lightning/pytorch_lightning/metrics/functional/__init__.py

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2020-10-13 11:18:07 +00:00
# Copyright The PyTorch Lightning team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from pytorch_lightning.metrics.functional.accuracy import accuracy # noqa: F401
from pytorch_lightning.metrics.functional.auc import auc # noqa: F401
from pytorch_lightning.metrics.functional.auroc import auroc # noqa: F401
from pytorch_lightning.metrics.functional.average_precision import average_precision # noqa: F401
from pytorch_lightning.metrics.functional.classification import ( # noqa: F401
dice_score,
get_num_classes,
multiclass_auroc,
stat_scores_multiple_classes,
to_categorical,
)
from pytorch_lightning.metrics.functional.confusion_matrix import confusion_matrix # noqa: F401
from pytorch_lightning.metrics.functional.explained_variance import explained_variance # noqa: F401
from pytorch_lightning.metrics.functional.f_beta import f1, fbeta # noqa: F401
Classification metrics overhaul: accuracy metrics (2/n) (#4838) * Add stuff * Change metrics documentation layout * Add stuff * Change testing utils * Replace len(*.shape) with *.ndim * More descriptive error message for input formatting * Replace movedim with permute * PEP 8 compliance * Division with float * Style changes in error messages * More error message style improvements * Fix typo in docs * Add more descriptive variable names in utils * Change internal var names * Break down error checking for inputs into separate functions * Remove the (N, ..., C) option in MD-MC * Simplify select_topk * Remove detach for inputs * Fix typos * Update pytorch_lightning/metrics/classification/utils.py Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> * Update docs/source/metrics.rst Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> * Minor error message changes * Update pytorch_lightning/metrics/utils.py Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> * Reuse case from validation in formatting * Refactor code in _input_format_classification * Small improvements * PEP 8 * Update pytorch_lightning/metrics/classification/utils.py Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> * Update pytorch_lightning/metrics/classification/utils.py Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> * Update docs/source/metrics.rst Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> * Update pytorch_lightning/metrics/classification/utils.py Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> * Apply suggestions from code review Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> * Alphabetical reordering of regression metrics * Change default value of top_k and add error checking * Extract basic validation into separate function * Update to new top_k default * Update desciption of parameters in input formatting * Apply suggestions from code review Co-authored-by: Nicki Skafte <skaftenicki@gmail.com> * Check that probabilities in preds sum to 1 (for MC) * Fix coverage * Split accuracy and hamming loss * Remove old redundant accuracy * Minor changes * Fix imports * Improve docstring descriptions * Fix edge case and simplify testing * Fix docs * PEP8 * Reorder imports * Update changelog * Update docstring * Update docstring * Reverse formatting changes for tests * Change parameter order * Remove formatting changes 2/2 * Remove formatting 3/3 * . * Improve description of top_k parameter * Apply suggestions from code review * Apply suggestions from code review Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> * Remove unneeded assert * Update pytorch_lightning/metrics/functional/accuracy.py Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> * Remove unneeded assert * Explicit checking of parameter values * Apply suggestions from code review Co-authored-by: Nicki Skafte <skaftenicki@gmail.com> * Apply suggestions from code review * Fix top_k checking * PEP8 * Don't check dist_sync in test * add back check_dist_sync_on_step * Make sure half-precision inputs are transformed (#5013) * Fix typo * Rename hamming loss to hamming distance * Fix tests for half precision * Fix docs underline length * Fix doc undeline length * Replace mdmc_accuracy parameter with subset_accuracy * Update changelog * Apply suggestions from code review Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> * Suggestions from code review * Fix number in docs * Update pytorch_lightning/metrics/classification/accuracy.py * Replace topk by argsort in select_topk * Fix changelog * Add test for wrong params * Add Google Colab badges (#5111) * Add colab badges to notebook Add colab badges to notebook to notebooks 4 & 5 * Add colab badges Co-authored-by: chaton <thomas@grid.ai> * Fix hanging metrics tests (#5134) * Use torch.topk again as ddp hanging tests fixed in #5134 * Fix unwanted notebooks change * Fix too long line in hamming_distance * Apply suggestions from code review * Apply suggestions from code review * protect * Update CHANGELOG.md Co-authored-by: Teddy Koker <teddy.koker@gmail.com> Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> Co-authored-by: chaton <thomas@grid.ai> Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> Co-authored-by: Nicki Skafte <skaftenicki@gmail.com> Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com> Co-authored-by: Roger Shieh <sh.rog@protonmail.ch> Co-authored-by: Shachar Mirkin <shacharmirkin@gmail.com>
2020-12-21 15:42:51 +00:00
from pytorch_lightning.metrics.functional.hamming_distance import hamming_distance # noqa: F401
from pytorch_lightning.metrics.functional.image_gradients import image_gradients # noqa: F401
from pytorch_lightning.metrics.functional.iou import iou # noqa: F401
from pytorch_lightning.metrics.functional.mean_absolute_error import mean_absolute_error # noqa: F401
from pytorch_lightning.metrics.functional.mean_squared_error import mean_squared_error # noqa: F401
from pytorch_lightning.metrics.functional.mean_squared_log_error import mean_squared_log_error # noqa: F401
from pytorch_lightning.metrics.functional.nlp import bleu_score # noqa: F401
