diff --git a/.github/Architecture.md b/.github/Architecture.md index 3e377957e..1e3182ef0 100644 --- a/.github/Architecture.md +++ b/.github/Architecture.md @@ -4,44 +4,44 @@ ``` 📦 backend -| |- 📂 aws_helpers: -| | |- 📂 dynamo_db_utils: -| | | |- 📜 DynamoUnitTests.md -| | | |- 📜 dynamo_db_utils.py -| | | |- 📜 trainspace_db.py -| | | |- 📜 constants.py : list of helpful constants -| | | |- 📜 userprogress_db.py -| | |- 📜 __init__.py -| |- 📂 ml: -| | |- 📜 ml_trainer.py : train a classical machine learning learning model on the dataset -| | |- 📜 __init__.py -| | |- 📜 ml_model_parser.py | |- 📂 dl: -| | |- 📜 __init__.py +| | |- 📜 dl_model_parser.py : parse the user specified pytorch model | | |- 📜 dl_trainer.py : train a deep learning model on the dataset +| | |- 📜 __init__.py | | |- 📜 dl_model.py : torch model based on user specifications from drag and drop -| | |- 📜 dl_model_parser.py : parse the user specified pytorch model | | |- 📜 detection.py | | |- 📜 dl_eval.py : Evaluation functions for deep learning models in Pytorch (eg: accuracy, loss, etc) +| |- 📂 ml: +| | |- 📜 ml_trainer.py : train a classical machine learning learning model on the dataset +| | |- 📜 ml_model_parser.py +| | |- 📜 __init__.py | |- 📂 common: -| | |- 📜 default_datasets.py : store logic to load in default datasets from scikit-learn +| | |- 📜 optimizer.py : what optimizer to use (ie: SGD or Adam for now) +| | |- 📜 dataset.py : read in the dataset through URL or file upload +| | |- 📜 loss_functions.py : loss function enum | | |- 📜 __init__.py | | |- 📜 preprocessing.py -| | |- 📜 dataset.py : read in the dataset through URL or file upload | | |- 📜 constants.py : list of helpful constants -| | |- 📜 optimizer.py : what optimizer to use (ie: SGD or Adam for now) | | |- 📜 ai_drive.py +| | |- 📜 default_datasets.py : store logic to load in default datasets from scikit-learn +| | |- 📜 utils.py : utility functions that could be helpful | | |- 📜 email_notifier.py : Endpoint to send email notification of training results via API Gateway + AWS SES -| | |- 📜 loss_functions.py : loss function enum | | |- 📜 kernel.py -| | |- 📜 utils.py : utility functions that could be helpful -| |- 📜 __init__.py -| |- 📜 middleware.py -| |- 📜 poetry.lock +| |- 📂 aws_helpers: +| | |- 📂 dynamo_db_utils: +| | | |- 📜 DynamoUnitTests.md +| | | |- 📜 dynamo_db_utils.py +| | | |- 📜 constants.py : list of helpful constants +| | | |- 📜 trainspace_db.py +| | | |- 📜 userprogress_db.py +| | |- 📜 __init__.py | |- 📜 epoch_times.csv | |- 📜 app.py : run the backend (entrypoint script) -| |- 📜 data.csv : data csv file for use in the playground +| |- 📜 __init__.py | |- 📜 pyproject.toml +| |- 📜 data.csv : data csv file for use in the playground +| |- 📜 poetry.lock +| |- 📜 middleware.py ``` ## Frontend Architecture @@ -49,173 +49,175 @@ ``` 📦 frontend | |- 📂 src: -| | |- 📂 backend_outputs: -| | | |- 📜 model.pt : Last model.pt output -| | | |- 📜 my_deep_learning_model.onnx : Last ONNX file output -| | | |- 📜 model.pkl -| | |- 📂 pages: -| | | |- 📂 train: -| | | | |- 📜 [train_space_id].tsx -| | | | |- 📜 index.tsx -| | | |- 📜 feedback.tsx -| | | |- 📜 settings.tsx -| | | |- 📜 _app.tsx -| | | |- 📜 learn.tsx -| | | |- 📜 login.tsx -| | | |- 📜 wiki.tsx -| | | |- 📜 _document.tsx -| | | |- 📜 about.tsx -| | | |- 📜 forgot.tsx -| | | |- 📜 dashboard.tsx -| | | |- 📜 LearnContent.tsx | | |- 📂 features: | | | |- 📂 Train: -| | | | |- 📂 constants: -| | | | | |- 📜 trainConstants.ts +| | | | |- 📂 redux: +| | | | | |- 📜 trainspaceSlice.ts +| | | | | |- 📜 trainspaceApi.ts | | | | |- 📂 features: -| | | | | |- 📂 Image: -| | | | | | |- 📂 constants: -| | | | | | | |- 📜 imageConstants.ts -| | | | | | |- 📂 components: -| | | | | | | |- 📜 ImageTrainspace.tsx -| | | | | | | |- 📜 ImageDatasetStep.tsx -| | | | | | | |- 📜 ImageReviewStep.tsx -| | | | | | | |- 📜 ImageParametersStep.tsx -| | | | | | |- 📂 types: -| | | | | | | |- 📜 imageTypes.ts -| | | | | | |- 📂 redux: -| | | | | | | |- 📜 imageActions.ts -| | | | | | | |- 📜 imageApi.ts -| | | | | | |- 📜 index.ts | | | | | |- 📂 Tabular: +| | | | | | |- 📂 redux: +| | | | | | | |- 📜 tabularApi.ts +| | | | | | | |- 📜 tabularActions.ts | | | | | | |- 📂 constants: | | | | | | | |- 📜 tabularConstants.ts +| | | | | | |- 📂 types: +| | | | | | | |- 📜 tabularTypes.ts | | | | | | |- 📂 components: -| | | | | | | |- 📜 TabularParametersStep.tsx +| | | | | | | |- 📜 TabularReviewStep.tsx | | | | | | | |- 📜 TabularDatasetStep.tsx +| | | | | | | |- 📜 TabularParametersStep.tsx | | | | | | | |- 📜 TabularTrainspace.tsx -| | | | | | | |- 📜 TabularReviewStep.tsx -| | | | | | |- 📂 types: -| | | | | | | |- 📜 tabularTypes.ts +| | | | | | | |- 📜 TabularFlow.tsx +| | | | | | |- 📜 index.ts +| | | | | |- 📂 Image: | | | | | | |- 📂 redux: -| | | | | | | |- 📜 tabularActions.ts -| | | | | | | |- 📜 tabularApi.ts +| | | | | | | |- 📜 imageActions.ts +| | | | | | | |- 📜 imageApi.ts +| | | | | | |- 📂 constants: +| | | | | | | |- 📜 imageConstants.ts +| | | | | | |- 📂 types: +| | | | | | | |- 📜 imageTypes.ts +| | | | | | |- 📂 components: +| | | | | | | |- 📜 ImageParametersStep.tsx +| | | | | | | |- 📜 ImageFlow.tsx +| | | | | | | |- 📜 ImageTrainspace.tsx +| | | | | | | |- 📜 ImageReviewStep.tsx +| | | | | | | |- 📜 ImageDatasetStep.tsx | | | | | | |- 📜 index.ts -| | | | |- 📂 components: -| | | | | |- 📜 CreateTrainspace.tsx -| | | | | |- 📜 DatasetStepLayout.tsx -| | | | | |- 📜 TrainspaceLayout.tsx +| | | | |- 📂 constants: +| | | | | |- 📜 trainConstants.ts | | | | |- 📂 types: | | | | | |- 📜 trainTypes.ts -| | | | |- 📂 redux: -| | | | | |- 📜 trainspaceApi.ts -| | | | | |- 📜 trainspaceSlice.ts -| | | |- 📂 Dashboard: | | | | |- 📂 components: -| | | | | |- 📜 TrainDoughnutChart.tsx -| | | | | |- 📜 TrainBarChart.tsx -| | | | | |- 📜 TrainDataGrid.tsx +| | | | | |- 📜 TrainspaceLayout.tsx +| | | | | |- 📜 DatasetStepLayout.tsx +| | | | | |- 📜 CreateTrainspace.tsx +| | | |- 📂 Feedback: | | | | |- 📂 redux: -| | | | | |- 📜 dashboardApi.ts +| | | | | |- 📜 feedbackApi.ts +| | | |- 📂 OpenAi: +| | | | |- 📜 openAiUtils.ts | | | |- 📂 LearnMod: -| | | | |- 📜 LearningModulesContent.tsx -| | | | |- 📜 Exercise.tsx -| | | | |- 📜 ImageComponent.tsx | | | | |- 📜 ModulesSideBar.tsx +| | | | |- 📜 ImageComponent.tsx | | | | |- 📜 MCQuestion.tsx -| | | | |- 📜 FRQuestion.tsx | | | | |- 📜 ClassCard.tsx -| | | |- 📂 Feedback: +| | | | |- 📜 FRQuestion.tsx +| | | | |- 📜 Exercise.tsx +| | | | |- 📜 LearningModulesContent.tsx +| | | |- 📂 Dashboard: | | | | |- 📂 redux: -| | | | | |- 📜 feedbackApi.ts -| | | |- 📂 OpenAi: -| | | | |- 📜 openAiUtils.ts +| | | | | |- 📜 dashboardApi.ts +| | | | |- 📂 components: +| | | | | |- 📜 TrainDoughnutChart.tsx +| | | | | |- 📜 TrainDataGrid.tsx +| | | | | |- 📜 TrainBarChart.tsx | | |- 📂 common: +| | | |- 📂 redux: +| | | | |- 📜 backendApi.ts +| | | | |- 📜 userLogin.ts +| | | | |- 📜 train.ts +| | | | |- 📜 store.ts +| | | | |- 📜 hooks.ts | | | |- 📂 styles: | | | | |- 📜 globals.css | | | | |- 📜 Home.module.css | | | |- 📂 components: | | | | |- 📜 ClientOnlyPortal.tsx | | | | |- 📜 EmailInput.tsx -| | | | |- 📜 TitleText.tsx | | | | |- 📜 NavBarMain.tsx -| | | | |- 📜 Footer.tsx | | | | |- 📜 Spacer.tsx +| | | | |- 📜 HtmlTooltip.tsx +| | | | |- 📜 TitleText.tsx +| | | | |- 📜 DlpTooltip.tsx +| | | | |- 📜 Footer.tsx | | | |- 📂 utils: +| | | | |- 📜 dndHelpers.ts | | | | |- 📜 firebase.ts | | | | |- 📜 dateFormat.ts -| | | | |- 📜 dndHelpers.ts -| | | |- 📂 redux: -| | | | |- 📜 backendApi.ts -| | | | |- 📜 userLogin.ts -| | | | |- 📜 hooks.ts -| | | | |- 📜 store.ts -| | | | |- 📜 train.ts +| | |- 📂 pages: +| | | |- 📂 train: +| | | | |- 📜 [train_space_id].tsx +| | | | |- 📜 index.tsx +| | | |- 📜 _document.tsx +| | | |- 📜 dashboard.tsx +| | | |- 📜 _app.tsx +| | | |- 📜 LearnContent.tsx +| | | |- 📜 forgot.tsx +| | | |- 📜 learn.tsx +| | | |- 📜 settings.tsx +| | | |- 📜 feedback.tsx +| | | |- 📜 about.tsx +| | | |- 📜 login.tsx +| | | |- 📜 wiki.tsx +| | |- 📂 backend_outputs: +| | | |- 📜 model.pkl +| | | |- 📜 model.pt : Last model.pt output +| | | |- 📜 my_deep_learning_model.onnx : Last ONNX file output | | |- 📜 iris.csv : Sample CSV data -| | |- 📜 next-env.d.ts | | |- 📜 constants.ts | | |- 📜 GlobalStyle.ts -| |- 📂 layer_docs: -| | |- 📜 Linear.md : Doc for Linear layer -| | |- 📜 Softmax.md : Doc for Softmax layer -| | |- 📜 softmax_equation.png : PNG file of Softmax equation -| | |- 📜 