def _GetInterfaceBlobObject(builder, op_name):
sess = session_ctx.GetDefaultSession()
if oneflow_api.EagerExecutionEnabled():
return sess.var_name2var_blob[op_name].blob_object
sess = session_ctx.GetDefaultSession()
op_attribute = sess.OpAttribute4InterfaceOpName(op_name)
cfg_op_attribute = oneflow_api.deprecated.MakeOpAttributeByString(str(op_attribute))
parallel_conf = sess.ParallelConf4LazyInterfaceOpName(op_name)
if not isinstance(
parallel_conf, oneflow_api.oneflow.core.job.placement.ParallelConf
):
parallel_conf_cfg = placement_cfg.ParallelConf()
parallel_conf_cfg.set_device_tag(parallel_conf.device_tag)
for device_name in parallel_conf.device_name:
parallel_conf_cfg.add_device_name(device_name)
if parallel_conf.HasField("hierarchy"):
hierarchy = shape_proto_cfg.ShapeProto()
for dim in parallel_conf.hierarchy.dim:
hierarchy.add_dim(dim)
assert hierarchy.dim_size() > 0
parallel_conf_cfg.mutable_hierarchy().CopyFrom(hierarchy)
parallel_conf = parallel_conf_cfg
blob_object = builder.MakeLazyRefBlobObject(
op_name, cfg_op_attribute, parallel_conf
)
return blob_object
def _inferface_blob_conf_proto_to_cfg(inferface_blob_conf_proto,
mut_inferface_blob_conf_cfg):
assert isinstance(inferface_blob_conf_proto,
interface_blob_conf_proto.InterfaceBlobConf)
assert isinstance(mut_inferface_blob_conf_cfg,
interface_blob_conf_proto_cfg.InterfaceBlobConf)
shape = shape_proto_cfg.ShapeProto()
for dim in inferface_blob_conf_proto.shape.dim:
shape.add_dim(dim)
mut_inferface_blob_conf_cfg.mutable_shape().CopyFrom(shape)
dtype = dtype_proto_cfg.DataType(int(inferface_blob_conf_proto.data_type))
mut_inferface_blob_conf_cfg.set_data_type(dtype)
if inferface_blob_conf_proto.HasField("parallel_distribution"):
# TODO(guoran): Process Nd sbp, parallel_distribution_cfg CopyFrom parallel_distribution_proto
assert len(
inferface_blob_conf_proto.parallel_distribution.sbp_parallel) == 1
sbp_proto = inferface_blob_conf_proto.parallel_distribution.sbp_parallel[
0]
if sbp_proto.HasField("split_parallel"):
split_axis = sbp_proto.split_parallel.axis
sbp = sbp_parallel_cfg.SbpParallel()
sbp.mutable_split_parallel().set_axis(split_axis)
mut_inferface_blob_conf_cfg.mutable_parallel_distribution(
).mutable_sbp_parallel().Add().CopyFrom(sbp)
mut_inferface_blob_conf_cfg.set_is_dynamic(
inferface_blob_conf_proto.is_dynamic)
def _inferface_blob_conf_proto_to_cfg(
inferface_blob_conf_proto, mut_inferface_blob_conf_cfg
):
assert isinstance(
inferface_blob_conf_proto, interface_blob_conf_proto.InterfaceBlobConf
)
assert isinstance(
mut_inferface_blob_conf_cfg, interface_blob_conf_proto_cfg.InterfaceBlobConf
)
shape = shape_proto_cfg.ShapeProto()
for dim in inferface_blob_conf_proto.shape.dim:
shape.add_dim(dim)
mut_inferface_blob_conf_cfg.mutable_shape().CopyFrom(shape)
dtype = dtype_proto_cfg.DataType(int(inferface_blob_conf_proto.data_type))
mut_inferface_blob_conf_cfg.set_data_type(dtype)
split_axis = dtype_proto_cfg.OptInt64()
if inferface_blob_conf_proto.split_axis.HasField("value"):
split_axis.set_value(inferface_blob_conf_proto.split_axis.value)
mut_inferface_blob_conf_cfg.mutable_split_axis().CopyFrom(split_axis)
batch_axis = dtype_proto_cfg.OptInt64()
if inferface_blob_conf_proto.batch_axis.HasField("value"):
batch_axis.set_value(inferface_blob_conf_proto.batch_axis.value)
mut_inferface_blob_conf_cfg.mutable_batch_axis().CopyFrom(batch_axis)
mut_inferface_blob_conf_cfg.set_is_dynamic(inferface_blob_conf_proto.is_dynamic)
mut_inferface_blob_conf_cfg.set_is_tensor_list(
inferface_blob_conf_proto.is_tensor_list
)
def GetConcatSplitBoxingParallelDescSymbol(builder, blob_parallel_desc_symbol,
max_parallel_num):
random_rank_id = random.randint(0, max_parallel_num - 1)
parallel_conf = placement_cfg.ParallelConf()
parallel_conf.set_device_tag("cpu")
for machine_id, _ in blob_parallel_desc_symbol.machine_id2device_id_list.items(
):
parallel_conf.add_device_name("%s:%s" % (machine_id, random_rank_id))
hierarchy = shape_proto_cfg.ShapeProto()
for dim in blob_parallel_desc_symbol.hierarchy:
hierarchy.add_dim(dim)
assert hierarchy.dim_size() > 0
parallel_conf.mutable_hierarchy().CopyFrom(hierarchy)
return builder.GetParallelDescSymbol(parallel_conf)
def ReplaceDeviceTag(parallel_desc_symbol, device_tag, builder=None):
assert parallel_desc_symbol.device_tag != device_tag
parallel_conf = placement_cfg.ParallelConf()
parallel_conf.set_device_tag(device_tag)
for device_name in parallel_desc_symbol.parallel_conf.device_name():
parallel_conf.add_device_name(device_name)
hierarchy = shape_proto_cfg.ShapeProto()
for dim in parallel_desc_symbol.hierarchy:
hierarchy.add_dim(dim)
assert hierarchy.dim_size() > 0
parallel_conf.mutable_hierarchy().CopyFrom(hierarchy)
if builder is None:
return oneflow_api.PlacementSymbol(parallel_desc_symbol.symbol_id,
parallel_conf)
else:
return builder.GetParallelDescSymbol(parallel_conf)
def Attr(self, attr_name, attr_value, attr_type_name=None):
r"""Set value of op's attribute.
