(dataset, learn_step=0.005,
weight_decay=1e-4, num_epochs=500,
max_patience=100, data_augmentation={},
savepath=None, loadpath=None,
early_stop_class=None,
batch_size=None,
resume=False,
train_from_0_255=False)
| 112 | |
| 113 | |
| 114 | def train(dataset, learn_step=0.005, |
| 115 | weight_decay=1e-4, num_epochs=500, |
| 116 | max_patience=100, data_augmentation={}, |
| 117 | savepath=None, loadpath=None, |
| 118 | early_stop_class=None, |
| 119 | batch_size=None, |
| 120 | resume=False, |
| 121 | train_from_0_255=False): |
| 122 | |
| 123 | # |
| 124 | # Prepare load/save directories |
| 125 | # |
| 126 | exp_name = 'unet_' + 'data_aug' if bool(data_augmentation) else '' |
| 127 | |
| 128 | if savepath is None: |
| 129 | raise ValueError('A saving directory must be specified') |
| 130 | |
| 131 | savepath = os.path.join(savepath, dataset, exp_name) |
| 132 | # loadpath = os.path.join(loadpath, dataset, exp_name) |
| 133 | print(savepath) |
| 134 | # print loadpath |
| 135 | |
| 136 | if not os.path.exists(savepath): |
| 137 | os.makedirs(savepath) |
| 138 | else: |
| 139 | print('\033[93m The following folder already exists {}. ' |
| 140 | 'It will be overwritten in a few seconds...\033[0m'.format( |
| 141 | savepath)) |
| 142 | |
| 143 | print('Saving directory : ' + savepath) |
| 144 | with open(os.path.join(savepath, "config.txt"), "w") as f: |
| 145 | for key, value in locals().items(): |
| 146 | f.write('{} = {}\n'.format(key, value)) |
| 147 | |
| 148 | # |
| 149 | # Define symbolic variables |
| 150 | # |
| 151 | input_var = T.tensor4('input_var') |
| 152 | target_var = T.ivector('target_var') |
| 153 | |
| 154 | # |
| 155 | # Build dataset iterator |
| 156 | # |
| 157 | if batch_size is not None: |
| 158 | bs = batch_size |
| 159 | else: |
| 160 | bs = [10, 1, 1] |
| 161 | |
| 162 | |
| 163 | train_iter = IsbiEmStacksDataset(which_set='train', |
| 164 | batch_size=batch_size[0], |
| 165 | seq_per_subset=0, |
| 166 | seq_length=0, |
| 167 | data_augm_kwargs=data_augmentation, |
| 168 | return_one_hot=False, |
| 169 | return_01c=False, |
| 170 | overlap=0, |
| 171 | use_threads=True, |
no test coverage detected