org.bytedeco.javacpp

Class tensorflow.Tensor

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.javacpp.helper.tensorflow.AbstractTensor

org.bytedeco.javacpp.tensorflow.Tensor

All Implemented Interfaces:

AutoCloseable, Indexable

Enclosing class:

tensorflow

@Namespace(value="tensorflow")
 @NoOffset
public static class tensorflow.Tensor
extends tensorflow.AbstractTensor

\ingroup core Represents an n-dimensional array of values.

Nested Class Summary

Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator

Field Summary

Fields inherited from class org.bytedeco.javacpp.Pointer

address, capacity, limit, position

Constructor Summary

Constructors

Constructor and Description
Tensor() \brief Creates a 1-dimensional, 0-element float tensor.
Tensor(int type) \brief Creates an empty Tensor of the given data type.
Tensor(int type, tensorflow.TensorShape shape) \brief Creates a Tensor of the given type and shape.
Tensor(int type, tensorflow.TensorShape shape, Pointer data)
Tensor(int type, tensorflow.TensorShape shape, tensorflow.TensorBuffer buf) \brief Move constructor.
Tensor(long size) Native array allocator.
Tensor(Pointer p) Pointer cast constructor.
Tensor(tensorflow.Allocator a, int type, tensorflow.TensorShape shape) \brief Creates a tensor with the input type and shape, using the allocator a to allocate the underlying buffer.
Tensor(tensorflow.Allocator a, int type, tensorflow.TensorShape shape, tensorflow.AllocationAttributes allocation_attr) \brief Creates a tensor with the input type and shape, using the allocator a and the specified "allocation_attr" to allocate the underlying buffer.
Tensor(tensorflow.Tensor other) Copy constructor.

Method Summary

Modifier and Type	Method and Description
long	AllocatedBytes()
void	AsProtoField(tensorflow.TensorProto proto) \brief Fills in proto with *this tensor's content.
void	AsProtoTensorContent(tensorflow.TensorProto proto)
boolean	CopyFrom(tensorflow.Tensor other, tensorflow.TensorShape shape) \brief Copy the other tensor into this tensor and reshape it.
BytePointer	DebugString() A human-readable summary of the tensor suitable for debugging.
long	dim_size(int d) Convenience accessor for the tensor shape.
int	dims() \brief Convenience accessor for the tensor shape.
int	dtype() Returns the data type.
void	FillDescription(tensorflow.TensorDescription description) Fill in the TensorDescription proto with metadata about the tensor that is useful for monitoring and debugging.
boolean	FromProto(tensorflow.Allocator a, tensorflow.TensorProto other)
boolean	FromProto(tensorflow.TensorProto other) \brief Parse other and construct the tensor.
boolean	IsAligned() Returns true iff this tensor is aligned.
boolean	IsInitialized() \brief If necessary, has this Tensor been initialized? Zero-element Tensors are always considered initialized, even if they have never been assigned to and do not have any memory allocated.
boolean	IsSameSize(tensorflow.Tensor b)
long	NumElements() Convenience accessor for the tensor shape.
tensorflow.Tensor	position(long position)
tensorflow.Tensor	put(tensorflow.Tensor other) Assign operator.
tensorflow.TensorShape	shape() Returns the shape of the tensor.
boolean	SharesBufferWith(tensorflow.Tensor b)
tensorflow.Tensor	Slice(long dim0_start, long dim0_limit) \brief Slice this tensor along the 1st dimension.
tensorflow.Tensor	SubSlice(long index) \brief Select a subslice from this tensor along the 1st dimension.
BytePointer	SummarizeValue(long max_entries)
BytePointer	SummarizeValue(long max_entries, boolean print_v2) Render the first max_entries values in *this into a string.
BytePointer	tensor_data() \brief Returns a StringPiece mapping the current tensor's buffer.
long	TotalBytes() Returns the estimated memory usage of this tensor.
void	UnsafeCopyFromInternal(tensorflow.Tensor arg0, int dtype, tensorflow.TensorShape arg2) Copy the other tensor into this tensor and reshape it and reinterpret the buffer's datatype.

Methods inherited from class org.bytedeco.javacpp.helper.tensorflow.AbstractTensor

create, create, create, create, create, create, create, createBuffer, createBuffer, createIndexer, createIndexer, createStringArray

Methods inherited from class org.bytedeco.javacpp.Pointer

address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, put, realloc, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

Tensor

public Tensor(Pointer p)

Pointer cast constructor. Invokes Pointer.Pointer(Pointer).

Tensor

public Tensor(long size)

Native array allocator. Access with Pointer.position(long).

