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qX6WI9sYy)%a!V)c@q}~ru;rJQ6qJ@s@!Qefpu!zMiwoe$w@rnn-BBMW@HTC9M4z43ILdF384T0 diff --git a/latest/_modules/index.html b/latest/_modules/index.html index 4249a7c..0eff0e7 100644 --- a/latest/_modules/index.html +++ b/latest/_modules/index.html @@ -1,21 +1,22 @@ - + Overview: module code — pytorch-caney 0.1.0 documentation - - + + + + - - - - - - + + + + + diff --git a/latest/_modules/pytorch_caney/processing.html b/latest/_modules/pytorch_caney/processing.html index d87c968..6b0edc9 100644 --- a/latest/_modules/pytorch_caney/processing.html +++ b/latest/_modules/pytorch_caney/processing.html @@ -1,21 +1,22 @@ - + pytorch_caney.processing — pytorch-caney 0.1.0 documentation - - + + + + - - - - - - + + + + + @@ -108,7 +109,9 @@

Source code for pytorch_caney.processing

 
 
 # --------------------------- Normalization Functions ----------------------- #
-
[docs]def normalize(images, factor=65535.0) -> np.array: +
+[docs] +def normalize(images, factor=65535.0) -> np.array: """ Normalize numpy array in the range of [0,1] :param images: numpy array in the format (n,w,h,c). @@ -118,8 +121,11 @@

Source code for pytorch_caney.processing

     return images / factor
+ # ------------------------ Standardization Functions ----------------------- # -
[docs]def global_standardization(images, strategy='per-batch') -> np.array: +
+[docs] +def global_standardization(images, strategy='per-batch') -> np.array: """ Standardize numpy array using global standardization. :param images: numpy array in the format (n,w,h,c). @@ -139,7 +145,10 @@

Source code for pytorch_caney.processing

     return images
-
[docs]def local_standardization(images, filename='normalization_data', + +
+[docs] +def local_standardization(images, filename='normalization_data', ndata=None, strategy='per-batch' ) -> np.array: """ @@ -189,7 +198,10 @@

Source code for pytorch_caney.processing

     return images
-
[docs]def standardize_image( + +
+[docs] +def standardize_image( image, standardization_type: str, mean: list = None, @@ -225,7 +237,10 @@

Source code for pytorch_caney.processing

     return image
-
[docs]def standardize_batch( + +
+[docs] +def standardize_batch( image_batch, standardization_type: str, mean: list = None, @@ -240,10 +255,13 @@

Source code for pytorch_caney.processing

             image_batch[item, :, :, :], standardization_type, mean, std)
     return image_batch
+ # ------------------------ Data Preparation Functions ----------------------- # -
[docs]def get_rand_patches_rand_cond(img, mask, n_patches=16000, sz=160, nclasses=6, +
+[docs] +def get_rand_patches_rand_cond(img, mask, n_patches=16000, sz=160, nclasses=6, nodata_ascloud=True, method='rand' ) -> np.array: """ @@ -321,7 +339,10 @@

Source code for pytorch_caney.processing

     return np.asarray(patches), np.asarray(labels)
-
[docs]def get_rand_patches_aug_augcond(img, mask, n_patches=16000, sz=256, + +
+[docs] +def get_rand_patches_aug_augcond(img, mask, n_patches=16000, sz=256, nclasses=6, over=50, nodata_ascloud=True, nodata=-9999, method='augcond' ) -> np.array: @@ -421,6 +442,7 @@

