Tensor (pytorch_android 1.9.0 API)

java.lang.Object
- org.pytorch.Tensor

```
public abstract class Tensor
extends java.lang.Object
```
Representation of a Tensor. Behavior is similar to PyTorch's tensor objects.
Most tensors will be constructed as Tensor.fromBlob(data, shape), where data can be an array or a direct Buffer (of the proper subclass). Helper methods are provided to allocate buffers properly.
To access Tensor data, see dtype(), shape(), and various getDataAs* methods.
When constructing Tensor objects with data as an array, it is not specified whether this data is is copied or retained as a reference so it is recommended not to modify it after constructing. data passed as a Buffer is not copied, so it can be modified between Module calls to avoid reallocation. Data retrieved from Tensor objects may be copied or may be a reference to the Tensor's internal data buffer. shape is always copied.

Method Summary

All Methods Static Methods Instance Methods Abstract Methods Concrete Methods
Modifier and Type	Method and Description
`static java.nio.ByteBuffer`	`allocateByteBuffer(int numElements)` Allocates a new direct `ByteBuffer` with native byte order with specified capacity that can be used in `fromBlob(ByteBuffer, long[])`, `fromBlobUnsigned(ByteBuffer, long[])`.
`static java.nio.DoubleBuffer`	`allocateDoubleBuffer(int numElements)` Allocates a new direct `DoubleBuffer` with native byte order with specified capacity that can be used in `fromBlob(DoubleBuffer, long[])`.
`static java.nio.FloatBuffer`	`allocateFloatBuffer(int numElements)` Allocates a new direct `FloatBuffer` with native byte order with specified capacity that can be used in `fromBlob(FloatBuffer, long[])`.
`static java.nio.IntBuffer`	`allocateIntBuffer(int numElements)` Allocates a new direct `IntBuffer` with native byte order with specified capacity that can be used in `fromBlob(IntBuffer, long[])`.
`static java.nio.LongBuffer`	`allocateLongBuffer(int numElements)` Allocates a new direct `LongBuffer` with native byte order with specified capacity that can be used in `fromBlob(LongBuffer, long[])`.
`abstract DType`	`dtype()`
`static Tensor`	`fromBlob(byte[] data, long[] shape)`
`static Tensor`	`fromBlob(byte[] data, long[] shape, MemoryFormat memoryFormat)` Creates a new Tensor instance with dtype torch.int8 with specified shape and data as array of bytes.
`static Tensor`	`fromBlob(java.nio.ByteBuffer data, long[] shape)`
`static Tensor`	`fromBlob(java.nio.ByteBuffer data, long[] shape, MemoryFormat memoryFormat)` Creates a new Tensor instance with dtype torch.int8 with specified shape and data.
`static Tensor`	`fromBlob(double[] data, long[] shape)`
`static Tensor`	`fromBlob(double[] data, long[] shape, MemoryFormat memoryFormat)` Creates a new Tensor instance with dtype torch.float64 with specified shape and data as array of doubles.
`static Tensor`	`fromBlob(java.nio.DoubleBuffer data, long[] shape)`
`static Tensor`	`fromBlob(java.nio.DoubleBuffer data, long[] shape, MemoryFormat memoryFormat)` Creates a new Tensor instance with dtype torch.float64 with specified shape and data.
`static Tensor`	`fromBlob(float[] data, long[] shape)`
`static Tensor`	`fromBlob(float[] data, long[] shape, MemoryFormat memoryFormat)` Creates a new Tensor instance with dtype torch.float32 with specified shape and data as array of floats.
`static Tensor`	`fromBlob(java.nio.FloatBuffer data, long[] shape)`
`static Tensor`	`fromBlob(java.nio.FloatBuffer data, long[] shape, MemoryFormat memoryFormat)` Creates a new Tensor instance with dtype torch.float32 with specified shape and data.
`static Tensor`	`fromBlob(int[] data, long[] shape)`
`static Tensor`	`fromBlob(int[] data, long[] shape, MemoryFormat memoryFormat)` Creates a new Tensor instance with dtype torch.int32 with specified shape and data as array of ints.
`static Tensor`	`fromBlob(java.nio.IntBuffer data, long[] shape)`
`static Tensor`	`fromBlob(java.nio.IntBuffer data, long[] shape, MemoryFormat memoryFormat)` Creates a new Tensor instance with dtype torch.int32 with specified shape and data.
`static Tensor`	`fromBlob(long[] data, long[] shape)`
`static Tensor`	`fromBlob(long[] data, long[] shape, MemoryFormat memoryFormat)` Creates a new Tensor instance with dtype torch.int64 with specified shape and data as array of longs.
`static Tensor`	`fromBlob(java.nio.LongBuffer data, long[] shape)`
`static Tensor`	`fromBlob(java.nio.LongBuffer data, long[] shape, MemoryFormat memoryFormat)` Creates a new Tensor instance with dtype torch.int64 with specified shape and data.
`static Tensor`	`fromBlobUnsigned(byte[] data, long[] shape)`
`static Tensor`	`fromBlobUnsigned(byte[] data, long[] shape, MemoryFormat memoryFormat)` Creates a new Tensor instance with dtype torch.uint8 with specified shape and data as array of bytes.
`static Tensor`	`fromBlobUnsigned(java.nio.ByteBuffer data, long[] shape)`
`static Tensor`	`fromBlobUnsigned(java.nio.ByteBuffer data, long[] shape, MemoryFormat memoryFormat)` Creates a new Tensor instance with dtype torch.uint8 with specified shape and data.
`byte[]`	`getDataAsByteArray()`
`double[]`	`getDataAsDoubleArray()`
`float[]`	`getDataAsFloatArray()`
`int[]`	`getDataAsIntArray()`
`long[]`	`getDataAsLongArray()`
`byte[]`	`getDataAsUnsignedByteArray()`
`MemoryFormat`	`memoryFormat()` Returns the memory format of this tensor.
`long`	`numel()` Returns the number of elements in this tensor.
`static long`	`numel(long[] shape)` Calculates the number of elements in a tensor with the specified shape.
`long[]`	`shape()` Returns the shape of this tensor.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Method Detail
  - allocateByteBuffer
```
public static java.nio.ByteBuffer allocateByteBuffer(int numElements)
```
    Allocates a new direct ByteBuffer with native byte order with specified capacity that can be used in fromBlob(ByteBuffer, long[]), fromBlobUnsigned(ByteBuffer, long[]).
    
