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Adding NNPBE #3418

Merged
merged 10 commits into from
Jun 27, 2023
Merged

Adding NNPBE #3418

merged 10 commits into from
Jun 27, 2023

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advikavs
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@advikavs advikavs commented Jun 5, 2023

Description

Fix #(issue)

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

xi = (nu - nd) / n_offset
s = safenorm(densinfo.u.grad + densinfo.d.grad, dim=-1).unsqueeze(-1)

print("s_1", s.shape)
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remove print after testing.

@advikavs advikavs marked this pull request as ready for review June 21, 2023 08:49
"""

def __init__(self, nnmodel: torch.nn.Module):
# nnmodel should receives input with shape (..., 3)
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Can you move this into the docstring instead of leaving as comments?

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done.

# (2) normalized gradients (s): |del(n)| / [2(3*pi^2)^(1/3) * n^(4/3)]
# the output of the model must have shape of (..., 1)
# it represents the energy density per density per volume
super().__init__()
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This should come after the docstring

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LGTM

@rbharath rbharath merged commit 32cd7e6 into deepchem:master Jun 27, 2023
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2 participants