update org Lightning-AI

.github/CONTRIBUTING.md

@@ -40,7 +40,7 @@ help you or finish it with you :\]_
 
 1. Add/update the relevant tests!
 
-- [This PR](https://github.com/PyTorchLightning/metrics/pull/98) is a good example for adding a new metric
+- [This PR](https://github.com/Lightning-AI/metrics/pull/98) is a good example for adding a new metric
 
 ### Test cases:
 

.github/ISSUE_TEMPLATE/config.yml

@@ -1,7 +1,7 @@
 blank_issues_enabled: false
 contact_links:
   - name: Ask a Question
-    url: https://github.com/PyTorchLightning/metrics/discussions/new
+    url: https://github.com/Lightning-AI/metrics/discussions/new
     about: Ask and answer TorchMetrics related questions
   - name: 💬 Slack
     url: https://app.slack.com/client/TR9DVT48M/CQXV8BRH9/thread/CQXV8BRH9-1591382895.254600

.github/PULL_REQUEST_TEMPLATE.md

@@ -5,7 +5,7 @@ Fixes #\<issue_number>
 ## Before submitting
 
 - [ ] Was this **discussed/approved** via a Github issue? (no need for typos and docs improvements)
-- [ ] Did you read the [contributor guideline](https://github.com/PyTorchLightning/metrics/blob/master/.github/CONTRIBUTING.md), Pull Request section?
+- [ ] Did you read the [contributor guideline](https://github.com/Lightning-AI/metrics/blob/master/.github/CONTRIBUTING.md), Pull Request section?
 - [ ] Did you make sure to **update the docs**?
 - [ ] Did you write any new **necessary tests**?
 

.github/assistant.py

@@ -99,7 +99,7 @@ def changed_domains(
         """Determine what domains were changed in particular PR."""
         if not pr:
             return "unittests"
-        url = f"https://api.github.com/repos/PyTorchLightning/metrics/pulls/{pr}/files"
+        url = f"https://api.github.com/repos/Lightning-AI/metrics/pulls/{pr}/files"
         logging.debug(url)
         data = request_url(url, auth_token)
         if not data:

.github/mergify.yml

@@ -78,4 +78,4 @@ pull_request_rules:
     actions:
       request_reviews:
         teams:
-          - "@PyTorchLightning/core-metrics"
+          - "@Lightning-AI/core-metrics"

CHANGELOG.md

@@ -40,63 +40,63 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Fixed
 
-- Fixed mAP calculation for areas with 0 predictions ([#1080](https://github.com/PyTorchLightning/metrics/pull/1080))
+- Fixed mAP calculation for areas with 0 predictions ([#1080](https://github.com/Lightning-AI/metrics/pull/1080))
 
 
-- Fixed bug where avg precision state and auroc state was not merge when using MetricCollections ([#1086](https://github.com/PyTorchLightning/metrics/pull/1086))
+- Fixed bug where avg precision state and auroc state was not merge when using MetricCollections ([#1086](https://github.com/Lightning-AI/metrics/pull/1086))
 
 
-- Skip box conversion if no boxes are present in `MeanAveragePrecision` ([#1097](https://github.com/PyTorchLightning/metrics/pull/1097))
+- Skip box conversion if no boxes are present in `MeanAveragePrecision` ([#1097](https://github.com/Lightning-AI/metrics/pull/1097))
 
 
 ## [0.9.1] - 2022-06-08
 
 ### Added
 
-- Added specific `RuntimeError` when metric object is on the wrong device ([#1056](https://github.com/PyTorchLightning/metrics/pull/1056))
-- Added an option to specify own n-gram weights for `BLEUScore` and `SacreBLEUScore` instead of using uniform weights only. ([#1075](https://github.com/PyTorchLightning/metrics/pull/1075))
+- Added specific `RuntimeError` when metric object is on the wrong device ([#1056](https://github.com/Lightning-AI/metrics/pull/1056))
+- Added an option to specify own n-gram weights for `BLEUScore` and `SacreBLEUScore` instead of using uniform weights only. ([#1075](https://github.com/Lightning-AI/metrics/pull/1075))
 
