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- # Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
- #
- # 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 parl
- import paddle.fluid as fluid
- from parl import layers
-
-
- class AtariModel(parl.Model):
- def __init__(self, act_dim):
-
- self.conv1 = layers.conv2d(
- num_filters=32, filter_size=8, stride=4, padding=1, act='relu')
- self.conv2 = layers.conv2d(
- num_filters=64, filter_size=4, stride=2, padding=2, act='relu')
- self.conv3 = layers.conv2d(
- num_filters=64, filter_size=3, stride=1, padding=0, act='relu')
-
- self.fc = layers.fc(size=512, act='relu')
-
- self.policy_fc = layers.fc(size=act_dim)
- self.value_fc = layers.fc(size=1)
-
- def policy(self, obs):
- """
- Args:
- obs: A float32 tensor of shape [B, C, H, W]
-
- Returns:
- policy_logits: B * ACT_DIM
- """
- obs = obs / 255.0
- conv1 = self.conv1(obs)
- conv2 = self.conv2(conv1)
- conv3 = self.conv3(conv2)
-
- flatten = layers.flatten(conv3, axis=1)
- fc_output = self.fc(flatten)
-
- policy_logits = self.policy_fc(fc_output)
- return policy_logits
-
- def value(self, obs):
- """
- Args:
- obs: A float32 tensor of shape [B, C, H, W]
-
- Returns:
- values: B
- """
- obs = obs / 255.0
- conv1 = self.conv1(obs)
- conv2 = self.conv2(conv1)
- conv3 = self.conv3(conv2)
-
- flatten = layers.flatten(conv3, axis=1)
- fc_output = self.fc(flatten)
-
- values = self.value_fc(fc_output)
- values = layers.squeeze(values, axes=[1])
- return values
-
- def policy_and_value(self, obs):
- """
- Args:
- obs: A float32 tensor of shape [B, C, H, W]
-
- Returns:
- policy_logits: B * ACT_DIM
- values: B
- """
- obs = obs / 255.0
- conv1 = self.conv1(obs)
- conv2 = self.conv2(conv1)
- conv3 = self.conv3(conv2)
-
- flatten = layers.flatten(conv3, axis=1)
- fc_output = self.fc(flatten)
-
- policy_logits = self.policy_fc(fc_output)
-
- values = self.value_fc(fc_output)
- values = layers.squeeze(values, axes=[1])
-
- return policy_logits, values
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