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				|  | @ -20,7 +20,7 @@ def create_modules(module_defs): | |||
|         modules = nn.Sequential() | ||||
| 
 | ||||
|         if module_def['type'] == 'convolutional': | ||||
|             bn = int(module_def['batch_normalize']) if 'batch_normalize' in module_def else 0 | ||||
|             bn = int(module_def['batch_normalize']) | ||||
|             filters = int(module_def['filters']) | ||||
|             kernel_size = int(module_def['size']) | ||||
|             pad = (kernel_size - 1) // 2 if int(module_def['pad']) else 0 | ||||
|  |  | |||
|  | @ -10,7 +10,7 @@ def parse_model_cfg(path): | |||
|             module_defs.append({}) | ||||
|             module_defs[-1]['type'] = line[1:-1].rstrip() | ||||
|             if module_defs[-1]['type'] == 'convolutional': | ||||
|                 module_defs[-1]['batch_normalize'] = 0 | ||||
|                 module_defs[-1]['batch_normalize'] = 0  # pre-populate with zeros (may be overwritten later) | ||||
|         else: | ||||
|             key, value = line.split("=") | ||||
|             value = value.strip() | ||||
|  |  | |||
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