 ### Fixed
 
-- Fixed aggregation metrics when input only contains zero ([#1070](https://github.com/PyTorchLightning/metrics/pull/1070))
-- Fixed `TypeError` when providing superclass arguments as `kwargs` ([#1069](https://github.com/PyTorchLightning/metrics/pull/1069))
-- Fixed bug related to state reference in metric collection when using compute groups ([#1076](https://github.com/PyTorchLightning/metrics/pull/1076))
+- Fixed aggregation metrics when input only contains zero ([#1070](https://github.com/Lightning-AI/metrics/pull/1070))
+- Fixed `TypeError` when providing superclass arguments as `kwargs` ([#1069](https://github.com/Lightning-AI/metrics/pull/1069))
+- Fixed bug related to state reference in metric collection when using compute groups ([#1076](https://github.com/Lightning-AI/metrics/pull/1076))
 
 
 ## [0.9.0] - 2022-05-30
 
 ### Added
 
-- Added `RetrievalPrecisionRecallCurve` and `RetrievalRecallAtFixedPrecision` to retrieval package ([#951](https://github.com/PyTorchLightning/metrics/pull/951))
+- Added `RetrievalPrecisionRecallCurve` and `RetrievalRecallAtFixedPrecision` to retrieval package ([#951](https://github.com/Lightning-AI/metrics/pull/951))
 - Added class property `full_state_update` that determines `forward` should call `update` once or twice (
-    [#984](https://github.com/PyTorchLightning/metrics/pull/984),
-    [#1033](https://github.com/PyTorchLightning/metrics/pull/1033))
-- Added support for nested metric collections ([#1003](https://github.com/PyTorchLightning/metrics/pull/1003))
-- Added `Dice` to classification package ([#1021](https://github.com/PyTorchLightning/metrics/pull/1021))
-- Added support to segmentation type `segm` as IOU for mean average precision ([#822](https://github.com/PyTorchLightning/metrics/pull/822))
+    [#984](https://github.com/Lightning-AI/metrics/pull/984),
+    [#1033](https://github.com/Lightning-AI/metrics/pull/1033))
+- Added support for nested metric collections ([#1003](https://github.com/Lightning-AI/metrics/pull/1003))
+- Added `Dice` to classification package ([#1021](https://github.com/Lightning-AI/metrics/pull/1021))
+- Added support to segmentation type `segm` as IOU for mean average precision ([#822](https://github.com/Lightning-AI/metrics/pull/822))
 
 ### Changed
 
-- Renamed `reduction` argument to `average` in Jaccard score and added additional options ([#874](https://github.com/PyTorchLightning/metrics/pull/874))
+- Renamed `reduction` argument to `average` in Jaccard score and added additional options ([#874](https://github.com/Lightning-AI/metrics/pull/874))
 
 ### Removed
 
 - Removed deprecated `compute_on_step` argument (
-    [#962](https://github.com/PyTorchLightning/metrics/pull/962),
-    [#967](https://github.com/PyTorchLightning/metrics/pull/967),
-    [#979](https://github.com/PyTorchLightning/metrics/pull/979),
-    [#990](https://github.com/PyTorchLightning/metrics/pull/990),
-    [#991](https://github.com/PyTorchLightning/metrics/pull/991),
-    [#993](https://github.com/PyTorchLightning/metrics/pull/993),
-    [#1005](https://github.com/PyTorchLightning/metrics/pull/1005),
-    [#1004](https://github.com/PyTorchLightning/metrics/pull/1004),
-    [#1007](https://github.com/PyTorchLightning/metrics/pull/1007)
+    [#962](https://github.com/Lightning-AI/metrics/pull/962),
+    [#967](https://github.com/Lightning-AI/metrics/pull/967),
+    [#979](https://github.com/Lightning-AI/metrics/pull/979),
+    [#990](https://github.com/Lightning-AI/metrics/pull/990),
+    [#991](https://github.com/Lightning-AI/metrics/pull/991),
+    [#993](https://github.com/Lightning-AI/metrics/pull/993),
+    [#1005](https://github.com/Lightning-AI/metrics/pull/1005),
+    [#1004](https://github.com/Lightning-AI/metrics/pull/1004),
+    [#1007](https://github.com/Lightning-AI/metrics/pull/1007)
 )
 
 ### Fixed
 
-- Fixed non-empty state dict for a few metrics ([#1012](https://github.com/PyTorchLightning/metrics/pull/1012))
-- Fixed bug when comparing states while finding compute groups ([#1022](https://github.com/PyTorchLightning/metrics/pull/1022))
+- Fixed non-empty state dict for a few metrics ([#1012](https://github.com/Lightning-AI/metrics/pull/1012))
+- Fixed bug when comparing states while finding compute groups ([#1022](https://github.com/Lightning-AI/metrics/pull/1022))
 - Fixed `torch.double` support in stat score metrics ([#1023](https://github.com/PyTorchLightning/metrics/pull/1023))
 - Fixed `FID` calculation for non-equal size real and fake input ([#1028](https://github.com/PyTorchLightning/metrics/pull/1028))
 - Fixed case where `KLDivergence` could output `Nan` ([#1030](https://github.com/PyTorchLightning/metrics/pull/1030))

