(model, print_out=True, model_name="model")
| 243 | |
| 244 | |
| 245 | def num_params(model, print_out=True, model_name="model"): |
| 246 | parameters = filter(lambda p: p.requires_grad, model.parameters()) |
| 247 | parameters = sum([np.prod(p.size()) for p in parameters]) / 1_000_000 |
| 248 | if print_out: |
| 249 | print(f'| {model_name} Trainable Parameters: %.3fM' % parameters) |
| 250 | return parameters |