mirror of
https://github.com/gryf/coach.git
synced 2025-12-17 19:20:19 +01:00
64 lines
2.8 KiB
Python
64 lines
2.8 KiB
Python
#
|
|
# Copyright (c) 2017 Intel Corporation
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
#
|
|
|
|
import tensorflow as tf
|
|
|
|
from rl_coach.architectures.tensorflow_components.layers import Dense
|
|
from rl_coach.architectures.tensorflow_components.heads.head import Head
|
|
from rl_coach.base_parameters import AgentParameters
|
|
from rl_coach.core_types import QActionStateValue
|
|
from rl_coach.spaces import SpacesDefinition, BoxActionSpace, DiscreteActionSpace
|
|
from rl_coach.utils import force_list
|
|
|
|
|
|
class RegressionHead(Head):
|
|
def __init__(self, agent_parameters: AgentParameters, spaces: SpacesDefinition, network_name: str,
|
|
head_idx: int = 0, loss_weight: float = 1., is_local: bool = True, activation_function: str='relu',
|
|
dense_layer=Dense, scheme=[Dense(256), Dense(256)], output_bias_initializer=None):
|
|
super().__init__(agent_parameters, spaces, network_name, head_idx, loss_weight, is_local, activation_function,
|
|
dense_layer=dense_layer)
|
|
self.name = 'regression_head'
|
|
self.scheme = scheme
|
|
self.layers = []
|
|
if isinstance(self.spaces.action, BoxActionSpace):
|
|
self.num_actions = self.spaces.action.shape[0]
|
|
elif isinstance(self.spaces.action, DiscreteActionSpace):
|
|
self.num_actions = len(self.spaces.action.actions)
|
|
self.return_type = QActionStateValue
|
|
if agent_parameters.network_wrappers[self.network_name].replace_mse_with_huber_loss:
|
|
self.loss_type = tf.losses.huber_loss
|
|
else:
|
|
self.loss_type = tf.losses.mean_squared_error
|
|
self.output_bias_initializer = output_bias_initializer
|
|
|
|
def _build_module(self, input_layer):
|
|
self.layers.append(input_layer)
|
|
for idx, layer_params in enumerate(self.scheme):
|
|
self.layers.extend(force_list(
|
|
layer_params(input_layer=self.layers[-1], name='{}_{}'.format(layer_params.__class__.__name__, idx))
|
|
))
|
|
|
|
self.layers.append(self.dense_layer(self.num_actions)(self.layers[-1], name='output',
|
|
bias_initializer=self.output_bias_initializer))
|
|
self.output = self.layers[-1]
|
|
|
|
def __str__(self):
|
|
result = []
|
|
for layer in self.layers:
|
|
result.append(str(layer))
|
|
return '\n'.join(result)
|
|
|