def test_replay_balanced_memory(self):
mem_size = 25
policies = [
None,
ExperienceBalancedBuffer(max_size=mem_size),
ClassBalancedBuffer(max_size=mem_size),
]
for policy in policies:
self._test_replay_balanced_memory(policy, mem_size)
def __init__(
self,
mem_size: int = 200,
storage_policy: Optional["ExemplarsBuffer"] = None,
force_data_batch_size: int = None,
):
super().__init__()
self.mem_size = mem_size
self.force_data_batch_size = force_data_batch_size
if storage_policy is not None: # Use other storage policy
self.storage_policy = storage_policy
assert storage_policy.max_size == self.mem_size
else: # Default
self.storage_policy = ExperienceBalancedBuffer(
max_size=self.mem_size, adaptive_size=True)
def __init__(self,
mem_size: int = 200,
batch_size: int = None,
batch_size_mem: int = None,
task_balanced_dataloader: bool = False,
storage_policy: Optional["ExemplarsBuffer"] = None):
super().__init__()
self.mem_size = mem_size
self.batch_size = batch_size
self.batch_size_mem = batch_size_mem
self.task_balanced_dataloader = task_balanced_dataloader
if storage_policy is not None: # Use other storage policy
self.storage_policy = storage_policy
assert storage_policy.max_size == self.mem_size
else: # Default
self.storage_policy = ExperienceBalancedBuffer(
max_size=self.mem_size, adaptive_size=True)
def test_balancing(self):
p1 = ExperienceBalancedBuffer(100, adaptive_size=True)
p2 = ClassBalancedBuffer(100, adaptive_size=True)
for policy in [p1, p2]:
self.assert_balancing(policy)