    Parameters:
    
    numElements - capacity (number of elements) of result buffer.
  - allocateIntBuffer
```
public static java.nio.IntBuffer allocateIntBuffer(int numElements)
```
    Allocates a new direct IntBuffer with native byte order with specified capacity that can be used in fromBlob(IntBuffer, long[]).
    
    Parameters:
    
    numElements - capacity (number of elements) of result buffer.
  - allocateFloatBuffer
```
public static java.nio.FloatBuffer allocateFloatBuffer(int numElements)
```
    Allocates a new direct FloatBuffer with native byte order with specified capacity that can be used in fromBlob(FloatBuffer, long[]).
    
    Parameters:
    
    numElements - capacity (number of elements) of result buffer.
  - allocateLongBuffer
```
public static java.nio.LongBuffer allocateLongBuffer(int numElements)
```
    Allocates a new direct LongBuffer with native byte order with specified capacity that can be used in fromBlob(LongBuffer, long[]).
    
    Parameters:
    
    numElements - capacity (number of elements) of result buffer.
  - allocateDoubleBuffer
```
public static java.nio.DoubleBuffer allocateDoubleBuffer(int numElements)
```
    Allocates a new direct DoubleBuffer with native byte order with specified capacity that can be used in fromBlob(DoubleBuffer, long[]).
    
    Parameters:
    
    numElements - capacity (number of elements) of result buffer.
  - fromBlobUnsigned
```
public static Tensor fromBlobUnsigned(byte[] data,
                                      long[] shape,
                                      MemoryFormat memoryFormat)
```
    Creates a new Tensor instance with dtype torch.uint8 with specified shape and data as array of bytes.
    
    Parameters:
    
    data - Tensor elements
    
    shape - Tensor shape
  - fromBlobUnsigned
```
public static Tensor fromBlobUnsigned(byte[] data,
                                      long[] shape)
```
  - fromBlob
```
public static Tensor fromBlob(byte[] data,
                              long[] shape,
                              MemoryFormat memoryFormat)
```
    Creates a new Tensor instance with dtype torch.int8 with specified shape and data as array of bytes.
    
