Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Removing numba deprecation warnings #262

Merged
merged 2 commits into from
Oct 18, 2022
Merged

Removing numba deprecation warnings #262

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
4b085fd
initial commit
Oct 18, 2022
1127af5
flake8 fixes
Oct 18, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
14 changes: 8 additions & 6 deletions aydin/it/normalisers/base.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -195,14 +195,16 @@ def denormalise(

return array

@jit(parallel=True, error_model='numpy')
def normalize_numba(self, array, min_value, max_value, epsilon):
for _ in prange(numpy.prod(array.shape)):
@staticmethod
@jit(nopython=True, parallel=True, error_model='numpy')
def normalize_numba(array, min_value, max_value, epsilon):
for _ in prange(numpy.prod(numpy.array(array.shape))):
array.flat[_] -= min_value
array.flat[_] /= max_value - min_value + epsilon

@jit(parallel=True, error_model='numpy')
def denormalize_numba(self, array, min_value, max_value, epsilon):
for _ in prange(numpy.prod(array.shape)):
@staticmethod
@jit(nopython=True, parallel=True, error_model='numpy')
def denormalize_numba(array, min_value, max_value, epsilon):
for _ in prange(numpy.prod(numpy.array(array.shape))):
array.flat[_] *= max_value - min_value + epsilon
array.flat[_] += min_value