Drop Python 3.6 support (#11117)
This commit is contained in:
Carlos Mocholí
GitHub
parent
9da78a94bd
commit
3692eba807
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@ -37,10 +37,7 @@ references:
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run:
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name: Make Documentation
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command: |
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# First run the same pipeline as Read-The-Docs
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# apt-get update && apt-get install -y cmake
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# using: https://hub.docker.com/r/readthedocs/build
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# we need to use py3.7 ot higher becase of an issue with metaclass inheritence
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# the image uses python 2.7 by default, force a different version
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pyenv global 3.7.3
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python --version
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pip install -r requirements/docs.txt
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@ -16,7 +16,7 @@ jobs:
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# max-parallel: 6
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matrix:
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os: [ubuntu-20.04, macOS-10.15, windows-2019]
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python-version: [3.6, 3.9]
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python-version: [3.7, 3.9]
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steps:
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- uses: actions/checkout@v2
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@ -21,11 +21,7 @@ jobs:
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python-version: ["3.7", "3.9"] # minimum, maximum
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requires: ["oldest", "latest"]
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release: ["stable"]
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include:
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# test 3.6 only on oldest until EOL: https://github.com/PyTorchLightning/pytorch-lightning/issues/9981
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- {os: ubuntu-18.04, python-version: "3.6", requires: "oldest", release: "stable"}
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- {os: windows-2019, python-version: "3.6", requires: "oldest", release: "stable"}
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- {os: macOS-10.15, python-version: "3.6", requires: "oldest", release: "stable"}
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#include:
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# nightly: add when there's a release candidate
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#- {os: ubuntu-20.04, python-version: "3.10", requires: "latest", release: "pre"}
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@ -15,7 +15,7 @@ jobs:
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strategy:
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fail-fast: false
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matrix:
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python_version: ["3.6", "3.7", "3.8", "3.9"]
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python_version: ["3.7", "3.8", "3.9"]
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pytorch_version: ["1.7", "1.8", "1.9", "1.10"]
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steps:
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- name: Checkout
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@ -49,7 +49,7 @@ repos:
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rev: v2.29.0
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hooks:
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- id: pyupgrade
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args: [--py36-plus]
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args: [--py37-plus]
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name: Upgrade code
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- repo: https://github.com/myint/docformatter
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@ -80,8 +80,8 @@ repos:
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rev: v1.11.0
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hooks:
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- id: blacken-docs
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args: [ --line-length=120 ]
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additional_dependencies: [ black==21.7b0 ]
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args: [--line-length=120]
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additional_dependencies: [black==21.7b0]
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- repo: https://github.com/executablebooks/mdformat
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rev: 0.7.10
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@ -308,6 +308,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
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- Removed `Accelerator.on_train_start` ([#10999](https://github.com/PyTorchLightning/pytorch-lightning/pull/10999))
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- Removed support for Python 3.6 ([#11117](https://github.com/PyTorchLightning/pytorch-lightning/pull/11117))
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### Fixed
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- Fixed `NeptuneLogger` when using DDP ([#11030](https://github.com/PyTorchLightning/pytorch-lightning/pull/11030))
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@ -86,9 +86,6 @@ Lightning is rigorously tested across multiple GPUs, TPUs CPUs and against major
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| Linux py3.{7,9} | [](https://github.com/PyTorchLightning/pytorch-lightning/actions/workflows/ci_test-full.yml) | - | - | [](https://github.com/PyTorchLightning/pytorch-lightning/actions/workflows/ci_test-full.yml) |
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| OSX py3.{7,9} | [](https://github.com/PyTorchLightning/pytorch-lightning/actions/workflows/ci_test-full.yml) | - | - | [](https://github.com/PyTorchLightning/pytorch-lightning/actions/workflows/ci_test-full.yml) |
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| Windows py3.{7,9} | [](https://github.com/PyTorchLightning/pytorch-lightning/actions/workflows/ci_test-full.yml) | - | - | [](https://github.com/PyTorchLightning/pytorch-lightning/actions/workflows/ci_test-full.yml) |
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| Linux py3.6 | [](https://github.com/PyTorchLightning/pytorch-lightning/actions/workflows/ci_test-full.yml) | - | - | - |
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| OSX py3.6 | [](https://github.com/PyTorchLightning/pytorch-lightning/actions/workflows/ci_test-full.yml) | - | - | - |
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| Windows py3.6 | [](https://github.com/PyTorchLightning/pytorch-lightning/actions/workflows/ci_test-full.yml) | - | - | - |
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- _\*\* tests run on two NVIDIA P100_
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- _\*\*\* tests run on Google GKE TPUv2/3. TPU py3.7 means we support Colab and Kaggle env._
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@ -16,7 +16,7 @@ FROM google/cloud-sdk:slim
