ExecuTorch Runtime API Reference

The ExecuTorch C++ API provides an on-device execution framework for exported PyTorch models.

For a tutorial style introduction to the runtime API, check out the runtime tutorial and its simplified version.

For detailed information on how APIs evolve and the deprecation process, please refer to the ExecuTorch API Life Cycle and Deprecation Policy.

Model Loading and Execution

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Values

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class Tensor

A minimal Tensor type whose API is a source compatible subset of at::Tensor.

NOTE: Instances of this class do not own the TensorImpl given to it, which means that the caller must guarantee that the TensorImpl lives longer than any Tensor instances that point to it.

See the documention on TensorImpl for details about the return/parameter types used here and how they relate to at::Tensor.

Public Types

using SizesType = TensorImpl::SizesType

The type used for elements of sizes().

using DimOrderType = TensorImpl::DimOrderType

The type used for elements of dim_order().

using StridesType = TensorImpl::StridesType

The type used for elements of strides().

Public Functions

inline TensorImpl *unsafeGetTensorImpl() const

Returns a pointer to the underlying TensorImpl.

NOTE: Clients should be wary of operating on the TensorImpl directly instead of the Tensor. It is easy to break things.

inline size_t nbytes() const

Returns the size of the tensor in bytes.

NOTE: Only the alive space is returned not the total capacity of the underlying data blob.

inline ssize_t size(ssize_t dim) const

Returns the size of the tensor at the given dimension.

NOTE: that size() intentionally does not return SizeType even though it returns an element of an array of SizeType. This is to help make calls of this method more compatible with at::Tensor, and more consistent with the rest of the methods on this class and in ETensor.

inline ssize_t dim() const

Returns the tensor’s number of dimensions.

inline ssize_t numel() const

Returns the number of elements in the tensor.

inline ScalarType scalar_type() const

Returns the type of the elements in the tensor (int32, float, bool, etc).

inline ssize_t element_size() const

Returns the size in bytes of one element of the tensor.

inline const ArrayRef<SizesType> sizes() const

Returns the sizes of the tensor at each dimension.

inline const ArrayRef<DimOrderType> dim_order() const

Returns the order the dimensions are laid out in memory.

inline const ArrayRef<StridesType> strides() const

Returns the strides of the tensor at each dimension.

inline TensorShapeDynamism shape_dynamism() const

Returns the mutability of the shape of the tensor.

template<typename T>
inline const T *const_data_ptr() const

Returns a pointer of type T to the constant underlying data blob.

inline const void *const_data_ptr() const

Returns a pointer to the constant underlying data blob.

template<typename T>
inline T *mutable_data_ptr() const

Returns a pointer of type T to the mutable underlying data blob.

inline void *mutable_data_ptr() const

Returns a pointer to the mutable underlying data blob.

template<typename T> inline ET_DEPRECATED T * data_ptr () const

DEPRECATED: Use const_data_ptr or mutable_data_ptr instead.

inline ET_DEPRECATED void * data_ptr () const

DEPRECATED: Use const_data_ptr or mutable_data_ptr instead.

inline ET_DEPRECATED void set_data (void *ptr) const

DEPRECATED: Changes the data_ptr the tensor aliases. Does not free the previously pointed to data, does not assume ownership semantics of the new ptr. This api does not exist in at::Tensor so kernel developers should avoid it.