def _WatcherHandler(handler_uuid, of_blob_ptr):
uuid2handler = session_ctx.GetDefaultSession().uuid2watch_handler
assert handler_uuid in uuid2handler
blob_watched, handler = uuid2handler[handler_uuid]
assert callable(handler)
ndarray = ofblob.OfBlob(of_blob_ptr).CopyToNdarray()
local_blob = local_blob_util.LocalBlob(ndarray, blob_watched.is_dynamic)
handler(oft_util.TransformWatchedBlob(local_blob, handler))
def result(self):
if self.local_mirrored_blob_ is not None:
return self.local_mirrored_blob_
local_blob_list = [x.result.numpy() for x in self.sub_pullers_]
local_numpy = local_blob_list[0]
# TODO(chengcheng): check list length = 1 in single client. fix after multi-client
if len(local_blob_list) > 1:
print("WARNING: return tensor list will concat as axis = 0.")
local_numpy = np.concatenate(local_blob_list, axis=0)
self.local_mirrored_blob_ = local_blob_util.LocalBlob(
local_numpy, self.mirrored_blob_.is_dynamic)
return self.local_mirrored_blob_
def HandlerParallelIdAndLocalBlob(parallel_id, local_blob):
assert parallel_id not in parallel_id2consistent_local_blob
parallel_id2consistent_local_blob[parallel_id] = local_blob
if len(parallel_id2consistent_local_blob) != len_sub_remote_blobs:
return
local_blob_list = [
parallel_id2consistent_local_blob[parallel_id]
for i in range(len_sub_remote_blobs)
]
local_numpy = local_blob_list[0].numpy()
if len(local_blob_list) > 1:
print("WARNING: watch return tensor list will concat as axis = 0.")
local_numpy_list = [x.numpy() for x in local_blob_list]
local_numpy = np.concatenate(local_numpy_list, axis=0)
local_blob = local_blob_util.LocalBlob(local_numpy,
blob_watched.is_dynamic)
handler(oft_util.TransformWatchedBlob(local_blob, handler))
def PullCallback(of_blob):
self.result_ = local_blob_util.LocalBlob(
of_blob.CopyToNdarray(), self.consistent_blob_.is_dynamic)
pull_cb()
