TensorProto.DataType): 张量的数据类型。ONNX 定义了多种数据类型,比如 FLOAT (对应 Python 的 float32)、INT64、STRING 等。 shape (List[int] 或 None): 张量的形状。如果形状中的某个维度是未知的,可以用 None 或-1 来表示。 返回值 返回一个 ValueInfoProto 对象,该
data_type, # tensor内数据类型(TensorProto.dataType) dims, # tensor的shape(list of int) vals, # tensor的值 raw=False # 当为false时,该方法会根据data_type类型来存储vals,当为true时,该方法会使用raw_data来存储vals(在该方法中指的是bytes类型) -> 此处理解存疑(proto field ?) ): # type: (....
TensorProto 结构 message TensorProto { enum DataType { UNDEFINED = 0; FLOAT = 1; UINT8 = 2; INT8 = 3; UINT16 = 4; INT16 = 5; INT32 = 6; INT64 = 7; STRING = 8; BOOL = 9; FLOAT16 = 10; DOUBLE = 11; UINT32 = 12; UINT64 = 13; COMPLEX64 = 14; COMPLEX128 = 15;...
在GraphProto里面又包含了四个repeated数组,它们分别是node(NodeProto类型),input(ValueInfoProto类型),output(ValueInfoProto类型)和initializer(TensorProto类型),其中node中存放了模型中所有的计算节点,input存放了模型的输入节点,output存放了模型中所有的输出节点,initializer存放了模型的所有权重参数。 code 这里用python...
Variable(name: str, dtype: dtype | onnx.TensorProto.DataType = None, shape: Sequence[int | str] = None, type: str = 'tensor_type') Bases: Tensor Represents a Tensor whose value is not known until inference-time. Parameters: name (str)– The name of the tensor. dtype (Union[...
onnx.helper---tensor、tensor value info、attribute make_tensor [类型:TensorProto] make_tensor(name,data_type,dims,vals,raw=False) name:数据名字,要与该数据的信息tensor value info中名字对应 [类型:字符串] data_type:数据类型 [类型:TensorProto.DataType] 如TensorProto.FLOAT、TensorProto.UINT8、Ten...
inputTensor = node.inputs[0] gammaNode = node.o().o().o().o().o().o().o().o().o().o().o() index = [type(i) == gs.ir.tensor.ConstantforiingammaNode.inputs].index(True) gamma = np.array(deepcopy(gammaNode.inputs[index].values.tolist()), dtype=np.float32) ...
message(STATUS " version: ${Protobuf_VERSION}") message(STATUS " libraries: ${PROTOBUF_LIBRARIES}") message(STATUS " include path: ${PROTOBUF_INCLUDE_DIR}") else() message(WARNING "Protobuf not found, onnx model convert tool won't be built") ...
it can be a node of type "Conv" that takes in an image, a filter// tensor and a bias tensor, and produces the convolved output.// Node就是神经网络中的一个个操作结点,例如conv、reshape、relu等之类的操作message NodeProto{repeated string input=1;// namespace Valuerepeated string output=2;...
def make_tensor(name, # tensor名称(string)data_type, # tensor内数据类型(TensorProto.dataType)dims, # tensor的shape(list of int)vals, # tensor的值 raw=False # 当为false时，该⽅法会根据data_type类型来存储vals，当为true时，该⽅法会使⽤raw_data来存储vals(在该⽅法中指...