Tensor

public Tensor()

\brief Creates a 1-dimensional, 0-element float tensor. The returned Tensor is not a scalar (shape {}), but is instead an empty one-dimensional Tensor (shape {0}, NumElements() == 0). Since it has no elements, it does not need to be assigned a value and is initialized by default (IsInitialized() is true). If this is undesirable, consider creating a one-element scalar which does require initialization:

 c++
 
      Tensor(DT_FLOAT, TensorShape({}))
 
  

Tensor

public Tensor(@Cast(value="tensorflow::DataType")
              int type,
              @Const @ByRef
              tensorflow.TensorShape shape)

\brief Creates a Tensor of the given type and shape. If LogMemory::IsEnabled() the allocation is logged as coming from an unknown kernel and step. Calling the Tensor constructor directly from within an Op is deprecated: use the OpKernelConstruction/OpKernelContext allocate_* methods to allocate a new tensor, which record the kernel and step. The underlying buffer is allocated using a CPUAllocator.

Tensor

public Tensor(tensorflow.Allocator a,
              @Cast(value="tensorflow::DataType")
              int type,
              @Const @ByRef
              tensorflow.TensorShape shape)

\brief Creates a tensor with the input type and shape, using the allocator a to allocate the underlying buffer. If LogMemory::IsEnabled() the allocation is logged as coming from an unknown kernel and step. Calling the Tensor constructor directly from within an Op is deprecated: use the OpKernelConstruction/OpKernelContext allocate_* methods to allocate a new tensor, which record the kernel and step. a must outlive the lifetime of this Tensor.

Tensor

public Tensor(tensorflow.Allocator a,
              @Cast(value="tensorflow::DataType")
              int type,
              @Const @ByRef
              tensorflow.TensorShape shape,
              @Const @ByRef
              tensorflow.AllocationAttributes allocation_attr)

\brief Creates a tensor with the input type and shape, using the allocator a and the specified "allocation_attr" to allocate the underlying buffer. If the kernel and step are known allocation_attr.allocation_will_be_logged should be set to true and LogMemory::RecordTensorAllocation should be called after the tensor is constructed. Calling the Tensor constructor directly from within an Op is deprecated: use the OpKernelConstruction/OpKernelContext allocate_* methods to allocate a new tensor, which record the kernel and step. a must outlive the lifetime of this Tensor.

Tensor

public Tensor(@Cast(value="tensorflow::DataType")
              int type)

\brief Creates an empty Tensor of the given data type. Like Tensor(), returns a 1-dimensional, 0-element Tensor with IsInitialized() returning True. See the Tensor() documentation for details.

Tensor

public Tensor(@Const @ByRef
              tensorflow.Tensor other)

Copy constructor.

Tensor

public Tensor(@Cast(value="tensorflow::DataType")
              int type,
              tensorflow.TensorShape shape,
              tensorflow.TensorBuffer buf)

\brief Move constructor. After this call, is safely destructible and can be assigned to, but other calls on it (e.g. shape manipulation) are not valid.

Tensor

public Tensor(@Cast(value="tensorflow::DataType")
              int type,
              tensorflow.TensorShape shape,
              Pointer data)

Method Detail

position

public tensorflow.Tensor position(long position)

Overrides:

position in class Pointer

dtype

@Cast(value="tensorflow::DataType")
public int dtype()

Returns the data type.

Specified by:

dtype in class tensorflow.AbstractTensor

shape

@Const
 @ByRef
public tensorflow.TensorShape shape()

Returns the shape of the tensor.

dims

public int dims()

\brief Convenience accessor for the tensor shape. For all shape accessors, see comments for relevant methods of TensorShape in tensor_shape.h.

Specified by:

dims in class tensorflow.AbstractTensor

dim_size

@Cast(value="tensorflow::int64")
public long dim_size(int d)

Convenience accessor for the tensor shape.

Specified by:

dim_size in class tensorflow.AbstractTensor

NumElements

@Cast(value="tensorflow::int64")
public long NumElements()

Convenience accessor for the tensor shape.

Specified by:

NumElements in class tensorflow.AbstractTensor

IsSameSize

@Cast(value="bool")
public boolean IsSameSize(@Const @ByRef
                                               tensorflow.Tensor b)

SharesBufferWith

@Cast(value="bool")
public boolean SharesBufferWith(@Const @ByRef
                                                     tensorflow.Tensor b)

IsInitialized

@Cast(value="bool")
public boolean IsInitialized()

\brief If necessary, has this Tensor been initialized? Zero-element Tensors are always considered initialized, even if they have never been assigned to and do not have any memory allocated.

TotalBytes

@Cast(value="size_t")
public long TotalBytes()

Returns the estimated memory usage of this tensor.

