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Batch RL Tutorial (#372)

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Gal Leibovich
2019-07-14 18:43:48 +03:00
committed by GitHub
parent b82414138d
commit 19ad2d60a7
40 changed files with 1155 additions and 182 deletions
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34
rl_coach/architectures/head_parameters.py
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@@ -50,43 +50,51 @@ class PPOHeadParameters(HeadParameters):
class VHeadParameters(HeadParameters):
def __init__(self, activation_function: str ='relu', name: str='v_head_params',
num_output_head_copies: int = 1, rescale_gradient_from_head_by_factor: float = 1.0,
loss_weight: float = 1.0, dense_layer=None, initializer='normalized_columns'):
loss_weight: float = 1.0, dense_layer=None, initializer='normalized_columns',
output_bias_initializer=None):
super().__init__(parameterized_class_name="VHead", activation_function=activation_function, name=name,
dense_layer=dense_layer, num_output_head_copies=num_output_head_copies,
rescale_gradient_from_head_by_factor=rescale_gradient_from_head_by_factor,
loss_weight=loss_weight)
self.initializer = initializer
self.output_bias_initializer = output_bias_initializer
class DDPGVHeadParameters(HeadParameters):
def __init__(self, activation_function: str ='relu', name: str='ddpg_v_head_params',
num_output_head_copies: int = 1, rescale_gradient_from_head_by_factor: float = 1.0,
loss_weight: float = 1.0, dense_layer=None, initializer='normalized_columns'):
loss_weight: float = 1.0, dense_layer=None, initializer='normalized_columns',
output_bias_initializer=None):
super().__init__(parameterized_class_name="DDPGVHead", activation_function=activation_function, name=name,
dense_layer=dense_layer, num_output_head_copies=num_output_head_copies,
rescale_gradient_from_head_by_factor=rescale_gradient_from_head_by_factor,
loss_weight=loss_weight)
self.initializer = initializer
self.output_bias_initializer = output_bias_initializer
class CategoricalQHeadParameters(HeadParameters):
def __init__(self, activation_function: str ='relu', name: str='categorical_q_head_params',
num_output_head_copies: int = 1, rescale_gradient_from_head_by_factor: float = 1.0,
loss_weight: float = 1.0, dense_layer=None):
loss_weight: float = 1.0, dense_layer=None,
output_bias_initializer=None):
super().__init__(parameterized_class_name="CategoricalQHead", activation_function=activation_function, name=name,
dense_layer=dense_layer, num_output_head_copies=num_output_head_copies,
rescale_gradient_from_head_by_factor=rescale_gradient_from_head_by_factor,
loss_weight=loss_weight)
self.output_bias_initializer = output_bias_initializer
class RegressionHeadParameters(HeadParameters):
def __init__(self, activation_function: str ='relu', name: str='q_head_params',
num_output_head_copies: int = 1, rescale_gradient_from_head_by_factor: float = 1.0,
loss_weight: float = 1.0, dense_layer=None, scheme=None):
loss_weight: float = 1.0, dense_layer=None, scheme=None,
output_bias_initializer=None):
super().__init__(parameterized_class_name="RegressionHead", activation_function=activation_function, name=name,
dense_layer=dense_layer, num_output_head_copies=num_output_head_copies,
rescale_gradient_from_head_by_factor=rescale_gradient_from_head_by_factor,
loss_weight=loss_weight)
self.output_bias_initializer = output_bias_initializer
class DDPGActorHeadParameters(HeadParameters):
@@ -153,21 +161,23 @@ class PolicyHeadParameters(HeadParameters):
class PPOVHeadParameters(HeadParameters):
def __init__(self, activation_function: str ='relu', name: str='ppo_v_head_params',
num_output_head_copies: int = 1, rescale_gradient_from_head_by_factor: float = 1.0,
loss_weight: float = 1.0, dense_layer=None):
loss_weight: float = 1.0, dense_layer=None, output_bias_initializer=None):
super().__init__(parameterized_class_name="PPOVHead", activation_function=activation_function, name=name,
dense_layer=dense_layer, num_output_head_copies=num_output_head_copies,
rescale_gradient_from_head_by_factor=rescale_gradient_from_head_by_factor,
loss_weight=loss_weight)
self.output_bias_initializer = output_bias_initializer
class QHeadParameters(HeadParameters):
def __init__(self, activation_function: str ='relu', name: str='q_head_params',
num_output_head_copies: int = 1, rescale_gradient_from_head_by_factor: float = 1.0,
loss_weight: float = 1.0, dense_layer=None):
loss_weight: float = 1.0, dense_layer=None, output_bias_initializer=None):
super().__init__(parameterized_class_name="QHead", activation_function=activation_function, name=name,
dense_layer=dense_layer, num_output_head_copies=num_output_head_copies,
rescale_gradient_from_head_by_factor=rescale_gradient_from_head_by_factor,
loss_weight=loss_weight)
self.output_bias_initializer = output_bias_initializer
class ClassificationHeadParameters(HeadParameters):
@@ -183,11 +193,12 @@ class ClassificationHeadParameters(HeadParameters):
class QuantileRegressionQHeadParameters(HeadParameters):
def __init__(self, activation_function: str ='relu', name: str='quantile_regression_q_head_params',
num_output_head_copies: int = 1, rescale_gradient_from_head_by_factor: float = 1.0,
loss_weight: float = 1.0, dense_layer=None):
loss_weight: float = 1.0, dense_layer=None, output_bias_initializer=None):
super().__init__(parameterized_class_name="QuantileRegressionQHead", activation_function=activation_function, name=name,
dense_layer=dense_layer, num_output_head_copies=num_output_head_copies,
rescale_gradient_from_head_by_factor=rescale_gradient_from_head_by_factor,
loss_weight=loss_weight)
self.output_bias_initializer = output_bias_initializer
class RainbowQHeadParameters(HeadParameters):
@@ -218,18 +229,21 @@ class SACPolicyHeadParameters(HeadParameters):
class SACQHeadParameters(HeadParameters):
def __init__(self, activation_function: str ='relu', name: str='sac_q_head_params', dense_layer=None,
layers_sizes: tuple = (256, 256)):
layers_sizes: tuple = (256, 256), output_bias_initializer=None):
super().__init__(parameterized_class_name='SACQHead', activation_function=activation_function, name=name,
dense_layer=dense_layer)
self.network_layers_sizes = layers_sizes
self.output_bias_initializer = output_bias_initializer
class TD3VHeadParameters(HeadParameters):
def __init__(self, activation_function: str ='relu', name: str='td3_v_head_params',
num_output_head_copies: int = 1, rescale_gradient_from_head_by_factor: float = 1.0,
loss_weight: float = 1.0, dense_layer=None, initializer='xavier'):
loss_weight: float = 1.0, dense_layer=None, initializer='xavier',
output_bias_initializer=None):
super().__init__(parameterized_class_name="TD3VHead", activation_function=activation_function, name=name,
dense_layer=dense_layer, num_output_head_copies=num_output_head_copies,
rescale_gradient_from_head_by_factor=rescale_gradient_from_head_by_factor,
loss_weight=loss_weight)
self.initializer = initializer
self.initializer = initializer
self.output_bias_initializer = output_bias_initializer