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agent_cfg.py
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agent_cfg.py
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# Copyright (c) 2024, RoboVerse community
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
unitree_go2_agent_cfg = {
'seed': 42,
'device': 'cuda',
'num_steps_per_env': 24,
'max_iterations': 15000,
'empirical_normalization': False,
'policy': {
'class_name': 'ActorCritic',
'init_noise_std': 1.0,
'actor_hidden_dims': [512, 256, 128],
'critic_hidden_dims': [512, 256, 128],
'activation': 'elu'
},
'algorithm': {
'class_name': 'PPO',
'value_loss_coef': 1.0,
'use_clipped_value_loss': True,
'clip_param': 0.2,
'entropy_coef': 0.01,
'num_learning_epochs': 5,
'num_mini_batches': 4,
'learning_rate': 0.001,
'schedule': 'adaptive',
'gamma': 0.99,
'lam': 0.95,
'desired_kl': 0.01,
'max_grad_norm': 1.0
},
'save_interval': 50,
'experiment_name': 'unitree_go2_rough',
'run_name': '',
'logger': 'tensorboard',
'neptune_project': 'orbit',
'wandb_project': 'orbit',
'resume': False,
'load_run': '.*',
'load_checkpoint': 'model_.*.pt'
}
unitree_g1_agent_cfg = {
'seed': 42,
'device': 'cuda',
'num_steps_per_env': 24,
'max_iterations': 15000,
'empirical_normalization': False,
'policy': {
'class_name': 'ActorCritic',
'init_noise_std': 1.0,
'actor_hidden_dims': [512, 256, 128],
'critic_hidden_dims': [512, 256, 128],
'activation': 'elu'
},
'algorithm': {
'class_name': 'PPO',
'value_loss_coef': 1.0,
'use_clipped_value_loss': True,
'clip_param': 0.2,
'entropy_coef': 0.01,
'num_learning_epochs': 5,
'num_mini_batches': 4,
'learning_rate': 0.001,
'schedule': 'adaptive',
'gamma': 0.99,
'lam': 0.95,
'desired_kl': 0.01,
'max_grad_norm': 1.0
},
'save_interval': 50,
'experiment_name': 'g1_rough',
'run_name': '',
'logger': 'tensorboard',
'neptune_project': 'orbit',
'wandb_project': 'orbit',
'resume': False,
'load_run': '.*',
'load_checkpoint': 'model_.*.pt'
}