Specified by:

TotalBytes in class tensorflow.AbstractTensor

AllocatedBytes

@Cast(value="size_t")
public long AllocatedBytes()

IsAligned

@Cast(value="bool")
public boolean IsAligned()

Returns true iff this tensor is aligned.

put

@ByRef
 @Name(value="operator =")
public tensorflow.Tensor put(@Const @ByRef
                                                                 tensorflow.Tensor other)

Assign operator. This tensor shares other's underlying storage.

CopyFrom

@Cast(value="bool")
public boolean CopyFrom(@Const @ByRef
                                             tensorflow.Tensor other,
                                             @Const @ByRef
                                             tensorflow.TensorShape shape)

\brief Copy the other tensor into this tensor and reshape it. This tensor shares other's underlying storage. Returns true iff other.shape() has the same number of elements of the given shape.

Slice

@ByVal
public tensorflow.Tensor Slice(@Cast(value="tensorflow::int64")
                                       long dim0_start,
                                       @Cast(value="tensorflow::int64")
                                       long dim0_limit)

\brief Slice this tensor along the 1st dimension.

I.e., the returned tensor satisfies returned[i, ...] == this[dim0_start + i, ...]. The returned tensor shares the underlying tensor buffer with this tensor. NOTE: The returned tensor may not satisfy the same alignment requirement as this tensor depending on the shape. The caller must check the returned tensor's alignment before calling certain methods that have alignment requirement (e.g., flat(), tensor()). NOTE: When fed with an N-dimensional tensor, this method returns a tensor also with N dimensions. If you want to select a sub tensor, see SubSlice. REQUIRES: dims() >= 1 REQUIRES: 0 <= dim0_start <= dim0_limit <= dim_size(0)

SubSlice

@ByVal
public tensorflow.Tensor SubSlice(@Cast(value="tensorflow::int64")
                                          long index)

\brief Select a subslice from this tensor along the 1st dimension. When fed with an N-dimensional tensor, this method returns a tensor with N-1 dimensions, where the returned tensor is a subslice of the input tensor along the first dimension. The N-1 dimensions of the returned tensor are the last N-1 dimensions of the input tensor. NOTE: The returned tensor may not satisfy the same alignment requirement as this tensor depending on the shape. The caller must check the returned tensor's alignment before calling certain methods that have alignment requirement (e.g., flat(), tensor()). REQUIRES: dims() >= 1 REQUIRES: 0 <= dim0_start < dim_size(0)

FromProto

@Cast(value="bool")
public boolean FromProto(@Const @ByRef
                                              tensorflow.TensorProto other)

\brief Parse other and construct the tensor.

Returns true iff the parsing succeeds. If the parsing fails, the state of *this is unchanged.

FromProto

@Cast(value="bool")
public boolean FromProto(tensorflow.Allocator a,
                                              @Const @ByRef
                                              tensorflow.TensorProto other)

AsProtoField

public void AsProtoField(tensorflow.TensorProto proto)

\brief Fills in proto with *this tensor's content. AsProtoField() fills in the repeated field for proto.dtype(), while AsProtoTensorContent() encodes the content in proto.tensor_content() in a compact form.

AsProtoTensorContent

public void AsProtoTensorContent(tensorflow.TensorProto proto)

SummarizeValue

@StdString
public BytePointer SummarizeValue(@Cast(value="tensorflow::int64")
                                              long max_entries,
                                              @Cast(value="bool")
                                              boolean print_v2)

Render the first max_entries values in *this into a string.

SummarizeValue

@StdString
public BytePointer SummarizeValue(@Cast(value="tensorflow::int64")
                                              long max_entries)

DebugString

@StdString
public BytePointer DebugString()

A human-readable summary of the tensor suitable for debugging.

FillDescription

public void FillDescription(tensorflow.TensorDescription description)

Fill in the TensorDescription proto with metadata about the tensor that is useful for monitoring and debugging.

tensor_data

@tensorflow.StringPiece
public BytePointer tensor_data()

\brief Returns a StringPiece mapping the current tensor's buffer. The returned StringPiece may point to memory location on devices that the CPU cannot address directly. NOTE: The underlying tensor buffer is refcounted, so the lifetime of the contents mapped by the StringPiece matches the lifetime of the buffer; callers should arrange to make sure the buffer does not get destroyed while the StringPiece is still used. REQUIRES: DataTypeCanUseMemcpy(dtype()).

Specified by:

tensor_data in class tensorflow.AbstractTensor

UnsafeCopyFromInternal

public void UnsafeCopyFromInternal(@Const @ByRef
                                   tensorflow.Tensor arg0,
                                   @Cast(value="tensorflow::DataType")
                                   int dtype,
                                   @Const @ByRef
                                   tensorflow.TensorShape arg2)

Copy the other tensor into this tensor and reshape it and reinterpret the buffer's datatype. This tensor shares other's underlying storage.