CITATION.cff

@@ -31,7 +31,7 @@ authors:
 doi: 10.21105/joss.04101
 license: "Apache-2.0"
 url: "https://www.pytorchlightning.ai"
-repository-code: "https://github.com/PyTorchLightning/metrics"
+repository-code: "https://github.com/Lightning-AI/metrics"
 date-released: 2022-02-11
 keywords:
   - machine learning

README.md

@@ -24,16 +24,15 @@ ______________________________________________________________________
 ![Conda](https://img.shields.io/conda/dn/conda-forge/torchmetrics)
 [![license](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/Lightning-AI/metrics/blob/master/LICENSE)
 
-[![CI testing - base](https://github.com/PyTorchLightning/metrics/actions/workflows/ci_test-base.yml/badge.svg?branch=master&event=push)](https://github.com/PyTorchLightning/metrics/actions/workflows/ci_test-base.yml)
-[![PyTorch & Conda](https://github.com/PyTorchLightning/metrics/actions/workflows/ci_test-conda.yml/badge.svg?branch=master&event=push)](https://github.com/PyTorchLightning/metrics/actions/workflows/ci_test-conda.yml)
-[![Build Status](https://dev.azure.com/Lightning-AI/Metrics/_apis/build/status/PyTorchLightning.metrics?branchName=master)](https://dev.azure.com/Lightning-AI/Metrics/_build/latest?definitionId=3&branchName=master)
-[![codecov](https://codecov.io/gh/PyTorchLightning/metrics/branch/master/graph/badge.svg?token=NER6LPI3HS)](https://codecov.io/gh/PyTorchLightning/metrics)
+[![PyTorch & Conda](https://github.com/Lightning-AI/metrics/actions/workflows/ci_test-conda.yml/badge.svg?branch=master&event=push)](https://github.com/Lightning-AI/metrics/actions/workflows/ci_test-conda.yml)
+[![Build Status](https://dev.azure.com/Lightning-AI/Metrics/_apis/build/status/Lightning-AI.metrics?branchName=master)](https://dev.azure.com/Lightning-AI/Metrics/_build/latest?definitionId=3&branchName=master)
+[![codecov](https://codecov.io/gh/Lightning-AI/metrics/branch/master/graph/badge.svg?token=NER6LPI3HS)](https://codecov.io/gh/Lightning-AI/metrics)
 
 [![Slack](https://img.shields.io/badge/slack-chat-green.svg?logo=slack)](https://www.pytorchlightning.ai/community)
 [![Documentation Status](https://readthedocs.org/projects/torchmetrics/badge/?version=latest)](https://torchmetrics.readthedocs.io/en/latest/?badge=latest)
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5844769.svg)](https://doi.org/10.5281/zenodo.5844769)
 [![JOSS status](https://joss.theoj.org/papers/561d9bb59b400158bc8204e2639dca43/status.svg)](https://joss.theoj.org/papers/561d9bb59b400158bc8204e2639dca43)
-[![pre-commit.ci status](https://results.pre-commit.ci/badge/github/PyTorchLightning/metrics/master.svg)](https://results.pre-commit.ci/latest/github/PyTorchLightning/metrics/master)
+[![pre-commit.ci status](https://results.pre-commit.ci/badge/github/Lightning-AI/metrics/master.svg)](https://results.pre-commit.ci/latest/github/Lightning-AI/metrics/master)
 
 ______________________________________________________________________
 
@@ -66,7 +65,7 @@ pip install git+https://github.com/Lightning-AI/metrics.git@release/latest
 Pip from archive
 
 ```bash
-pip install https://github.com/PyTorchLightning/metrics/archive/refs/heads/release/latest.zip
+pip install https://github.com/Lightning-AI/metrics/archive/refs/heads/release/latest.zip
 ```
 
 Extra dependencies for specialized metrics:
@@ -81,7 +80,7 @@ pip install torchmetrics[all]  # install all of the above
 Install latest developer version
 
 ```bash
-pip install https://github.com/PyTorchLightning/metrics/archive/master.zip
+pip install https://github.com/Lightning-AI/metrics/archive/master.zip
 ```
 
 </details>
@@ -329,7 +328,7 @@ For help or questions, join our huge community on [Slack](https://www.pytorchlig
 We’re excited to continue the strong legacy of open source software and have been inspired
 over the years by Caffe, Theano, Keras, PyTorch, torchbearer, ignite, sklearn and fast.ai.
 
