Intel® oneAPI Deep Neural Network Developer Guide and Reference
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Tensor
Overview
Tensor is an abstraction for multi-dimensional input and output data needed in the execution of a compiled partition. More…
// typedefs
typedef struct dnnl_graph_tensor* dnnl_graph_tensor_t;
typedef const struct dnnl_graph_tensor* const_dnnl_graph_tensor_t;
// classes
class dnnl::graph::tensor;
// global functions
dnnl_status_t DNNL_API dnnl_graph_tensor_create(
    dnnl_graph_tensor_t* tensor,
    const dnnl_graph_logical_tensor_t* logical_tensor,
    dnnl_engine_t engine,
    void* handle
    );
dnnl_status_t DNNL_API dnnl_graph_tensor_destroy(dnnl_graph_tensor_t tensor);
dnnl_status_t DNNL_API dnnl_graph_tensor_get_data_handle(
    const_dnnl_graph_tensor_t tensor,
    void** handle
    );
dnnl_status_t DNNL_API dnnl_graph_tensor_set_data_handle(
    dnnl_graph_tensor_t tensor,
    void* handle
    );
dnnl_status_t DNNL_API dnnl_graph_tensor_get_engine(
    const_dnnl_graph_tensor_t tensor,
    dnnl_engine_t* engine
    );Detailed Documentation
Tensor is an abstraction for multi-dimensional input and output data needed in the execution of a compiled partition.
A tensor object encapsulates a handle to a memory buffer allocated on a specific engine and a logical tensor which describes the dimensions, elements data type, and memory layout.
Typedefs
typedef struct dnnl_graph_tensor* dnnl_graph_tensor_tA tensor handle.
typedef const struct dnnl_graph_tensor* const_dnnl_graph_tensor_tA constant tensor handle.
Global Functions
dnnl_status_t DNNL_API dnnl_graph_tensor_create(
    dnnl_graph_tensor_t* tensor,
    const dnnl_graph_logical_tensor_t* logical_tensor,
    dnnl_engine_t engine,
    void* handle
    )Creates a tensor with logical tensor, engine, and data handle.
Parameters:
| tensor | Output tensor. | 
| logical_tensor | Description for this tensor. | 
| engine | Engine to use. | 
| handle | Handle of the memory buffer to use as an underlying storage. | 
Returns:
dnnl_success on success or a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_graph_tensor_destroy(dnnl_graph_tensor_t tensor)Destroys a tensor.
Parameters:
| tensor | The tensor to be destroyed. | 
Returns:
dnnl_success on success or a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_graph_tensor_get_data_handle(
    const_dnnl_graph_tensor_t tensor,
    void** handle
    )Gets the data handle of a tensor.
Parameters:
| tensor | The input tensor. | 
| handle | Pointer to the data of input tensor. | 
Returns:
dnnl_success on success or a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_graph_tensor_set_data_handle(
    dnnl_graph_tensor_t tensor,
    void* handle
    )Set data handle for a tensor.
Parameters:
| tensor | The input tensor. | 
| handle | New data handle for tensor. | 
Returns:
dnnl_success on success or a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_graph_tensor_get_engine(
    const_dnnl_graph_tensor_t tensor,
    dnnl_engine_t* engine
    )Returns the engine of a tensor object.
Parameters:
| tensor | The input tensor. | 
| engine | Output engine on which the tensor is located. | 
Returns:
dnnl_success on success or a status describing the error otherwise.