Source code for pytorch_caney.processing

     return np.asarray(patches), np.asarray(labels)
+ # ------------------------ Artifact Removal Functions ----------------------- # def _2d_spline(window_size=128, power=2) -> np.array: diff --git a/latest/_static/_sphinx_javascript_frameworks_compat.js b/latest/_static/_sphinx_javascript_frameworks_compat.js index 8549469..8141580 100644 --- a/latest/_static/_sphinx_javascript_frameworks_compat.js +++ b/latest/_static/_sphinx_javascript_frameworks_compat.js @@ -1,20 +1,9 @@ -/* - * _sphinx_javascript_frameworks_compat.js - * ~~~~~~~~~~ - * - * Compatability shim for jQuery and underscores.js. - * - * WILL BE REMOVED IN Sphinx 6.0 - * xref RemovedInSphinx60Warning +/* Compatability shim for jQuery and underscores.js. * + * Copyright Sphinx contributors + * Released under the two clause BSD licence */ -/** - * select a different prefix for underscore - */ -$u = _.noConflict(); - - /** * small helper function to urldecode strings * diff --git a/latest/_static/basic.css b/latest/_static/basic.css index 4e9a9f1..30fee9d 100644 --- a/latest/_static/basic.css +++ b/latest/_static/basic.css @@ -4,7 +4,7 @@ * * Sphinx stylesheet -- basic theme. * - * :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS. + * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. * :license: BSD, see LICENSE for details. * */ @@ -237,6 +237,10 @@ a.headerlink { visibility: hidden; } +a:visited { + color: #551A8B; +} + h1:hover > a.headerlink, h2:hover > a.headerlink, h3:hover > a.headerlink, @@ -324,6 +328,7 @@ aside.sidebar { p.sidebar-title { font-weight: bold; } + nav.contents, aside.topic, div.admonition, div.topic, blockquote { @@ -331,6 +336,7 @@ div.admonition, div.topic, blockquote { } /* -- topics ---------------------------------------------------------------- */ + nav.contents, aside.topic, div.topic { @@ -606,6 +612,7 @@ ol.simple p, ul.simple p { margin-bottom: 0; } + aside.footnote > span, div.citation > span { float: left; @@ -667,6 +674,16 @@ dd { margin-left: 30px; } +.sig dd { + margin-top: 0px; + margin-bottom: 0px; +} + +.sig dl { + margin-top: 0px; + margin-bottom: 0px; +} + dl > dd:last-child, dl > dd:last-child > :last-child { margin-bottom: 0; @@ -735,6 +752,14 @@ abbr, acronym { cursor: help; } +.translated { + background-color: rgba(207, 255, 207, 0.2) +} + +.untranslated { + background-color: rgba(255, 207, 207, 0.2) +} + /* -- code displays --------------------------------------------------------- */ pre { diff --git a/latest/_static/doctools.js b/latest/_static/doctools.js index 527b876..d06a71d 100644 --- a/latest/_static/doctools.js +++ b/latest/_static/doctools.js @@ -4,7 +4,7 @@ * * Base JavaScript utilities for all Sphinx HTML documentation. * - * :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS. + * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. * :license: BSD, see LICENSE for details. * */ diff --git a/latest/_static/documentation_options.js b/latest/_static/documentation_options.js index e49ed18..13d90ff 100644 --- a/latest/_static/documentation_options.js +++ b/latest/_static/documentation_options.js @@ -1,5 +1,4 @@ -var DOCUMENTATION_OPTIONS = { - URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'), +const DOCUMENTATION_OPTIONS = { VERSION: '0.1.0', LANGUAGE: 'en', COLLAPSE_INDEX: false, diff --git a/latest/_static/language_data.js b/latest/_static/language_data.js index 2e22b06..250f566 100644 --- a/latest/_static/language_data.js +++ b/latest/_static/language_data.js @@ -5,7 +5,7 @@ * This script contains the language-specific data used by searchtools.js, * namely the list of stopwords, stemmer, scorer and splitter. * - * :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS. + * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. * :license: BSD, see LICENSE for details. * */ diff --git a/latest/_static/searchtools.js b/latest/_static/searchtools.js index e89e34d..7918c3f 100644 --- a/latest/_static/searchtools.js +++ b/latest/_static/searchtools.js @@ -4,7 +4,7 @@ * * Sphinx JavaScript utilities for the full-text search. * - * :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS. + * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. * :license: BSD, see LICENSE for details. * */ @@ -57,12 +57,12 @@ const _removeChildren = (element) => { const _escapeRegExp = (string) => string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string -const _displayItem = (item, searchTerms) => { +const _displayItem = (item, searchTerms, highlightTerms) => { const docBuilder = DOCUMENTATION_OPTIONS.BUILDER; - const docUrlRoot = DOCUMENTATION_OPTIONS.URL_ROOT; const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX; const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX; const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY; + const contentRoot = document.documentElement.dataset.content_root; const [docName, title, anchor, descr, score, _filename] = item; @@ -75,20 +75,24 @@ const _displayItem = (item, searchTerms) => { if (dirname.match(/\/index\/$/)) dirname = dirname.substring(0, dirname.length - 6); else if (dirname === "index/") dirname = ""; - requestUrl = docUrlRoot + dirname; + requestUrl = contentRoot + dirname; linkUrl = requestUrl; } else { // normal html builders - requestUrl = docUrlRoot + docName + docFileSuffix; + requestUrl = contentRoot + docName + docFileSuffix; linkUrl = docName + docLinkSuffix; } let linkEl = listItem.appendChild(document.createElement("a")); linkEl.href = linkUrl + anchor; linkEl.dataset.score = score; linkEl.innerHTML = title; - if (descr) + if (descr) { listItem.appendChild(document.createElement("span")).innerHTML = " (" + descr + ")"; + // highlight search terms in the description + if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js + highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); + } else if (showSearchSummary) fetch(requestUrl) .then((responseData) => responseData.text()) @@ -97,6 +101,9 @@ const _displayItem = (item, searchTerms) => { listItem.appendChild( Search.makeSearchSummary(data, searchTerms) ); + // highlight search terms in the summary + if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js + highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); }); Search.output.appendChild(listItem); }; @@ -115,14 +122,15 @@ const _finishSearch = (resultCount) => { const _displayNextItem = ( results, resultCount, - searchTerms + searchTerms, + highlightTerms, ) => { // results left, load the summary and display it // this is intended to be dynamic (don't sub resultsCount) if (results.length) { - _displayItem(results.pop(), searchTerms); + _displayItem(results.pop(), searchTerms, highlightTerms); setTimeout( - () => _displayNextItem(results, resultCount, searchTerms), + () => _displayNextItem(results, resultCount, searchTerms, highlightTerms), 5 ); } @@ -360,7 +368,7 @@ const Search = { // console.info("search results:", Search.lastresults); // print the results - _displayNextItem(results, results.length, searchTerms); + _displayNextItem(results, results.length, searchTerms, highlightTerms); }, /** diff --git a/latest/_static/sphinx_highlight.js b/latest/_static/sphinx_highlight.js index aae669d..8a96c69 100644 --- a/latest/_static/sphinx_highlight.js +++ b/latest/_static/sphinx_highlight.js @@ -29,14 +29,19 @@ const _highlight = (node, addItems, text, className) => { } span.appendChild(document.createTextNode(val.substr(pos, text.length))); + const rest = document.createTextNode(val.substr(pos + text.length)); parent.insertBefore( span, parent.insertBefore( - document.createTextNode(val.substr(pos + text.length)), + rest, node.nextSibling ) ); node.nodeValue = val.substr(0, pos); + /* There may be more occurrences of search term in this node. So call this + * function recursively on the remaining fragment. + */ + _highlight(rest, addItems, text, className); if (isInSVG) { const rect = document.createElementNS( @@ -140,5 +145,10 @@ const SphinxHighlight = { }, }; -_ready(SphinxHighlight.highlightSearchWords); -_ready(SphinxHighlight.initEscapeListener); +_ready(() => { + /* Do not call highlightSearchWords() when we are on the search page. + * It will highlight words from the *previous* search query. + */ + if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords(); + SphinxHighlight.initEscapeListener(); +}); diff --git a/latest/examples.html b/latest/examples.html index 5da5b4f..9f59c51 100644 --- a/latest/examples.html +++ b/latest/examples.html @@ -1,22 +1,23 @@ - + - + <no title> — pytorch-caney 0.1.0 documentation - - + + + + - - - - - - + + + + + diff --git a/latest/genindex.html b/latest/genindex.html index ede8bd8..ddbc09d 100644 --- a/latest/genindex.html +++ b/latest/genindex.html @@ -1,21 +1,22 @@ - + Index — pytorch-caney 0.1.0 documentation - - + + + + - - - - - - + + + + + diff --git a/latest/index.html b/latest/index.html index fc5f2cf..16ec0bb 100644 --- a/latest/index.html +++ b/latest/index.html @@ -1,22 +1,23 @@ - + - + Welcome to pytorch-caney’s documentation! — pytorch-caney 0.1.0 documentation - - + + + + - - - - - - + + + + + @@ -78,7 +79,7 @@
-

