Comparison should be weight_decay >= 0.0
208 raise ValueError(
209 'Invalid beta parameter at index 1: {}'.format(betas[1])
210 )
211 if not 0.0 <= weight_decay:212 raise ValueError(
213 'Invalid weight_decay value: {}'.format(weight_decay)
214 )Comparison should be eps >= 0.0
198 ):
199 if not 0.0 <= lr:
200 raise ValueError('Invalid learning rate: {}'.format(lr))
201 if not 0.0 <= eps:202 raise ValueError('Invalid epsilon value: {}'.format(eps))
203 if not 0.0 <= betas[0] < 1.0:
204 raise ValueError(Comparison should be lr >= 0.0
196 amsgrad=False,
197 adamd_bias_correction: bool = False,
198 ):
199 if not 0.0 <= lr:200 raise ValueError('Invalid learning rate: {}'.format(lr))
201 if not 0.0 <= eps:
202 raise ValueError('Invalid epsilon value: {}'.format(eps))Comparison should be weight_decay >= 0.0
399 raise ValueError(
400 'Invalid beta parameter at index 1: {}'.format(betas[1])
401 )
402 if not 0.0 <= weight_decay:403 raise ValueError(
404 'Invalid weight_decay value: {}'.format(weight_decay)
405 )Comparison should be eps >= 0.0
389 ):
390 if not 0.0 <= lr:
391 raise ValueError('Invalid learning rate: {}'.format(lr))
392 if not 0.0 <= eps:393 raise ValueError('Invalid epsilon value: {}'.format(eps))
394 if not 0.0 <= betas[0] < 1.0:
395 raise ValueError(Comparison should be lr >= 0.0
387 amsgrad=False,
388 adamd_bias_correction: bool = False,
389 ):
390 if not 0.0 <= lr:391 raise ValueError('Invalid learning rate: {}'.format(lr))
392 if not 0.0 <= eps:
393 raise ValueError('Invalid epsilon value: {}'.format(eps))
Description
The constant is placed on the left side of a comparison. It is usually clearer in intent to place it in the right hand side of the comparison.
Bad practice
if 0 == x % 2:
...
Recommended:
if x % 2 == 0:
...