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network_imporvements branch merge

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This commit is contained in:
Shadi Endrawis
2018-10-02 13:41:46 +03:00
parent 72ea933384
commit 51726a5b80
110 changed files with 1639 additions and 1161 deletions
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41
rl_coach/architectures/tensorflow_components/middlewares/lstm_middleware.py
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@@ -18,19 +18,21 @@
import numpy as np
import tensorflow as tf
from rl_coach.architectures.tensorflow_components.architecture import batchnorm_activation_dropout, Dense
from rl_coach.architectures.tensorflow_components.layers import batchnorm_activation_dropout, Dense
from rl_coach.architectures.tensorflow_components.middlewares.middleware import Middleware, MiddlewareParameters
from rl_coach.base_parameters import MiddlewareScheme
from rl_coach.core_types import Middleware_LSTM_Embedding
from rl_coach.utils import force_list
class LSTMMiddlewareParameters(MiddlewareParameters):
def __init__(self, activation_function='relu', number_of_lstm_cells=256,
scheme: MiddlewareScheme = MiddlewareScheme.Medium,
batchnorm: bool = False, dropout: bool = False,
name="middleware_lstm_embedder", dense_layer=Dense):
name="middleware_lstm_embedder", dense_layer=Dense, is_training=False):
super().__init__(parameterized_class=LSTMMiddleware, activation_function=activation_function,
scheme=scheme, batchnorm=batchnorm, dropout=dropout, name=name, dense_layer=dense_layer)
scheme=scheme, batchnorm=batchnorm, dropout=dropout, name=name, dense_layer=dense_layer,
is_training=is_training)
self.number_of_lstm_cells = number_of_lstm_cells
@@ -38,9 +40,9 @@ class LSTMMiddleware(Middleware):
def __init__(self, activation_function=tf.nn.relu, number_of_lstm_cells: int=256,
scheme: MiddlewareScheme = MiddlewareScheme.Medium,
batchnorm: bool = False, dropout: bool = False,
name="middleware_lstm_embedder", dense_layer=Dense):
name="middleware_lstm_embedder", dense_layer=Dense, is_training=False):
super().__init__(activation_function=activation_function, batchnorm=batchnorm,
dropout=dropout, scheme=scheme, name=name, dense_layer=dense_layer)
dropout=dropout, scheme=scheme, name=name, dense_layer=dense_layer, is_training=is_training)
self.return_type = Middleware_LSTM_Embedding
self.number_of_lstm_cells = number_of_lstm_cells
self.layers = []
@@ -57,19 +59,12 @@ class LSTMMiddleware(Middleware):
self.layers.append(self.input)
# optionally insert some dense layers before the LSTM
if isinstance(self.scheme, MiddlewareScheme):
layers_params = self.schemes[self.scheme]
else:
layers_params = self.scheme
for idx, layer_params in enumerate(layers_params):
self.layers.append(
tf.layers.dense(self.layers[-1], layer_params[0], name='fc{}'.format(idx))
)
self.layers.extend(batchnorm_activation_dropout(self.layers[-1], self.batchnorm,
self.activation_function, self.dropout,
self.dropout_rate, idx))
# optionally insert some layers before the LSTM
for idx, layer_params in enumerate(self.layers_params):
self.layers.extend(force_list(
layer_params(self.layers[-1], name='fc{}'.format(idx),
is_training=self.is_training)
))
# add the LSTM layer
lstm_cell = tf.nn.rnn_cell.BasicLSTMCell(self.number_of_lstm_cells, state_is_tuple=True)
@@ -97,20 +92,20 @@ class LSTMMiddleware(Middleware):
# ppo
MiddlewareScheme.Shallow:
[
[64]
self.dense_layer(64)
],
# dqn
MiddlewareScheme.Medium:
[
[512]
self.dense_layer(512)
],
MiddlewareScheme.Deep: \
[
[128],
[128],
[128]
self.dense_layer(128),
self.dense_layer(128),
self.dense_layer(128)
]
}