def GetInterfaceBlobConf(job_name, lbn, blob_conf=None):
assert isinstance(job_name, str)
assert isinstance(lbn, str)
if blob_conf is None:
blob_conf = interface_blob_conf_pb.InterfaceBlobConf()
else:
assert isinstance(blob_conf, interface_blob_conf_pb.InterfaceBlobConf)
shape = c_api_util.JobBuildAndInferCtx_GetStaticShape(job_name, lbn)
dtype = c_api_util.JobBuildAndInferCtx_GetDataType(job_name, lbn)
split_axis = c_api_util.JobBuildAndInferCtx_GetSplitAxisFromProducerView(
job_name, lbn)
batch_axis = c_api_util.JobBuildAndInferCtx_GetBatchAxis(job_name, lbn)
is_dynamic = c_api_util.JobBuildAndInferCtx_IsDynamic(job_name, lbn)
is_tensor_list = c_api_util.JobBuildAndInferCtx_IsTensorList(job_name, lbn)
blob_conf.shape.dim.extend(shape)
blob_conf.data_type = dtype
if split_axis is not None:
blob_conf.split_axis.value = split_axis
if batch_axis is not None:
blob_conf.batch_axis.value = batch_axis
blob_conf.is_dynamic = is_dynamic
blob_conf.is_tensor_list = is_tensor_list
return blob_conf
def ToInterfaceBlobConf(self):
interface_blob_conf = inter_face_blob_conf_util.InterfaceBlobConf()
interface_blob_conf.shape.dim.extend(self.shape_)
interface_blob_conf.data_type = self.dtype_.oneflow_proto_dtype
interface_blob_conf.is_dynamic = self.is_dynamic
interface_blob_conf.is_tensor_list = self.is_tensor_list
self.SetBatchAxisAndSplitAxis(interface_blob_conf)
return interface_blob_conf
def ToInterfaceBlobConf(self):
interface_blob_conf = inter_face_blob_conf_util.InterfaceBlobConf()
interface_blob_conf.shape.dim.extend(self.shape_)
interface_blob_conf.data_type = oneflow_api.deprecated.GetProtoDtype4OfDtype(
self.dtype_)
interface_blob_conf.is_dynamic = self.is_dynamic
# NOTE(chengcheng): rm batch_axis, so set split_axis always = 0 for safe. will support
# set sbp in future, or will delete in multi-client
interface_blob_conf.split_axis.value = 0
return interface_blob_conf
def ToInterfaceBlobConf(self):
interface_blob_conf = inter_face_blob_conf_util.InterfaceBlobConf()
interface_blob_conf.shape.dim.extend(self.shape_)
interface_blob_conf.data_type = self.dtype_.oneflow_proto_dtype
interface_blob_conf.is_dynamic = self.is_dynamic
interface_blob_conf.is_tensor_list = self.is_tensor_list
# NOTE(chengcheng): rm batch_axis, so set split_axis always = 0 for safe. will support
# set sbp in future, or will delete in multi-client
interface_blob_conf.split_axis.value = 0
return interface_blob_conf
def ToInterfaceBlobConf(self):
interface_blob_conf = inter_face_blob_conf_util.InterfaceBlobConf()
interface_blob_conf.shape.dim.extend(self.shape_)
interface_blob_conf.data_type = oneflow._oneflow_internal.deprecated.GetProtoDtype4OfDtype(
self.dtype_
)
interface_blob_conf.is_dynamic = self.is_dynamic
sbp_parallel = sbp_parallel_pb.SbpParallel()
sbp_parallel.split_parallel.axis = 0
interface_blob_conf.nd_sbp.sbp_parallel.extend([sbp_parallel])
return interface_blob_conf
def ToInterfaceBlobConf(self):
interface_blob_conf = inter_face_blob_conf_util.InterfaceBlobConf()
interface_blob_conf.shape.dim.extend(self.shape_)
interface_blob_conf.data_type = oneflow_api.deprecated.GetProtoDtype4OfDtype(
self.dtype_
)
interface_blob_conf.is_dynamic = self.is_dynamic
# NOTE(chengcheng): rm batch_axis, so set split_axis always = 0 for safe. will support
# set sbp in future, or will delete in multi-client
sbp_parallel = sbp_parallel_pb.SbpParallel()
sbp_parallel.split_parallel.axis = 0
interface_blob_conf.parallel_distribution.sbp_parallel.extend([sbp_parallel])
return interface_blob_conf
def _GenModelIOPathInputOpConfAndRetLbi():
op_conf = op_conf_util.OperatorConf()
op_conf.name = "model_io_path_input"
op_conf.device_tag = "cpu"
op_conf.input_conf.out = "out"
blob_conf = inter_face_blob_conf_util.InterfaceBlobConf()
blob_conf.shape.dim.append(65536)
blob_conf.data_type = oneflow._oneflow_internal.deprecated.GetProtoDtype4OfDtype(
flow.int8)
blob_conf.is_dynamic = True
op_conf.input_conf.blob_conf.CopyFrom(blob_conf)
lbi = logical_blob_id_util.LogicalBlobId()
lbi.op_name = op_conf.name
lbi.blob_name = op_conf.input_conf.out
return (op_conf, lbi)
def _GenModelIOPathInputOpConfAndRetLbi():
op_conf = op_conf_util.OperatorConf()
op_conf.name = "model_io_path_input"
op_conf.device_tag = "cpu"
op_conf.input_conf.out = "out"
blob_conf = inter_face_blob_conf_util.InterfaceBlobConf()
blob_conf.shape.dim.append(65536)
blob_conf.data_type = dtype_util.int8.oneflow_proto_dtype
blob_conf.batch_axis.value = 0
blob_conf.is_dynamic = True
op_conf.input_conf.blob_conf.CopyFrom(blob_conf)
lbi = logical_blob_id_util.LogicalBlobId()
lbi.op_name = op_conf.name
lbi.blob_name = op_conf.input_conf.out
return op_conf, lbi
def GetInterfaceBlobConf(job_name, lbn, blob_conf=None):
assert isinstance(job_name, str)
assert isinstance(lbn, str)
if blob_conf is None:
blob_conf = interface_blob_conf_pb.InterfaceBlobConf()
else:
assert isinstance(blob_conf, interface_blob_conf_pb.InterfaceBlobConf)
shape = c_api_util.JobBuildAndInferCtx_GetStaticShape(job_name, lbn)
dtype = c_api_util.JobBuildAndInferCtx_GetDataType(job_name, lbn)
split_axis = c_api_util.JobBuildAndInferCtx_GetSplitAxisFromProducerView(
job_name, lbn)
is_dynamic = c_api_util.JobBuildAndInferCtx_IsDynamic(job_name, lbn)
blob_conf.shape.dim.extend(shape)
blob_conf.data_type = dtype
if split_axis is not None:
sbp_parallel = sbp_parallel_pb.SbpParallel()
sbp_parallel.split_parallel.axis = split_axis
blob_conf.nd_sbp.sbp_parallel.extend([sbp_parallel])
blob_conf.is_dynamic = is_dynamic
return blob_conf