64 lines
1.5 KiB
Markdown
64 lines
1.5 KiB
Markdown
# PyTorch-Lightning Tests
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## Running tests
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The automatic travis tests ONLY run CPU-based tests. Although these cover most of the use cases,
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run on a 2-GPU machine to validate the full test-suite.
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To run all tests do the following:
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```bash
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git clone https://github.com/williamFalcon/pytorch-lightning
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cd pytorch-lightning
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# install module locally
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pip install -e .
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# install dev deps
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pip install -r requirements.txt
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# run tests
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py.test -v
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```
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To test models that require GPU make sure to run the above command on a GPU machine.
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The GPU machine must have:
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1. At least 2 GPUs.
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2. [NVIDIA-apex](https://github.com/NVIDIA/apex#linux) installed.
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### test_models.py
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This file fits a tiny model on MNIST using these different set-ups.
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1. CPU only.
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2. Single GPU with DP.
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3. Multiple (2) GPUs using DP.
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3. Multiple (2) GPUs using DDP.
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3. Multiple (2) GPUs using DP + apex (for 16-bit precision).
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3. Multiple (2) GPUs using DDP + apex (for 16-bit precision).
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For each set up it also tests:
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1. model saving.
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2. model loading.
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3. predicting with a loaded model.
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4. simulated save from HPC signal.
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5. simulated load from HPC signal.
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## Running Coverage
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Make sure to run coverage on a GPU machine with at least 2 GPUs and NVIDIA apex installed.
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```bash
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cd pytorch-lightning
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# generate coverage
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pip install coverage
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coverage run --source pytorch_lightning -m py.test pytorch_lightning tests examples -v --doctest-modules
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# print coverage stats
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coverage report -m
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# exporting resulys
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coverage xml
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codecov -t 17327163-8cca-4a5d-86c8-ca5f2ef700bc -v
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```
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