@Properties(inherit=mkldnn.class) public class mkldnn_memory_desc_t extends Pointer
Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter
Constructor and Description |
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mkldnn_memory_desc_t()
Default native constructor.
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mkldnn_memory_desc_t(long size)
Native array allocator.
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mkldnn_memory_desc_t(Pointer p)
Pointer cast constructor.
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Modifier and Type | Method and Description |
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int |
data_type()
Data type of the tensor elements.
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mkldnn_memory_desc_t |
data_type(int setter) |
IntPointer |
dims()
Dimensions in the following order:
- CNN data tensors: mini-batch, channel, spatial
(
{N, C, [[D,] H,] W} )
- CNN weight tensors: group (optional), output channel, input channel,
spatial ({[G,] O, I, [[D,] H,] W} )
- RNN data tensors: time, mini-batch, channels ({T, N, C} )
or layers, directions, states, mini-batch, channels ({L, D, S, N, C} )
- RNN weight tensor: layers, directions, input channel, gates, output channels
({L, D, I, G, O} ). |
int |
format()
Memory format.
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mkldnn_memory_desc_t |
format(int setter) |
mkldnn_memory_desc_t |
getPointer(long i) |
mkldnn_blocking_desc_t |
layout_desc_blocking()
Description of the data layout for memory formats that use
blocking.
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mkldnn_memory_desc_t |
layout_desc_blocking(mkldnn_blocking_desc_t setter) |
mkldnn_rnn_packed_desc_t |
layout_desc_rnn_packed_desc()
Tensor of packed weights for RNN.
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mkldnn_memory_desc_t |
layout_desc_rnn_packed_desc(mkldnn_rnn_packed_desc_t setter) |
mkldnn_wino_desc_t |
layout_desc_wino_desc()
Tensor of weights for integer 8bit winograd convolution.
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mkldnn_memory_desc_t |
layout_desc_wino_desc(mkldnn_wino_desc_t setter) |
int |
ndims()
Number of dimensions
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mkldnn_memory_desc_t |
ndims(int setter) |
mkldnn_memory_desc_t |
position(long position) |
int |
primitive_kind()
The kind of primitive.
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mkldnn_memory_desc_t |
primitive_kind(int setter) |
address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, getDirectBufferAddress, getPointer, getPointer, getPointer, hashCode, interruptDeallocatorThread, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetAddress, offsetof, offsetof, parseBytes, physicalBytes, physicalBytesInaccurate, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, sizeof, toString, totalBytes, totalCount, totalPhysicalBytes, withDeallocator, zero
public mkldnn_memory_desc_t()
public mkldnn_memory_desc_t(long size)
Pointer.position(long)
.public mkldnn_memory_desc_t(Pointer p)
Pointer(Pointer)
.public mkldnn_memory_desc_t position(long position)
public mkldnn_memory_desc_t getPointer(long i)
getPointer
in class Pointer
@Cast(value="mkldnn_primitive_kind_t") public int primitive_kind()
public mkldnn_memory_desc_t primitive_kind(int setter)
public int ndims()
public mkldnn_memory_desc_t ndims(int setter)
@MemberGetter public IntPointer dims()
{N, C, [[D,] H,] W}
)
- CNN weight tensors: group (optional), output channel, input channel,
spatial ({[G,] O, I, [[D,] H,] W}
)
- RNN data tensors: time, mini-batch, channels ({T, N, C}
)
or layers, directions, states, mini-batch, channels ({L, D, S, N, C}
)
- RNN weight tensor: layers, directions, input channel, gates, output channels
({L, D, I, G, O}
).
\note
The order of dimensions does not depend on the memory format, so
whether the data is laid out in #mkldnn_nchw or #mkldnn_nhwc
the dims for 4D CN data tensor would be {N, C, H, W}
.@Cast(value="mkldnn_data_type_t") public int data_type()
public mkldnn_memory_desc_t data_type(int setter)
public mkldnn_memory_desc_t format(int setter)
@Name(value="layout_desc.blocking") @ByRef public mkldnn_blocking_desc_t layout_desc_blocking()
public mkldnn_memory_desc_t layout_desc_blocking(mkldnn_blocking_desc_t setter)
@Name(value="layout_desc.wino_desc") @ByRef public mkldnn_wino_desc_t layout_desc_wino_desc()
public mkldnn_memory_desc_t layout_desc_wino_desc(mkldnn_wino_desc_t setter)
@Name(value="layout_desc.rnn_packed_desc") @ByRef public mkldnn_rnn_packed_desc_t layout_desc_rnn_packed_desc()
public mkldnn_memory_desc_t layout_desc_rnn_packed_desc(mkldnn_rnn_packed_desc_t setter)
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