###Member Details
tensorflow::TensorShape::TensorShape(gtl::ArraySlice< int64 > dim_sizes) {#tensorflow_TensorShape_TensorShape}
Construct a TensorShape from the provided sizes. REQUIRES: dim_sizes[i] >= 0
tensorflow::TensorShape::TensorShape(std::initializer_list< int64 > dim_sizes) {#tensorflow_TensorShape_TensorShape}
tensorflow::TensorShape::TensorShape(const TensorShapeProto &proto) {#tensorflow_TensorShape_TensorShape}
REQUIRES: IsValid(proto)
Create a tensor shape with no dimensions and one element, which you can then call AddDim() on.
Copy the specified shape.
void tensorflow::TensorShape::operator=(const TensorShape &b) {#void_tensorflow_TensorShape_operator_}
Clear a tensor shape.
Add a dimension to the end ("inner-most"). REQUIRES: size >= 0
void tensorflow::TensorShape::AppendShape(const TensorShape &shape) {#void_tensorflow_TensorShape_AppendShape}
Appends all the dimensions from shape.
Insert a dimension somewhere in the TensorShape. REQUIRES: 0 <= d <= dims() REQUIRES: size >= 0
Modifies the size of the dimension d to be size REQUIRES: 0 <= d < dims() REQUIRES: size >= 0
Removes dimension d from the TensorShape. REQUIRES: 0 <= d < dims()
Return the number of dimensions in the tensor.
Returns the number of elements in dimension d. REQUIRES: 0 <= d < dims()
gtl::InlinedVector< int64, 4 > tensorflow::TensorShape::dim_sizes() const {#gtl_InlinedVector_int64_4_tensorflow_TensorShape_dim_sizes}
Returns sizes of all dimensions.
Returns the number of elements in the tensor.
We use int64 and not size_t to be compatible with Eigen::Tensor which uses ptrdiff_t.
bool tensorflow::TensorShape::IsSameSize(const TensorShape &b) const {#bool_tensorflow_TensorShape_IsSameSize}
Returns true if *this and b have the same sizes. Ignores dimension names.
bool tensorflow::TensorShape::operator==(const TensorShape &b) const {#bool_tensorflow_TensorShape_operator_}
bool tensorflow::TensorShape::operator!=(const TensorShape &b) const {#bool_tensorflow_TensorShape_operator_}
void tensorflow::TensorShape::AsProto(TensorShapeProto *proto) const {#void_tensorflow_TensorShape_AsProto}
Fill *proto from *this.
Eigen::DSizes< Eigen::DenseIndex, NDIMS > tensorflow::TensorShape::AsEigenDSizes() const {#Eigen_DSizes_Eigen_DenseIndex_NDIMS_tensorflow_TensorShape_AsEigenDSizes}
Fill *dsizes from *this.
Eigen::DSizes< Eigen::DenseIndex, NDIMS > tensorflow::TensorShape::AsEigenDSizesWithPadding() const {#Eigen_DSizes_Eigen_DenseIndex_NDIMS_tensorflow_TensorShape_AsEigenDSizesWithPadding}
Same as AsEigenDSizes() but allows for NDIMS > dims() in which case we pad the rest of the sizes with 1.
TensorShapeIter tensorflow::TensorShape::begin() const {#TensorShapeIter_tensorflow_TensorShape_begin}
For iterating through the dimensions.
For error messages.
bool tensorflow::TensorShape::IsValid(const TensorShapeProto &proto) {#bool_tensorflow_TensorShape_IsValid}
Returns true iff proto is a valid tensor shape.
Status tensorflow::TensorShape::IsValidShape(const TensorShapeProto &proto) {#Status_tensorflow_TensorShape_IsValidShape}
Returns OK iff proto is a valid tensor shape, and a descriptive error status otherwise.
static constexpr int tensorflow::TensorShape::MaxDimensions() {#static_constexpr_int_tensorflow_TensorShape_MaxDimensions}
string tensorflow::TensorShape::DebugString(const TensorShapeProto &proto) {#string_tensorflow_TensorShape_DebugString}
Same as TensorShape(proto). DebugString() but doesn't crash for invalid protos.