Welcome to pytorch-caney’s documentation!

+

Welcome to pytorch-caney’s documentation!

Contents:

    @@ -139,7 +140,7 @@

    Welcome to pytorch-caney’s documentation! -

    Indices and tables

    +

    Indices and tables

    • Index

    • Module Index

    • diff --git a/latest/modules.html b/latest/modules.html index 2436fa2..07257ba 100644 --- a/latest/modules.html +++ b/latest/modules.html @@ -1,22 +1,23 @@ - + - + pytorch-caney package — pytorch-caney 0.1.0 documentation - - + + + + - - - - - - + + + + + @@ -124,93 +125,93 @@
      -

      pytorch-caney package

      +

      pytorch-caney package

      -

      pytorch_caney.config

      +

      pytorch_caney.config

      -

      pytorch_caney.data.datamodules.finetune_datamodule

      +

      pytorch_caney.data.datamodules.finetune_datamodule

      -

      pytorch_caney.data.datamodules.mim_datamodule

      +

      pytorch_caney.data.datamodules.mim_datamodule

      -

      pytorch_caney.data.datamodules.segmentation_datamodule

      +

      pytorch_caney.data.datamodules.segmentation_datamodule

      -

      pytorch_caney.data.datamodules.simmim_datamodule

      +

      pytorch_caney.data.datamodules.simmim_datamodule

      -

      pytorch_caney.data.datasets.classification_dataset

      -
      +

      pytorch_caney.data.datasets.classification_dataset

      +
      -

      pytorch_caney.data.datasets.modis_dataset

      +

      pytorch_caney.data.datasets.modis_dataset

      -

      pytorch_caney.data.transforms

      +

      pytorch_caney.data.transforms

      -

      pytorch_caney.data.utils

      +

      pytorch_caney.data.utils

      -

      pytorch_caney.inference

      +

      pytorch_caney.inference

      -

      pytorch_caney.loss.build

      +

      pytorch_caney.loss.build

      -

      pytorch_caney.loss.utils

      +

      pytorch_caney.loss.utils

      -

      pytorch_caney.lr_scheduler

      +

      pytorch_caney.lr_scheduler

      -

      pytorch_caney.metrics

      +

      pytorch_caney.metrics

      -

      pytorch_caney.models.decoders.unet_decoder

      +

      pytorch_caney.models.decoders.unet_decoder

      -

      pytorch_caney.models.mim.mim

      +

      pytorch_caney.models.mim.mim

      -

      pytorch_caney.models.simmim.simmim

      +

      pytorch_caney.models.simmim.simmim

      -

      pytorch_caney.models.build

      +

      pytorch_caney.models.build

      -

      pytorch_caney.models.maskrcnn_model

      -
      +

      pytorch_caney.models.maskrcnn_model

      +
-

pytorch_caney.models.swinv2_model

+

pytorch_caney.models.swinv2_model

-

pytorch_caney.models.unet_model

+

pytorch_caney.models.unet_model

-

pytorch_caney.models.unet_swin_model

+

pytorch_caney.models.unet_swin_model

-

pytorch_caney.network.attention

+

pytorch_caney.network.attention

-

pytorch_caney.network.mlp

+

pytorch_caney.network.mlp

-

pytorch_caney.pipelines.finetuning.finetune

+

pytorch_caney.pipelines.finetuning.finetune

-

pytorch_caney.pipelines.pretraining.mim

+

pytorch_caney.pipelines.pretraining.mim

-

pytorch_caney.pipelines.modis_segmentation

+

pytorch_caney.pipelines.modis_segmentation

-

pytorch_caney.processing

-
+

pytorch_caney.processing

+
-pytorch_caney.processing.get_rand_patches_aug_augcond(img, mask, n_patches=16000, sz=256, nclasses=6, over=50, nodata_ascloud=True, nodata=-9999, method='augcond')[source]
+pytorch_caney.processing.get_rand_patches_aug_augcond(img, mask, n_patches=16000, sz=256, nclasses=6, over=50, nodata_ascloud=True, nodata=-9999, method='augcond')[source]

Generate training data. :param images: ndarray in the format (w,h,c). :type mask: @@ -238,7 +239,7 @@

pytorch_caney.processing
Return type:
-

array

+

array

Returns:

two numpy array with data and labels.

@@ -248,7 +249,7 @@

pytorch_caney.processing
-pytorch_caney.processing.get_rand_patches_rand_cond(img, mask, n_patches=16000, sz=160, nclasses=6, nodata_ascloud=True, method='rand')[source]
+pytorch_caney.processing.get_rand_patches_rand_cond(img, mask, n_patches=16000, sz=160, nclasses=6, nodata_ascloud=True, method='rand')[source]

Generate training data. :param images: ndarray in the format (w,h,c). :type mask: @@ -273,7 +274,7 @@

pytorch_caney.processing
Return type:
-

array

+

array

Returns:

two numpy array with data and labels.

