def get_data_config(self, conf_module):
# get default data config
path = os.path.join(
get_dataset_path(conf_module.configuration['dataset_name']),
'dataset_spec.py')
data_conf_file = imp.load_source('dataset_spec', path)
data_conf = AttrDict()
data_conf.dataset_spec = AttrDict(data_conf_file.dataset_spec)
# update with custom params if available
update_data_conf = {}
if hasattr(conf_module, 'data_config'):
update_data_conf = conf_module.data_config
elif conf_module.configuration.dataset_name is not None:
update_data_conf = importlib.import_module(
'gcp.datasets.configs.' +
conf_module.configuration.dataset_name).config
for key in update_data_conf:
if key == "dataset_spec":
data_conf.dataset_spec.update(update_data_conf.dataset_spec)
else:
data_conf[key] = update_data_conf[key]
if not 'fps' in data_conf:
data_conf.fps = 4
return data_conf
def get_data_config(self, conf_module):
# get default data config
path = os.path.join(
get_dataset_path(conf_module.configuration['dataset_name']),
'dataset_spec.py')
data_conf_file = imp.load_source('dataset_spec', path)
data_conf = AttrDict()
data_conf.dataset_spec = AttrDict(data_conf_file.dataset_spec)
# update with custom params if available
try:
update_data_conf = conf_module.data_config
except AttributeError:
pass
for key in update_data_conf:
if key == "dataset_spec":
data_conf.dataset_spec.update(update_data_conf.dataset_spec)
else:
data_conf[key] = update_data_conf[key]
if not 'fps' in data_conf:
data_conf.fps = 4
return data_conf
'nz_mid_lstm': 512,
'n_lstm_layers': 3,
'nz_mid': 128,
'nz_enc': 128,
'nz_vae': 256,
'regress_length': True,
'attach_state_regressor': True,
'attach_cost_mdl': True,
'cost_mdl_params': AttrDict(
cost_fcn=EuclideanPathLength,
),
'attach_inv_mdl': True,
'inv_mdl_params': AttrDict(
n_actions=2,
use_convs=False,
build_encoder=False,
),
'decoder_distribution': 'discrete_logistic_mixture',
})
model_config.pop("add_weighted_pixel_copy")
## Dataset
data_config = AttrDict()
data_config.dataset_spec = AttrDict()
data_config.dataset_spec.max_seq_len = 100
data_config.dataset_spec.dataset_class = MazeTopRenderedGlobalSplitVarLenVideoDataset
data_config.n_rooms = configuration['n_rooms']
data_config.crop_window = 40
data_config.dataset_spec.split = AttrDict(train=0.994, val=0.006, test=0.00)
