def create_default_memory(self):
return prioritized_replay_buffer.OutOfGraphPrioritizedReplayBuffer(
SCREEN_SIZE,
STACK_SIZE,
REPLAY_CAPACITY,
BATCH_SIZE,
max_sample_attempts=10) # For faster tests.
def _build_replay_buffer(self):
"""Creates the prioritized replay buffer used by the agent."""
return prioritized_replay_buffer.OutOfGraphPrioritizedReplayBuffer(
observation_shape=self.observation_shape,
stack_size=self.stack_size,
update_horizon=self.update_horizon,
gamma=self.gamma,
observation_dtype=self.observation_dtype)
def testConstructorWithExtraStorageTypes(self):
prioritized_replay_buffer.OutOfGraphPrioritizedReplayBuffer(
SCREEN_SIZE,
STACK_SIZE,
REPLAY_CAPACITY,
BATCH_SIZE,
extra_storage_types=[
prioritized_replay_buffer.ReplayElement('extra1', [], np.float32),
prioritized_replay_buffer.ReplayElement('extra2', [2], np.int8)
])
def _build_replay_buffer(self):
"""Creates the replay buffer used by the agent."""
if self._replay_scheme not in ['uniform', 'prioritized']:
raise ValueError('Invalid replay scheme: {}'.format(
self._replay_scheme))
return prioritized_replay_buffer.OutOfGraphPrioritizedReplayBuffer(
observation_shape=self.observation_shape,
stack_size=self.stack_size,
update_horizon=self.update_horizon,
gamma=self.gamma,
observation_dtype=self.observation_dtype)
def _build_replay_buffer(self):
"""Creates the replay buffer used by the agent."""
if self._replay_scheme not in ['uniform', 'prioritized']:
raise ValueError('Invalid replay scheme: {}'.format(self._replay_scheme))
# Both replay schemes use the same data structure, but the 'uniform' scheme
# sets all priorities to the same value (which yields uniform sampling).
return prioritized_replay_buffer.OutOfGraphPrioritizedReplayBuffer(
observation_shape=self.observation_shape,
stack_size=self.stack_size,
update_horizon=self.update_horizon,
gamma=self.gamma,
observation_dtype=self.observation_dtype)
def testSampleIndexBatch(self):
memory = prioritized_replay_buffer.OutOfGraphPrioritizedReplayBuffer(
SCREEN_SIZE,
STACK_SIZE,
REPLAY_CAPACITY,
BATCH_SIZE,
max_sample_attempts=REPLAY_CAPACITY)
# This will ensure we end up with cursor == 1.
for _ in range(REPLAY_CAPACITY - STACK_SIZE + 2):
self.add_blank(memory)
self.assertEqual(memory.cursor(), 1)
samples = memory.sample_index_batch(REPLAY_CAPACITY)
# Because cursor == 1, the invalid range as set by circular_replay_buffer.py
# will be # [0, 1, 2, 3], resulting in all samples being in
# [STACK_SIZE, REPLAY_CAPACITY - 1].
for sample in samples:
self.assertGreaterEqual(sample, STACK_SIZE)
self.assertLessEqual(sample, REPLAY_CAPACITY - 1)
