TfLiteTensor
#include <common.h>
A tensor in the interpreter system which is a wrapper around a buffer of data including a dimensionality (or NULL if not currently defined).
Summary
Public attributes |
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allocation
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const void *
An opaque pointer to a tflite::MMapAllocation.
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allocation_type
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TfLiteAllocationType
How memory is mapped kTfLiteMmapRo: Memory mapped read only.
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buffer_handle
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TfLiteBufferHandle
An integer buffer handle that can be handled by
delegate. |
bytes
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size_t
The number of bytes required to store the data of this Tensor.
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data
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A union of data pointers.
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data_is_stale
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bool
If the delegate uses its own buffer (e.g.
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delegate
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struct TfLiteDelegate *
The delegate which knows how to handle
buffer_handle. |
dims
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A pointer to a structure representing the dimensionality interpretation that the buffer should have.
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dims_signature
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const TfLiteIntArray *
Optional.
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is_variable
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bool
True if the tensor is a variable.
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name
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const char *
Null-terminated name of this tensor.
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params
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Quantization information.
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quantization
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Quantization information. Replaces params field above.
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sparsity
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Parameters used to encode a sparse tensor.
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type
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TfLiteType
The data type specification for data stored in
data. |
Public attributes
allocation
const void * TfLiteTensor::allocation
An opaque pointer to a tflite::MMapAllocation.
allocation_type
TfLiteAllocationType TfLiteTensor::allocation_type
How memory is mapped kTfLiteMmapRo: Memory mapped read only.
i.e. weights kTfLiteArenaRw: Arena allocated read write memory (i.e. temporaries, outputs).
buffer_handle
TfLiteBufferHandle TfLiteTensor::buffer_handle
An integer buffer handle that can be handled by delegate.
The value is valid only when delegate is not null.
WARNING: This is an experimental interface that is subject to change.
bytes
size_t TfLiteTensor::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.
data
TfLitePtrUnion TfLiteTensor::data
A union of data pointers.
The appropriate type should be used for a typed tensor based on type.
data_is_stale
bool TfLiteTensor::data_is_stale
If the delegate uses its own buffer (e.g.
GPU memory), the delegate is responsible to set data_is_stale to true. delegate->CopyFromBufferHandle can be called to copy the data from delegate buffer.
WARNING: This is an experimental interface that is subject to change.
delegate
struct TfLiteDelegate * TfLiteTensor::delegate
The delegate which knows how to handle buffer_handle.
WARNING: This is an experimental interface that is subject to change.
dims
TfLiteIntArray * TfLiteTensor::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.
dims_signature
const TfLiteIntArray * TfLiteTensor::dims_signature
Optional.
Encodes shapes with unknown dimensions with -1. This field is only populated when unknown dimensions exist in a read-write tensor (i.e. an input or output tensor). (e.g. dims contains [1, 1, 1, 3] and dims_signature contains [1, -1, -1, 3]). If no unknown dimensions exist then dims_signature is either null, or set to an empty array. Note that this field only exists when TF_LITE_STATIC_MEMORY is not defined.
is_variable
bool TfLiteTensor::is_variable
True if the tensor is a variable.
name
const char * TfLiteTensor::name
Null-terminated name of this tensor.
quantization
TfLiteQuantization TfLiteTensor::quantization
Quantization information. Replaces params field above.
sparsity
TfLiteSparsity * TfLiteTensor::sparsity
Parameters used to encode a sparse tensor.
This is optional. The field is NULL if a tensor is dense.
WARNING: This is an experimental interface that is subject to change.
type
TfLiteType TfLiteTensor::type
The data type specification for data stored in data.
This affects what member of data union should be used.