Specifies the data type of the values in a tensor. DirectML operators may not support all data types; see the documentation for each specific operator to find which data types it supports. Syntax C++ typedefenum
Tensor of data type int16. WINML_TENSOR_INT32 Tensor of data type int32. WINML_TENSOR_INT64 Tensor of data type int64. WINML_TENSOR_STRING Tensor of data type string. WINML_TENSOR_BOOLEAN Tensor of data type Boolean. WINML_TENSOR_FLOAT16 ...
Tensor(DataType type, const TensorShape& shape); /// \brief Creates a tensor with the input `type` and `shape`, using /// the allocator `a` to allocate the underlying buffer. If /// LogMemory::IsEnabled() the allocation is logged as coming from /// an unknown kernel and step. ...
print("Elements number along the last axis of tensor:", ndim_4_tensor.shape[-1]) Data Type of every element: VarType.FP32 Number of dimensions: 4 Shape of tensor: [2, 3, 4, 5] Elements number along axis 0 of tensor: 2 Elements number along the last axis of tensor: 5 对shape进...
dataType 是预期服务器返回的数据类型。如果不指定，jQuery 将自动根据 HTTP 包 MIME 信息来智能判断...
创建浮点数的方法默认(不设置dtype)情况下都是torch.float32(torch.FloatTensor),创建整形的方法默认是64(torch.LongTensor),这个需要特别注意!!不同类型的tensor不能作运算 size就是元组,可以通过tensor.size()得到,创建一维tensor最好写成(m, ),要是写m有些方法会报错* torch方法创建tensor主要分三类: 1.按照...
可以使用使用 torch.tensor() 方法将 python 的 list 或序列数据转换成 Tensor 数据,生成的是dtype默认是torch.FloatTensor。 注意torch.tensor()总是拷贝 data。如果你有一个 tensor data 并且仅仅想改变它的requires_grad属性,可用requires_grad_()或者detach()来避免拷贝。如果你有一个numpy数组并且想避免拷贝,请...
dtype--data type temp = torch.tensor( [data], dytpe= xxx) 可以指定tensor的元素的数据类型,一共有9种类型 device--存储tensor的设备 temp = torch.tensor( [data], devoce='cuda') 使用字符串表示tensor存储的设备,可以是'cpu'或者'cuda’
CheckTypeAndIsAligned(DataTypeToEnum<T>::v()); return typename TTypes<T, NDIMS>::Tensor(base<T>(), shape().AsEigenDSizes<NDIMS>()); } 由上述代码可见,调用tensor()是把TF Tensor转化成了TTypes<T,NDIMS>::Tensor,而后者本质上是Eigen::TensorMap。至此,我们搞清楚了TF Tensor与Eigen库的关系,...
POST /v2/models/mymodel/infer HTTP/1.1 Host: localhost:8000 Content-Type: application/octet-stream Inference-Header-Content-Length: <xx> Content-Length: <xx+19> { "model_name" : "mymodel", "inputs" : [ { "name" : "input0", "shape" : [ 2, 2 ], "datatype" : "UINT32...