ReLU.md : Doc for ReLU later +| | |- 📜 next-env.d.ts | |- 📂 public: | | |- 📂 images: +| | | |- 📂 wiki_images: +| | | | |- 📜 maxpool2d.gif +| | | | |- 📜 tanh_plot.png +| | | | |- 📜 avgpool_maxpool.gif +| | | | |- 📜 batchnorm_diagram.png +| | | | |- 📜 softmax_equation.png : PNG file of Softmax equation +| | | | |- 📜 conv2d.gif +| | | | |- 📜 conv2d2.gif +| | | | |- 📜 tanh_equation.png +| | | | |- 📜 dropout_diagram.png +| | | | |- 📜 sigmoid_equation.png +| | | |- 📂 learn_mod_images: +| | | | |- 📜 ReLUactivation.png +| | | | |- 📜 binarystepactivation.png +| | | | |- 📜 lossExampleEquation.png +| | | | |- 📜 sigmoidactivation.png +| | | | |- 📜 sigmoidfunction.png +| | | | |- 📜 robotImage.jpg +| | | | |- 📜 lossExample.png +| | | | |- 📜 lossExampleTable.png +| | | | |- 📜 neuronWithEquation.png +| | | | |- 📜 LeakyReLUactivation.png +| | | | |- 📜 neuron.png +| | | | |- 📜 neuralnet.png +| | | | |- 📜 tanhactivation.png | | | |- 📂 logos: | | | | |- 📂 dlp_branding: | | | | | |- 📜 dlp-logo.svg : DLP Logo, duplicate of files in public, but essential as the frontend can't read public | | | | | |- 📜 dlp-logo.png : DLP Logo, duplicate of files in public, but essential as the frontend can't read public | | | | |- 📜 dsgt-logo-dark.png | | | | |- 📜 github.png -| | | | |- 📜 dsgt-logo-light.png -| | | | |- 📜 pandas-logo.png -| | | | |- 📜 react-logo.png +| | | | |- 📜 google.png | | | | |- 📜 python-logo.png +| | | | |- 📜 dsgt-logo-white-back.png +| | | | |- 📜 pandas-logo.png +| | | | |- 📜 aws-logo.png | | | | |- 📜 flask-logo.png +| | | | |- 📜 react-logo.png +| | | | |- 📜 dsgt-logo-light.png | | | | |- 📜 pytorch-logo.png -| | | | |- 📜 aws-logo.png -| | | | |- 📜 google.png -| | | | |- 📜 dsgt-logo-white-back.png -| | | |- 📂 learn_mod_images: -| | | | |- 📜 lossExampleTable.png -| | | | |- 📜 tanhactivation.png -| | | | |- 📜 sigmoidactivation.png -| | | | |- 📜 LeakyReLUactivation.png -| | | | |- 📜 ReLUactivation.png -| | | | |- 📜 robotImage.jpg -| | | | |- 📜 lossExample.png -| | | | |- 📜 binarystepactivation.png -| | | | |- 📜 lossExampleEquation.png -| | | | |- 📜 neuronWithEquation.png -| | | | |- 📜 neuron.png -| | | | |- 📜 neuralnet.png -| | | | |- 📜 sigmoidfunction.png -| | | |- 📂 wiki_images: -| | | | |- 📜 avgpool_maxpool.gif -| | | | |- 📜 conv2d2.gif -| | | | |- 📜 dropout_diagram.png -| | | | |- 📜 batchnorm_diagram.png -| | | | |- 📜 tanh_plot.png -| | | | |- 📜 softmax_equation.png : PNG file of Softmax equation -| | | | |- 📜 maxpool2d.gif -| | | | |- 📜 tanh_equation.png -| | | | |- 📜 conv2d.gif -| | | | |- 📜 sigmoid_equation.png | | | |- 📜 demo_video.gif : GIF tutorial of a simple classification training session -| | |- 📜 dlp-logo.svg : DLP Logo, duplicate of files in public, but essential as the frontend can't read public -| | |- 📜 robots.txt -| | |- 📜 dlp-logo.png : DLP Logo, duplicate of files in public, but essential as the frontend can't read public -| | |- 📜 manifest.json : Default React file for choosing icon based on -| | |- 📜 index.html : Base HTML file that will be initially rendered | | |- 📜 dlp-logo.ico : DLP Logo +| | |- 📜 index.html : Base HTML file that will be initially rendered +| | |- 📜 manifest.json : Default React file for choosing icon based on +| | |- 📜 robots.txt +| |- 📂 layer_docs: +| | |- 📜 Softmax.md : Doc for Softmax layer +| | |- 📜 Linear.md : Doc for Linear layer +| | |- 📜 softmax_equation.png : PNG file of Softmax equation +| | |- 📜 ReLU.md : Doc for ReLU later +| |- 📜 .eslintrc.json +| |- 📜 .eslintignore | |- 📜 package.json | |- 📜 jest.config.js -| |- 📜 .eslintrc.json | |- 📜 tsconfig.json +| |- 📜 next.config.js | |- 📜 yarn.lock -| |- 📜 .eslintignore | |- 📜 next-env.d.ts -| |- 📜 next.config.js ``` diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md index 5b4a55ffc..4c6584a76 100644 --- a/.github/pull_request_template.md +++ b/.github/pull_request_template.md @@ -1,5 +1,6 @@ # Title of Pull Request HERE +Github Issue Number Here: **What user problem are we solving?** **What solution does this PR provide?** diff --git a/CODEOWNERS b/CODEOWNERS index 008e903ed..43b524cd1 100644 --- a/CODEOWNERS +++ b/CODEOWNERS @@ -3,4 +3,4 @@ # the contributors all will be requested for # review when someone opens a pull request. -* @karkir0003 @farisdurrani @dwu359 +* @DSGT-DLP/project-lead diff --git a/aws_write/poetry.lock b/aws_write/poetry.lock index dcd0e9fbd..3a6814ec1 100644 --- a/aws_write/poetry.lock +++ b/aws_write/poetry.lock @@ -225,7 +225,7 @@ name = "boto3" version = "1.28.9" description = "The AWS SDK for Python" optional = false -python-versions = ">= 3.7" +python-versions = "*" files = [ {file = "boto3-1.28.9-py3-none-any.whl", hash = "sha256:01f078047eb4d238c6b9c6cc623f2af33b4ae67980c5326691e35cb5493ff6c7"}, {file = "boto3-1.28.9.tar.gz", hash = "sha256:4cc0c6005be910e52077227e670930ab55a41ba86cdb6d1c052571d08cd4d32c"}, @@ -236,24 +236,21 @@ botocore = ">=1.31.9,<1.32.0" jmespath = ">=0.7.1,<2.0.0" s3transfer = ">=0.6.0,<0.7.0" -[package.extras] -crt = ["botocore[crt] (>=1.21.0,<2.0a0)"] - [[package]] name = "botocore" version = "1.31.9" description = "Low-level, data-driven core of boto 3." optional = false -python-versions = ">= 3.7" +python-versions = "*" files = [ {file = "botocore-1.31.9-py3-none-any.whl", hash = "sha256:e56ccd3536a90094ea5b176b5dd33bfe4f049efdf71af468ea1661bd424c787d"}, {file = "botocore-1.31.9.tar.gz", hash = "sha256:bd849d3ac95f1781385ed831d753a04a3ec870a59d6598175aaedd71dc2baf5f"}, ] [package.dependencies] -jmespath = ">=0.7.1,<2.0.0" -python-dateutil = ">=2.1,<3.0.0" -urllib3 = ">=1.25.4,<1.27" +docutils = ">=0.10" +jmespath = ">=0.7.1,<1.0.0" +python-dateutil = {version = ">=2.1,<3.0.0", markers = "python_version >= \"2.7\""} [package.extras] crt = ["awscrt (==0.16.26)"] @@ -929,13 +926,13 @@ i18n = ["Babel (>=2.7)"] [[package]] name = "jmespath" -version = "1.0.1" +version = "0.10.0" description = "JSON Matching Expressions" optional = false -python-versions = ">=3.7" +python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*" files = [ - {file = "jmespath-1.0.1-py3-none-any.whl", hash = "sha256:02e2e4cc71b5bcab88332eebf907519190dd9e6e82107fa7f83b1003a6252980"}, - {file = "jmespath-1.0.1.tar.gz", hash = "sha256:90261b206d6defd58fdd5e85f478bf633a2901798906be2ad389150c5c60edbe"}, + {file = "jmespath-0.10.0-py2.py3-none-any.whl", hash = "sha256:cdf6525904cc597730141d61b36f2e4b8ecc257c420fa2f4549bac2c2d0cb72f"}, + {file = "jmespath-0.10.0.tar.gz", hash = "sha256:b85d0567b8666149a93172712e68920734333c0ce7e89b78b3e987f71e5ed4f9"}, ] [[package]] @@ -2336,20 +2333,17 @@ files = [ [[package]] name = "s3transfer" -version = "0.6.1" +version = "0.1.13" description = "An Amazon S3 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files a/frontend/public/dlp-logo.ico and b/frontend/public/dlp-logo.ico differ diff --git a/frontend/public/dlp-logo.png b/frontend/public/dlp-logo.png deleted file mode 100644 index 80a9ada54..000000000 Binary files a/frontend/public/dlp-logo.png and /dev/null differ diff --git a/frontend/public/dlp-logo.svg b/frontend/public/dlp-logo.svg deleted file mode 100644 index 30fe0140d..000000000 --- a/frontend/public/dlp-logo.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/frontend/public/images/logos/dlp_branding/dlp-logo.png b/frontend/public/images/logos/dlp_branding/dlp-logo.png index 8b839ec8e..841c7fa9a 100644 Binary files a/frontend/public/images/logos/dlp_branding/dlp-logo.png and b/frontend/public/images/logos/dlp_branding/dlp-logo.png differ diff --git a/frontend/public/images/logos/dlp_branding/dlp-logo.svg b/frontend/public/images/logos/dlp_branding/dlp-logo.svg index 30fe0140d..8dbd4fe28 100644 --- a/frontend/public/images/logos/dlp_branding/dlp-logo.svg +++ b/frontend/public/images/logos/dlp_branding/dlp-logo.svg @@ -1 +1,16 @@ - \ No newline at end of file + + + + + + + + + + + + + + + + diff --git a/frontend/src/common/components/DlpTooltip.tsx b/frontend/src/common/components/DlpTooltip.tsx new file mode 100644 index 000000000..73e22914c --- /dev/null +++ b/frontend/src/common/components/DlpTooltip.tsx @@ -0,0 +1,61 @@ +import React from "react"; +import IconButton from "@mui/material/IconButton"; +import Tooltip, { tooltipClasses } from "@mui/material/Tooltip"; +import { styled } from "@mui/material/styles"; + +interface DlpTooltipProps { + children: React.ReactNode; + title: React.ReactNode; + isIcon?: boolean; + onClick?: () => void; + className?: string; + disabled?: boolean; +} + +const DlpTooltip = (props: DlpTooltipProps) => { + const { children, title, isIcon, onClick, className, disabled } = props; + + if (isIcon) { + return ( + + + + {children} + + + + ); + } + + return styled( + ({ + className, + title, + children, + ...props + }: { + className?: string; + children: React.ReactElement; + title: React.ReactNode; + }) => ( + + {children} + + ) + )(({ theme }) => ({ + [`& .