Implemented a Siamese Network Example #1003
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Can you please setup a test here as well? https://github.com/pytorch/examples/blob/main/run_python_examples.sh |
| pip install -r requirements.txt | ||
| python main.py | ||
| # CUDA_VISIBLE_DEVICES=2 python main.py # to specify GPU id to ex. 2 | ||
| ``` |
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Can you also reference the paper you're using a baseline for your implementation?
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I have referenced FaceNet, the closest implementation to the example's implementation. This implementation varies from FaceNet as we use the ResNet-18 model as our feature extractor. In addition, we aren't using TripletLoss as the MNIST dataset is simple, so BCELoss can do the trick.
siamese_network/main.py
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| output1 = self.forward_once(input1) | ||
| output2 = self.forward_once(input2) | ||
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| # concatnate both images' features |
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theres's a few simple typos around, a quick spell checker would help
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Thanks for pointing it out! I have fixed it! 😄
siamese_network/main.py
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| def main(): | ||
| # Training settings | ||
| parser = argparse.ArgumentParser(description='PyTorch MNIST Example') |
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Oh, I missed it. Thanks!
siamese_network/main.py
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| self.dataset = datasets.MNIST(root, train=train, download=download) | ||
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| # get targets (labels) and data (images) | ||
| self.targets = copy.deepcopy(self.dataset.targets) |
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what's the goal of the group sets section? Could you add some comments explaining why the deep copies are needed and what this is doing exactly?
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I have removed unwanted copying of objects and included detailed comments to explain the process.
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| test_loss /= len(test_loader.dataset) | ||
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| print('\nTest set: Average loss: {:.4f}, Accuracy: {}/{} ({:.0f}%)\n'.format( |
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Add comment around how much loss is expected to be if default settings are used
| def __len__(self): | ||
| return self.data.shape[0] | ||
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| def __getitem__(self, index): |
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add more comments in this section
- Included `siamese_network` setup to `run_python_examples.sh` - In `siamese_network/main.py`, included more explanation and detailed comments per @msaroufim's feedback.
`sphinx-serve -d build` doesn't work as `-d` flag doesn't exist. The correct flag is `-b` per `sphinx-serve` help page. Hence, the edit was meant to reflect the correct command `sphinx-serve -b build`.
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| # Siamese Network Example | |||
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OK last thing can you please quickly explain what a Siamese network is here, the high-level architecture and what users should expect to input and get as an output for this example. Not a tutorial.
Also, post some proof in a screenshot here on the PR that this thing works
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I have included an explanation in the class definition. I will update the read me to include the same definition.
Here is a screenshot to prove that the model works using the default setup.
…k_example Implemented a Siamese Network Example
I have followed
mnist/main.pysetup and modified it a bit to include the definition ofSiamese Networkand custom configuration ofMNISTset but for theObject Matchingtask.This PR was created per #645