Convert ppo_cart_pole to python configuration

alf/examples/ppo_cart_pole_conf.py

+# Copyright (c) 2021 Horizon Robotics and ALF Contributors. 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 alf
+from alf.examples import ppo_conf
+from alf.algorithms.data_transformer import RewardScaling
+from alf.networks import ActorDistributionNetwork, ValueNetwork
+from alf.utils.losses import element_wise_huber_loss
+
+# Environment Configuration
+alf.config(
+    'create_environment', env_name='CartPole-0', num_parallel_environments=8)
+
+# Reward Scailing
+alf.config('TrainerConfig', data_transformer_ctor=RewardScaling)
+alf.config('RewardScaling', scale=0.01)
+
+# algorithm config
+alf.config('ActorDistributionNetwork', fc_layer_params=(100, ))
+alf.config('ValueNetwork', fc_layer_params=(100, ))
+
+alf.config(
+    'ActorCriticAlgorithm',
+    actor_network_ctor=ActorDistributionNetwork,
+    value_network_ctor=ValueNetwork,
+    optimizer=alf.optimizers.Adam(lr=1e-3))
+
+alf.config(
+    'PPOLoss',
+    entropy_regularization=1e-4,
+    gamma=0.98,
+    td_error_loss_fn=element_wise_huber_loss,
+    normalize_advantages=False)
+
+# training config
+alf.config(
+    'TrainerConfig',
+    mini_batch_length=1,
+    unroll_length=32,
+    mini_batch_size=128,
+    num_updates_per_train_iter=4,
+    num_iterations=600,
+    num_checkpoints=5,
+    evaluate=True,
+    eval_interval=50,
+    debug_summaries=False,
+    summary_interval=5)
+
+alf.config('ReplayBuffer', max_length=2048)