def decode_random(
shape: Sequence[int],
dtype: flow.dtype,
batch_size: int = 1,
initializer: Optional[initializer_conf_util.InitializerConf] = None,
tick: Optional[oneflow._oneflow_internal.BlobDesc] = None,
name: Optional[str] = None,
) -> oneflow._oneflow_internal.BlobDesc:
op_conf = op_conf_util.OperatorConf()
if name is None:
name = id_util.UniqueStr("DecodeRandom_")
assert isinstance(name, str)
op_conf.name = name
assert isinstance(shape, (list, tuple))
op_conf.decode_random_conf.shape.dim.extend(shape)
assert dtype is not None
setattr(
op_conf.decode_random_conf,
"data_type",
oneflow._oneflow_internal.deprecated.GetProtoDtype4OfDtype(dtype),
)
op_conf.decode_random_conf.batch_size = batch_size
if initializer is not None:
op_conf.decode_random_conf.data_initializer.CopyFrom(initializer)
else:
op_conf.decode_random_conf.data_initializer.CopyFrom(
flow.random_uniform_initializer())
if tick:
op_conf.decode_random_conf.tick = tick.unique_name
op_conf.decode_random_conf.out = "out"
lbi = logical_blob_id_util.LogicalBlobId()
lbi.op_name = op_conf.name
lbi.blob_name = "out"
interpret_util.ConsistentForward(op_conf)
return remote_blob_util.RemoteBlob(lbi)
def distribute_add(xs, name=None):
assert flow.current_scope(
).device_parallel_desc_symbol.parallel_num == len(xs)
if name is None:
name = id_util.UniqueStr("DistributeAdd_")
op_conf = op_conf_util.OperatorConf()
op_conf.name = name
getattr(op_conf.distribute_add_conf,
"in").extend([_SoleConsistentLbn(x) for x in xs])
op_conf.distribute_add_conf.out = "out"
interpret_util.ConsistentForward(op_conf)
lbi = logical_blob_id_util.LogicalBlobId()
lbi.op_name = op_conf.name
lbi.blob_name = "out"
return remote_blob_util.RemoteBlob(lbi)
def distribute_clone(x, name=None):
if name is None:
name = id_util.UniqueStr("DistributeClone_")
op_conf = op_conf_util.OperatorConf()
op_conf.name = name
setattr(op_conf.distribute_clone_conf, "in", x.unique_name)
parallel_size = flow.current_scope(
).device_parallel_desc_symbol.parallel_num
op_conf.distribute_clone_conf.out.extend(
["out_%d" % i for i in range(parallel_size)])
interpret_util.ConsistentForward(op_conf)
ret = []
for i in range(parallel_size):
out = "out_%d" % i
lbi = logical_blob_id_util.LogicalBlobId()
lbi.op_name = op_conf.name
lbi.blob_name = out
ret.append(remote_blob_util.RemoteBlob(lbi))
return tuple(ret)
def InferAndTryRun(self):
interpret_util.ConsistentForward(self.op_conf_)
return self