-If you want to cite this framework feel free to use GitHub's built-in citation option to generate a bibtex or APA-Style citation based on [this file](https://github.com/PyTorchLightning/metrics/blob/master/CITATION.cff) (but only if you loved it 😊).
+If you want to cite this framework feel free to use GitHub's built-in citation option to generate a bibtex or APA-Style citation based on [this file](https://github.com/Lightning-AI/metrics/blob/master/CITATION.cff) (but only if you loved it 😊).
 
 ## License
 

docs/paper_JOSS/paper.md

@@ -99,7 +99,7 @@ In addition to stateful metrics (called modular metrics in TorchMetrics), we als
 
 TorchMetrics exhibits high test coverage on the various configurations, including all three major OS platforms (Linux, macOS, and Windows), and various Python, CUDA, and PyTorch versions. We test both minimum and latest package requirements for all combinations of OS and Python versions and include additional tests for each PyTorch version from 1.3 up to future development versions. On every pull request and merge to master, we run a full test suite. All standard tests run on CPU. In addition, we run all tests on a multi-GPU setting which reflects realistic Deep Learning workloads. For usability, we have auto-generated HTML documentation (hosted at [readthedocs](https://torchmetrics.readthedocs.io/en/stable/)) from the source code which updates in real-time with new merged pull requests.
 
-TorchMetrics is released under the Apache 2.0 license. The source code is available at https://github.com/PyTorchLightning/metrics.
+TorchMetrics is released under the Apache 2.0 license. The source code is available at https://github.com/Lightning-AI/metrics.
 
 # Acknowledgement
 

docs/source/_templates/theme_variables.jinja

@@ -1,7 +1,7 @@
 {%- set external_urls = {
   'github': 'https://github.com/Lightning-AI/metrics',
   'github_issues': 'https://github.com/Lightning-AI/metrics/issues',
-  'contributing': 'https://github.com/PyTorchLightning/metrics/blob/master/.github/CONTRIBUTING.md',
+  'contributing': 'https://github.com/Lightning-AI/metrics/blob/master/.github/CONTRIBUTING.md',
   'docs': 'https://torchmetrics.readthedocs.io/en/latest',
   'twitter': 'https://twitter.com/PyTorchLightnin',
   'discuss': 'https://pytorch-lightning.slack.com',

docs/source/conf.py

@@ -44,7 +44,7 @@
 
 # Options for the linkcode extension
 # ----------------------------------
-github_user = "PyTorchLightning"
+github_user = "Lightning-AI"
 github_repo = "metrics"
 
 # -- Project documents -------------------------------------------------------

docs/source/governance.rst

@@ -47,7 +47,7 @@ and start tracking the development. It is possible that priorities change over t
 
 Commits to the project are exclusively to be added by pull requests on GitHub and anyone in the community is welcome to review them.
 However, reviews submitted by
-`code owners <https://github.com/PyTorchLightning/metrics/blob/master/.github/CODEOWNERS>`_
+`code owners <https://github.com/Lightning-AI/metrics/blob/master/.github/CODEOWNERS>`_
 have higher weight and it is necessary to get the approval of code owners before a pull request can be merged.
 Additional requirements may apply case by case.
 

docs/source/links.rst

@@ -64,7 +64,7 @@
 .. _Demystifying MMD GANs: https://arxiv.org/abs/1801.01401
 .. _Computes Peak Signal-to-Noise Ratio: https://en.wikipedia.org/wiki/Peak_signal-to-noise_ratio
 .. _Turn a Metric into a Bootstrapped: https://en.wikipedia.org/wiki/Bootstrapping_(statistics)
-.. _Metric Test for Reset: https://github.com/PyTorchLightning/pytorch-lightning/pull/7055
+.. _Metric Test for Reset: https://github.com/Lightning-AI/pytorch-lightning/pull/7055
 .. _Computes Mean Absolute Error: https://en.wikipedia.org/wiki/Mean_absolute_error
 .. _Mean Absolute Percentage Error: https://en.wikipedia.org/wiki/Mean_absolute_percentage_error
 .. _mean squared error: https://en.wikipedia.org/wiki/Mean_squared_error

docs/source/pages/implement.rst

@@ -137,7 +137,7 @@ and tests gets formatted in the following way:
      makes up the functional interface for the metric.
 
