exp_args_0 = [
'--env_id', env_name_0[i_env], '--exp_id',
model_name + '_fooobj_' + str(0), '--random_seed',
str(0), '--agent_alg', model_name, '--verbose', '2',
'--render', '0', '--gamma', '0.99', '--n_episodes', '50',
'--n_cycles', '50', '--n_rollouts', '38', '--n_test_rollouts',
'38', '--n_envs', '1', '--n_batches', '40', '--batch_size',
'4864', '--obj_action_type', '0123456', '--max_nb_objects',
'1', '--observe_obj_grp', 'False', '--rob_policy', '01'
]
config_0 = get_params(args=exp_args_0)
model_0, experiment_args_0 = init(config_0,
agent='object',
her=True,
object_Qfunc=None,
backward_dyn=None,
object_policy=None)
env_0, memory_0, noise_0, config_0, normalizer_0, agent_id_0 = experiment_args_0
#loading the object model
if ENV == 'Egg':
path = './models_paper/obj/egg_rotate_7d_50ep/'
elif ENV == 'Block':
path = './models_paper/obj/block_rotate_7d_50ep/'
elif ENV == 'Pen':
path = './models_paper/obj/pen_rotate_7d_50ep/'
print('loading object model for rotation')
print(path)
model_0.critics[0].load_state_dict(K.load(path +
model_name = 'DDPG_BD'
exp_args = [
'--env_id', env_name, '--exp_id',
model_name + '_fooobj_' + str(0), '--random_seed',
str(0), '--agent_alg', model_name, '--verbose', '2',
'--render', '0', '--gamma', '0.99', '--n_episodes', '50',
'--n_cycles', '50', '--n_rollouts', '38', '--n_test_rollouts',
'38', '--n_envs', '1', '--n_batches', '40', '--batch_size',
'4864', '--obj_action_type', '0123456', '--max_nb_objects',
'1', '--observe_obj_grp', 'False', '--rob_policy', '01'
]
config = get_params(args=exp_args)
model, experiment_args = init(config,
agent='object',
her=True,
object_Qfunc=None,
backward_dyn=None,
object_policy=None)
env, memory, noise, config, normalizer, agent_id = experiment_args
#loading the object model
if env_name == 'HandManipulateEggRotateMulti-v0':
path = './models_paper/obj/egg_rotate_7d_50ep/'
elif env_name == 'HandManipulateBlockRotateXYZMulti-v0':
path = './models_paper/obj/block_rotate_7d_50ep/'
elif env_name == 'HandManipulatePenRotateMulti-v0':
path = './models_paper/obj/pen_rotate_7d_50ep/'
print('loading object model')
print(path)
model.critics[0].load_state_dict(K.load(path + 'object_Qfunc.pt'))
'--n_bd_batches',
'400',
'--obj_action_type',
'012',
'--max_nb_objects',
'1',
'--observe_obj_grp',
'False',
'--rob_policy',
'01',
]
config = get_params(args=exp_args)
model, experiment_args = init(config,
agent='object',
her=True,
object_Qfunc=None,
backward_dyn=None,
object_policy=None)
env, memory, noise, config, normalizer, agent_id = experiment_args
#loading the object model
if exp_config['env'] == 'Push':
path = './models/obj/obj_push_xyz/'
elif exp_config['env'] == 'PnP':
path = './models/obj/obj_pnp_xyz/'
model.critics[0].load_state_dict(K.load(path + 'object_Qfunc.pt'))
model.backward.load_state_dict(K.load(path + 'backward_dyn.pt'))
model.actors[0].load_state_dict(K.load(path + 'object_policy.pt'))
with open(path + 'normalizer.pkl', 'rb') as file:
normalizer = pickle.load(file)