigger the [unassigned] event again, it should not rerun |
| # 2. Probot Phase 1 (manual on 1 workflow) |
| # step 1. Probot automatically add labels based on the context |
| # step 2. Manually let probot trigger [unassigned] event |
| # 3. Probot Phase 2 (auto on 1 workflows) |
| # step 1. Modify the workflows so that they only listen on [unassigned] events |
| # step 2. Probot automatically adds labels automatically based on the context |
| # step 3. Probot automatically triggers [unassigned] event |
| # 4. Probot Phase 3 (auto on many workflows) |
| # step 1. Enable it for all workflows |
| # ----------------------------------------------------------------------- |
| @dataclass |
| class CIFlowConfig: |
| enabled: bool = False |
| labels: Set[str] = field(default_factory=set) |
| trigger_action: str = 'unassigned' |
| trigger_actor: str = 'pytorchbot' |
| root_job_name: str = 'ciflow_should_run' |
| root_job_condition: str = '' |
| |
| # trigger_action_only controls if we listen only on the trigger_action of a pull_request. |
| # If it's False, we listen on all default pull_request actions, this is useful when |
| # ciflow (via probot) is not automated yet. |
| trigger_action_only: bool = False |
| |
| def gen_root_job_condition(self) -> None: |
| # TODO: Make conditions strict |
| # At the beginning of the rollout of ciflow, we keep everything the same as what we have |
| # Once fully rollout, we can have strict constraints |
| # e.g. ADD env.GITHUB_ACTOR == '{self.trigger_actor} |
| # REMOVE github.event.action !='{self.trigger_action}' |
| label_conditions = [f"github.event.action == '{self.trigger_action}'"] + \ |
| [f"contains(github.event.pull_request.labels.*.name, '{label}')" for label in self.labels] |
| self.root_job_condition = f"(github.event_name != 'pull_request') || " \ |
| f"(github.event.action !='{self.trigger_action}') || " \ |
| f"({' && '.join(label_conditions)})" |
| |
| def reset_root_job(self) -> None: |
| self.root_job_name = '' |
| self.root_job_condition = '' |
| |
| def __post_init__(self) -> None: |
| if not self.enabled: |
| self.reset_root_job() |
| return |
| self.gen_root_job_condition() |
| |
| |
| @dataclass |
| class CIWorkflow: |
| # Required fields |
| arch: Arch |
| build_environment: str |
| test_runner_type: str |
| |
| # Optional fields |
| ciflow_config: CIFlowConfig = field(default_factory=CIFlowConfig) |
| cuda_version: str = '' |
| docker_image_base: str = '' |
| enable_doc_jobs: bool = False |
| exclude_test: bool = False |
| is_libtorch: bool = False |
| is_scheduled: str = '' |
| num_test_shards: int = 1 |
| on_pull_request: bool = False |
| only_build_on_pull_request: bool = False |
| |
| # The following variables will be set as environment variables, |
| # so it's easier for both shell and Python scripts to consume it if false is represented as the empty string. |
| enable_jit_legacy_test: YamlShellBool = "''" |
| enable_multigpu_test: YamlShellBool = "''" |
| enable_nogpu_no_avx_test: YamlShellBool = "''" |
| enable_nogpu_no_avx2_test: YamlShellBool = "''" |
| enable_slow_test: YamlShellBool = "''" |
| |
| def __post_init__(self) -> None: |
| if self.is_libtorch: |
| self.exclude_test = True |
| |
| # The following code allows for scheduled jobs to be debuggable by |
| # adding the label 'ciflow/scheduled' and assigning + unassigning pytorchbot, |
| # without overwriting the workflow's own ciflow_config, if already enabled. |
| if self.is_scheduled: |
| if self.ciflow_config.enabled: |
| self.ciflow_config.labels.add('ciflow/scheduled') |
| else: |
| self.ciflow_config = CIFlowConfig( |
| enabled=True, |
| labels={'ciflow/scheduled'} |
| ) |
| |
| # CIFlow requires on_pull_request to be set in order to be enabled. |
| # If on_pull_request wasn't previously specified, we set trigger_action_only |
| # to True as we want to avoid unintentional pull_request event triggers |
| if self.ciflow_config.enabled: |
| self.ciflow_config.trigger_action_only = self.ciflow_config.trigger_action_only or not self.on_pull_request |
| self.on_pull_request = True |
| |
| if not self.on_pull_request: |
