def _render_stacked_frames(self):
if self._image_obs:
# stack past frames along first dimension
img = numpy_all_the_way(self._frames)
if self.channel_config == 'CHW':
return img
elif self.channel_config == 'HWC':
return np.transpose(img, axes=[1, 2, 0])
else:
raise Exception(f'Unknown channel config {self.channel_config}')
else:
return np.array(self._frames).flatten()
def _maybe_trajectory_summaries(self, trajectory_buffer, env_steps):
time_since_last = time.time() - self._last_trajectory_summary
if time_since_last < self.params.gif_save_rate or not trajectory_buffer.complete_trajectories:
return
start_gif_summaries = time.time()
self._last_trajectory_summary = time.time()
num_envs = self.params.gif_summary_num_envs
trajectories = [
numpy_all_the_way(t.obs)[:, :, :, -3:]
for t in trajectory_buffer.complete_trajectories[:num_envs]
]
self._write_gif_summaries(tag='obs_trajectories',
gif_images=trajectories,
step=env_steps)
log.info('Took %.3f seconds to write gif summaries',
time.time() - start_gif_summaries)
def _render_stacked_frames(self):
if self._image_obs:
return np.transpose(numpy_all_the_way(self._frames),
axes=[1, 2, 0])
else:
return np.array(self._frames).flatten()
def test_numpy_all_the_way(self):
a = np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]])
lst = [np.array([0, 1, 2]), np.array([3, 4, 5]), np.array([6, 7, 8])]
numpy_arr = numpy_all_the_way(lst)
self.assertTrue(np.array_equal(a, numpy_arr))