def train_dae(NET, dae_layer, sgd_params, datasets):
"""Run DAE training test."""
# Run denoising autoencoder training on the given layer of NET
NT.train_dae(NET=NET, \
dae_layer=dae_layer, \
sgd_params=sgd_params, \
datasets=datasets)
return
def train_dae(NET, dae_layer, sgd_params, datasets):
"""Run DAE training test."""
# Run denoising autoencoder training on the given layer of NET
NT.train_dae(NET=NET, \
dae_layer=dae_layer, \
sgd_params=sgd_params, \
datasets=datasets)
return
def train_dae(NET, dae_layer, mlp_params, sgd_params):
"""Run DAE training test."""
# Load some data to train/validate/test with
dataset = 'data/mnist.pkl.gz'
datasets = load_udm(dataset)
# Run denoising autoencoder training on the given layer of NET
NT.train_dae(NET=NET, \
dae_layer=dae_layer, \
mlp_params=mlp_params, \
sgd_params=sgd_params, \
datasets=datasets)
return 1
def train_dae(NET, dae_layer, mlp_params, sgd_params):
"""Run DAE training test."""
# Load some data to train/validate/test with
dataset = 'data/mnist.pkl.gz'
datasets = load_udm(dataset)
# Run denoising autoencoder training on the given layer of NET
NT.train_dae(NET=NET, \
dae_layer=dae_layer, \
mlp_params=mlp_params, \
sgd_params=sgd_params, \
datasets=datasets)
return