Args:
attr_name (str): attribute name of op
attr_value (Any): attribute value of op
Raises:
ValueError: raised when value is not idential to op's attribute type.
Returns:
[type]: [description]
"""
if attr_type_name is not None:
print(
"""WARNING: Argument 'attr_type_name' of UserOpConfBuilder.Attr has been deprecated. Please remove it.
For instance:
- .Attr("out_num", out_num, "AttrTypeInt64")
+ .Attr("out_num", out_num)
"""
)
print(traceback.format_stack()[-2])
attribute = user_op_attr_cfg.AttrValue()
assert isinstance(attr_name, str)
assert self._op_type_name is not None
attr_type = oneflow_api.GetUserOpAttrType(self._op_type_name, attr_name)
if attr_type == user_op_attr_cfg.kAtInt32:
assert isinstance(attr_value, int)
attribute.set_at_int32(attr_value)
elif attr_type == user_op_attr_cfg.kAtInt64:
assert isinstance(attr_value, int)
attribute.set_at_int64(attr_value)
elif attr_type == user_op_attr_cfg.kAtBool:
assert isinstance(attr_value, bool)
attribute.set_at_bool(attr_value)
elif attr_type == user_op_attr_cfg.kAtFloat:
assert isinstance(attr_value, (float, int))
attribute.set_at_float(attr_value)
elif attr_type == user_op_attr_cfg.kAtDouble:
assert isinstance(attr_value, (float, int))
attribute.set_at_double(attr_value)
elif attr_type == user_op_attr_cfg.kAtString:
assert isinstance(attr_value, str)
attribute.set_at_string(attr_value)
elif attr_type == user_op_attr_cfg.kAtShape:
assert isinstance(attr_value, (tuple, list))
attribute_mutable_at_shape = attribute.mutable_at_shape()
for x in attr_value:
assert isinstance(x, int)
attribute_mutable_at_shape.add_dim(x)
elif attr_type == user_op_attr_cfg.kAtDataType:
assert attr_value in oneflow.dtypes()
attr_value = oneflow_api.deprecated.GetProtoDtype4OfDtype(attr_value)
assert isinstance(attr_value, int)
attribute.set_at_data_type(data_type_cfg.DataType(attr_value))
elif attr_type == user_op_attr_cfg.kAtListInt32:
assert isinstance(attr_value, (tuple, list))
attribute_mutable_at_list_int32 = attribute.mutable_at_list_int32()
for x in attr_value:
assert isinstance(x, int)
attribute_mutable_at_list_int32.add_val(x)
elif attr_type == user_op_attr_cfg.kAtListInt64:
assert isinstance(attr_value, (tuple, list))
attribute_mutable_at_list_int64 = attribute.mutable_at_list_int64()
for x in attr_value:
assert isinstance(x, int)
attribute_mutable_at_list_int64.add_val(x)
elif attr_type == user_op_attr_cfg.kAtListFloat:
assert isinstance(attr_value, (tuple, list))
attribute_mutable_at_list_float = attribute.mutable_at_list_float()
for x in attr_value:
assert isinstance(x, (float, int))
attribute_mutable_at_list_float.add_val(x)
elif attr_type == user_op_attr_cfg.kAtListDataType:
assert isinstance(attr_value, (tuple, list))
attribute_mutable_at_list_data_type = attribute.mutable_at_list_data_type()
for x in attr_value:
assert x in oneflow.dtypes()
x = oneflow_api.deprecated.GetProtoDtype4OfDtype(x)
assert isinstance(x, int)
attribute_mutable_at_list_data_type.add_val(data_type_cfg.DataType(x))
elif attr_type == user_op_attr_cfg.kAtListShape:
assert isinstance(attr_value, (tuple, list))
attribute_mutable_at_list_shape = (
attribute.mutable_at_list_shape().mutable_val()
)
for x in attr_value:
assert isinstance(x, (tuple, list))
shape = shape_cfg.ShapeProto()
for dim in x:
assert isinstance(dim, int)
shape.add_dim(dim)
attribute_mutable_at_list_shape.Add().CopyFrom(shape)
elif attr_type == user_op_attr_cfg.kAtListString:
assert isinstance(attr_value, (tuple, list))
attribute_mutable_at_list_string = attribute.mutable_at_list_string()
