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Wgan Porting #3666

Merged
merged 16 commits into from
Dec 1, 2023
Merged

Wgan Porting #3666

merged 16 commits into from
Dec 1, 2023

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shreyasvinaya
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@shreyasvinaya shreyasvinaya commented Nov 8, 2023

Description

WGAN Porting from Tensorflow to Pytorch

Type of change

Please check the option that is related to your PR.

  • Bug fix (non-breaking change which fixes an issue)
  • New feature (non-breaking change which adds functionality)
  • Breaking change (fix or feature that would cause existing functionality to not work as expected)
    • In this case, we recommend to discuss your modification on GitHub issues before creating the PR
  • Documentations (modification for documents)

Checklist

  • My code follows the style guidelines of this project
    • Run yapf -i <modified file> and check no errors (yapf version must be 0.32.0)
    • Run mypy -p deepchem and check no errors
    • Run flake8 <modified file> --count and check no errors
    • Run python -m doctest <modified file> and check no errors
  • I have performed a self-review of my own code
  • I have commented my code, particularly in hard-to-understand areas
  • I have made corresponding changes to the documentation
  • I have added tests that prove my fix is effective or that my feature works
  • New unit tests pass locally with my changes
  • I have checked my code and corrected any misspellings

@shreyasvinaya shreyasvinaya mentioned this pull request Nov 8, 2023
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References
----------
[1] Arjovsky, Martin, Soumith Chintala, and Léon Bottou.
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Can you check this renders correctly on the docs locally? It needs to be in numpydoc style

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fixed

(https://arxiv.org/abs/1704.00028)
"""

def __init__(self, gradient_penalty=10.0, **kwargs):
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Type annotations are missing

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done

discrim_output_gen[1]) + discrim_output_train[1]


class GradientPenaltyLayer(nn.Module):
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More detailed docstrings and usage examples

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done

discrim_output_gen[1]) + discrim_output_train[1]


class GradientPenaltyLayer(nn.Module):
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Need a unit test for this layer

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done

class GradientPenaltyLayer(nn.Module):
"""Implements the gradient penalty loss term for WGANs."""

def __init__(self, gan, discriminator, **kwargs):
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Type annotations here and rest of the layer

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done

self.gan = gan
self.discriminator = discriminator

def forward(self, inputs, conditional_inputs):
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Type annotations and return type

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done

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@rbharath rbharath left a comment

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Needs more docs and type annotations


Notes
-----
This class is not intended to be used directly. It is used internally by
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Let's remove this comment

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Done

the output from the discriminator, followed by the gradient penalty.
"""
# concatenate inputs and conditional_inputs
# inputs = list(inputs) + list(conditional_inputs)
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Cruft? Should be removed

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done

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@rbharath rbharath left a comment

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A few cleanup comments and requests for documentation

discrim_output_gen[1]) + discrim_output_train[1]


class GradientPenaltyLayer(nn.Module):
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You need to add thhis layer to the docs; can do in a follow up PR

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LGTM

@rbharath rbharath merged commit 2cd7e0f into deepchem:master Dec 1, 2023
23 of 33 checks passed
@shreyasvinaya shreyasvinaya deleted the WGAN-NEW branch March 24, 2024 12:13
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2 participants