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parameter noise exploration - using Noisy Nets

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Gal Leibovich
2018-08-27 18:19:01 +03:00
parent 658b437079
commit 1aa2ab0590
49 changed files with 536 additions and 433 deletions
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33
rl_coach/base_parameters.py
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@@ -199,7 +199,7 @@ class NetworkParameters(Parameters):
self.learning_rate_decay_steps = 0
# structure
self.input_embedders_parameters = []
self.input_embedders_parameters = {}
self.embedding_merger_type = EmbeddingMergerType.Concat
self.middleware_parameters = None
self.heads_parameters = []
@@ -220,32 +220,9 @@ class NetworkParameters(Parameters):
self.tensorflow_support = True
class InputEmbedderParameters(Parameters):
def __init__(self, activation_function: str='relu', scheme: Union[List, EmbedderScheme]=EmbedderScheme.Medium,
batchnorm: bool=False, dropout=False, name: str='embedder', input_rescaling=None, input_offset=None,
input_clipping=None):
super().__init__()
self.activation_function = activation_function
self.scheme = scheme
self.batchnorm = batchnorm
self.dropout = dropout
if input_rescaling is None:
input_rescaling = {'image': 255.0, 'vector': 1.0}
if input_offset is None:
input_offset = {'image': 0.0, 'vector': 0.0}
self.input_rescaling = input_rescaling
self.input_offset = input_offset
self.input_clipping = input_clipping
self.name = name
@property
def path(self):
return {
"image": 'image_embedder:ImageEmbedder',
"vector": 'vector_embedder:VectorEmbedder'
}
class NetworkComponentParameters(Parameters):
def __init__(self, dense_layer):
self.dense_layer = dense_layer
class VisualizationParameters(Parameters):
@@ -287,7 +264,7 @@ class AgentParameters(Parameters):
self.input_filter = None
self.output_filter = None
self.pre_network_filter = NoInputFilter()
self.full_name_id = None # TODO: do we really want to hold this parameters here?
self.full_name_id = None # TODO: do we really want to hold this parameter here?
self.name = None
self.is_a_highest_level_agent = True
self.is_a_lowest_level_agent = True