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 shape(self):
if oneflow.scope.mirrored_view_enabled():
print(
"WARNING:",
"You access a consistent blob shape in mirrored view, there may be problems,",
"you should add 'x = flow.cast_to_current_logical_view(x)'.",
file=sys.stderr,
)
print(traceback.format_stack()[-2])
return c_api_util.JobBuildAndInferCtx_GetStaticShape(self.job_name_, self.lbn_)
def _get_op_blob_info(self, job_name, op_name, blob_name):
self._check_status(self.SessionStatus.OPEN, self.SessionStatus.RUNNING)
if op_name in self.inferface_name2info_:
return self.inferface_name2info_[op_name]
job_name = job_name or self.cur_job_name_
if job_name is None:
raise ValueError("please specify job_name")
lbn = oneflow_api.JobBuildAndInferCtx_GetOpBlobLbn(job_name, op_name, blob_name)
shape = c_api_util.JobBuildAndInferCtx_GetStaticShape(job_name, lbn)
dtype = c_api_util.JobBuildAndInferCtx_GetDataType(job_name, lbn)
dtype = dtype_util.convert_proto_dtype_to_oneflow_dtype(dtype)
# TODO: other info
info = dict(shape=shape, dtype=dtype)
self.inferface_name2info_[op_name] = info
return info
def input_info(self, input_name):
self._check_status(self.SessionStatus.RUNNING)
if input_name in self.inferface_name2info_:
return self.inferface_name2info_[input_name]
input_lbn = "{}/out".format(input_name)
if input_name not in self.inferface_name2job_name_:
raise ValueError('can not find input with name "{}"'.format(input_name))
job_name = self.inferface_name2job_name_[input_name]
input_shape = c_api_util.JobBuildAndInferCtx_GetStaticShape(job_name, input_lbn)
input_dtype = c_api_util.JobBuildAndInferCtx_GetDataType(job_name, input_lbn)
input_dtype = dtype_util.convert_proto_dtype_to_oneflow_dtype(input_dtype)
# input_dtype = dtype_util.convert_oneflow_dtype_to_numpy_dtype(input_dtype)
# TODO: other info
input_info = dict(shape=input_shape, dtype=input_dtype)
self.inferface_name2info_[input_name] = input_info
return input_info
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.parallel_distribution.sbp_parallel.extend([sbp_parallel])
blob_conf.is_dynamic = is_dynamic
return blob_conf