| self.only_build_on_pull_request = False |
| |
| self.assert_valid() |
| |
| def assert_valid(self) -> None: |
| err_message = f"invalid test_runner_type for {self.arch}: {self.test_runner_type}" |
| if self.arch == 'linux': |
| assert self.test_runner_type in LINUX_RUNNERS, err_message |
| if self.arch == 'windows': |
| assert self.test_runner_type in WINDOWS_RUNNERS, err_message |
| |
| def generate_workflow_file(self, workflow_template: jinja2.Template) -> None: |
| output_file_path = GITHUB_DIR / f"workflows/{workflow.build_environment}.yml" |
| with open(output_file_path, "w") as output_file: |
| GENERATED = "generated" |
| output_file.writelines([f"# @{GENERATED} DO NOT EDIT MANUALLY\n"]) |
| output_file.write(workflow_template.render(asdict(workflow))) |
| output_file.write("\n") |
| print(output_file_path) |
| |
| |
| WINDOWS_WORKFLOWS = [ |
| CIWorkflow( |
| arch="windows", |
| build_environment="pytorch-win-vs2019-cpu-py3", |
| cuda_version="cpu", |
| test_runner_type=WINDOWS_CPU_TEST_RUNNER, |
| on_pull_request=True, |
| num_test_shards=2, |
| ), |
| CIWorkflow( |
| arch="windows", |
| build_environment="pytorch-win-vs2019-cuda10-cudnn7-py3", |
| cuda_version="10.1", |
| test_runner_type=WINDOWS_CUDA_TEST_RUNNER, |
| on_pull_request=True, |
| num_test_shards=2, |
| ), |
| CIWorkflow( |
| arch="windows", |
| build_environment="pytorch-win-vs2019-cuda11-cudnn8-py3", |
| cuda_version="11.1", |
| test_runner_type=WINDOWS_CUDA_TEST_RUNNER, |
| num_test_shards=2, |
| ), |
| CIWorkflow( |
| arch="windows", |
| build_environment="periodic-pytorch-win-vs2019-cuda11-cudnn8-py3", |
| cuda_version="11.3", |
| test_runner_type=WINDOWS_CUDA_TEST_RUNNER, |
| num_test_shards=2, |
| is_scheduled="45 0,4,8,12,16,20 * * *", |
| ), |
| ] |
| |
| LINUX_WORKFLOWS = [ |
| CIWorkflow( |
| arch="linux", |
| build_environment="pytorch-linux-xenial-py3.6-gcc5.4", |
| docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3.6-gcc5.4", |
| test_runner_type=LINUX_CPU_TEST_RUNNER, |
| on_pull_request=True, |
| enable_doc_jobs=True, |
| num_test_shards=2, |
| ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-paralleltbb-linux-xenial-py3.6-gcc5.4", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3.6-gcc5.4", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-parallelnative-linux-xenial-py3.6-gcc5.4", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3.6-gcc5.4", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-pure_torch-linux-xenial-py3.6-gcc5.4", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3.6-gcc5.4", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-linux-xenial-py3.6-gcc7", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3.6-gcc7", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-linux-xenial-py3.6-clang5-asan", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-asan", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-linux-xenial-py3.6-clang7-onnx", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang7-onnx", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| CIWorkflow( |
| arch="linux", |
| build_environment="pytorch-linux-bionic-cuda10.2-cudnn7-py3.9-gcc7", |
| docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-bionic-cuda10.2-cudnn7-py3.9-gcc7", |
| test_runner_type=LINUX_CUDA_TEST_RUNNER, |
| num_test_shards=2, |
| ), |
| CIWorkflow( |
| arch="linux", |
| build_environment="pytorch-linux-xenial-cuda10.2-cudnn7-py3.6-gcc7", |
| docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7", |
| test_runner_type=LINUX_CUDA_TEST_RUNNER, |
| enable_jit_legacy_test=1, |
| enable_multigpu_test=1, |
| enable_nogpu_no_avx_test=1, |
| enable_nogpu_no_avx2_test=1, |
| enable_slow_test=1, |
| num_test_shards=2, |
| on_pull_request=True, |
| ciflow_config=CIFlowConfig( |
| enabled=True, |
| trigger_action_only=True, |
| labels=set(['ciflow/slow']), |
| ) |
| ), |
| CIWorkflow( |
| arch="linux", |
| build_environment="pytorch-libtorch-linux-xenial-cuda10.2-cudnn7-py3.6-gcc7", |
| docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7", |
| test_runner_type=LINUX_CUDA_TEST_RUNNER, |
| is_libtorch=True, |
| ), |
| CIWorkflow( |
| arch="linux", |