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LABEL maintainer="PyTorchLightning <https://github.com/PyTorchLightning>"
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# CALL: docker image build -t pytorch-lightning:XLA-extras-py3.6 -f dockers/base-xla/Dockerfile . --build-arg PYTHON_VERSION=3.8
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# CALL: docker image build -t pytorch-lightning:XLA-image -f dockers/base-xla/Dockerfile . --build-arg PYTHON_VERSION=3.8
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ARG PYTHON_VERSION=3.9
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ARG CONDA_VERSION=4.9.2
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ARG XLA_VERSION=1.8
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@ -26,7 +26,7 @@ channels:
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- conda-forge
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dependencies:
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- python>=3.6
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- python>=3.7
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- pip>20.1
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- numpy>=1.17.2
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- pytorch>=1.7.*
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@ -110,8 +110,7 @@ def get_nvidia_gpu_stats(device: torch.device) -> Dict[str, float]:
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result = subprocess.run(
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[nvidia_smi_path, f"--query-gpu={gpu_query}", "--format=csv,nounits,noheader", f"--id={gpu_id}"],
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encoding="utf-8",
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE, # for backward compatibility with python version 3.6
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capture_output=True,
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check=True,
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)
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@ -214,8 +214,7 @@ class GPUStatsMonitor(Callback):
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f"--id={gpu_ids}",
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],
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encoding="utf-8",
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE, # for backward compatibility with python version 3.6
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capture_output=True,
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check=True,
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)
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@ -20,7 +20,7 @@ from torch.nn import Module
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try:
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from typing_extensions import Self
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except ImportError:
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# workaround for Python 3.6 and 3.7.
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# workaround for Python 3.7.
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# see https://www.python.org/dev/peps/pep-0673/
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from typing import TypeVar
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@ -129,9 +129,9 @@ class BaseProfiler(AbstractProfiler):
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def describe(self) -> None:
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"""Logs a profile report after the conclusion of run."""
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# there are pickling issues with open file handles in Python 3.6
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# so to avoid them, we open and close the files within this function
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# by calling `_prepare_streams` and `teardown`
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# users might call `describe` directly as the profilers can be used by themselves.
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# to allow this, we open and close the files within this function by calling `_prepare_streams` and `teardown`
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# manually instead of letting the `Trainer` do it through `setup` and `teardown`
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self._prepare_streams()
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summary = self.summary()
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if summary:
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@ -14,7 +14,7 @@
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from collections.abc import Generator
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from dataclasses import asdict, dataclass, replace
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from functools import partial, wraps
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from typing import Any, Callable, Dict, List, Optional, Tuple, Union
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from typing import Any, Callable, cast, Dict, List, Optional, Tuple, Union
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import torch
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from torchmetrics import Metric
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@ -29,8 +29,7 @@ from pytorch_lightning.utilities.memory import recursive_detach
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from pytorch_lightning.utilities.metrics import metrics_to_scalars
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from pytorch_lightning.utilities.warnings import WarningCache
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# TODO(@tchaton): Typing-pickle issue on python<3.7 (https://github.com/cloudpipe/cloudpickle/pull/318)
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_IN_METRIC = Any # Union[Metric, torch.Tensor] # Do not include scalars as they were converted to tensors
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_IN_METRIC = Union[Metric, torch.Tensor] # Do not include scalars as they were converted to tensors
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_OUT_METRIC = Union[torch.Tensor, Dict[str, torch.Tensor]]
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_PBAR_METRIC = Union[float, Dict[str, float]]
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_OUT_DICT = Dict[str, _OUT_METRIC]
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@ -217,6 +216,7 @@ class _ResultMetric(Metric, DeviceDtypeModuleMixin):
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def update(self, value: _IN_METRIC, batch_size: int) -> None: # type: ignore[override]
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if self.is_tensor:
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value = cast(torch.Tensor, value)
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if not torch.is_floating_point(value):
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dtype = torch.get_default_dtype()
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warning_cache.warn(
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@ -244,6 +244,7 @@ class _ResultMetric(Metric, DeviceDtypeModuleMixin):
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elif self.meta.is_sum_reduction:
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self.value += value.mean()
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else:
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value = cast(Metric, value)
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self.value = value