    Parameters:
    
    data - Tensor elements
    
    shape - Tensor shape
  - fromBlob
```
public static Tensor fromBlob(byte[] data,
                              long[] shape)
```
  - fromBlob
```
public static Tensor fromBlob(int[] data,
                              long[] shape,
                              MemoryFormat memoryFormat)
```
    Creates a new Tensor instance with dtype torch.int32 with specified shape and data as array of ints.
    
    Parameters:
    
    data - Tensor elements
    
    shape - Tensor shape
  - fromBlob
```
public static Tensor fromBlob(int[] data,
                              long[] shape)
```
  - fromBlob
```
public static Tensor fromBlob(float[] data,
                              long[] shape,
                              MemoryFormat memoryFormat)
```
    Creates a new Tensor instance with dtype torch.float32 with specified shape and data as array of floats.
    
    Parameters:
    
    data - Tensor elements
    
    shape - Tensor shape
  - fromBlob
```
public static Tensor fromBlob(float[] data,
                              long[] shape)
```
  - fromBlob
```
public static Tensor fromBlob(long[] data,
                              long[] shape,
                              MemoryFormat memoryFormat)
```
    Creates a new Tensor instance with dtype torch.int64 with specified shape and data as array of longs.
    
    Parameters:
    
    data - Tensor elements
    
    shape - Tensor shape
  - fromBlob
```
public static Tensor fromBlob(long[] data,
                              long[] shape)
```
  - fromBlob
```
public static Tensor fromBlob(double[] data,
                              long[] shape,
                              MemoryFormat memoryFormat)
```
    Creates a new Tensor instance with dtype torch.float64 with specified shape and data as array of doubles.
    
    Parameters:
    
    shape - Tensor shape
    
    data - Tensor elements
  - fromBlob
```
public static Tensor fromBlob(double[] data,
                              long[] shape)
```
  - fromBlobUnsigned
```
public static Tensor fromBlobUnsigned(java.nio.ByteBuffer data,
                                      long[] shape,
                                      MemoryFormat memoryFormat)
```
    Creates a new Tensor instance with dtype torch.uint8 with specified shape and data.
    
    Parameters:
    
    data - Direct buffer with native byte order that contains Tensor.numel(shape) elements. The buffer is used directly without copying, and changes to its content will change the tensor.
    
    shape - Tensor shape
  - fromBlobUnsigned
```
public static Tensor fromBlobUnsigned(java.nio.ByteBuffer data,
                                      long[] shape)
```
  - fromBlob
```
public static Tensor fromBlob(java.nio.ByteBuffer data,
                              long[] shape,
                              MemoryFormat memoryFormat)
```
    Creates a new Tensor instance with dtype torch.int8 with specified shape and data.
    
    Parameters:
    
    data - Direct buffer with native byte order that contains Tensor.numel(shape) elements. The buffer is used directly without copying, and changes to its content will change the tensor.
    
    shape - Tensor shape
  - fromBlob
```
public static Tensor fromBlob(java.nio.ByteBuffer data,
                              long[] shape)
```
  - fromBlob
```
public static Tensor fromBlob(java.nio.IntBuffer data,
                              long[] shape,
                              MemoryFormat memoryFormat)
```
    Creates a new Tensor instance with dtype torch.int32 with specified shape and data.
    
    Parameters:
    
    data - Direct buffer with native byte order that contains Tensor.numel(shape) elements. The buffer is used directly without copying, and changes to its content will change the tensor.
    
    shape - Tensor shape
  - fromBlob
```
public static Tensor fromBlob(java.nio.IntBuffer data,
                              long[] shape)
```
  - fromBlob
```
public static Tensor fromBlob(java.nio.FloatBuffer data,
                              long[] shape,
                              MemoryFormat memoryFormat)
```
    Creates a new Tensor instance with dtype torch.float32 with specified shape and data.
    
