def __init__(self,
source=None,
num_outputs=None,
batch_size=-1,
cycle=None,
name=None,
layout=None,
batch=None,
batch_info=None):
if name is not None and num_outputs is not None:
raise ValueError(
"`num_outputs` is not compatible with named `ExternalSource`")
callback, source_desc = _get_callback_from_source(
source, cycle, batch_info or False)
self._name = name
self._layout = layout
self._num_outputs = num_outputs
self._batch = batch
self._batch_size = batch_size
self._callback = callback
self._source_desc = source_desc
self._batch_info = batch_info
self._current_iter = 0
self._current_sample = 0
self._feed_inputs = Queue()
if callback is not None:
arg_count = _accepted_arg_count(callback)
if arg_count not in [0, 1]:
raise TypeError(
"External source callback must be a callable with 0 or 1 argument"
)
self.accepts_arg = arg_count > 0
def __init__(self, callback, source_desc, is_multioutput, instances=[], *,
cuda_stream=None, use_copy_kernel=None, batch=True, parallel=False,
prefetch_queue_depth=None, batch_info=None):
self.instances = list(instances) # we need a copy!
self.utilized_instances = self.instances
self.is_multioutput = is_multioutput
self.callback = callback
self.source_desc = source_desc
self._cuda_stream = cuda_stream
self.use_copy_kernel = use_copy_kernel
self.batch = batch
self.batch_info = batch_info
# Index of a batch within the epoch that will be returned from
# get_batch or schedule_and_receive call. Contrary to Pipeline's
# `epoch_idx` it is tracked separately by ExternalSourceGroup due to
# prefetching of batches in parallel mode.
self.current_iter = 0
self.current_sample = 0
self.parallel = parallel
self.prefetch_queue_depth = prefetch_queue_depth
if callback is not None:
arg_count = _accepted_arg_count(callback)
if arg_count not in [0, 1]:
raise TypeError("External source callback must be a callable with 0 or 1 argument")
self.accepts_arg = arg_count > 0