dcl/CONFIG.py at dev · hatfield-c/dcl · GitHub

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# set to 0 for data generation
#timestep = 0
timestep = 1 / 240

app_index = 0
client_count = 1#37
render_scenario = False

episode_count = 10000
episode_length = 300
print_every_episode_generated = 500
pause_every_episode = False

state_data_path = "data/v5/state_data"
max_data_path = "data/v5/max_data"
value_data_path = "data/v5/value_data"

gravity_strength = 9.8

action = None
#action = "generate_data"
#action = "stitch_data"
#action = "train_hitpoly"
#action = "query_hitpoly"
#action = "render_hitpoly"
#action = "build_video"

possible_actions = {
	"help": "help",
	"generate_data": "generate_data",
	"stitch_data": "stitch_data",
	"build_video": "build_video",
	"train_hitpoly": "train_hitpoly",
	"query_hitpoly": "query_hitpoly",
	"render_hitpoly": "render_hitpoly",
	"extract_hitpoly": "extract_hitpoly",
	"test_hitpoly": "test_hitpoly",
	"playground": "playground"
}
possible_actions_list = list(possible_actions.keys())

simulation_episode_length = 1400
observer_episode_length = 700

############################
#	HITPOLY PARAMETERS
############################

#ai_type = "pid_align_pdb"
ai_type = "pid_align_ng"
#ai_type = "pid_align_ngn"

############################
#	NEURAL PARAMETERS
############################
state_data_path = "data/v6/state_data.float"
value_data_path = "data/v6/value_data.float"

epochs = 100000
learning_rate = 1e-3
dimensionality = 6
batch_size = 1024

print_every_epoch = 1000

model_path = "data/models/hitpoly/ng/"
param_path = "data/models/hitpoly/ng/parameters/"
#model_path = "data/models/hitpoly/ngn/"
#param_path = "data/models/hitpoly/ngn/parameters/"

############################
#	PDB PARAMETERS
############################

pdb_path = "data/pdb/state_positive.float"

############################
#	DIFFUSION PARAMETERS
############################

seed_path = state_data_path + ".pt"
seed_maxes_path = max_data_path + ".pt"
value_path = value_data_path + ".pt"

diffusion_model_path = "data/models/diffusion/v2/"
value_model_path = "data/models/value/v2/"

horizon = 4
horizon_scale = 1
state_size = 9
action_size = 1
total_size = state_size + action_size
n_timesteps = 100

diffusion_epochs = 10000
value_epochs = 10000

diffusion_dim = 32
value_dim = 32

#diffusion_dim_mults = (1, 4, 8)
diffusion_dim_mults = (1, 4, 8)
#value_dim_mults = (1, 2, 4)
value_dim_mults = (1, 4, 8)

num_diffusion_norm_groups = 8
num_value_norm_groups = 8

diffusion_lr = 2e-4
value_lr = 2e-4

diffusion_batch_size = 128
value_batch_size = 128