   .. note::
-     The `functional accuracy <https://github.com/PyTorchLightning/metrics/blob/master/src/torchmetrics/functional/classification/accuracy.py>`_
+     The `functional accuracy <https://github.com/Lightning-AI/metrics/blob/master/src/torchmetrics/functional/classification/accuracy.py>`_
      metric is a great example of this division of logic.
 
 3. In a corresponding file placed in ``torchmetrics/"domain"/"new_metric".py`` create the module interface:
@@ -150,7 +150,7 @@ and tests gets formatted in the following way:
      We do this to not have duplicate code to maintain.
 
    .. note::
-     The module `Accuracy <https://github.com/PyTorchLightning/metrics/blob/master/src/torchmetrics/classification/accuracy.py>`_
+     The module `Accuracy <https://github.com/Lightning-AI/metrics/blob/master/src/torchmetrics/classification/accuracy.py>`_
      metric that corresponds to the above functional example showcases these steps.
 
 4. Remember to add binding to the different relevant ``__init__`` files.
@@ -171,7 +171,7 @@ and tests gets formatted in the following way:
   5. (optional) If your metric raises any exception, please add tests that showcase this.
 
   .. note::
-    The `test file for accuracy <https://github.com/PyTorchLightning/metrics/blob/master/tests/unittests/classification/test_accuracy.py>`_ metric
+    The `test file for accuracy <https://github.com/Lightning-AI/metrics/blob/master/tests/unittests/classification/test_accuracy.py>`_ metric
     shows how to implement such tests.
 
 If you only can figure out part of the steps, do not fear to send a PR. We will much rather receive working

docs/source/pages/lightning.rst

@@ -9,7 +9,7 @@
 TorchMetrics in PyTorch Lightning
 #################################
 
-TorchMetrics was originally created as part of `PyTorch Lightning <https://github.com/PyTorchLightning/pytorch-lightning>`_, a powerful deep learning research
+TorchMetrics was originally created as part of `PyTorch Lightning <https://github.com/Lightning-AI/pytorch-lightning>`_, a powerful deep learning research
 framework designed for scaling models without boilerplate.
 
 .. note::

requirements/docs.txt

@@ -5,7 +5,7 @@ pandoc>=1.0
 docutils>=0.16
 sphinxcontrib-fulltoc>=1.0
 sphinxcontrib-mockautodoc
-https://github.com/PyTorchLightning/lightning_sphinx_theme/archive/master.zip#egg=pt-lightning-sphinx-theme
+https://github.com/Lightning-AI/lightning_sphinx_theme/archive/master.zip#egg=pt-lightning-sphinx-theme
 sphinx-autodoc-typehints>=1.0
 sphinx-paramlinks>=0.5.1
 sphinx-togglebutton>=0.2

setup.py

@@ -46,7 +46,7 @@ def _load_readme_description(path_dir: str, homepage: str, version: str) -> str:
     with open(path_readme, encoding="utf-8") as fp:
         text = fp.read()
 
-    # https://github.com/PyTorchLightning/torchmetrics/raw/master/docs/source/_static/images/lightning_module/pt_to_pl.png
+    # https://github.com/Lightning-AI/torchmetrics/raw/master/docs/source/_static/images/lightning_module/pt_to_pl.png
     github_source_url = os.path.join(homepage, "raw", version)
     # replace relative repository path to absolute link to the release
     #  do not replace all "docs" as in the readme we replace some other sources with particular path to docs

src/torchmetrics/__about__.py

@@ -1,9 +1,9 @@
 __version__ = "0.10.0dev"
-__author__ = "PyTorchLightning et al."
+__author__ = "Lightning-AI et al."
 __author_email__ = "name@pytorchlightning.ai"
 __license__ = "Apache-2.0"
 __copyright__ = f"Copyright (c) 2020-2022, {__author__}."
-__homepage__ = "https://github.com/PyTorchLightning/metrics"
+__homepage__ = "https://github.com/Lightning-AI/metrics"
 __docs__ = "PyTorch native Metrics"
 __docs_url__ = "https://torchmetrics.readthedocs.io/en/stable/"
 __long_doc__ = """

src/torchmetrics/detection/mean_ap.py

@@ -208,7 +208,7 @@ class MeanAveragePrecision(Metric):
     See the :meth:`update` method for more information about the input format to this metric.
 
     For an example on how to use this metric check the `torchmetrics examples
-    <https://github.com/PyTorchLightning/metrics/blob/master/examples/detection_map.py>`_
+    <https://github.com/Lightning-AI/metrics/blob/master/examples/detection_map.py>`_
 
     .. note::
         This metric is following the mAP implementation of