Tensor

Preview 0.4.0

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#include "modular/c/tensor.h"

Functions

M_TensorSpec *M_newTensorSpec(const int64_t *shape, size_t rankSize, M_Dtype dtype, const char *tensorName)

Creates a tensor specification.

You need this before you set the input tensors with M_borrowTensorInto().

When storing tensor data in memory, we always use a diminishing stride size. That is, earlier dimensions in the shape have larger strides than later dimensions. For example, a C array declared as int arr[1][2][3] would have a shape specified as {1, 2, 3}.

Parameters:

  • shape – The shape of the tensor.

  • rankSize – The rank size of the tensor.

  • dtype – The datatype for the tensor.

  • tensorName – The name for the tensor. This string gets copied as part of the operation of M_newTensorSpec, so your original string need not remain valid after the completion of this call.

Returns:

A pointer to the tensor spec. You are responsible for the memory associated with the pointer returned. The memory can be deallocated by calling M_freeTensorSpec().

int64_t M_getDimAt(const M_TensorSpec *spec, size_t axis)

Gets the element at a particular axis.

Parameters:

  • spec – The tensor spec.

  • axis – The requested axis

Returns:

The dimension at requested axis if the spec and axis are valid. Otherwise, 0. A dimension of -1 indicates dynamic dimension e.g. batch-size of a model expecting a batched tensor.

size_t M_getRank(const M_TensorSpec *spec)

Gets the rank from the tensor spec.

Parameters:

spec – The tensor spec.

Returns:

The number of dimensions in the tensor spec if the spec is valid. Otherwise, 0.

M_Dtype M_getDtype(const M_TensorSpec *spec)

Gets the datatype from the tensor spec.

Parameters:

spec – The tensor spec.

Returns:

The element type from the tensor spec if the tensor spec is valid. Otherwise, M_UNKNOWN.

const char *M_getName(M_TensorSpec *spec)

Gets the name of the tensor from the tensor spec.

Parameters:

spec – The tensor spec.

Returns:

A null-terminated string containing the name of the tensor if the spec is valid. Otherwise, NULL. The memory associated with the returned string is owned by spec.

M_AsyncTensorMap *M_newAsyncTensorMap(const M_RuntimeContext *context)

Creates a map of tensor names to async tensors.

Parameters:

  • context – The runtime context.

  • size – The size of the collection.

Returns:

A pointer to the tensor map. You are responsible for the memory associated with the pointer returned. The memory can be deallocated by calling M_freeAsyncTensorMap().

size_t M_getTensorMapSize(const M_AsyncTensorMap *tensorMap, M_Status *status)

Gets the size of the tensor map.

Parameters:

  • tensorMap – The tensor map.

  • status – The status object for reporting errors.

Returns:

The size of the tensor map if the tensor map is valid. Otherwise, 0 and the status parameter contains an error message.

void M_borrowTensorInto(M_AsyncTensorMap *tensors, const void *input, const M_TensorSpec *tensorSpec, M_Status *status)

Adds a tensor to the tensor map.

You are responsible for the lifetime of the input tensor data. Its data gets “borrowed” into the Tensor Map.

Parameters:

  • tensors – The tensor map, from M_newAsyncTensorMap().

  • input – The input tensor data.

  • tensorSpec – The tensor spec, from M_newTensorSpec(). This gets copied as part of the operation of M_borrowTensorInto, so your original tensorSpec need not exist through the lifetime of the tensor map.

  • status – The status object for reporting errors.

M_AsyncTensor *M_getTensorByNameFrom(M_AsyncTensorMap *tensorMap, const char *name, M_Status *status)

Gets a tensor from the tensor map by name.

Parameters:

  • tensorMap – The tensor map.

  • tensorName – The name of the tensor

  • status – The status object for reporting errors.

Returns:

A pointer to the tensor. You are responsible for the memory associated with the pointer returned. The memory can be deallocated by calling M_freeTensor(). The held tensor inside the return value is simply borrowed from the corresponding input M_AsyncTensorMap. If the tensor map or name are invalid, a NULL pointer is returned and the status parameter contains an error message.

size_t M_getTensorNumElements(const M_AsyncTensor *tensor)

Gets the number of elements for the tensor.

Parameters:

tensor – The tensor which must not be NULL.

Returns:

The number of elements for the given tensor.

M_Dtype M_getTensorType(const M_AsyncTensor *tensor)

Gets the corresponding M_Dtype for the tensor.

Parameters:

tensor – The tensor which must not be NULL.

Returns:

The corresponding M_Dtype for the tensor.

const void *M_getTensorData(const M_AsyncTensor *tensor)

Gets a pointer to underlying data of the tensor.

Parameters:

tensor – The tensor which must not be NULL.

Returns:

A pointer to the underlying data of the tensor. This pointer is valid for the lifetime of the underlying tensor.

M_TensorSpec *M_getTensorSpec(const M_AsyncTensor *tensor)

Gets a Tensor Spec for the tensor.

Parameters:

tensor – The tensor.

Returns:

The tensor spec for the tensor if the tensor is valid. Otherwise, NULL.

void M_freeTensor(M_AsyncTensor *tensor)

Deallocates the memory for the tensor. No-op if tensor is NULL.

Parameters:

tensor – The tensor to deallocate.

void M_freeTensorNameArray(M_TensorNameArray *names)

Deallocates the memory for the array of tensor names. No-op if names is NULL.

Parameters:

names – The tensor names to deallocate.

void M_freeTensorSpec(M_TensorSpec *spec)

Deallocates the memory for the tensor spec. No-op if spec is NULL.

Parameters:

spec – The tensor spec to deallocate.

void M_freeAsyncTensorMap(M_AsyncTensorMap *tensorMap)

Deallocates the memory for the tensor map. No-op if tensorMap is NULL.

Parameters:

tensorMap – The tensor map to deallocate.