TfLiteTensor

Tensor data, dimensions, quantization and allocation metadata for static-memory builds.

struct TfLiteTensor

A tensor in the interpreter system which is a wrapper around a buffer of data including a dimensionality (or NULL if not currently defined). NOTE: This flag is opt-in only at compile time.

Specific reduced TfLiteTensor struct for TF Micro runtime. This struct contains only the minimum fields required to initialize and prepare a micro inference graph. The fields in this struct have been ordered from largest-to-smallest for optimal struct sizeof.

This struct does not use:

allocation
buffer_handle
data_is_stale
delegate
dims_signature
name
sparsity

TfLiteQuantization quantization

TODO(b/155784997): Consider consolidating these quantization fields: Quantization information. Replaces params field above.

TfLiteQuantizationParams params

Quantization information.

TfLitePtrUnion data

A union of data pointers. The appropriate type should be used for a typed tensor based on type.

TfLiteIntArray * dims

A pointer to a structure representing the dimensionality interpretation that the buffer should have. NOTE: the product of elements of dims and the element datatype size should be equal to bytes below.

size_t bytes

The number of bytes required to store the data of this Tensor. I.e. (bytes of each element) * dims[0] * … * dims[n-1]. For example, if type is kTfLiteFloat32 and dims = {3, 2} then bytes = sizeof(float) * 3 * 2 = 4 * 3 * 2 = 24.

TfLiteType type

The data type specification for data stored in data. This affects what member of data union should be used.

TfLiteAllocationType allocation_type

How memory is mapped kTfLiteMmapRo: Memory mapped read only. i.e. weights kTfLiteArenaRw: Arena allocated read write memory (i.e. temporaries, outputs).

bool is_variable

True if the tensor is a variable.