${tooltipClasses.tooltip}`]: { + backgroundColor: "rgba(255, 255, 255, 0.95)", + color: "rgba(0, 0, 0, 0.87)", + maxWidth: 220, + fontSize: theme.typography.pxToRem(12), + border: "none", + }, + })); +}; + +export default DlpTooltip; diff --git a/frontend/src/common/components/HtmlTooltip.tsx b/frontend/src/common/components/HtmlTooltip.tsx new file mode 100644 index 000000000..4aa66cae9 --- /dev/null +++ b/frontend/src/common/components/HtmlTooltip.tsx @@ -0,0 +1,30 @@ +import { tooltipClasses, Tooltip } from "@mui/material"; +import { styled } from "@mui/material/styles"; +import React from "react"; + +const HtmlTooltip = styled( + ({ + className, + title, + children, + ...props + }: { + className?: string; + children: React.ReactElement; + title: React.ReactNode; + }) => ( + + {children} + + ) +)(({ theme }) => ({ + [`& .${tooltipClasses.tooltip}`]: { + backgroundColor: "rgba(255, 255, 255, 0.95)", + color: "rgba(0, 0, 0, 0.87)", + maxWidth: 220, + fontSize: theme.typography.pxToRem(12), + border: "none", + }, +})); + +export default HtmlTooltip; diff --git a/frontend/src/common/components/NavBarMain.tsx b/frontend/src/common/components/NavBarMain.tsx index c045119b4..579746a9f 100644 --- a/frontend/src/common/components/NavBarMain.tsx +++ b/frontend/src/common/components/NavBarMain.tsx @@ -1,28 +1,23 @@ -import AppBar from "@mui/material/AppBar"; +import { useAppDispatch, useAppSelector } from "@/common/redux/hooks"; +import { isSignedIn, signOutUser } from "@/common/redux/userLogin"; +import ArrowDropDownIcon from "@mui/icons-material/ArrowDropDown"; import { FormControlLabel, Icon, Switch } from "@mui/material"; -import Toolbar from "@mui/material/Toolbar"; -import Typography from "@mui/material/Typography"; -import MenuList from "@mui/material/Menu"; -import Container from "@mui/material/Container"; +import AppBar from "@mui/material/AppBar"; import Button from "@mui/material/Button"; -import MenuItem from "@mui/material/MenuItem"; +import Container from "@mui/material/Container"; import Grid from "@mui/material/Grid"; -import ArrowDropDownIcon from "@mui/icons-material/ArrowDropDown"; +import MenuList from "@mui/material/Menu"; +import MenuItem from "@mui/material/MenuItem"; import Stack from "@mui/material/Stack"; +import Toolbar from "@mui/material/Toolbar"; +import Typography from "@mui/material/Typography"; import storage from "local-storage-fallback"; +import Image from "next/image"; +import Link from "next/link"; import React, { useEffect, useState } from "react"; import { ThemeProvider } from "styled-components"; import { URLs } from "../../constants"; import DSGTLogo from "/public/images/logos/dlp_branding/dlp-logo.png"; -import { useAppDispatch, useAppSelector } from "@/common/redux/hooks"; -import { - UserType, - isSignedIn, - setCurrentUser, - signOutUser, -} from "@/common/redux/userLogin"; -import Image from "next/image"; -import Link from "next/link"; const NavbarMain = () => { const user = useAppSelector((state) => state.currentUser.user); @@ -79,24 +74,19 @@ const NavbarMain = () => { DSGT Logo Deep Learning Playground @@ -174,7 +164,6 @@ const NavbarMain = () => { - Learn diff --git a/frontend/src/features/Dashboard/components/TrainDataGrid.tsx b/frontend/src/features/Dashboard/components/TrainDataGrid.tsx index d7ac75e76..a00815848 100644 --- a/frontend/src/features/Dashboard/components/TrainDataGrid.tsx +++ b/frontend/src/features/Dashboard/components/TrainDataGrid.tsx @@ -16,7 +16,7 @@ import { useRouter } from "next/router"; import { useAppDispatch } from "@/common/redux/hooks"; import { ALL_TRAINSPACE_SETTINGS, - DATA_SOURCE_ARR, + IMPLEMENTED_DATA_SOURCE_ARR, } from "@/features/Train/constants/trainConstants"; import { formatDate } from "@/common/utils/dateFormat"; import { removeTrainspaceData } from "@/features/Train/redux/trainspaceSlice"; @@ -178,7 +178,7 @@ const NewTrainSpaceMenu = ({ open={open} onClose={handleClose} > - {DATA_SOURCE_ARR.map((source) => ( + {IMPLEMENTED_DATA_SOURCE_ARR.map((source) => ( { @@ -18,9 +18,7 @@ const CreateTrainspace = () => { control, setValue, } = useForm({ - defaultValues: { - name: "My Trainspace", - }, + defaultValues: { name: "My Trainspace" }, }); const dispatch = useAppDispatch(); const router = useRouter(); @@ -32,6 +30,7 @@ const CreateTrainspace = () => { setValue("dataSource", router.query.source as DATA_SOURCE); } }, [router.isReady]); + return ( { value={value ?? ""} helperText={errors.dataSource ? "Data Source is required" : ""} > - {DATA_SOURCE_ARR.map((source) => ( + {IMPLEMENTED_DATA_SOURCE_ARR.map((source) => ( {ALL_TRAINSPACE_SETTINGS[source].name} diff --git a/frontend/src/features/Train/constants/trainConstants.ts b/frontend/src/features/Train/constants/trainConstants.ts index 4ee59a95c..05b16c52c 100644 --- a/frontend/src/features/Train/constants/trainConstants.ts +++ b/frontend/src/features/Train/constants/trainConstants.ts @@ -19,13 +19,11 @@ export const DATA_SOURCE_ARR = [ export const ALL_TRAINSPACE_SETTINGS = { TABULAR: TABULAR_TRAINSPACE_SETTINGS, - PRETRAINED: TABULAR_TRAINSPACE_SETTINGS, IMAGE: IMAGE_TRAINSPACE_SETTINGS, - AUDIO: TABULAR_TRAINSPACE_SETTINGS, - TEXTUAL: TABULAR_TRAINSPACE_SETTINGS, - CLASSICAL_ML: TABULAR_TRAINSPACE_SETTINGS, - OBJECT_DETECTION: TABULAR_TRAINSPACE_SETTINGS, }; +export const IMPLEMENTED_DATA_SOURCE_ARR = Object.keys( + ALL_TRAINSPACE_SETTINGS +) as (keyof typeof ALL_TRAINSPACE_SETTINGS)[]; export const ALL_STEP_SETTINGS = { TABULAR: TABULAR_STEP_SETTINGS, diff --git a/frontend/src/features/Train/features/Image/components/ImageFlow.tsx b/frontend/src/features/Train/features/Image/components/ImageFlow.tsx new file mode 100644 index 000000000..03d250c47 --- /dev/null +++ b/frontend/src/features/Train/features/Image/components/ImageFlow.tsx @@ -0,0 +1,313 @@ +import HtmlTooltip from "@/common/components/HtmlTooltip"; +import InfoIcon from "@mui/icons-material/Info"; +import { + Button, + Card, + Divider, + Paper, + Stack, + TextField, + Typography, +} from "@mui/material"; +import React, { useEffect } from "react"; +import ReactFlow, { + Background, + BackgroundVariant, + Controls, + Edge, + Handle, + Node, + NodeTypes, + Position, + addEdge, + useEdgesState, + useNodesState, +} from "reactflow"; +import "reactflow/dist/style.css"; +import { + ALL_LAYERS, + DEFAULT_LAYERS, + STEP_SETTINGS, +} from "../constants/imageConstants"; +import { ParameterData } from "../types/imageTypes"; +import assert from "assert"; +import { nanoid } from "nanoid/non-secure"; +import { toast } from "react-toastify"; + +interface ImageFlowProps { + setLayers?: (layers: ParameterData["layers"]) => void; +} + +export default function ImageFlow(props: ImageFlowProps) { + const { setLayers } = props; + + const initialNodes: Node[] = [ + ROOT_NODE, + ...DEFAULT_LAYERS.MNIST.map((layer, i) => ({ + id: `${layer.value}-${i}`, + type: "textUpdater", + position: { + x: DEFAULT_X_POSITION, + y: (i + 1) * 100, + }, + data: { + label: STEP_SETTINGS.PARAMETERS.layers[layer.value].label, + value: layer.value, + parameters: layer.parameters.slice(), + onChange: onChange, + }, + })), + ]; + const initialEdges: Edge[] = createInitialEdges(); + + const [nodes, setNodes, onNodesChange] = useNodesState(initialNodes); + const [edges, setEdges, onEdgesChange] = useEdgesState(initialEdges); + + useEffect(() => { + if (setLayers) { + const layers = handleExportLayers(); + setLayers(layers); + } + }, [nodes, edges]); + + function handleExportLayers(): ParameterData["layers"] { + const layers: ParameterData["layers"] = []; + const visited = new Set(["root"]); + + const directedEdges: Record> = {}; + edges.forEach((edge) => { + const sourceNode = nodes.find((node) => node.id === edge.source); + const targetNode = nodes.find((node) => node.id === edge.target); + if (sourceNode && targetNode) { + directedEdges[sourceNode.id] = targetNode; + } + }); + + let nextNode = directedEdges["root"]; + + // appending all layers from the graph + while (nextNode) { + assert(nextNode.data.value !== "root"); + + if (visited.has(nextNode.id)) { + toast.error("Cycle detected in layers"); + return layers; + } + visited.add(nextNode.id); + layers.push({ + value: nextNode.data.value, + parameters: nextNode.data.parameters || [], + }); + nextNode = directedEdges[nextNode.id]; + } + + return layers; + } + + function onChange(args: OnChangeArgs) { + setNodes((nds) => + nds.map((node) => { + if (node.id !== args.id) return node; + if (!node.data.parameters) return node; + + node.data.parameters[args.parameterIndex] = args.newValue; + return node; + }) + ); + } + + return ( + <> + + + + Layers + + + {STEP_SETTINGS.PARAMETERS.layerValues.map((value) => ( + + ))} + + + +