    Parameters:
    
    data - Direct buffer with native byte order that contains Tensor.numel(shape) elements. The buffer is used directly without copying, and changes to its content will change the tensor.
    
    shape - Tensor shape
  - fromBlob
```
public static Tensor fromBlob(java.nio.FloatBuffer data,
                              long[] shape)
```
  - fromBlob
```
public static Tensor fromBlob(java.nio.LongBuffer data,
                              long[] shape,
                              MemoryFormat memoryFormat)
```
    Creates a new Tensor instance with dtype torch.int64 with specified shape and data.
    
    Parameters:
    
    data - Direct buffer with native byte order that contains Tensor.numel(shape) elements. The buffer is used directly without copying, and changes to its content will change the tensor.
    
    shape - Tensor shape
  - fromBlob
```
public static Tensor fromBlob(java.nio.LongBuffer data,
                              long[] shape)
```
  - fromBlob
```
public static Tensor fromBlob(java.nio.DoubleBuffer data,
                              long[] shape,
                              MemoryFormat memoryFormat)
```
    Creates a new Tensor instance with dtype torch.float64 with specified shape and data.
    
    Parameters:
    
    data - Direct buffer with native byte order that contains Tensor.numel(shape) elements. The buffer is used directly without copying, and changes to its content will change the tensor.
    
    shape - Tensor shape
  - fromBlob
```
public static Tensor fromBlob(java.nio.DoubleBuffer data,
                              long[] shape)
```
  - numel
```
public long numel()
```
    Returns the number of elements in this tensor.
  - numel
```
public static long numel(long[] shape)
```
    Calculates the number of elements in a tensor with the specified shape.
  - shape
```
public long[] shape()
```
    Returns the shape of this tensor. (The array is a fresh copy.)
  - memoryFormat
```
public MemoryFormat memoryFormat()
```
    Returns the memory format of this tensor.
  - dtype
```
public abstract DType dtype()
```
    Returns:
    
    data type of this tensor.
  - getDataAsByteArray
```
public byte[] getDataAsByteArray()
```
    Returns:
    
    a Java byte array that contains the tensor data. This may be a copy or reference.
    
    Throws:
    
    java.lang.IllegalStateException - if it is called for a non-int8 tensor.
  - getDataAsUnsignedByteArray
```
public byte[] getDataAsUnsignedByteArray()
```
    Returns:
    
    a Java byte array that contains the tensor data. This may be a copy or reference.
    
    Throws:
    
    java.lang.IllegalStateException - if it is called for a non-uint8 tensor.
  - getDataAsIntArray
```
public int[] getDataAsIntArray()
```
    Returns:
    
    a Java int array that contains the tensor data. This may be a copy or reference.
    
    Throws:
    
    java.lang.IllegalStateException - if it is called for a non-int32 tensor.
  - getDataAsFloatArray
```
public float[] getDataAsFloatArray()
```
    Returns:
    
    a Java float array that contains the tensor data. This may be a copy or reference.
    
    Throws:
    
    java.lang.IllegalStateException - if it is called for a non-float32 tensor.
  - getDataAsLongArray
```
public long[] getDataAsLongArray()
```
    Returns:
    
    a Java long array that contains the tensor data. This may be a copy or reference.
    
    Throws:
    
    java.lang.IllegalStateException - if it is called for a non-int64 tensor.
  - getDataAsDoubleArray
```
public double[] getDataAsDoubleArray()
```
    Returns:
    
    a Java double array that contains the tensor data. This may be a copy or reference.
    
    Throws:
    
    java.lang.IllegalStateException - if it is called for a non-float64 tensor.

Class Tensor

Method Summary

Methods inherited from class java.lang.Object

Method Detail

allocateByteBuffer

allocateIntBuffer

allocateFloatBuffer

allocateLongBuffer

allocateDoubleBuffer

fromBlobUnsigned

fromBlobUnsigned

fromBlob

fromBlob

fromBlob

fromBlob

fromBlob

fromBlob

fromBlob

fromBlob

fromBlob

fromBlob

fromBlobUnsigned

fromBlobUnsigned

fromBlob

fromBlob

fromBlob

fromBlob

fromBlob

fromBlob

fromBlob

fromBlob

fromBlob

fromBlob

numel

numel

shape

memoryFormat

dtype

getDataAsByteArray

getDataAsUnsignedByteArray

getDataAsIntArray

getDataAsFloatArray

getDataAsLongArray

getDataAsDoubleArray