@@ -283,19 +284,19 @@

pytorch_caney.processing
-pytorch_caney.processing.global_standardization(images, strategy='per-batch')[source]
+pytorch_caney.processing.global_standardization(images, strategy='per-batch')[source]

Standardize numpy array using global standardization. :type images: :param images: numpy array in the format (n,w,h,c). :type strategy: :param strategy: can select between per-image or per-batch. -:rtype: array +:rtype: array :return: globally standardized numpy array

-pytorch_caney.processing.local_standardization(images, filename='normalization_data', ndata=None, strategy='per-batch')[source]
+pytorch_caney.processing.local_standardization(images, filename='normalization_data', ndata=None, strategy='per-batch')[source]

Standardize numpy array using local standardization. :type images: :param images: numpy array in the format (n,w,h,c). @@ -305,57 +306,57 @@

pytorch_caney.processingarray +:rtype: array :return: locally standardized numpy array

-pytorch_caney.processing.normalize(images, factor=65535.0)[source]
+pytorch_caney.processing.normalize(images, factor=65535.0)[source]

Normalize numpy array in the range of [0,1] :type images: :param images: numpy array in the format (n,w,h,c). :type factor: :param factor: float number to normalize images, e.g. 2^(16)-1 -:rtype: array +:rtype: array :return: numpy array in the [0,1] range

-pytorch_caney.processing.standardize_batch(image_batch, standardization_type, mean=None, std=None)[source]
+pytorch_caney.processing.standardize_batch(image_batch, standardization_type, mean=None, std=None)[source]

Standardize image within parameter, simple scaling of values. Loca, Global, and Mixed options.

-pytorch_caney.processing.standardize_image(image, standardization_type, mean=None, std=None, global_min=None, global_max=None)[source]
+pytorch_caney.processing.standardize_image(image, standardization_type, mean=None, std=None, global_min=None, global_max=None)[source]

Standardize image within parameter, simple scaling of values. Loca, Global, and Mixed options.

-

pytorch_caney.ptc_logging

+

pytorch_caney.ptc_logging

-

pytorch_caney.training.fine_tuning

-
+

pytorch_caney.training.fine_tuning

+
-

pytorch_caney.training.mim_utils

+

pytorch_caney.training.mim_utils

-

pytorch_caney.training.pre_training

-
+

pytorch_caney.training.pre_training

+
-

pytorch_caney.training.simmim_utils

+

pytorch_caney.training.simmim_utils

-

pytorch_caney.training.utils

-
+

pytorch_caney.training.utils

+
-

pytorch_caney.utils

+

pytorch_caney.utils

diff --git a/latest/py-modindex.html b/latest/py-modindex.html index 6f46251..23afa38 100644 --- a/latest/py-modindex.html +++ b/latest/py-modindex.html @@ -1,21 +1,22 @@ - + Python Module Index — pytorch-caney 0.1.0 documentation - - + + + + - - - - - - + + + + + diff --git a/latest/pytorch_caney.html b/latest/pytorch_caney.html index 1368297..5ba6cc6 100644 --- a/latest/pytorch_caney.html +++ b/latest/pytorch_caney.html @@ -1,22 +1,23 @@ - + - + pytorch-caney — pytorch-caney 0.1.0 documentation - - + + + + - - - - - - + + + + + @@ -77,27 +78,27 @@
-

pytorch-caney

+

pytorch-caney

Python package for lots of Pytorch tools for geospatial science problems.

-

Installation

+

Installation

Install with pip

pip install pytorch-caney
 
-

API

+

API

-

Authors

+

Authors

Jordan A. Caraballo-Vega, jordan.a.caraballo-vega@nasa.gov Caleb S. Spradlin, caleb.s.spradlin@nasa.gov Jian Li, jian.li@nasa.gov

-

License

+

License

The package is released under the MIT License.

diff --git a/latest/readme.html b/latest/readme.html index 1d8c98c..886c04d 100644 --- a/latest/readme.html +++ b/latest/readme.html @@ -1,22 +1,23 @@ - + - + pytorch-caney — pytorch-caney 0.1.0 documentation - - + + + + - - - - - - + + + + + @@ -93,11 +94,11 @@
-

pytorch-caney

+

pytorch-caney

Python package for lots of Pytorch tools for geospatial science problems.

https://zenodo.org/badge/472450059.svg
-

Objectives

+

Objectives

  • Library to process remote sensing imagery using GPU and CPU parallelization.