+ setEdges((eds) => addEdge(params, eds))} + nodeTypes={nodeTypes} + > + + + +
+ + ); +} + +interface TextUpdaterNodeProps { + id: string; + data: LayerNodeData; + isConnectable: boolean; +} + +function TextUpdaterNode(props: TextUpdaterNodeProps) { + const { data, isConnectable, id } = props; + assert(data.value !== "root"); + const layer = STEP_SETTINGS.PARAMETERS.layers[data.value]; + + return ( + <> + +
+ + + + {layer.label} + {layer.description} + + } + > + Info + + + + {layer.label} + + + } + > + {layer.parameters.map((parameter, index) => ( + + data.onChange({ + id: id, + newValue: Number(e.target.value), + parameterIndex: index, + }) + } + key={index} + label={parameter.label} + defaultValue={data.parameters?.[index]} + size="small" + type={parameter.type} + required + /> + ))} + + + + +
+ + + ); +} + +interface OnChangeArgs { + id: string; + newValue: number; + parameterIndex: number; +} + +interface LayerNodeData { + label: + | (typeof STEP_SETTINGS.PARAMETERS.layers)[ALL_LAYERS]["label"] + | "Start"; + value: ALL_LAYERS | "root"; + parameters?: number[]; + onChange: (args: OnChangeArgs) => void; +} + +const DEFAULT_X_POSITION = 10; + +const ROOT_NODE: Node = { + id: `root`, + type: "input", + position: { x: DEFAULT_X_POSITION, y: 0 }, + deletable: false, + data: { + label: "Start", + value: "root", + parameters: [], + onChange: () => undefined, + }, +}; +const nodeTypes: NodeTypes = { textUpdater: TextUpdaterNode }; + +function createInitialEdges(): Edge[] { + const edges: Edge[] = []; + const defaultLayers = DEFAULT_LAYERS.MNIST; + + // connecting root to first layer + edges.push({ + id: `eroot-0`, + source: "root", + target: `${defaultLayers[0].value}-0`, + }); + + // connecting all layers + for (let i = 0; i < defaultLayers.length - 1; i++) { + edges.push({ + id: `e${i}-${i + 1}`, + source: `${defaultLayers[i].value}-${i}`, + target: `${defaultLayers[i + 1].value}-${i + 1}`, + }); + } + return edges; +} diff --git a/frontend/src/features/Train/features/Image/components/ImageParametersStep.tsx b/frontend/src/features/Train/features/Image/components/ImageParametersStep.tsx index 332572cb5..2c8311b2d 100644 --- a/frontend/src/features/Train/features/Image/components/ImageParametersStep.tsx +++ b/frontend/src/features/Train/features/Image/components/ImageParametersStep.tsx @@ -1,25 +1,39 @@ -import React, { useEffect, useMemo, useState } from "react"; -import { useLazyGetColumnsFromDatasetQuery } from "@/features/Train/redux/trainspaceApi"; import { useAppDispatch, useAppSelector } from "@/common/redux/hooks"; -import { styled } from "@mui/material/styles"; -import Tooltip, { tooltipClasses } from "@mui/material/Tooltip"; import InfoIcon from "@mui/icons-material/Info"; +import Tooltip, { tooltipClasses } from "@mui/material/Tooltip"; +import { styled } from "@mui/material/styles"; +import React, { useEffect, useMemo, useState } from "react"; +import ClientOnlyPortal from "@/common/components/ClientOnlyPortal"; +import { + useCustomKeyboardSensor, + useCustomPointerSensor, +} from "@/common/utils/dndHelpers"; +import { + Active, + DndContext, + DragOverlay, + closestCenter, + useDraggable, + useSensors, +} from "@dnd-kit/core"; +import { + SortableContext, + sortableKeyboardCoordinates, + useSortable, + verticalListSortingStrategy, +} from "@dnd-kit/sortable"; +import { CSS } from "@dnd-kit/utilities"; +import DeleteIcon from "@mui/icons-material/Delete"; import { - Autocomplete, Card, Container, Divider, - FormControl, FormControlLabel, FormGroup, - FormLabel, IconButton, MenuItem, Paper, - Radio, - RadioGroup, - Slider, Stack, Switch, TextField, @@ -32,30 +46,10 @@ import { useFieldArray, useForm, } from "react-hook-form"; -import { ParameterData, TrainspaceData } from "../types/imageTypes"; -import { STEP_SETTINGS } from "../constants/imageConstants"; -import { CSS } from "@dnd-kit/utilities"; -import { - SortableContext, - sortableKeyboardCoordinates, - useSortable, - verticalListSortingStrategy, -} from "@dnd-kit/sortable"; -import { - Active, - DndContext, - DragOverlay, - closestCenter, - useDraggable, - useSensors, -} from "@dnd-kit/core"; -import DeleteIcon from "@mui/icons-material/Delete"; -import { - useCustomKeyboardSensor, - useCustomPointerSensor, -} from "@/common/utils/dndHelpers"; -import ClientOnlyPortal from "@/common/components/ClientOnlyPortal"; +import { DEFAULT_LAYERS, STEP_SETTINGS } from "../constants/imageConstants"; import { updateImageTrainspaceData } from "../redux/imageActions"; +import { ParameterData, TrainspaceData } from "../types/imageTypes"; +import ImageFlow from "./ImageFlow"; const HtmlTooltip = styled( ({ @@ -100,6 +94,7 @@ const ImageParametersStep = ({ handleSubmit, formState: { errors, isDirty }, control, + setValue, } = useForm({ defaultValues: { criterion: trainspace?.parameterData?.criterion ?? "CELOSS", @@ -135,34 +130,17 @@ const ImageParametersStep = ({ parameters: [32, 32], }, ], - layers: trainspace?.parameterData?.layers ?? [ - { - value: "CONV2D", - parameters: [1, 5, 3, 1, 1], - }, - { - value: "MAXPOOL2D", - parameters: [3, 1], - }, - { - value: "FLATTEN", - parameters: [1, -1], - }, - { - value: "LINEAR", - parameters: [500, 10], - }, - { - value: "SIGMOID", - parameters: [], - }, - ], + layers: trainspace?.parameterData?.layers ?? DEFAULT_LAYERS.MNIST, }, }); useEffect(() => { setIsModified(isDirty); }, [isDirty]); - if (!trainspace) return <>; + + if (!trainspace) return null; + + const [layers, setLayers] = React.useState([]); + return ( - + + + {renderStepperButtons((trainspaceData) => { + setValue("layers", layers); handleSubmit((data) => { dispatch( updateImageTrainspaceData({ @@ -255,350 +236,6 @@ const ImageParametersStep = ({ ); }; -const LayersDnd = ({ - control, - errors, -}: { - control: Control; - errors: FieldErrors; -}) => { - const { fields, move, insert, remove } = useFieldArray({ - control: control, - name: "layers", - }); - const genLayerInvIds = () => - Object.fromEntries( - STEP_SETTINGS.PARAMETERS.layerValues.map((layerValue) => [ - layerValue, - Math.floor(Math.random() * Date.now()), - ]) - ); - const [layerInvIds, setLayerInvIds] = useState<{ - [layerValue: string]: number; - }>(genLayerInvIds()); - const [dndActive, setDndActive] = useState(null); - const [invHovering, setInvHovering] = useState(false); - - const dndActiveItem = useMemo(() => { - if (!dndActive) return; - if (dndActive.data.current && "inventory" in dndActive.data.current) { - const value = dndActive.data.current.inventory - .value as (typeof STEP_SETTINGS.PARAMETERS.layerValues)[number]; - return { - id: layerInvIds[value], - value: value, - parameters: STEP_SETTINGS.PARAMETERS.layers[value].parameters.map( - () => "" - ) as ""[], - }; - } else if (dndActive.data.current && "sortable" in dndActive.data.current) { - return fields[dndActive.data.current.sortable.index]; - } - }, [dndActive]); - const sensors = useSensors( - useCustomPointerSensor(), - useCustomKeyboardSensor({ coordinateGetter: sortableKeyboardCoordinates }) - ); - return ( - { - if (dndActive !