for x in attr_value:
assert isinstance(x, str)
attribute_mutable_at_list_string.add_val(x)
else:
raise ValueError("Invalid op attribute type {}".format(attr_type))
self._builder.attr(attr_name, attribute)
return self
def convert_to_user_attr_value(op_type_name, attr_name, attr_value):
attribute = user_op_attr_cfg.AttrValue()
assert isinstance(attr_name, str)
attr_type = oneflow_api.GetUserOpAttrType(op_type_name, attr_name)
if attr_type == user_op_attr_cfg.kAtInt32:
assert isinstance(attr_value, int)
attribute.set_at_int32(attr_value)
elif attr_type == user_op_attr_cfg.kAtInt64:
assert isinstance(attr_value, int)
attribute.set_at_int64(attr_value)
elif attr_type == user_op_attr_cfg.kAtBool:
assert isinstance(attr_value, bool)
attribute.set_at_bool(attr_value)
elif attr_type == user_op_attr_cfg.kAtFloat:
assert isinstance(attr_value, (float, int))
attribute.set_at_float(attr_value)
elif attr_type == user_op_attr_cfg.kAtDouble:
assert isinstance(attr_value, (float, int))
attribute.set_at_double(attr_value)
elif attr_type == user_op_attr_cfg.kAtString:
assert isinstance(attr_value, str)
attribute.set_at_string(attr_value)
elif attr_type == user_op_attr_cfg.kAtShape:
assert isinstance(attr_value, (tuple, list))
attribute_mutable_at_shape = attribute.mutable_at_shape()
for x in attr_value:
assert isinstance(x, int)
attribute_mutable_at_shape.add_dim(x)
elif attr_type == user_op_attr_cfg.kAtDataType:
assert attr_value in oneflow.dtypes()
attr_value = oneflow_api.deprecated.GetProtoDtype4OfDtype(attr_value)
assert isinstance(attr_value, int)
attribute.set_at_data_type(data_type_cfg.DataType(attr_value))
elif attr_type == user_op_attr_cfg.kAtListInt32:
assert isinstance(attr_value, (tuple, list))
attribute_mutable_at_list_int32 = attribute.mutable_at_list_int32()
for x in attr_value:
assert isinstance(x, int)
attribute_mutable_at_list_int32.add_val(x)
elif attr_type == user_op_attr_cfg.kAtListInt64:
assert isinstance(attr_value, (tuple, list))
attribute_mutable_at_list_int64 = attribute.mutable_at_list_int64()
for x in attr_value:
assert isinstance(x, int)
attribute_mutable_at_list_int64.add_val(x)
elif attr_type == user_op_attr_cfg.kAtListFloat:
assert isinstance(attr_value, (tuple, list))
attribute_mutable_at_list_float = attribute.mutable_at_list_float()
for x in attr_value:
assert isinstance(x, (float, int))
attribute_mutable_at_list_float.add_val(x)
elif attr_type == user_op_attr_cfg.kAtListDataType:
assert isinstance(attr_value, (tuple, list))
attribute_mutable_at_list_data_type = attribute.mutable_at_list_data_type()
for x in attr_value:
assert x in oneflow.dtypes()
x = oneflow_api.deprecated.GetProtoDtype4OfDtype(x)
assert isinstance(x, int)
attribute_mutable_at_list_data_type.add_val(data_type_cfg.DataType(x))
elif attr_type == user_op_attr_cfg.kAtListShape:
assert isinstance(attr_value, (tuple, list))
attribute_mutable_at_list_shape = (
attribute.mutable_at_list_shape().mutable_val()
)
for x in attr_value:
assert isinstance(x, (tuple, list))
shape = shape_cfg.ShapeProto()
for dim in x:
assert isinstance(dim, int)
shape.add_dim(dim)
attribute_mutable_at_list_shape.Add().CopyFrom(shape)
elif attr_type == user_op_attr_cfg.kAtListString:
assert isinstance(attr_value, (tuple, list))
attribute_mutable_at_list_string = attribute.mutable_at_list_string()
for x in attr_value:
assert isinstance(x, str)
attribute_mutable_at_list_string.add_val(x)
else:
raise ValueError("Invalid op attribute type {}".format(attr_type))
return attribute