  • Machine Learning and Deep Learning image classification and regression.

  • @@ -107,7 +108,7 @@

    Objectives -

    Installation

    +

    Installation

    The following library is intended to be used to accelerate the development of data science products for remote sensing satellite imagery, or any other applications. pytorch-caney can be installed by itself, but instructions for installing the full environments are listed under the requirements @@ -120,11 +121,11 @@

    Installation -

    Why Caney?

    +

    Why Caney?

    “Caney” means longhouse in Taíno.

-

Contributors

+

Contributors

-

SatVision

+

SatVision

@@ -155,7 +156,7 @@

SatVision -

SatVision Datasets

+

SatVision Datasets

Name

@@ -174,7 +175,7 @@

SatVision Datasets -

MODIS Surface Reflectance (MOD09GA) Band Details

+

MODIS Surface Reflectance (MOD09GA) Band Details

Name

@@ -207,7 +208,7 @@

MODIS Surface Reflectance (MOD09GA) Band Details -

Pre-training with Masked Image Modeling

+

Pre-training with Masked Image Modeling

To pre-train the swinv2 base model with masked image modeling pre-training, run:

torchrun --nproc_per_node <NGPUS> pytorch-caney/pytorch_caney/pipelines/pretraining/mim.py --cfg <config-file> --dataset <dataset-name> --data-paths <path-to-data-subfolder-1> --batch-size <batch-size> --output <output-dir> --enable-amp
 
@@ -226,7 +227,7 @@

Pre-training with Masked Image Modeling -

Fine-tuning Satvision-base

+

Fine-tuning Satvision-base

To fine-tune the satvision-base pre-trained model, run:

torchrun --nproc_per_node <NGPUS> pytorch-caney/pytorch_caney/pipelines/finetuning/finetune.py --cfg <config-file> --pretrained <path-to-pretrained> --dataset <dataset-name> --data-paths <path-to-data-subfolder-1> --batch-size <batch-size> --output <output-dir> --enable-amp
 
@@ -234,7 +235,7 @@

Fine-tuning Satvision-base -

Testing

+

Testing

For unittests, run this bash command to run linting and unit test runs. This will execute unit tests and linting in a temporary venv environment only used for testing.

git clone git@github.com:nasa-nccs-hpda/pytorch-caney.git
 cd pytorch-caney; bash test.sh
@@ -255,7 +256,7 @@ 

Testing -

References

+

References

  • Pytorch Lightning

  • Swin Transformer

  • diff --git a/latest/search.html b/latest/search.html index 29f9fee..78c0c88 100644 --- a/latest/search.html +++ b/latest/search.html @@ -1,22 +1,23 @@ - + Search — pytorch-caney 0.1.0 documentation - - + + + + - - - - - - + + + + + diff --git a/latest/searchindex.js b/latest/searchindex.js index 111fb2a..688629d 100644 --- a/latest/searchindex.js +++ b/latest/searchindex.js @@ -1 +1 @@ -Search.setIndex({"docnames": ["examples", "index", "modules", "pytorch_caney", "readme", "source/index"], "filenames": ["examples.rst", "index.rst", "modules.rst", "pytorch_caney.rst", "readme.rst", "source/index.rst"], "titles": ["<no title>", "Welcome to pytorch-caney\u2019s documentation!", "pytorch-caney package", "pytorch-caney", "pytorch-caney", "Welcome to tensorflow-caney\u2019s documentation!"], "terms": {"object": 1, "instal": 1, "why": 1, "contributor": 1, "contribut": 1, "satvis": 1, "dataset": 1, "modi": 1, "surfac": 1, "reflect": 1, "mod09ga": 1, "band": 1, "detail": 1, "pre": 1, 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"pytorch_caney": [[3, "module-pytorch_caney"]]}}) \ No newline at end of file diff --git a/latest/source/index.html b/latest/source/index.html index 3aeccd3..ca1d981 100644 --- a/latest/source/index.html +++ b/latest/source/index.html @@ -1,22 +1,23 @@ - + - + Welcome to tensorflow-caney’s documentation! — pytorch-caney 0.1.0 documentation - - + + + + - - - - - - + + + + + @@ -77,12 +78,12 @@
    -

    Welcome to tensorflow-caney’s documentation!

    +

    Welcome to tensorflow-caney’s documentation!

    -

    Indices and tables

    +

    Indices and tables

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