import configargparse
def list_of_list_of_floats(x):
temp = x.replace('[', '').replace(']', '').split(',')
temp2 = [float(temp_e) for temp_e in temp]
return temp2
def list_of_string_names(x):
return x
def list_of_tuples_of_strings(x):
temp = x.replace('[', '').replace(']', '').split(';')
return temp
def boolean_string(s):
if s not in {'False', 'True'}:
raise ValueError('Not a valid boolean string')
return s == 'True'
def config_parser():
parser = configargparse.ArgumentParser()
parser.add_argument("--config", is_config_file=True, help="config file path")
parser.add_argument('--model',
type=str,
default="rnn",
help='rnn, gru')
parser.add_argument('--gamma',
type=float,
default=0.99,
help='discount factor for reward (default: 0.99)')
parser.add_argument('--tau',
type=float,
default=0.005,
help='target smoothing coefficient(τ) (default: 0.005)')
parser.add_argument('--lr',
type=float,
default=0.0003,
help='learning rate (default: 0.001)')
parser.add_argument('--alpha',
type=float,
default=0.2,
help='Temperature parameter α determines the relative importance of the entropy\
term against the reward (default: 0.2)')
parser.add_argument('--automatic_entropy_tuning',
type=boolean_string,
default=True,
help='Automaically adjust α (default: False)')
parser.add_argument('--seed',
type=int,
default=123456,
help='random seed (default: 123456)')
parser.add_argument('--policy_batch_size',
type=int,
default=8,
help='batch size (default: 8)')
parser.add_argument('--hidden_size',
type=int,
default=256,
help='hidden size (default: 1000)')
parser.add_argument('--policy_replay_size',
type=int,
default=50000,
help='size of replay buffer (default: 2800)')
parser.add_argument('--multi_policy_loss',
type=boolean_string,
default=False,
help='use additional policy losses')
parser.add_argument('--batch_iters',
type=int,
default=1,
help='iterations to apply update')
parser.add_argument('--cuda',
action="store_true",
help='run on CUDA (default: False)')
parser.add_argument('--visualize',
type=boolean_string,
default=False,
help='visualize monkey/mouse')
parser.add_argument('--root_dir',
type=str,
default='',
help='specify you root directory')
parser.add_argument('--checkpoint_file',
type=str,
default='agent_networks',
help='specify the name of the file in which you would like to save model weights/training params (do not add extension). Also saves statistics file in root of project folder with same name')
parser.add_argument('--checkpoint_folder',
type=str,
default= 'checkpoint',
help='specify the name of the folder in which you would like to save the checkpoint file')
parser.add_argument('--statistics_folder',
type=str,
default= 'training_statistics',
help='specify the name of the folder in which you would like to save the training statistics')
parser.add_argument('--total_episodes',
type=int,
default=5000000,
help='total number of episodes')
parser.add_argument('--save_iter',
type=int,
default=100,
help='number of episodes until checkpoint is saved')
parser.add_argument('--mode',
type=str,
default="train",
help='select whether to train or test a model (train, test, SFE, sensory_pert, neural_pert, musculo_properties)')
parser.add_argument('--verbose_training',
type=boolean_string,
default=False,
help='Print statistics during training')
parser.add_argument('--load_saved_nets_for_training',
type=boolean_string,
default=False,
help='select whether to train or test a model (train, test)')
parser.add_argument('--musculoskeletal_model_path',
type=str,
default='musculoskeletal_model/musculoskeletal_model.xml',
help='path of musculoskeletal model')
parser.add_argument('--initial_pose_path',
type=str,
default='initial_pose',
help='path of musculoskeletal model')
parser.add_argument('--kinematics_path',
type=str,
default='kinematics_data',
help='path to kinematics data')
parser.add_argument('--nusim_data_path',
type=str,
default='nusim_neural_data',
help='path to nusim neural data for training and testing')
parser.add_argument('--stimulus_data_path',
type=str,
default='stimulus_data',
help='path to experimental stimulus data for training and testing')
parser.add_argument('--test_data_filename',
type=str,
default='test_data',
help='filename for saving the testing data')
parser.add_argument('--condition_selection_strategy',
type=str,
default='reward',
help='whether to select the next condition based on the corresponding average reward accumulated so far')
parser.add_argument('--sim_dt',
type=int,
default=0,
help='The timestep for the simulation: Keep 0 for default simulation timestep')
parser.add_argument('--frame_repeat',
type=int,
default=5,
help='The frames/timepoints for which the same action should be repeated during training of the agent')
parser.add_argument('--n_fixedsteps',
type=int,
default=25,
help='The target will remain at kinematic[timestep=0] for n_fixedsteps')
parser.add_argument('--timestep_limit',
type=int,
default=1000,
help='Timestep limit is max number of timesteps after which the episode will terminate.')
parser.add_argument('--trajectory_scaling',
type= float,
nargs= '+',
default= None,
help='Adjusts/scales the length of the trajectory')
parser.add_argument('--center',
type= list_of_list_of_floats,
nargs= '+',
default= None,
help='Adjusts the starting point of the kinematics trajectory')
parser.add_argument('--stimulus_feedback',
type= boolean_string,
default= False,
help='Experimental stimulus feedback to be included in the sensory feedback')
parser.add_argument('--proprioceptive_feedback',
type= boolean_string,
default= True,
help='Proprioceptive feedback consists of muscle lengths and velocities')
parser.add_argument('--muscle_forces',
type= boolean_string,
default= False,
help='Muscle forces consist of appled muscle forces')
parser.add_argument('--joint_feedback',
type= boolean_string,
default= False,
help='Joint feedback consists of joint positions and velocities')
parser.add_argument('--visual_feedback',
type= boolean_string,
default= False,
help='Visual feedback consists of x/y/z coordinates of the specified bodies in the model')
parser.add_argument('--visual_feedback_bodies',
type= list_of_string_names,
nargs= '*',
default= None,
help='Append the names musculo bodies from which visual feedback should be included')
parser.add_argument('--visual_distance_bodies',
type= list_of_tuples_of_strings,
nargs= '*',
default= None,
help='Specify the names of the bodies as tuples for which the visual distance should be included in the feedback')
parser.add_argument('--visual_velocity',
type= list_of_string_names,
nargs= '*',
default= None,
help='Specify the names of the bodies for which the visual velocity should be included in the feedback')
parser.add_argument('--sensory_delay_timepoints',
type= int,
default= 0,
help='Specify the delay in the sensory feedback in terms of the timepoints')
parser.add_argument('--alpha_usim',
type= float,
default= 0.1,
help='weighting with loss for enforcing simple neural dynamics for uSim/nuSim')
parser.add_argument('--beta_usim',
type= float,
default= 0.01,
help='weighting with loss for minimizing the neural activations for uSim/nuSim')
parser.add_argument('--gamma_usim',
type= float,
default= 0.001,
help='weighting with loss for minimizing the synaptic weights for uSim/nuSim')
parser.add_argument('--zeta_nusim',
type= float,
default= 0,
help='weighting with loss for nuSim constraining a sub-population of RNN units to experimentally recorded neurons for nuSim')
return parser
Datasets
Models