Classification metrics overhaul: precision & recall (4/n) (#4842) * Add stuff * Change metrics documentation layout * Add stuff * Add stat scores * Change testing utils * Replace len(*.shape) with *.ndim * More descriptive error message for input formatting * Replace movedim with permute * PEP 8 compliance * WIP * Add reduce_scores function * Temporarily add back legacy class_reduce * Division with float * PEP 8 compliance * Remove precision recall * Replace movedim with permute * Add back tests * Add empty newlines * Add precision recall back * Add empty line * Fix permute * Fix some issues with old versions of PyTorch * Style changes in error messages * More error message style improvements * Fix typo in docs * Add more descriptive variable names in utils * Change internal var names * Revert unwanted changes * Revert unwanted changes pt 2 * Update metrics interface * Add top_k parameter * Add back reduce function * Add stuff * PEP3 * Add depreciation * PEP8 * Deprecate param * PEP8 * Fix and simplify testing for older PT versions * Update Changelog * Remove redundant import * Add tests to increase coverage * Remove zero_division * fix zero_division * Add zero_div + edge case tests * Reorder cls metric args * Add back quotes for is_multiclass * Add precision_recall and tests * PEP8 * Fix docs * Fix docs * Update * Change precision_recall output * PEP8/isort * Add method _get_final_stats * Fix depr test * Add comment to deprecation tests * isort * Apply suggestions from code review Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> * Add typing to test * Add matc str to pytest.raises Co-authored-by: chaton <thomas@grid.ai> Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
2021-01-18 08:24:13 +00:00
from pytorch_lightning.metrics.functional.precision_recall import precision, precision_recall, recall # noqa: F401
from pytorch_lightning.metrics.functional.precision_recall_curve import precision_recall_curve # noqa: F401
from pytorch_lightning.metrics.functional.psnr import psnr # noqa: F401
from pytorch_lightning.metrics.functional.r2score import r2score # noqa: F401
from pytorch_lightning.metrics.functional.roc import roc # noqa: F401
from pytorch_lightning.metrics.functional.self_supervised import embedding_similarity # noqa: F401
from pytorch_lightning.metrics.functional.ssim import ssim # noqa: F401
Classification metrics overhaul: stat scores (3/n) (#4839) * Add stuff * Change metrics documentation layout * Add stuff * Add stat scores * Change testing utils * Replace len(*.shape) with *.ndim * More descriptive error message for input formatting * Replace movedim with permute * PEP 8 compliance * WIP * Add reduce_scores function * Temporarily add back legacy class_reduce * Division with float * PEP 8 compliance * Remove precision recall * Replace movedim with permute * Add back tests * Add empty newlines * Add empty line * Fix permute * Fix some issues with old versions of PyTorch * Style changes in error messages * More error message style improvements * Fix typo in docs * Add more descriptive variable names in utils * Change internal var names * Break down error checking for inputs into separate functions * Remove the (N, ..., C) option in MD-MC * Simplify select_topk * Remove detach for inputs * Fix typos * Update pytorch_lightning/metrics/classification/utils.py Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> * Update docs/source/metrics.rst Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> * Minor error message changes * Update pytorch_lightning/metrics/utils.py Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> * Reuse case from validation in formatting * Refactor code in _input_format_classification * Small improvements * PEP 8 * Update pytorch_lightning/metrics/classification/utils.py Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> * Update pytorch_lightning/metrics/classification/utils.py Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> * Update docs/source/metrics.rst Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> * Update pytorch_lightning/metrics/classification/utils.py Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> * Apply suggestions from code review Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> * Alphabetical reordering of regression metrics * Change default value of top_k and add error checking * Extract basic validation into separate function * Update to new top_k default * Update desciption of parameters in input formatting * Apply suggestions from code review Co-authored-by: Nicki Skafte <skaftenicki@gmail.com> * Check that probabilities in preds sum to 1 (for MC) * Fix coverage * Split accuracy and hamming loss * Remove old redundant accuracy * Minor changes * Fix imports * Improve docstring descriptions * Fix imports * Fix edge case and simplify testing * Fix docs * PEP8 * Reorder imports * Add top_k parameter * Update changelog * Update docstring * Update docstring * Reverse formatting changes for tests * Change parameter order * Remove formatting changes 2/2 * Remove formatting 3/3 * . * Improve description of top_k parameter * Apply suggestions from code review * Apply suggestions from code review Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> * Remove unneeded assert * Update pytorch_lightning/metrics/functional/accuracy.py Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> * Remove unneeded assert * Explicit checking of parameter values * Apply suggestions from code review Co-authored-by: Nicki Skafte <skaftenicki@gmail.com> * Apply suggestions from code review * Fix top_k checking * PEP8 * Don't check dist_sync in test * add back check_dist_sync_on_step * Make sure half-precision inputs are transformed (#5013) * Fix typo * Rename hamming loss to hamming distance * Fix tests for half precision * Fix docs underline length * Fix doc undeline length * Replace mdmc_accuracy parameter with subset_accuracy * Update changelog * Fix unwanted accuracy change * Enable top_k for ML prob inputs * Test that default threshold is 0.5 * Fix typo * Update top_k description in helpers * updates * Update styling and add back tests * Remove excess spaces * fix torch.where for old versions * fix linting * Update docstring * Fix docstring * Apply suggestions from code review (mostly docs) * Default threshold to None, accept only (0,1) * Change wrong threshold message * Improve documentation and add tests * Add back ddp tests * Change stat reduce method and default * Remove DDP tests and fix doctests * Fix doctest * Update changelog * Refactoring * Fix typo * Refactor * Increase coverage * Fix linting * Consistent use of backticks * Fix too long line in docs * Apply suggestions from code review * Fix deprecation test * Fix deprecation test * Default threshold back to 0.5 * Minor documentation fixes * Add types to tests Co-authored-by: Teddy Koker <teddy.koker@gmail.com> Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> Co-authored-by: chaton <thomas@grid.ai> Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com> Co-authored-by: Nicki Skafte <skaftenicki@gmail.com> Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com>
2020-12-30 19:49:50 +00:00
from pytorch_lightning.metrics.functional.stat_scores import stat_scores # noqa: F401