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fixing the dropout rate code (#72)

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addresses issue #53
This commit is contained in:
Itai Caspi
2018-11-08 16:53:47 +02:00
committed by GitHub
parent 389c65cbbe
commit 3a0a1159e9
11 changed files with 33 additions and 33 deletions
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12
rl_coach/architectures/middleware_parameters.py
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@@ -22,12 +22,12 @@ from rl_coach.base_parameters import MiddlewareScheme, NetworkComponentParameter
class MiddlewareParameters(NetworkComponentParameters):
def __init__(self, parameterized_class_name: str,
activation_function: str='relu', scheme: Union[List, MiddlewareScheme]=MiddlewareScheme.Medium,
batchnorm: bool=False, dropout: bool=False, name='middleware', dense_layer=None, is_training=False):
batchnorm: bool=False, dropout_rate: float=0.0, name='middleware', dense_layer=None, is_training=False):
super().__init__(dense_layer=dense_layer)
self.activation_function = activation_function
self.scheme = scheme
self.batchnorm = batchnorm
self.dropout = dropout
self.dropout_rate = dropout_rate
self.name = name
self.is_training = is_training
self.parameterized_class_name = parameterized_class_name
@@ -36,19 +36,19 @@ class MiddlewareParameters(NetworkComponentParameters):
class FCMiddlewareParameters(MiddlewareParameters):
def __init__(self, activation_function='relu',
scheme: Union[List, MiddlewareScheme] = MiddlewareScheme.Medium,
batchnorm: bool = False, dropout: bool = False,
batchnorm: bool = False, dropout_rate: float = 0.0,
name="middleware_fc_embedder", dense_layer=None, is_training=False):
super().__init__(parameterized_class_name="FCMiddleware", activation_function=activation_function,
scheme=scheme, batchnorm=batchnorm, dropout=dropout, name=name, dense_layer=dense_layer,
scheme=scheme, batchnorm=batchnorm, dropout_rate=dropout_rate, name=name, dense_layer=dense_layer,
is_training=is_training)
class LSTMMiddlewareParameters(MiddlewareParameters):
def __init__(self, activation_function='relu', number_of_lstm_cells=256,
scheme: MiddlewareScheme = MiddlewareScheme.Medium,
batchnorm: bool = False, dropout: bool = False,
batchnorm: bool = False, dropout_rate: float = 0.0,
name="middleware_lstm_embedder", dense_layer=None, is_training=False):
super().__init__(parameterized_class_name="LSTMMiddleware", activation_function=activation_function,
scheme=scheme, batchnorm=batchnorm, dropout=dropout, name=name, dense_layer=dense_layer,
scheme=scheme, batchnorm=batchnorm, dropout_rate=dropout_rate, name=name, dense_layer=dense_layer,
is_training=is_training)
self.number_of_lstm_cells = number_of_lstm_cells