# model.labels_ph
# model.is_training_ph
# # Metrics
# model.loss
# model.loss_l2
# model.success_rate
# model.number_of_errors
# Core libraries
import numpy as np
import tensorflow as tf
# G-splinet specific
import importlib
import gsplinets_tf as gsplinets
layers = gsplinets.layers('R2R+')
class CelebALandmarks_FixedScale:
def __init__(
self,
args={
'N_h': 1,
'N_k_h': 1,
'N_c': 32,
'h_range': 2,
'h_origin_at': 'center',
'h_kernel_type': 'dense'
}):
## Check arguments
# model.is_training_ph
# # Metrics
# model.loss
# model.loss_l2
# model.success_rate
# model.number_of_errors
# Core libraries
import numpy as np
import tensorflow as tf
# G-splinet specific
import importlib
import gsplinets_tf as gsplinets
layers = gsplinets.layers('SE2')
class PCAM_SE2_norotaugm:
def __init__(self, args = {'N_h':1,'N_k_h':1,'N_c':32,'h_kernel_type':'dense'}):
## Check arguments
N_h = int(args['N_h']) # 1, 4, 8, 16
N_k_h = int(args['N_k_h'])
N_c = int(args['N_c']) # 36, 18, 13, 19
h_kernel_type = args['h_kernel_type'] # 'dense', 'atrous', 'localized'
## Some attributes
self.all_weights={}
self.all_kernels={}