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self._forward_cache = value._forward_cache
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@ -405,7 +406,9 @@ class _ResultCollection(dict):
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apply_to_collection(list(self.values()), _ResultMetric, append_fn)
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return o
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def _extract_batch_size(self, value: _METRIC_COLLECTION, batch_size: Optional[int], meta: _Metadata) -> int:
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def _extract_batch_size(
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self, value: Union[_ResultMetric, _ResultMetricCollection], batch_size: Optional[int], meta: _Metadata
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) -> int:
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# check if we have extracted the batch size already
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if batch_size is None:
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batch_size = self.batch_size
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@ -35,11 +35,7 @@ def _module_available(module_path: str) -> bool:
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"""
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try:
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return find_spec(module_path) is not None
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except AttributeError:
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# Python 3.6
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return False
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except ModuleNotFoundError:
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# Python 3.7+
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return False
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@ -163,9 +163,7 @@ def get_gpu_memory_map() -> Dict[str, float]:
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result = subprocess.run(
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[nvidia_smi_path, "--query-gpu=memory.used", "--format=csv,nounits,noheader"],
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encoding="utf-8",
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# capture_output=True, # valid for python version >=3.7
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE, # for backward compatibility with python version 3.6
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capture_output=True,
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check=True,
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)
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@ -14,7 +14,6 @@
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import contextlib
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import logging
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import sys
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from collections import OrderedDict
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from typing import Any, Dict, List, Optional, Tuple, Union
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@ -267,10 +266,8 @@ class ModelSummary:
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if trainer is not None:
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forward_context = trainer.precision_plugin.forward_context()
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elif sys.version_info >= (3, 7):
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forward_context = contextlib.nullcontext()
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else:
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forward_context = contextlib.suppress()
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forward_context = contextlib.nullcontext()
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with torch.no_grad(), forward_context:
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# let the model hooks collect the input- and output shapes
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@ -2,7 +2,6 @@
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numpy>=1.17.2
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torch>=1.7.*
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future>=0.17.1 # required for builtins in setup.py
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tqdm>=4.41.0
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PyYAML>=5.4
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fsspec[http]>=2021.05.0, !=2021.06.0
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10
setup.py
10
setup.py
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@ -80,7 +80,7 @@ setup(
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long_description_content_type="text/markdown",
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zip_safe=False,
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keywords=["deep learning", "pytorch", "AI"],
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python_requires=">=3.6",
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python_requires=">=3.7",
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setup_requires=[],
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install_requires=setup_tools._load_requirements(_PATH_ROOT),
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extras_require=extras,
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@ -92,9 +92,7 @@ setup(
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classifiers=[
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"Environment :: Console",
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"Natural Language :: English",
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# How mature is this project? Common values are
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# 3 - Alpha, 4 - Beta, 5 - Production/Stable
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"Development Status :: 4 - Beta",
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"Development Status :: 5 - Production/Stable",
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# Indicate who your project is intended for
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"Intended Audience :: Developers",
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"Topic :: Scientific/Engineering :: Artificial Intelligence",
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@ -103,10 +101,8 @@ setup(
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# Pick your license as you wish
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"License :: OSI Approved :: Apache Software License",
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"Operating System :: OS Independent",
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# Specify the Python versions you support here. In particular, ensure
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# that you indicate whether you support Python 2, Python 3 or both.
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# Specify the Python versions you support here.
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3.6",
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"Programming Language :: Python :: 3.7",
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"Programming Language :: Python :: 3.8",
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"Programming Language :: Python :: 3.9",
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@ -13,7 +13,6 @@
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# limitations under the License.