| build_environment="pytorch-linux-xenial-cuda11.1-cudnn8-py3.6-gcc7", |
| docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-cuda11.1-cudnn8-py3-gcc7", |
| test_runner_type=LINUX_CUDA_TEST_RUNNER, |
| num_test_shards=2, |
| ), |
| CIWorkflow( |
| arch="linux", |
| build_environment="pytorch-libtorch-linux-xenial-cuda11.1-cudnn8-py3.6-gcc7", |
| docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-cuda11.1-cudnn8-py3-gcc7", |
| test_runner_type=LINUX_CUDA_TEST_RUNNER, |
| is_libtorch=True, |
| ), |
| CIWorkflow( |
| arch="linux", |
| build_environment="periodic-pytorch-linux-xenial-cuda11.3-cudnn8-py3.6-gcc7", |
| docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7", |
| test_runner_type=LINUX_CUDA_TEST_RUNNER, |
| num_test_shards=2, |
| is_scheduled="45 0,4,8,12,16,20 * * *", |
| ), |
| CIWorkflow( |
| arch="linux", |
| build_environment="periodic-pytorch-libtorch-linux-xenial-cuda11.3-cudnn8-py3.6-gcc7", |
| docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7", |
| test_runner_type=LINUX_CUDA_TEST_RUNNER, |
| is_libtorch=True, |
| is_scheduled="45 0,4,8,12,16,20 * * *", |
| ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-linux-bionic-py3.6-clang9-noarch", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-bionic-py3.6-clang9", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-xla-linux-bionic-py3.6-clang9", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-bionic-py3.6-clang9", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-vulkan-linux-bionic-py3.6-clang9", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-bionic-py3.6-clang9", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| CIWorkflow( |
| arch="linux", |
| build_environment="pytorch-linux-bionic-py3.8-gcc9-coverage", |
| docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-bionic-py3.8-gcc9", |
| test_runner_type=LINUX_CPU_TEST_RUNNER, |
| on_pull_request=True, |
| num_test_shards=2, |
| ciflow_config=CIFlowConfig( |
| enabled=True, |
| labels=set(['ciflow/default']), |
| ), |
| ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-linux-bionic-rocm3.9-py3.6", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-bionic-rocm3.9-py3.6", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-linux-xenial-py3.6-clang5-android-ndk-r19c-x86_32", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-linux-xenial-py3.6-clang5-android-ndk-r19c-x86_64", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-linux-xenial-py3.6-clang5-android-ndk-r19c-arm-v7a", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-linux-xenial-py3.6-clang5-android-ndk-r19c-arm-v8a", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-linux-xenial-py3.6-clang5-mobile", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-asan", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-linux-xenial-py3.6-clang5-mobile-custom-dynamic", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-linux-xenial-py3.6-clang5-mobile-custom-static", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| # CIWorkflow( |
| # arch="linux", |
| # build_environment="pytorch-linux-xenial-py3.6-clang5-mobile-code-analysis", |
| # docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c", |
| # test_runner_type=LINUX_CPU_TEST_RUNNER, |
| # ), |
| ] |
| |
| |
| BAZEL_WORKFLOWS = [ |
| CIWorkflow( |
| arch="linux", |
| build_environment="pytorch-linux-xenial-py3.6-gcc7-bazel-test", |
| docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3.6-gcc7", |
| test_runner_type=LINUX_CPU_TEST_RUNNER, |
| ), |
| ] |
| |
| if __name__ == "__main__": |
| jinja_env = jinja2.Environment( |
| variable_start_string="!{{", |
| loader=jinja2.FileSystemLoader(str(GITHUB_DIR.joinpath("templates"))), |
| ) |
| template_and_workflows = [ |
| (jinja_env.get_template("linux_ci_workflow.yml.j2"), LINUX_WORKFLOWS), |
| (jinja_env.get_template("windows_ci_workflow.yml.j2"), WINDOWS_WORKFLOWS), |
| (jinja_env.get_template("bazel_ci_workflow.yml.j2"), BAZEL_WORKFLOWS), |
| ] |
| for template, workflows in template_and_workflows: |
| for workflow in workflows: |
| workflow.generate_workflow_file(workflow_template=template) |
