def enqueue_blobs_thread(self, gpu_id, blob_names):
"""Transfer mini-batches from a mini-batch queue to a BlobsQueue."""
batch_size=0
with self.coordinator.stop_on_exception():
while not self.coordinator.should_stop():
if self._minibatch_queue.qsize == 0:
logger.warning('Mini-batch queue is empty')
flag=True
if self._roidb_tmp is not None and batch_size%2==1:
flag=False
if flag:
blobs = coordinated_get(self.coordinator, self._minibatch_queue)
else:
blobs = coordinated_get(self.coordinator,self._unlabel_minibatch_queue)
self.enqueue_blobs(gpu_id, blob_names, blobs.values())
logger.debug(
'batch queue size {}'.format(self._minibatch_queue.qsize())
)
batch_size+=1
logger.info('Stopping enqueue thread')
def enqueue_blobs_thread(self, gpu_id, blob_names):
"""Transfer mini-batches from a mini-batch queue to a BlobsQueue."""
with self.coordinator.stop_on_exception():
while not self.coordinator.should_stop():
if self._minibatch_queue.qsize == 0:
logger.warning('Mini-batch queue is empty')
blobs = coordinated_get(self.coordinator, self._minibatch_queue)
self.enqueue_blobs(gpu_id, blob_names, blobs.values())
logger.info(
'batch queue size {}'.format(self._minibatch_queue.qsize())
)
logger.info('Stopping enqueue thread')
def enqueue_blobs_thread(self, gpu_id, blob_names):
"""Transfer mini-batches from a mini-batch queue to a BlobsQueue."""
with self.coordinator.stop_on_exception():
while not self.coordinator.should_stop():
if self._minibatch_queue.qsize == 0:
logger.warning('Mini-batch queue is empty')
blobs = coordinated_get(self.coordinator, self._minibatch_queue)
self.enqueue_blobs(gpu_id, blob_names, blobs.values())
logger.debug(
'batch queue size {}'.format(self._minibatch_queue.qsize())
)
logger.info('Stopping enqueue thread')
def enqueue_blobs_thread_mp(self, gpu_id, blob_names):
"""Transfer mini-batches from a mini-batch queue to a BlobsQueue."""
with self.coordinator.stop_on_exception():
while not self.coordinator.should_stop():
if self._minibatch_queue_mp.qsize() == 0:
logger.warning('minibatch_queue_mp -batch queue is empty')
blobs = coordinated_get(self.coordinator, self._minibatch_queue_mp)
if cfg.LOG_IMAGES and np.random.random() <= 0.01:
self.save_im_masks(blobs)
self.enqueue_blobs(gpu_id, blob_names, blobs.values())
logger.debug(
'batch queue size {}'.format(self._minibatch_queue_mp.qsize())
)
logger.info('Stopping enqueue thread')