tensor blob class that can be used to hold tensor of any dimension, any device and any data type, This is a weak type that can be used to transfer data through interface TBlob itself do not involve any arithmentic operations, but it can be converted to tensor of fixed dimension for further operations  
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|  | TBlob (void) | 
|  | storing mkl chunk buffer blob, use for experimental only  More... 
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| template<typename DType > | 
|  | TBlob (DType *dptr, const TShape &shape, int dev_mask, int dev_id=-1) | 
|  | constructor that construct TBlob from contiguous memory  More... 
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|  | TBlob (void *dptr, const TShape &shape, int dev_mask, int type_flag, int dev_id=-1) | 
|  | constructor that construct TBlob from contiguous memory  More... 
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| template<typename Device , int dim, typename DType > | 
|  | TBlob (const mshadow::Tensor< Device, dim, DType > &src) | 
|  | constructor from tensor  More... 
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| template<typename Device , int dim, typename DType > | 
| TBlob & | operator= (const mshadow::Tensor< Device, dim, DType > &src) | 
|  | assignment from tensor  More... 
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| bool | CheckContiguous (void) const | 
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| TBlob | reshape (const TShape &shape) const | 
|  | reshape to shape  More... 
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| template<typename Device , typename DType > | 
| mshadow::Tensor< Device, 2, DType > | FlatTo2D (mshadow::Stream< Device > *stream=NULL) const | 
|  | flatten the tensor to 2 dimension, collapse the higher dimensions together  More... 
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| template<typename Device , typename DType > | 
| mshadow::Tensor< Device, 1, DType > | FlatTo1D (mshadow::Stream< Device > *stream=NULL) const | 
|  | flatten the tensor to 1 dimension, collapse all the dimensions together.  More... 
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| int | ndim (void) const | 
|  | return number of dimension of the tensor inside  More... 
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| index_t | size (index_t idx) const | 
|  | return size of i-th dimension, start counting from highest dimension  More... 
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| index_t | Size (void) const | 
|  | total number of elements in the tensor  More... 
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| template<typename DType > | 
| DType * | dptr () const | 
|  | get pointer in dtype  More... 
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| int | dev_mask () const | 
|  | device mask of the corresponding device  More... 
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| int | dev_id () const | 
|  | device index of the corresponding device  More... 
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| const DLTensor & | dltensor () const | 
|  | return the corresponding DLTensor  More... 
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| template<typename Device , int dim, typename DType > | 
| mshadow::Tensor< Device, dim, DType > | get (mshadow::Stream< Device > *stream=NULL) const | 
|  | fetch the tensor, with respect to specific dimension if dim do not match the stored dimension, an error will be issued  More... 
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| template<typename Device , int dim, typename DType > | 
| mshadow::Tensor< Device, dim, DType > | get_with_shape (const mshadow::Shape< dim > &shape, mshadow::Stream< Device > *stream=NULL) const | 
|  | fetch a tensor in given shape If size do not match the stored size, an error will be issued  More... 
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| template<typename Device , typename DType > | 
| mshadow::Tensor< Device, 3, DType > | FlatTo3D (int axis, mshadow::Stream< Device > *stream=NULL) const | 
|  | flatten the tensor to 3 dimension, collapse the dimension before and after specified axis.  More... 
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| template<typename Device , typename DType > | 
| mshadow::Tensor< Device, 3, DType > | FlatTo3D (int axis_begin, int axis_end, mshadow::Stream< Device > *stream=NULL) const | 
|  | flatten the tensor to 3 dimension, collapse the dimension: [0, axis_begin), [axis_begin, axis_end], (axis_end, ndim).  More... 
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| template<typename Device , int dim, typename DType > | 
| mshadow::Tensor< Device, dim, DType > | FlatToKD (mshadow::Stream< Device > *stream=NULL) const | 
|  | flatten the tensor to specified number of dimensions, collapse the highest dimensions or pad with higher dimensions  More... 
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tensor blob class that can be used to hold tensor of any dimension, any device and any data type, This is a weak type that can be used to transfer data through interface TBlob itself do not involve any arithmentic operations, but it can be converted to tensor of fixed dimension for further operations 
Like tensor, this data structure is like a pointer class and do not implicit allocated, de-allocate space. This data structure can be helpful to hold tensors of different dimensions and wait for further processing