From b165de6dcc3708a0e42d1e9e9149a540c0520ce7 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Wed, 17 Mar 2021 09:05:19 +0000 Subject: [PATCH] chore(deps): bump pytorch-lightning from 1.2.3 to 1.2.4 Bumps [pytorch-lightning](https://github.com/PyTorchLightning/pytorch-lightning) from 1.2.3 to 1.2.4. - [Release notes](https://github.com/PyTorchLightning/pytorch-lightning/releases) - [Changelog](https://github.com/PyTorchLightning/pytorch-lightning/blob/1.2.4/CHANGELOG.md) - [Commits](https://github.com/PyTorchLightning/pytorch-lightning/compare/1.2.3...1.2.4) Signed-off-by: dependabot[bot] <support@github.com> --- poetry.lock | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/poetry.lock b/poetry.lock index b37c138a..6acd552d 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1679,7 +1679,7 @@ six = ">=1.5" [[package]] name = "pytorch-lightning" -version = "1.2.3" +version = "1.2.4" description = "PyTorch Lightning is the lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate." category = "main" optional = false @@ -1695,14 +1695,14 @@ torch = ">=1.4" tqdm = ">=4.41.0" [package.extras] -all = ["matplotlib (>3.1)", "horovod (>=0.21.2)", "omegaconf (>=2.0.1)", "torchtext (>=0.5,<0.7)", "onnx (>=1.7.0)", "onnxruntime (>=1.3.0)", "hydra-core (>=1.0)", "neptune-client (>=0.4.109)", "comet-ml (>=3.1.12)", "mlflow (>=1.0.0)", "test-tube (>=0.7.5)", "wandb (>=0.8.21)", "coverage (>=5.0)", "codecov (>=2.1)", "pytest (>=5.0)", "flake8 (>=3.6)", "check-manifest", "twine (==3.2)", "scikit-learn (>=0.22.2)", "scikit-image (>=0.17.2)", "isort (>=5.6.4)", "mypy (>=0.720,<0.800)", "pre-commit (>=1.0)", "cloudpickle (>=1.3)", "nltk (>=3.3)", "pandas", "torchvision (>=0.5)", "gym (>=0.17.0)"] -cpu = ["matplotlib (>3.1)", "omegaconf (>=2.0.1)", "torchtext (>=0.5,<0.7)", "onnx (>=1.7.0)", "onnxruntime (>=1.3.0)", "hydra-core (>=1.0)", "neptune-client (>=0.4.109)", "comet-ml (>=3.1.12)", "mlflow (>=1.0.0)", "test-tube (>=0.7.5)", "wandb (>=0.8.21)", "coverage (>=5.0)", "codecov (>=2.1)", "pytest (>=5.0)", "flake8 (>=3.6)", "check-manifest", "twine (==3.2)", "scikit-learn (>=0.22.2)", "scikit-image (>=0.17.2)", "isort (>=5.6.4)", "mypy (>=0.720,<0.800)", "pre-commit (>=1.0)", "cloudpickle (>=1.3)", "nltk (>=3.3)", "pandas", "torchvision (>=0.5)", "gym (>=0.17.0)"] -cpu-extra = ["matplotlib (>3.1)", "omegaconf (>=2.0.1)", "torchtext (>=0.5,<0.7)", "onnx (>=1.7.0)", "onnxruntime (>=1.3.0)", "hydra-core (>=1.0)"] -dev = ["matplotlib (>3.1)", "horovod (>=0.21.2)", "omegaconf (>=2.0.1)", "torchtext (>=0.5,<0.7)", "onnx (>=1.7.0)", "onnxruntime (>=1.3.0)", "hydra-core (>=1.0)", "neptune-client (>=0.4.109)", "comet-ml (>=3.1.12)", "mlflow (>=1.0.0)", "test-tube (>=0.7.5)", "wandb (>=0.8.21)", "coverage (>=5.0)", "codecov (>=2.1)", "pytest (>=5.0)", "flake8 (>=3.6)", "check-manifest", "twine (==3.2)", "scikit-learn (>=0.22.2)", "scikit-image (>=0.17.2)", "isort (>=5.6.4)", "mypy (>=0.720,<0.800)", "pre-commit (>=1.0)", "cloudpickle (>=1.3)", "nltk (>=3.3)", "pandas"] +all = ["matplotlib (>3.1)", "horovod (>=0.21.2)", "omegaconf (>=2.0.1)", "torchtext (>=0.5)", "onnxruntime (>=1.3.0)", "hydra-core (>=1.0)", "neptune-client (>=0.4.109)", "comet-ml (>=3.1.12)", "mlflow (>=1.0.0)", "test-tube (>=0.7.5)", "wandb (>=0.8.21)", "coverage (>=5.2)", "codecov (>=2.1)", "pytest (>=6.0)", "pytest-cov (>2.10)", "flake8 (>=3.6)", "check-manifest", "twine (==3.2)", "scikit-learn (>=0.22.2)", "scikit-image (>=0.17.2)", "isort (>=5.6.4)", "mypy (>=0.720,<0.800)", "pre-commit (>=1.0)", "cloudpickle (>=1.3)", "nltk (>=3.3)", "pandas", "torchvision (>=0.5)", "gym (>=0.17.0)"] +cpu = ["matplotlib (>3.1)", "omegaconf (>=2.0.1)", "torchtext (>=0.5)", "onnxruntime (>=1.3.0)", "hydra-core (>=1.0)", "neptune-client (>=0.4.109)", "comet-ml (>=3.1.12)", "mlflow (>=1.0.0)", "test-tube (>=0.7.5)", "wandb (>=0.8.21)", "coverage (>=5.2)", "codecov (>=2.1)", "pytest (>=6.0)", "pytest-cov (>2.10)", "flake8 (>=3.6)", "check-manifest", "twine (==3.2)", "scikit-learn (>=0.22.2)", "scikit-image (>=0.17.2)", "isort (>=5.6.4)", "mypy (>=0.720,<0.800)", "pre-commit (>=1.0)", "cloudpickle (>=1.3)", "nltk (>=3.3)", "pandas", "torchvision (>=0.5)", "gym (>=0.17.0)"] +cpu-extra = ["matplotlib (>3.1)", "omegaconf (>=2.0.1)", "torchtext (>=0.5)", "onnxruntime (>=1.3.0)", "hydra-core (>=1.0)"] +dev = ["matplotlib (>3.1)", "horovod (>=0.21.2)", "omegaconf (>=2.0.1)", "torchtext (>=0.5)", "onnxruntime (>=1.3.0)", "hydra-core (>=1.0)", "neptune-client (>=0.4.109)", "comet-ml (>=3.1.12)", "mlflow (>=1.0.0)", "test-tube (>=0.7.5)", "wandb (>=0.8.21)", "coverage (>=5.2)", "codecov (>=2.1)", "pytest (>=6.0)", "pytest-cov (>2.10)", "flake8 (>=3.6)", "check-manifest", "twine (==3.2)", "scikit-learn (>=0.22.2)", "scikit-image (>=0.17.2)", "isort (>=5.6.4)", "mypy (>=0.720,<0.800)", "pre-commit (>=1.0)", "cloudpickle (>=1.3)", "nltk (>=3.3)", "pandas"] examples = ["torchvision (>=0.5)", "gym (>=0.17.0)"] -extra = ["matplotlib (>3.1)", "horovod (>=0.21.2)", "omegaconf (>=2.0.1)", "torchtext (>=0.5,<0.7)", "onnx (>=1.7.0)", "onnxruntime (>=1.3.0)", "hydra-core (>=1.0)"] +extra = ["matplotlib (>3.1)", "horovod (>=0.21.2)", "omegaconf (>=2.0.1)", "torchtext (>=0.5)", "onnxruntime (>=1.3.0)", "hydra-core (>=1.0)"] loggers = ["neptune-client (>=0.4.109)", "comet-ml (>=3.1.12)", "mlflow (>=1.0.0)", "test-tube (>=0.7.5)", "wandb (>=0.8.21)"] -test = ["coverage (>=5.0)", "codecov (>=2.1)", "pytest (>=5.0)", "flake8 (>=3.6)", "check-manifest", "twine (==3.2)", "scikit-learn (>=0.22.2)", "scikit-image (>=0.17.2)", "isort (>=5.6.4)", "mypy (>=0.720,<0.800)", "pre-commit (>=1.0)", "cloudpickle (>=1.3)", "nltk (>=3.3)", "pandas"] +test = ["coverage (>=5.2)", "codecov (>=2.1)", "pytest (>=6.0)", "pytest-cov (>2.10)", "flake8 (>=3.6)", "check-manifest", "twine (==3.2)", "scikit-learn (>=0.22.2)", "scikit-image (>=0.17.2)", "isort (>=5.6.4)", "mypy (>=0.720,<0.800)", "pre-commit (>=1.0)", "cloudpickle (>=1.3)", "nltk (>=3.3)", "pandas"] [[package]] name = "pytz" @@ -3700,8 +3700,8 @@ python-dateutil = [ {file = "python_dateutil-2.8.1-py2.py3-none-any.whl", hash = "sha256:75bb3f31ea686f1197762692a9ee6a7550b59fc6ca3a1f4b5d7e32fb98e2da2a"}, ] pytorch-lightning = [ - {file = "pytorch-lightning-1.2.3.tar.gz", hash = "sha256:856698e1652020b1030155e643a9e03e621e1e6b123f4406ae77fd36f7bea439"}, - {file = "pytorch_lightning-1.2.3-py3-none-any.whl", hash = "sha256:f8d0dedc3dc1a030de639e2e7a47e2595dd51088f4d947f634ab0c982376d517"}, + {file = "pytorch-lightning-1.2.4.tar.gz", hash = "sha256:bcf9d963ef6e0faa2d9a2149e16c212e1d471c1b4b555392b1e59632c02da9ab"}, + {file = "pytorch_lightning-1.2.4-py3-none-any.whl", hash = "sha256:fefb0124558bc3c26b1b12a37ddb01d5c892131e21404bc9c28daba4d5f26f57"}, ] pytz = [ {file = "pytz-2020.4-py2.py3-none-any.whl", hash = "sha256:5c55e189b682d420be27c6995ba6edce0c0a77dd67bfbe2ae6607134d5851ffd"},