tensorflow::Tensor::tensor()

TTypes< T, NDIMS >::ConstTensor tensorflow::Tensor::tensor() const

tensorflow::Tensor::tensor()

TTypes< T, NDIMS >::Tensor tensorflow::Tensor::tensor()

tensorflow::Tensor::~Tensor()

tensorflow::Tensor::Tensor() Creates a 1-dimensional, 0-element float tensor. The returned Tensor is not a scalar (shape {}), but is instead an empty one-dimensional Tensor (shape {0}, NumElements() == 0). Since it has no elements, it does not need to be assigned a value and is initialized by default ( IsInitialized() is true). If this is undesirable, consider creating a one-element scalar which does require initialization:

tensorflow::Tensor::SummarizeValue()

string tensorflow::Tensor::SummarizeValue(int64 max_entries) const Render the first max_entries values in *this into a string.

tensorflow::Tensor::Slice()

Tensor tensorflow::Tensor::Slice(int64 dim0_start, int64 dim0_limit) const Slice this tensor along the 1st dimension. I.e., the returned tensor satisfies returned[i, ...] == this[dim0_start + i, ...]. The returned tensor shares the underlying tensor buffer with this tensor. NOTE: The returned tensor may not satisfies the same alignment requirement as this tensor depending on the shape. The caller must check the returned tensor's alignment before calling certain methods that have alignment requ

tensorflow::Tensor::SharesBufferWith()

bool tensorflow::Tensor::SharesBufferWith(const Tensor &b) const

tensorflow::Tensor::shaped()

TTypes< T, NDIMS >::ConstTensor tensorflow::Tensor::shaped(gtl::ArraySlice< int64 > new_sizes) const

tensorflow::Tensor::shaped()

TTypes< T, NDIMS >::Tensor tensorflow::Tensor::shaped(gtl::ArraySlice< int64 > new_sizes)

tensorflow::Tensor::shape()

const TensorShape& tensorflow::Tensor::shape() const Returns the shape of the tensor.

tensorflow::Tensor::scalar()

TTypes< T >::ConstScalar tensorflow::Tensor::scalar() const