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SAEHD: lr_dropout now can be ‘n’, ‘y’, ‘cpu’. ‘n’ and ’y’ are the same as before.

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‘cpu’ mean enabled on CPU. This allows not to use extra VRAM, sacrificing 20% time of iteration.

SAEHD: resolution >= 256 now has second dssim loss function
This commit is contained in:
Colombo 2020-06-08 14:18:33 +04:00
commit af98407f06
2 changed files with 30 additions and 10 deletions
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5
core/leras/optimizers/RMSprop.py
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@ -25,7 +25,7 @@ class RMSprop(nn.OptimizerBase):
def get_weights(self):
return [self.lr, self.rho, self.epsilon, self.iterations] + list(self.accumulators_dict.values())
def initialize_variables(self, trainable_weights, vars_on_cpu=True):
def initialize_variables(self, trainable_weights, vars_on_cpu=True, lr_dropout_on_cpu=False):
# Initialize here all trainable variables used in training
e = tf.device('/CPU:0') if vars_on_cpu else None
if e: e.__enter__()
@ -34,7 +34,10 @@ class RMSprop(nn.OptimizerBase):
self.accumulators_dict.update ( accumulators)
if self.lr_dropout != 1.0:
e = tf.device('/CPU:0') if lr_dropout_on_cpu else None
if e: e.__enter__()
lr_rnds = [ nn.random_binomial( v.shape, p=self.lr_dropout, dtype=v.dtype) for v in trainable_weights ]
if e: e.__exit__(None, None, None)
self.lr_rnds_dict.update ( { v.name : rnd for v,rnd in zip(trainable_weights,lr_rnds) } )
if e: e.__exit__(None, None, None)