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Add Flatten layer to architectures + make flatten optional in embedders (#483)

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Flatten layer required for embedders that mix conv and dense
(Cherry picking from #478)
This commit is contained in:
Guy Jacob
2021-05-12 11:11:10 +03:00
committed by GitHub
parent c369984c2e
commit 235a259223
7 changed files with 49 additions and 10 deletions
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3
rl_coach/architectures/embedder_parameters.py
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@@ -23,7 +23,7 @@ MOD_NAMES = {'image': 'ImageEmbedder', 'vector': 'VectorEmbedder', 'tensor': 'Te
class InputEmbedderParameters(NetworkComponentParameters):
def __init__(self, activation_function: str='relu', scheme: Union[List, EmbedderScheme]=EmbedderScheme.Medium,
batchnorm: bool=False, dropout_rate: float=0.0, name: str='embedder', input_rescaling=None,
input_offset=None, input_clipping=None, dense_layer=None, is_training=False):
input_offset=None, input_clipping=None, dense_layer=None, is_training=False, flatten=True):
super().__init__(dense_layer=dense_layer)
self.activation_function = activation_function
self.scheme = scheme
@@ -40,6 +40,7 @@ class InputEmbedderParameters(NetworkComponentParameters):
self.input_clipping = input_clipping
self.name = name
self.is_training = is_training
self.flatten = flatten
def path(self, emb_type):
return 'rl_coach.architectures.tensorflow_components.embedders:' + MOD_NAMES[emb_type]