== null) return; - setDndActive(active); - }} - onDragOver={({ over }) => { - if (!over || !over.data.current) { - setInvHovering(false); - return; - } - if (!invHovering) { - setInvHovering(true); - } - }} - onDragEnd={({ active, over }) => { - if (dndActive && dndActive.data.current && dndActiveItem) { - if ( - "inventory" in dndActive.data.current && - over?.data.current && - "sortable" in over.data.current - ) { - insert(over.data.current.sortable.index, { - value: dndActiveItem.value, - parameters: dndActiveItem.parameters as number[], - }); - } else if ( - "sortable" in dndActive.data.current && - over?.data.current && - "sortable" in over.data.current - ) { - move( - fields.findIndex((field) => field.id === active.id), - fields.findIndex((field) => field.id === over.id) - ); - } - } - setLayerInvIds(genLayerInvIds()); - setInvHovering(false); - setDndActive(null); - }} - onDragCancel={({ active }) => { - if (active.data.current && "inventory" in active.data.current) { - const index = fields.findIndex((field) => field.id === active.id); - if (index !== -1) { - remove(fields.findIndex((field) => field.id === active.id)); - } - } - setLayerInvIds(genLayerInvIds()); - setInvHovering(false); - setDndActive(null); - }} - > - - - - Layers - - - {STEP_SETTINGS.PARAMETERS.layerValues.map((value) => ( - - ))} - - - - - - - - {fields.length > 0 ? ( - [ - dndActiveItem && - dndActive?.data.current && - "inventory" in dndActive.data.current && - invHovering ? ( - - ) : null, - ...fields.map((field, index) => ( - remove(index), - }} - /> - )), - ] - ) : ( - This is Unimplemented - )} - - - - - - - {dndActiveItem ? ( - dndActive?.data.current && "sortable" in dndActive.data.current ? ( - - ) : ( - - ) - ) : null} - - - - ); -}; - -const LayerComponent = ({ - id, - data, - formProps, -}: { - id?: string | number; - data: ParameterData["layers"][number]; - formProps?: { - index: number; - control: Control; - errors: FieldErrors; - remove?: () => void; - }; -}) => { - const { - attributes, - listeners, - setNodeRef, - isDragging, - transform, - transition, - } = id - ? useSortable({ id }) - : { - attributes: undefined, - listeners: undefined, - setNodeRef: undefined, - isDragging: undefined, - transform: undefined, - transition: undefined, - }; - const style = transform - ? { - opacity: isDragging ? 0.4 : undefined, - transform: CSS.Transform.toString(transform), - transition: transition, - } - : undefined; - return ( -
- - - - - {STEP_SETTINGS.PARAMETERS.layers[data.value].label} - - {STEP_SETTINGS.PARAMETERS.layers[data.value].description} - - } - > - Info - - - {STEP_SETTINGS.PARAMETERS.layers[data.value].label} - - - } - > - {STEP_SETTINGS.PARAMETERS.layers[data.value].parameters.map( - (parameter, index) => ( -
- {formProps ? ( - ( - - )} - /> - ) : ( - - )} -
- ) - )} - -
- - - -
- - - -
- ); -}; - -const LayerInventoryComponent = ({ - id, - value, -}: { - id: number; - value: (typeof STEP_SETTINGS.PARAMETERS.layerValues)[number]; -}) => { - const { attributes, listeners, isDragging, setNodeRef } = useDraggable({ - id: id, - data: { - inventory: { - value, - }, - }, - }); - - const style = { - opacity: isDragging ? 0.4 : undefined, - }; - return ( -
- - {STEP_SETTINGS.PARAMETERS.layers[value].label} - -
- ); -}; - const TrainTransformsDnd = ({ control, errors, diff --git a/frontend/src/features/Train/features/Image/constants/imageConstants.ts b/frontend/src/features/Train/features/Image/constants/imageConstants.ts index b4aed9d9c..5c1ce2d26 100644 --- a/frontend/src/features/Train/features/Image/constants/imageConstants.ts +++ b/frontend/src/features/Train/features/Image/constants/imageConstants.ts @@ -26,21 +26,21 @@ export const STEP_SETTINGS = { component: ImageParametersStep, criterions: [ { - label: "CELOSS", - value: "CELOSS", - object_name: "nn.CrossEntropyLoss()", + label: "CELOSS", + value: "CELOSS", + object_name: "nn.CrossEntropyLoss()", }, { - label: "WCELOSS", - value: "WCELOSS", - object_name: "nn.CrossEntropyLoss()", // will define a randomized weights for classes in backend + label: "WCELOSS", + value: "WCELOSS", + object_name: "nn.CrossEntropyLoss()", // will define a randomized weights for classes in backend }, ], optimizers: [ { label: "Stochastic Gradient Descent", value: "SGD" }, { label: "Adam Optimization", value: "Adam" }, ], - layerValues: ["CONV2D", "MAXPOOL2D", "FLATTEN", "LINEAR", "SIGMOID"], + layerValues: ["CONV2D", "MAXPOOL2D", "FLATTEN", "LINEAR", "SIGMOID"], layers: { CONV2D: { label: "Conv2d", @@ -82,7 +82,8 @@ export const STEP_SETTINGS = { type: "number", }, ], - description: "The `CONV2d` function applies a filter to input data in a sliding window manner. By performing element-wise multiplication and sum of the overlapping portions, it captures local spatial patterns and features, enabling applications such as image recognition, object detection, and semantic segmentation in computer vision tasks.", + description: + "The `CONV2d` function applies a filter to input data in a sliding window manner. By performing element-wise multiplication and sum of the overlapping portions, it captures local spatial patterns and features, enabling applications such as image recognition, object detection, and semantic segmentation in computer vision tasks.", }, MAXPOOL2D: { label: "MaxPool2d", @@ -103,7 +104,8 @@ export const STEP_SETTINGS = { type: "number", }, ], - description: "MaxPool2d function reduces the size of input data by dividing it into non-overlapping rectangular regions and selecting the maximum value from each region. This downsampling operation preserves important features while decreasing spatial dimensions, making it beneficial for tasks like image classification and extracting spatial characteristics." + description: + "MaxPool2d function reduces the size of input data by dividing it into non-overlapping rectangular regions and selecting the maximum value from each region. This downsampling operation preserves important features while decreasing spatial dimensions, making it beneficial for tasks like image classification and extracting spatial characteristics.", }, FLATTEN: { label: "Flatten", @@ -124,7 +126,8 @@ export const STEP_SETTINGS = { type: "number", }, ], - description: "The flatten operation takes a two-dimensional image representation and transforms it into a one-dimensional vector. This process unravels the image structure by concatenating the rows or columns of pixels, creating a linear sequence of values. By doing so, it allows the network to process the image as a simple list of numbers, facilitating tasks such as image classification or object detection in neural networks." + description: + "The flatten operation takes a two-dimensional image representation and transforms it into a one-dimensional vector. This process unravels the image structure by concatenating the rows or columns of pixels, creating a linear sequence of values. By doing so, it allows the network to process the image as a simple list of numbers, facilitating tasks such as image classification or object detection in neural networks.", }, LINEAR: { label: "Linear", @@ -145,16 +148,26 @@ export const STEP_SETTINGS = { type: "number", }, ], - description: "A linear layer in an image dataset takes the flattened image representation and applies a learned linear transformation to map the input values to a new set of values, allowing the network to learn complex relationships for tasks like image classification or object recognition." + description: + "A linear layer in an image dataset takes the flattened image representation and applies a learned linear transformation to map the input values to a new set of values, allowing the network to learn complex relationships for tasks like image classification or object recognition.", }, SIGMOID: { label: "Sigmoid", objectName: "nn.Sigmoid", parameters: [], - description: "The sigmoid function takes the input values, typically the output of a linear layer, and applies a mathematical function that compresses them into a range between 0 and 1. This transformation is useful for interpreting the output as probabilities, where values closer to 1 indicate higher confidence in the presence of a particular feature or class in the image." + description: + "The sigmoid function takes the input values, typically the output of a linear layer, and applies a mathematical function that compresses them into a range between 0 and 1. This transformation is useful for interpreting the output as probabilities, where values closer to 1 indicate higher confidence in the