def get_filtered_observation_space(self, input_observation_space: ObservationSpace) -> ObservationSpace:
if self.stacking_axis == -1:
input_observation_space.shape = np.append(input_observation_space.shape, values=[self.stack_size], axis=0)
else:
input_observation_space.shape = np.insert(input_observation_space.shape, obj=self.stacking_axis,
values=[self.stack_size], axis=0)
return input_observation_space
def get_filtered_observation_space(
self,
input_observation_space: ObservationSpace) -> ObservationSpace:
axis_size = input_observation_space.shape[self.axis_origin]
input_observation_space.shape = np.delete(
input_observation_space.shape, self.axis_origin)
if self.axis_target == -1:
input_observation_space.shape = np.append(
input_observation_space.shape, axis_size)
elif self.axis_target < -1:
input_observation_space.shape = np.insert(
input_observation_space.shape, self.axis_target + 1, axis_size)
else:
input_observation_space.shape = np.insert(
input_observation_space.shape, self.axis_target, axis_size)
# move the channels axis according to the axis change
if isinstance(input_observation_space, PlanarMapsObservationSpace):
if input_observation_space.channels_axis == self.axis_origin:
input_observation_space.channels_axis = self.axis_target
elif input_observation_space.channels_axis == self.axis_target:
input_observation_space.channels_axis = self.axis_origin
elif self.axis_origin < input_observation_space.channels_axis < self.axis_target:
input_observation_space.channels_axis -= 1
elif self.axis_target < input_observation_space.channels_axis < self.axis_origin:
input_observation_space.channels_axis += 1
return input_observation_space
def get_filtered_observation_space(
self,
input_observation_space: ObservationSpace) -> ObservationSpace:
dummy_tensor = np.random.rand(*tuple(input_observation_space.shape))
input_observation_space.shape = dummy_tensor.squeeze(
axis=self.axis).shape
return input_observation_space
def get_filtered_observation_space(
self,
input_observation_space: ObservationSpace) -> ObservationSpace:
# replace -1 with the max size
crop_high = self._replace_negative_one_in_crop_size(
self.crop_high, input_observation_space.shape)
crop_low = self._replace_negative_one_in_crop_size(
self.crop_low, input_observation_space.shape)
input_observation_space.shape = crop_high - crop_low
return input_observation_space
def get_filtered_observation_space(
self,
input_observation_space: ObservationSpace) -> ObservationSpace:
input_observation_space.shape = input_observation_space.shape[:-1]
return input_observation_space
def get_filtered_observation_space(
self,
input_observation_space: ObservationSpace) -> ObservationSpace:
input_observation_space.shape = self.output_observation_space.shape
return input_observation_space
