(show_result=False)
| 318 | |
| 319 | |
| 320 | def plot_durations(show_result=False): |
| 321 | plt.figure(1) |
| 322 | durations_t = torch.tensor(episode_durations, dtype=torch.float) |
| 323 | if show_result: |
| 324 | plt.title('Result') |
| 325 | else: |
| 326 | plt.clf() |
| 327 | plt.title('Training...') |
| 328 | plt.xlabel('Episode') |
| 329 | plt.ylabel('Duration') |
| 330 | plt.plot(durations_t.numpy()) |
| 331 | # Take 100 episode averages and plot them too |
| 332 | if len(durations_t) >= 100: |
| 333 | means = durations_t.unfold(0, 100, 1).mean(1).view(-1) |
| 334 | means = torch.cat((torch.zeros(99), means)) |
| 335 | plt.plot(means.numpy()) |
| 336 | |
| 337 | plt.pause(0.001) # pause a bit so that plots are updated |
| 338 | if is_ipython: |
| 339 | if not show_result: |
| 340 | display.display(plt.gcf()) |
| 341 | display.clear_output(wait=True) |
| 342 | else: |
| 343 | display.display(plt.gcf()) |
| 344 | |
| 345 | |
| 346 | ###################################################################### |
no outgoing calls
no test coverage detected