presence of a particular feature or class in the image.", }, }, - transformValues: ["GAUSSIAN_BLUR", "GRAYSCALE", "NORMALIZE", "RANDOM_HORIZONTAL_FLIP", "RANDOM_VERTICAL_FLIP", "RESIZE", "TO_TENSOR"], + transformValues: [ + "GAUSSIAN_BLUR", + "GRAYSCALE", + "NORMALIZE", + "RANDOM_HORIZONTAL_FLIP", + "RANDOM_VERTICAL_FLIP", + "RESIZE", + "TO_TENSOR", + ], transforms: { GAUSSIAN_BLUR: { label: "Gaussian Blur", @@ -246,10 +259,24 @@ export const STEP_SETTINGS = { parameters: [], }, }, -}, + }, REVIEW: { name: "Review", optional: false, component: ImageReviewStep, }, } as const; + +export type ALL_LAYERS = keyof typeof STEP_SETTINGS.PARAMETERS.layers; + +export const DEFAULT_LAYERS: { + MNIST: { value: ALL_LAYERS; parameters: number[] }[]; +} = { + MNIST: [ + { value: "CONV2D", parameters: [1, 5, 3, 1, 1] }, + { value: "MAXPOOL2D", parameters: [3, 1] }, + { value: "FLATTEN", parameters: [1, -1] }, + { value: "LINEAR", parameters: [500, 10] }, + { value: "SIGMOID", parameters: [] }, + ], +}; diff --git a/frontend/src/features/Train/features/Tabular/components/TabularFlow.tsx b/frontend/src/features/Train/features/Tabular/components/TabularFlow.tsx new file mode 100644 index 000000000..e56e6b428 --- /dev/null +++ b/frontend/src/features/Train/features/Tabular/components/TabularFlow.tsx @@ -0,0 +1,313 @@ +import HtmlTooltip from "@/common/components/HtmlTooltip"; +import InfoIcon from "@mui/icons-material/Info"; +import { + Button, + Card, + Divider, + Paper, + Stack, + TextField, + Typography, +} from "@mui/material"; +import React, { useEffect } from "react"; +import ReactFlow, { + Background, + BackgroundVariant, + Controls, + Edge, + Handle, + Node, + NodeTypes, + Position, + addEdge, + useEdgesState, + useNodesState, +} from "reactflow"; +import "reactflow/dist/style.css"; +import { + ALL_LAYERS, + DEFAULT_LAYERS, + STEP_SETTINGS, +} from "../constants/tabularConstants"; +import { ParameterData } from "../types/tabularTypes"; +import assert from "assert"; +import { nanoid } from "nanoid/non-secure"; +import { toast } from "react-toastify"; + +interface TabularFlowProps { + setLayers?: (layers: ParameterData["layers"]) => void; +} + +export default function TabularFlow(props: TabularFlowProps) { + const { setLayers } = props; + + const initialNodes: Node[] = [ + ROOT_NODE, + ...DEFAULT_LAYERS.IRIS.map((layer, i) => ({ + id: `${layer.value}-${i}`, + type: "textUpdater", + position: { + x: DEFAULT_X_POSITION, + y: (i + 1) * 100, + }, + data: { + label: STEP_SETTINGS.PARAMETERS.layers[layer.value].label, + value: layer.value, + parameters: layer.parameters.slice(), + onChange: onChange, + }, + })), + ]; + const initialEdges: Edge[] = createInitialEdges(); + + const [nodes, setNodes, onNodesChange] = useNodesState(initialNodes); + const [edges, setEdges, onEdgesChange] = useEdgesState(initialEdges); + + useEffect(() => { + if (setLayers) { + const layers = handleExportLayers(); + setLayers(layers); + } + }, [nodes, edges]); + + function handleExportLayers(): ParameterData["layers"] { + const layers: ParameterData["layers"] = []; + const visited = new Set(["root"]); + + const directedEdges: Record> = {}; + edges.forEach((edge) => { + const sourceNode = nodes.find((node) => node.id === edge.source); + const targetNode = nodes.find((node) => node.id === edge.target); + if (sourceNode && targetNode) { + directedEdges[sourceNode.id] = targetNode; + } + }); + + let nextNode = directedEdges["root"]; + + // appending all layers from the graph + while (nextNode) { + assert(nextNode.data.value !== "root"); + + if (visited.has(nextNode.id)) { + toast.error("Cycle detected in layers"); + return layers; + } + visited.add(nextNode.id); + layers.push({ + value: nextNode.data.value, + parameters: nextNode.data.parameters || [], + }); + nextNode = directedEdges[nextNode.id]; + } + + return layers; + } + + function onChange(args: OnChangeArgs) { + setNodes((nds) => + nds.map((node) => { + if (node.id !== args.id) return node; + if (!node.data.parameters) return node; + + node.data.parameters[args.parameterIndex] = args.newValue; + return node; + }) + ); + } + + return ( + <> + + + + Layers + + + {STEP_SETTINGS.PARAMETERS.layerValues.map((value) => ( + + ))} + + + +
+ setEdges((eds) => addEdge(params, eds))} + nodeTypes={nodeTypes} + > + + + +
+ + ); +} + +interface TextUpdaterNodeProps { + id: string; + data: LayerNodeData; + isConnectable: boolean; +} + +function TextUpdaterNode(props: TextUpdaterNodeProps) { + const { data, isConnectable, id } = props; + assert(data.value !== "root"); + const layer = STEP_SETTINGS.PARAMETERS.layers[data.value]; + + return ( + <> + +
+ + + + {layer.label} + {layer.description} + + } + > + Info + + + + {layer.label} + + + } + > + {layer.parameters.map((parameter, index) => ( + + data.onChange({ + id: id, + newValue: Number(e.target.value), + parameterIndex: index, + }) + } + key={index} + label={parameter.label} + defaultValue={data.parameters?.[index]} + size="small" + type={parameter.type} + required + /> + ))} + + + + +
+ + + ); +} + +interface OnChangeArgs { + id: string; + newValue: number; + parameterIndex: number; +} + +interface LayerNodeData { + label: + | (typeof STEP_SETTINGS.PARAMETERS.layers)[ALL_LAYERS]["label"] + | "Start"; + value: ALL_LAYERS | "root"; + parameters?: number[]; + onChange: (args: OnChangeArgs) => void; +} + +const DEFAULT_X_POSITION = 10; + +const ROOT_NODE: Node = { + id: `root`, + type: "input", + position: { x: DEFAULT_X_POSITION, y: 0 }, + deletable: false, + data: { + label: "Start", + value: "root", + parameters: [], + onChange: () => undefined, + }, +}; +const nodeTypes: NodeTypes = { textUpdater: TextUpdaterNode }; + +function createInitialEdges(): Edge[] { + const edges: Edge[] = []; + const defaultLayers = DEFAULT_LAYERS.IRIS; + + // connecting root to first layer + edges.push({ + id: `eroot-0`, + source: "root", + target: `${defaultLayers[0].value}-0`, + }); + + // connecting all layers + for (let i = 0; i < defaultLayers.length - 1; i++) { + edges.push({ + id: `e${i}-${i + 1}`, + source: `${defaultLayers[i].value}-${i}`, + target: `${defaultLayers[i + 1].value}-${i + 1}`, + }); + } + return edges; +} diff --git a/frontend/src/features/Train/features/Tabular/components/TabularParametersStep.tsx b/frontend/src/features/Train/features/Tabular/components/TabularParametersStep.tsx index ee08a40cf..ab33fbe27 100644 --- a/frontend/src/features/Train/features/Tabular/components/TabularParametersStep.tsx +++ b/frontend/src/features/Train/features/Tabular/components/TabularParametersStep.tsx @@ -1,87 +1,31 @@ -import React, { useEffect, useMemo, useState } from "react"; -import { useLazyGetColumnsFromDatasetQuery } from "@/features/Train/redux/trainspaceApi"; import { useAppDispatch, useAppSelector } from "@/common/redux/hooks"; import { Autocomplete, - Card, - Container, - Divider, + Button, FormControl, FormControlLabel, FormGroup, FormLabel, - IconButton, MenuItem, Paper, Radio, RadioGroup, + Skeleton, Slider, Stack, Switch, TextField, Typography, - Skeleton, - Button, } from "@mui/material"; -import { styled } from "@mui/material/styles"; -import Tooltip, { tooltipClasses } from "@mui/material/Tooltip"; -import InfoIcon from "@mui/icons-material/Info"; -import { - Control, - Controller, - FieldErrors, - useFieldArray, - useForm, -} from "react-hook-form"; -import { ParameterData, TrainspaceData } from "../types/tabularTypes"; -import { STEP_SETTINGS } from "../constants/tabularConstants"; -import { CSS } from "@dnd-kit/utilities"; -import { - SortableContext, - sortableKeyboardCoordinates, - useSortable, - verticalListSortingStrategy, -} from "@dnd-kit/sortable"; -import { - Active, - DndContext, - DragOverlay, - closestCenter, - useDraggable, - useSensors, -} from "@dnd-kit/core"; -import DeleteIcon from "@mui/icons-material/Delete"; -import { - useCustomKeyboardSensor, - useCustomPointerSensor, -} from "@/common/utils/dndHelpers"; -import ClientOnlyPortal from "@/common/components/ClientOnlyPortal"; +import React, { useEffect } from "react"; +import { Controller, useForm } from "react-hook-form"; +import { DEFAULT_LAYERS, STEP_SETTINGS } from "../constants/tabularConstants"; import { updateTabularTrainspaceData } from "../redux/tabularActions"; +import { ParameterData, TrainspaceData } from "../types/tabularTypes"; -const HtmlTooltip = styled( - ({ - className, - title, - children, - ...props - }: { - className?: string; - children: React.ReactElement; - title: React.ReactNode; - }) => ( - - {children} - - ) -)(({ theme }) => ({ - [`& .