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 EagerReturnRemoteBlob(remote_blob, allow_cpu_return_op=True):
if not hob.is_trainable(None):
return remote_blob
(op_conf, lbi,
scope) = _GetReturnOpConfAndOutLbiAndScope(remote_blob,
allow_cpu_return_op)
if remote_blob.blob_object.op_arg_parallel_attr.is_mirrored():
add_and_infer = compile_context.CurJobAddMirroredOp
else:
add_and_infer = compile_context.CurJobAddConsistentOp
op_attribute = add_and_infer(op_conf, scope)
def BuildInstruction(builder):
get_blob_scope = blob_register_util.BnInOp2BlobObjectScope
with get_blob_scope(blob_register,
op_attribute) as bn_in_op2blob_object:
cfg_op_attribute = oneflow._oneflow_internal.deprecated.MakeOpAttributeByString(
str(op_attribute))
builder.StatelessCall(
cfg_op_attribute,
remote_blob.blob_object.parallel_desc_symbol.parallel_conf,
bn_in_op2blob_object,
boxing_util.BoxingTo,
)
oneflow._oneflow_internal.deprecated.LogicalRun(BuildInstruction)
return remote_blob_util.RemoteBlob(lbi)
def InputOpByArgBlobDef(blob_def):
assert isinstance(blob_def, input_blob_util.ArgBlobDef)
op_conf = op_conf_util.OperatorConf()
op_conf.name = blob_def.op_name
op_conf.input_conf.out = blob_def.blob_name
op_conf.input_conf.blob_conf.CopyFrom(blob_def.ToInterfaceBlobConf())
blob_def.AddAndInferOp(op_conf)
lbi = logical_blob_id_util.LogicalBlobId()
lbi.op_name = blob_def.op_name
lbi.blob_name = blob_def.blob_name
return remote_blob_util.RemoteBlob(lbi)
def LazyReturnRemoteBlob(remote_blob, allow_cpu_return_op=True):
assert isinstance(
remote_blob,
(
oneflow._oneflow_internal.LazyMirroredBlob,
oneflow._oneflow_internal.LazyConsistentBlob,
),
)
(op_conf, lbi,
scope) = _GetReturnOpConfAndOutLbiAndScope(remote_blob,
allow_cpu_return_op)
compile_context.CurJobAddOp(op_conf, scope)
return remote_blob_util.RemoteBlob(lbi)
def image_decoder_random_crop_resize(
input_blob: oneflow._oneflow_internal.BlobDesc,
target_width: int,
target_height: int,
num_attempts: Optional[int] = None,
seed: Optional[int] = None,
random_area: Optional[Sequence[float]] = None,
random_aspect_ratio: Optional[Sequence[float]] = None,
num_workers: Optional[int] = None,
warmup_size: Optional[int] = None,
max_num_pixels: Optional[int] = None,
name: Optional[str] = None,
) -> Tuple[oneflow._oneflow_internal.BlobDesc]:
if name is None:
name = id_util.UniqueStr("ImageDecoderRandomCropResize_")
op_conf = op_conf_util.OperatorConf()
op_conf.name = name
setattr(op_conf.image_decoder_random_crop_resize_conf, "in",
input_blob.unique_name)
op_conf.image_decoder_random_crop_resize_conf.out = "out"
op_conf.image_decoder_random_crop_resize_conf.target_width = target_width
op_conf.image_decoder_random_crop_resize_conf.target_height = target_height
if num_attempts is not None:
op_conf.image_decoder_random_crop_resize_conf.num_attempts = num_attempts
if seed is not None:
op_conf.image_decoder_random_crop_resize_conf.seed = seed
if random_area is not None:
assert len(random_area) == 2
op_conf.image_decoder_random_crop_resize_conf.random_area_min = random_area[
0]
op_conf.image_decoder_random_crop_resize_conf.random_area_max = random_area[
1]
if random_aspect_ratio is not None:
assert len(random_aspect_ratio) == 2
op_conf.image_decoder_random_crop_resize_conf.random_aspect_ratio_min = random_aspect_ratio[
0]
op_conf.image_decoder_random_crop_resize_conf.random_aspect_ratio_max = random_aspect_ratio[
1]
if num_workers is not None:
op_conf.image_decoder_random_crop_resize_conf.num_workers = num_workers
if warmup_size is not None:
op_conf.image_decoder_random_crop_resize_conf.warmup_size = warmup_size
if max_num_pixels is not None:
op_conf.image_decoder_random_crop_resize_conf.max_num_pixels = max_num_pixels
interpret_util.Forward(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_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 MakeRemoteBlob(self, lbi):
return remote_blob_util.RemoteBlob(lbi)
def _CreateVariableBlob(op_conf):
compile_context.CurJobAddConsistentOp(op_conf)
lbi = logical_blob_id_util.LogicalBlobId()
lbi.op_name = op_conf.name
lbi.blob_name = op_conf.variable_conf.out
return remote_blob_util.RemoteBlob(lbi)
def constant_like(
like: oneflow._oneflow_internal.BlobDesc,
value: Union[int, float],
dtype: Optional[flow.dtype] = None,
name: Optional[str] = None,
) -> oneflow._oneflow_internal.BlobDesc:
"""This operator creates a constant Blob that has the same shape as `like`.
Args:
like (oneflow._oneflow_internal.BlobDesc): A Blob.
value (Union[int, float]): The constant value of Blob.
dtype (Optional[flow.dtype], optional): The data type of Blob. Defaults to None.
name (Optional[str], optional): The name for the operation. Defaults to None.
Raises:
NotImplementedError: The data type of value should be int or float.
Returns:
oneflow._oneflow_internal.BlobDesc: The result Blob.
For example:
.. code-block:: python
import oneflow.compatible.single_client as flow
import numpy as np
import oneflow.compatible.single_client.typing as tp
@flow.global_function()
def constant_like_Job() -> tp.Numpy:
constant_blob = flow.constant(value=1.5,
shape=(1, 3, 3),
dtype=flow.float)
constant_like_blob = flow.constant_like(like=constant_blob,
value=5.5,
dtype=flow.float)
return constant_like_blob
out = constant_like_Job()
# out [[[5.5 5.5 5.5]
# [5.5 5.5 5.5]
# [5.5 5.5 5.5]]]
"""
op_conf = op_conf_util.OperatorConf()
setattr(
op_conf,
"name",
name if name is not None else id_util.UniqueStr("ConstantLike_"),
)
setattr(op_conf.constant_like_conf, "like", like.unique_name)
if isinstance(value, int):
op_conf.constant_like_conf.int_operand = value
elif isinstance(value, float):
op_conf.constant_like_conf.float_operand = value
else:
raise NotImplementedError
if dtype is not None:
setattr(
op_conf.constant_like_conf,
"data_type",
oneflow._oneflow_internal.deprecated.GetProtoDtype4OfDtype(dtype),
)
setattr(op_conf.constant_like_conf, "out", "out")
interpret_util.Forward(op_conf)
out_lbi = logical_blob_id_util.LogicalBlobId()
setattr(out_lbi, "op_name", op_conf.name)
setattr(out_lbi, "blob_name", "out")
return remote_blob_util.RemoteBlob(out_lbi)