Intel® oneAPI Deep Neural Network Developer Guide and Reference
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Compiled Partition
Overview
A compiled partition represents the generated kernels specialized for a partition on a target hardware (engine) with input and output information specified by the logical tensors. More…
// typedefs
typedef struct dnnl_graph_compiled_partition* dnnl_graph_compiled_partition_t;
typedef const struct dnnl_graph_compiled_partition* const_dnnl_graph_compiled_partition_t;
// structs
struct dnnl_graph_inplace_pair_t;
// classes
class dnnl::graph::compiled_partition;
// global functions
dnnl_status_t DNNL_API dnnl_graph_compiled_partition_create(
dnnl_graph_compiled_partition_t* compiled_partition,
dnnl_graph_partition_t partition
);
dnnl_status_t DNNL_API dnnl_graph_compiled_partition_execute(
const_dnnl_graph_compiled_partition_t compiled_partition,
dnnl_stream_t stream,
size_t num_inputs,
const_dnnl_graph_tensor_t* inputs,
size_t num_outputs,
const_dnnl_graph_tensor_t* outputs
);
dnnl_status_t DNNL_API dnnl_graph_compiled_partition_destroy(dnnl_graph_compiled_partition_t compiled_partition);
dnnl_status_t DNNL_API dnnl_graph_compiled_partition_query_logical_tensor(
const_dnnl_graph_compiled_partition_t compiled_partition,
size_t tid,
dnnl_graph_logical_tensor_t* lt
);
dnnl_status_t DNNL_API dnnl_graph_compiled_partition_get_inplace_ports(
const_dnnl_graph_compiled_partition_t compiled_partition,
size_t* num_inplace_pairs,
const dnnl_graph_inplace_pair_t** inplace_pairs
);Detailed Documentation
A compiled partition represents the generated kernels specialized for a partition on a target hardware (engine) with input and output information specified by the logical tensors.
Typedefs
typedef struct dnnl_graph_compiled_partition* dnnl_graph_compiled_partition_tA compiled partition handle.
typedef const struct dnnl_graph_compiled_partition* const_dnnl_graph_compiled_partition_tA constant compiled partition handle.
Global Functions
dnnl_status_t DNNL_API dnnl_graph_compiled_partition_create(
dnnl_graph_compiled_partition_t* compiled_partition,
dnnl_graph_partition_t partition
)Creates a new compiled partition handle.
Parameters:
compiled_partition |
The handle of output compiled partition. |
partition |
The handle of input partition. |
Returns:
dnnl_success on success or a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_graph_compiled_partition_execute(
const_dnnl_graph_compiled_partition_t compiled_partition,
dnnl_stream_t stream,
size_t num_inputs,
const_dnnl_graph_tensor_t* inputs,
size_t num_outputs,
const_dnnl_graph_tensor_t* outputs
)Executes a compiled partition.
Parameters:
compiled_partition |
The handle of target compiled partition. |
stream |
The stream used for execution. |
num_inputs |
The number of input tensors. |
inputs |
A list of input tensors. |
num_outputs |
The number of output tensors. |
outputs |
A non-empty list of output tensors. |
Returns:
dnnl_success on success or a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_graph_compiled_partition_destroy(dnnl_graph_compiled_partition_t compiled_partition)Destroys a compiled partition.
Parameters:
compiled_partition |
The compiled partition to be destroyed. |
Returns:
dnnl_success on success or a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_graph_compiled_partition_query_logical_tensor(
const_dnnl_graph_compiled_partition_t compiled_partition,
size_t tid,
dnnl_graph_logical_tensor_t* lt
)Queries an input or output logical tensor according to tensor ID.
If the tensor ID doesn’t belong to any input or output of the compiled partition, an error status dnnl_invalid_arguments will be returned by the API.
Parameters:
compiled_partition |
The handle of target compiled_partition. |
tid |
The unique id of required tensor. |
lt |
The output logical tensor. |
Returns:
dnnl_success on success or a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_graph_compiled_partition_get_inplace_ports(
const_dnnl_graph_compiled_partition_t compiled_partition,
size_t* num_inplace_pairs,
const dnnl_graph_inplace_pair_t** inplace_pairs
)Returns the hint of in-place pairs from a compiled partition.
It indicates that an input and an output of the partition can share the same memory buffer for computation. In-place computation helps to reduce the memory footprint and improves cache locality. But since the library may not have a global view of user’s application, it’s possible that the tensor with input_id is used at other places in user’s computation graph. In this case, the user should take the in-place pair as a hint and pass a different memory buffer for output tensor to avoid overwriting the input memory buffer which will probably cause unexpected incorrect results.
Parameters:
compiled_partition |
The handle of target compiled_partition. |
num_inplace_pairs |
The number of in-place pairs. |
inplace_pairs |
The handle of in-place pairs. |
Returns:
dnnl_success on success or a status describing the error otherwise.