${tooltipClasses.tooltip}`]: { - backgroundColor: "rgba(255, 255, 255, 0.95)", - color: "rgba(0, 0, 0, 0.87)", - maxWidth: 220, - fontSize: theme.typography.pxToRem(12), - border: "none", - }, -})); +import { useLazyGetColumnsFromDatasetQuery } from "@/features/Train/redux/trainspaceApi"; +import "reactflow/dist/style.css"; +import TabularFlow from "./TabularFlow"; const TabularParametersStep = ({ renderStepperButtons, @@ -112,6 +56,7 @@ const TabularParametersStep = ({ formState: { errors, isDirty }, control, watch, + setValue, } = useForm({ defaultValues: { targetCol: @@ -124,33 +69,18 @@ const TabularParametersStep = ({ epochs: trainspace?.parameterData?.epochs ?? 5, batchSize: trainspace?.parameterData?.batchSize ?? 20, testSize: trainspace?.parameterData?.testSize ?? 0.2, - layers: trainspace?.parameterData?.layers ?? [ - { - value: "LINEAR", - parameters: [4, 10], - }, - { - value: "RELU", - parameters: [], - }, - { - value: "LINEAR", - parameters: [10, 3], - }, - { - value: "SOFTMAX", - parameters: [-1], - }, - ], + layers: trainspace?.parameterData?.layers ?? DEFAULT_LAYERS.IRIS, }, }); useEffect(() => { setIsModified(isDirty); }, [isDirty]); - if (!trainspace) return <>; + if (!trainspace) return null; const targetCol = watch("targetCol"); const features = watch("features"); + const [layers, setLayers] = React.useState([]); + return ( {error ? ( @@ -346,8 +276,11 @@ const TabularParametersStep = ({ )} /> - + + + {renderStepperButtons((trainspaceData) => { + setValue("layers", layers); handleSubmit((data) => { dispatch( updateTabularTrainspaceData({ @@ -365,348 +298,4 @@ const TabularParametersStep = ({ ); }; -const LayersDnd = ({ - control, - errors, -}: { - control: Control; - errors: FieldErrors; -}) => { - const { fields, move, insert, remove } = useFieldArray({ - control: control, - name: "layers", - }); - const genLayerInvIds = () => - Object.fromEntries( - STEP_SETTINGS.PARAMETERS.layerValues.map((layerValue) => [ - layerValue, - Math.floor(Math.random() * Date.now()), - ]) - ); - const [layerInvIds, setLayerInvIds] = useState<{ - [layerValue: string]: number; - }>(genLayerInvIds()); - const [dndActive, setDndActive] = useState(null); - const [invHovering, setInvHovering] = useState(false); - - const dndActiveItem = useMemo(() => { - if (!dndActive) return; - if (dndActive.data.current && "inventory" in dndActive.data.current) { - const value = dndActive.data.current.inventory - .value as (typeof STEP_SETTINGS.PARAMETERS.layerValues)[number]; - return { - id: layerInvIds[value], - value: value, - parameters: STEP_SETTINGS.PARAMETERS.layers[value].parameters.map( - () => "" - ) as ""[], - }; - } else if (dndActive.data.current && "sortable" in dndActive.data.current) { - return fields[dndActive.data.current.sortable.index]; - } - }, [dndActive]); - const sensors = useSensors( - useCustomPointerSensor(), - useCustomKeyboardSensor({ coordinateGetter: sortableKeyboardCoordinates }) - ); - return ( - { - if (dndActive !== null) return; - setDndActive(active); - }} - onDragOver={({ over }) => { - if (!over || !over.data.current) { - setInvHovering(false); - return; - } - if (!invHovering) { - setInvHovering(true); - } - }} - onDragEnd={({ active, over }) => { - if (dndActive && dndActive.data.current && dndActiveItem) { - if ( - "inventory" in dndActive.data.current && - over?.data.current && - "sortable" in over.data.current - ) { - insert(over.data.current.sortable.index, { - value: dndActiveItem.value, - parameters: dndActiveItem.parameters as number[], - }); - } else if ( - "sortable" in dndActive.data.current && - over?.data.current && - "sortable" in over.data.current - ) { - move( - fields.findIndex((field) => field.id === active.id), - fields.findIndex((field) => field.id === over.id) - ); - } - } - setLayerInvIds(genLayerInvIds()); - setInvHovering(false); - setDndActive(null); - }} - onDragCancel={({ active }) => { - if (active.data.current && "inventory" in active.data.current) { - const index = fields.findIndex((field) => field.id === active.id); - if (index !== -1) { - remove(fields.findIndex((field) => field.id === active.id)); - } - } - setLayerInvIds(genLayerInvIds()); - setInvHovering(false); - setDndActive(null); - }} - > - - - - Layers - - - {STEP_SETTINGS.PARAMETERS.layerValues.map((value) => ( - - ))} - - - - - - - - {fields.length > 0 ? ( - [ - dndActiveItem && - dndActive?.data.current && - "inventory" in dndActive.data.current && - invHovering ? ( - - ) : null, - ...fields.map((field, index) => ( - remove(index), - }} - /> - )), - ] - ) : ( - This is Unimplemented - )} - - - - - - - {dndActiveItem ? ( - dndActive?.data.current && "sortable" in dndActive.data.current ? ( - - ) : ( - - ) - ) : null} - - - - ); -}; - -const LayerComponent = ({ - id, - data, - formProps, -}: { - id?: string | number; - data: ParameterData["layers"][number]; - formProps?: { - index: number; - control: Control; - errors: FieldErrors; - remove?: () => void; - }; -}) => { - const { - attributes, - listeners, - setNodeRef, - isDragging, - transform, - transition, - } = id - ? useSortable({ id }) - : { - attributes: undefined, - listeners: undefined, - setNodeRef: undefined, - isDragging: undefined, - transform: undefined, - transition: undefined, - }; - const style = transform - ? { - opacity: isDragging ? 0.4 : undefined, - transform: CSS.Transform.toString(transform), - transition: transition, - } - : undefined; - return ( -
- - - - - {STEP_SETTINGS.PARAMETERS.layers[data.value].label} - - {STEP_SETTINGS.PARAMETERS.layers[data.value].description} - - } - > - Info - - - - {STEP_SETTINGS.PARAMETERS.layers[data.value].label} - - - } - > - {STEP_SETTINGS.PARAMETERS.layers[data.value].parameters.map( - (parameter, index) => ( -
- {formProps ? ( - ( - - )} - /> - ) : ( - - )} -
- ) - )} - -
- - - -
- - - -
- ); -}; - -const LayerInventoryComponent = ({ - id, - value, -}: { - id: number; - value: (typeof STEP_SETTINGS.PARAMETERS.layerValues)[number]; -}) => { - const { attributes, listeners, isDragging, setNodeRef } = useDraggable({ - id: id, - data: { - inventory: { - value, - }, - }, - }); - - const style = { - opacity: isDragging ? 0.4 : undefined, - }; - return ( -
- - {STEP_SETTINGS.PARAMETERS.layers[value].label} - -
- ); -}; - export default TabularParametersStep; diff --git a/frontend/src/features/Train/features/Tabular/components/TabularTrainspace.tsx b/frontend/src/features/Train/features/Tabular/components/TabularTrainspace.tsx index 5c63a1570..40aef3e08 100644 --- a/frontend/src/features/Train/features/Tabular/components/TabularTrainspace.tsx +++ b/frontend/src/features/Train/features/Tabular/components/TabularTrainspace.tsx @@ -121,7 +121,8 @@ const TrainspaceStepInner = ({ }); } }, [trainspace]); - if (!Component) return <>; + + if (!Component) return null; return ( ( diff --git a/frontend/src/features/Train/features/Tabular/constants/tabularConstants.ts b/frontend/src/features/Train/features/Tabular/constants/tabularConstants.ts index 21d944e2e..533b4fa53 100644 --- a/frontend/src/features/Train/features/Tabular/constants/tabularConstants.ts +++ b/frontend/src/features/Train/features/Tabular/constants/tabularConstants.ts @@ -61,7 +61,6 @@ export const STEP_SETTINGS = { { label: "Adam Optimization", value: "Adam" }, ], layerValues: ["LINEAR", "RELU", "TANH", "SOFTMAX", "SIGMOID", "LOGSOFTMAX"], - layers: { LINEAR: { label: "Linear", @@ -82,19 +81,22 @@ export const STEP_SETTINGS = { type: "number", }, ], - description: "A linear layer performs a mathematical operation called linear transformation on a set of input values. It applies a combination of scaling and shifting to the input values, resulting in a new set of transformed values as output." + description: + "A linear layer performs a mathematical operation called linear transformation on a set of input values. It applies a combination of scaling and shifting to the input values, resulting in a new set of transformed values as output.", }, RELU: { label: "ReLU", objectName: "nn.ReLU", parameters: [], - description: "ReLU, short for Rectified Linear Unit, is an activation function that acts like a filter that selectively allows positive numbers to pass through unchanged, while converting negative numbers to zero." + description: + "ReLU, short for Rectified Linear Unit, is an activation function that acts like a filter that selectively allows positive numbers to pass through unchanged, while converting negative numbers to zero.", }, TANH: { label: "Tanh", objectName: "nn.Tanh", parameters: [], - description: "The tanh function maps input numbers to a range between -1 and 1, emphasizing values close to zero while diminishing the impact of extremely large or small numbers, making it useful for capturing complex patterns in data." + description: + "The tanh function maps input numbers to a range between -1 and 1, emphasizing values close to zero while diminishing the impact of extremely large or small numbers, making it useful for capturing complex patterns in data.", }, SOFTMAX: { label: "Softmax", @@ -108,13 +110,15 @@ export const STEP_SETTINGS = { type: "number", }, ], - description: "The softmax function takes a set of numbers as input and converts them into a probability distribution, assigning higher probabilities to larger numbers and lower probabilities to smaller numbers, making it useful for multi-class classification tasks." + description: + "The softmax function takes a set of numbers as input and converts them into a probability distribution, assigning higher probabilities to larger numbers and lower probabilities to smaller numbers, making it useful for multi-class classification tasks.", }, SIGMOID: { label: "Sigmoid", objectName: "nn.Sigmoid", parameters: [], - description: "The sigmoid function takes any input number and squeezes it to a range between 0 and 1, effectively converting it into a probability-like value, often used for binary classification tasks and as an activation function in neural networks." + description: + "The sigmoid function takes any input number and squeezes it to a range between 0 and 1, effectively converting it into a probability-like value, often used for binary classification tasks and as an activation function in neural networks.", }, LOGSOFTMAX: { label: "LogSoftmax", @@ -128,8 +132,9 @@ export const STEP_SETTINGS = { type: "number", }, ], - description: "The logsoftmax function converts a set of numbers into a probability distribution using the softmax function, and then applies a logarithm to the resulting probabilities. It is commonly used for multi-class classification tasks as an activation function and to calculate the logarithmic loss during neural network training." - } + description: + "The logsoftmax function converts a set of numbers into a probability distribution using the softmax function, and then applies a logarithm to the resulting probabilities. It is commonly used for multi-class classification tasks as an activation function and to calculate the logarithmic loss during neural network training.", + }, }, }, REVIEW: { @@ -138,3 +143,16 @@ export const STEP_SETTINGS = { component: TabularReviewStep, }, } as const; + +export type ALL_LAYERS = keyof typeof STEP_SETTINGS.PARAMETERS.layers; + +export const DEFAULT_LAYERS: { + IRIS: { value: ALL_LAYERS; parameters: number[] }[]; +} = { + IRIS: [ + { value: "LINEAR", parameters: [4, 10] }, + { value: "RELU", parameters: [] }, + { value: "LINEAR", parameters: [10, 3] }, + { value: "SOFTMAX", parameters: [-1] }, + ], +}; diff --git a/frontend/src/features/Train/redux/trainspaceApi.ts b/frontend/src/features/Train/redux/trainspaceApi.ts index 5388b6f90..82c2e179e 100644 --- a/frontend/src/features/Train/redux/trainspaceApi.ts +++ b/frontend/src/features/Train/redux/trainspaceApi.ts @@ -36,40 +36,34 @@ const trainspaceApi = backendApi }), uploadDatasetFile: builder.mutation< null, - { dataSource: DATA_SOURCE; file: File } + { dataSource: DATA_SOURCE; file: File; url: string } >({ queryFn: async ({ dataSource, file }, _, __, baseQuery) => { - const postObjResponse = await baseQuery({ - url: "/api/s3/getUserDatasetFileUploadPresignedPostObj", - method: "POST", - body: { - name: file.name, - data_source: dataSource.toLowerCase(), - }, + const getObjResponse = await baseQuery({ + url: `/api/lambda/datasets/user/${dataSource}/${file.name}/presigned_upload_url`, + method: "GET", }); - if (postObjResponse.error) { - return { error: postObjResponse.error }; + if (getObjResponse.error) { + return { error: getObjResponse.error }; } - const postObj = postObjResponse.data as { - presigned_post_obj: { url: string; fields: Record }; + const getObj = getObjResponse.data as { + data: string; + message: string; }; + const getObjUrl = getObj.data; const formData = new FormData(); - for (const [key, value] of Object.entries( - postObj.presigned_post_obj.fields - )) { - formData.append(key, value); - } formData.append("file", file); const uploadQuery = fetchBaseQuery(); const response = await uploadQuery( { - url: postObj.presigned_post_obj.url, - method: "POST", + url: getObjUrl, + method: "PUT", body: formData, }, _, __ ); + if (response.error) { return { error: response.error }; } diff --git a/frontend/yarn.lock b/frontend/yarn.lock index 128cca767..f706c317c 100644 --- a/frontend/yarn.lock +++ b/frontend/yarn.lock @@ -1281,6 +1281,72 @@ dependencies: "@swc/helpers" "^0.4.14" +"@reactflow/background@11.2.4": + version "11.2.4" + resolved "https://registry.yarnpkg.com/@reactflow/background/-/background-11.2.4.tgz#06cd4c9f222dbeb2d3ffb2a530b6d88bf130dd9c" + integrity sha512-SYQbCRCU0GuxT/40Tm7ZK+l5wByGnNJSLtZhbL9C/Hl7JhsJXV3UGXr0vrlhVZUBEtkWA7XhZM/5S9XEA5XSFA== + dependencies: + "@reactflow/core" "11.7.4" + classcat "^5.0.3" + zustand "^4.3.1" + +"@reactflow/controls@11.1.15": + version "11.1.15" + resolved 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version "5.0.4" + resolved "https://registry.yarnpkg.com/classcat/-/classcat-5.0.4.tgz#e12d1dfe6df6427f260f03b80dc63571a5107ba6" + integrity sha512-sbpkOw6z413p+HDGcBENe498WM9woqWHiJxCq7nvmxe9WmrUmqfAcxpIwAiMtM5Q3AhYkzXcNQHqsWq0mND51g== + classnames@^2.2.6, classnames@^2.3.1: version "2.3.2" resolved "https://registry.yarnpkg.com/classnames/-/classnames-2.3.2.tgz#351d813bf0137fcc6a76a16b88208d2560a0d924" @@ -2501,6 +2787,24 @@ d3-dispatch@1: resolved "https://registry.yarnpkg.com/d3-dispatch/-/d3-dispatch-1.0.6.tgz#00d37bcee4dd8cd97729dd893a0ac29caaba5d58" integrity sha512-fVjoElzjhCEy+Hbn8KygnmMS7Or0a9sI2UzGwoB7cCtvI1XpVN9GpoYlnb3xt2YV66oXYb1fLJ8GMvP4hdU1RA== +"d3-dispatch@1 - 3": + version "3.0.1" + resolved "https://registry.yarnpkg.com/d3-dispatch/-/d3-dispatch-3.0.1.tgz#5fc75284e9c2375c36c839411a0cf550cbfc4d5e" + integrity sha512-rzUyPU/S7rwUflMyLc1ETDeBj0NRuHKKAcvukozwhshr6g6c5d8zh4c2gQjY2bZ0dXeGLWc1PF174P2tVvKhfg== + +"d3-drag@2 - 3", d3-drag@^3.0.0: + version "3.0.0" + resolved 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django = "^4.2.3" django-ninja = "^0.22.2" scikit-learn = "^1.3.0" pandas = "^2.0.3" -torch = ">=2.0.0, !=2.0.1" -torchvision = "^0.15" firebase-admin = "^6.2.0" pre-commit = "^3.3.3" click = "^8.1.7" diff --git a/yml_to_req.py b/yml_to_req.py deleted file mode 100644 index e4fb05d9a..000000000 --- a/yml_to_req.py +++ /dev/null @@ -1,37 +0,0 @@ -""" -Utility file to convert our environment.yml file to a requirements.txt for deployment purpose. - -Credit to: https://gist.github.com/pemagrg1/f959c19ec18fee3ce2ff9b3b86b67c16 - -""" - -import ruamel.yaml - -yaml = ruamel.yaml.YAML() -data = yaml.load(open("conda/environment.yml")) - -requirements = [] -for dep in data["dependencies"]: - if isinstance(dep, str): - if dep == "pytorch": - requirements.append("torch") - elif dep.startswith("python"): - continue - else: - parsed_dep = dep.split("=") - if parsed_dep[0] == dep: - requirements.append(dep) - elif len(parsed_dep) > 2: - raise ValueError( - "Misformat in environment.yml file. Make sure that you have = or format" - ) - else: - package_name, package_version = parsed_dep[0], parsed_dep[1] - requirements.append(f"{parsed_dep[0]}=={parsed_dep[1]}") - elif isinstance(dep, dict): - for preq in dep.get("pip", []): - requirements.append(preq) - -with open("requirements.txt", "w") as fp: - for requirement in requirements: - fp.write(requirement + "\n")