Added vars to make it easier to work here
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39
.vscode/settings.json
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39
.vscode/settings.json
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{
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// For linux
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"terminal.integrated.env.linux": {
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"PYTHONPATH": "${workspaceFolder}"
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},
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// For OSX
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"terminal.integrated.env.osx": {
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"PYTHONPATH": "${workspaceFolder}"
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},
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// For Windows
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"terminal.integrated.env.windows": {
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"PYTHONPATH": "${workspaceFolder}"
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}
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}
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// {
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// // Always treat the project root as the working dir for Jupyter
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// "jupyter.notebookFileRoot": "${workspaceFolder}",
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//
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// // When you click "Run Python File in Terminal", DON'T cd into the file's folder
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// "python.terminal.executeInFileDir": false,
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//
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// // Start new integrated terminals at the project root
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// "terminal.integrated.cwd": "${workspaceFolder}",
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//
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// // Ensure Python can import from the project root no matter which file you run
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// // (so `src/` is on sys.path). Linux shown here; add osx/windows if needed.
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// "terminal.integrated.env.windows": {
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// "PYTHONPATH": "${workspaceFolder}"
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// },
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//
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// // Make pytest run from the root without needing a pytest.ini
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// "python.testing.pytestEnabled": true,
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// "python.testing.cwd": "${workspaceFolder}",
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// "python.testing.pytestArgs": ["src/test"],
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//
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// // Help Pylance resolve imports like `from src...` without red squiggles
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// "python.analysis.extraPaths": ["${workspaceFolder}"]
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// }
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21
README.md
21
README.md
@ -12,11 +12,30 @@ Create and activate you Conda enviroment with:
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conda env create -f environment.yaml
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conda env create -f environment.yaml
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conda activate deep_learning
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conda activate deep_learning
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Now install dependencies on pip:
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Now install dependencies on pip:
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pip install -r requirements.txt
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pip install -r requirements.txt
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Add the following on .vscode/settings.json
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```json
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{
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// For linux
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"terminal.integrated.env.linux": {
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"PYTHONPATH": "${workspaceFolder}"
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},
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// For OSX
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"terminal.integrated.env.osx": {
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"PYTHONPATH": "${workspaceFolder}"
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},
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// For Windows
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"terminal.integrated.env.windows": {
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"PYTHONPATH": "${workspaceFolder}"
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}
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}
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```
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## TroubleShooting
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## TroubleShooting
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Sometimes when uploading really large batch of data, git can stop the uploads thanks to the timeout.
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Sometimes when uploading really large batch of data, git can stop the uploads thanks to the timeout.
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