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import os
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import signal
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import sys
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import threading
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from functools import partial
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from http.server import SimpleHTTPRequestHandler
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@ -135,28 +134,8 @@ def caplog(caplog):
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@pytest.fixture
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def tmpdir_server(tmpdir):
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if sys.version_info >= (3, 7):
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Handler = partial(SimpleHTTPRequestHandler, directory=str(tmpdir))
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from http.server import ThreadingHTTPServer
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else:
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# unfortunately SimpleHTTPRequestHandler doesn't accept the directory arg in python3.6
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# so we have to hack it like this
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class Handler(SimpleHTTPRequestHandler):
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def translate_path(self, path):
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# get the path from cwd
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path = super().translate_path(path)
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# get the relative path
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relpath = os.path.relpath(path, os.getcwd())
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# return the full path from root_dir
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return os.path.join(str(tmpdir), relpath)
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# ThreadingHTTPServer was added in 3.7, so we need to define it ourselves
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from http.server import HTTPServer
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from socketserver import ThreadingMixIn
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class ThreadingHTTPServer(ThreadingMixIn, HTTPServer):
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daemon_threads = True
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Handler = partial(SimpleHTTPRequestHandler, directory=str(tmpdir))
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from http.server import ThreadingHTTPServer
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with ThreadingHTTPServer(("localhost", 0), Handler) as server:
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server_thread = threading.Thread(target=server.serve_forever)
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@ -147,7 +147,6 @@ def test_argparse_args_parsing(cli_args, expected):
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assert Trainer.from_argparse_args(args)
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@RunIf(min_python="3.7.0")
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@pytest.mark.parametrize(
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"cli_args,expected",
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[("", False), ("--fast_dev_run=0", False), ("--fast_dev_run=True", True), ("--fast_dev_run 2", 2)],
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@ -180,7 +179,6 @@ def test_argparse_args_parsing_gpus(cli_args, expected_parsed, expected_device_i
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assert trainer.data_parallel_device_ids == expected_device_ids
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@RunIf(min_python="3.7.0")
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@pytest.mark.parametrize(
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["cli_args", "extra_args"],
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[
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@ -213,12 +213,6 @@ def test_add_argparse_args_no_argument_group():
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assert args.my_parameter == 2
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def test_add_argparse_args_invalid():
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"""Test that `add_argparse_args` doesn't raise `TypeError` when a class has args typed as `typing.Generic` in
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Python 3.6."""
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add_argparse_args(AddArgparseArgsExampleClassGeneric, ArgumentParser())
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def test_gpus_allowed_type():
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assert _gpus_allowed_type("1,2") == "1,2"
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assert _gpus_allowed_type("1") == 1
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@ -1226,7 +1226,6 @@ def test_optimizers_and_lr_schedulers_add_arguments_to_parser_implemented_reload
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assert cli.model.sch_config["init_args"]["anneal_strategy"] == "linear"
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@RunIf(min_python="3.7.3") # bpo-17185: `autospec=True` and `inspect.signature` do not play well
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def test_lightning_cli_config_with_subcommand():
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config = {"test": {"trainer": {"limit_test_batches": 1}, "verbose": True, "ckpt_path": "foobar"}}
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with mock.patch("sys.argv", ["any.py", f"--config={config}"]), mock.patch(
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@ -1238,7 +1237,6 @@ def test_lightning_cli_config_with_subcommand():
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assert cli.trainer.limit_test_batches == 1
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@RunIf(min_python="3.7.3")
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def test_lightning_cli_config_before_subcommand():
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config = {
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"validate": {"trainer": {"limit_val_batches": 1}, "verbose": False, "ckpt_path": "barfoo"},
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@ -1262,7 +1260,6 @@ def test_lightning_cli_config_before_subcommand():
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assert cli.trainer.limit_val_batches == 1
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@RunIf(min_python="3.7.3")
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def test_lightning_cli_config_before_subcommand_two_configs():
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config1 = {"validate": {"trainer": {"limit_val_batches": 1}, "verbose": False, "ckpt_path": "barfoo"}}
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config2 = {"test": {"trainer": {"limit_test_batches": 1}, "verbose": True, "ckpt_path": "foobar"}}
|
||||
|
|
@ -1284,7 +1281,6 @@ def test_lightning_cli_config_before_subcommand_two_configs():
|
|||
assert cli.trainer.limit_val_batches == 1
|
||||
|
||||
|
||||
@RunIf(min_python="3.7.3")
|
||||
def test_lightning_cli_config_after_subcommand():
|
||||
config = {"trainer": {"limit_test_batches": 1}, "verbose": True, "ckpt_path": "foobar"}
|
||||
with mock.patch("sys.argv", ["any.py", "test", f"--config={config}"]), mock.patch(
|
||||
|
|
@ -1296,7 +1292,6 @@ def test_lightning_cli_config_after_subcommand():
|
|||
assert cli.trainer.limit_test_batches == 1
|
||||
|
||||
|
||||
@RunIf(min_python="3.7.3")
|
||||
def test_lightning_cli_config_before_and_after_subcommand():
|
||||
config1 = {"test": {"trainer": {"limit_test_batches": 1}, "verbose": True, "ckpt_path": "foobar"}}
|
||||
config2 = {"trainer": {"fast_dev_run": 1}, "verbose": False, "ckpt_path": "foobar"}
|
||||
|
|
|
|||
Loading…
Reference in New Issue