tensors.rst.txt

.. currentmodule:: torch

torch.Tensor

A :class:`torch.Tensor` is a multi-dimensional matrix containing elements of a single data type.

Torch defines seven CPU tensor types and eight GPU tensor types:

Data type	CPU tensor	GPU tensor
32-bit floating point	:class:`torch.FloatTensor`	:class:`torch.cuda.FloatTensor`
64-bit floating point	:class:`torch.DoubleTensor`	:class:`torch.cuda.DoubleTensor`
16-bit floating point	N/A	:class:`torch.cuda.HalfTensor`
8-bit integer (unsigned)	:class:`torch.ByteTensor`	:class:`torch.cuda.ByteTensor`
8-bit integer (signed)	:class:`torch.CharTensor`	:class:`torch.cuda.CharTensor`
16-bit integer (signed)	:class:`torch.ShortTensor`	:class:`torch.cuda.ShortTensor`
32-bit integer (signed)	:class:`torch.IntTensor`	:class:`torch.cuda.IntTensor`
64-bit integer (signed)	:class:`torch.LongTensor`	:class:`torch.cuda.LongTensor`

The :class:`torch.Tensor` constructor is an alias for the default tensor type (:class:`torch.FloatTensor`).

A tensor can be constructed from a Python :class:`list` or sequence:

>>> torch.FloatTensor([[1, 2, 3], [4, 5, 6]])
1  2  3
4  5  6
[torch.FloatTensor of size 2x3]

An empty tensor can be constructed by specifying its size:

>>> torch.IntTensor(2, 4).zero_()
0  0  0  0
0  0  0  0
[torch.IntTensor of size 2x4]

The contents of a tensor can be accessed and modified using Python's indexing and slicing notation:

>>> x = torch.FloatTensor([[1, 2, 3], [4, 5, 6]])
>>> print(x[1][2])
6.0
>>> x[0][1] = 8
>>> print(x)
 1  8  3
 4  5  6
[torch.FloatTensor of size 2x3]

Each tensor has an associated :class:`torch.Storage`, which holds its data. The tensor class provides multi-dimensional, strided view of a storage and defines numeric operations on it.

Note

Methods which mutate a tensor are marked with an underscore suffix. For example, :func:`torch.FloatTensor.abs_` computes the absolute value in-place and returns the modified tensor, while :func:`torch.FloatTensor.abs` computes the result in a new tensor.

Creates a new tensor from an optional size or data.

If no arguments are given, an empty zero-dimensional tensor is returned. If a :class:`numpy.ndarray`, :class:`torch.Tensor`, or :class:`torch.Storage` is given, a new tensor that shares the same data is returned. If a Python sequence is given, a new tensor is created from a copy of the sequence.

.. automethod:: abs

.. automethod:: abs_

.. automethod:: acos

.. automethod:: acos_

.. automethod:: add

.. automethod:: add_

.. automethod:: addbmm

.. automethod:: addbmm_

.. automethod:: addcdiv

.. automethod:: addcdiv_

.. automethod:: addcmul

.. automethod:: addcmul_

.. automethod:: addmm

.. automethod:: addmm_

.. automethod:: addmv

.. automethod:: addmv_

.. automethod:: addr

.. automethod:: addr_

.. automethod:: apply_

.. automethod:: asin

.. automethod:: asin_

.. automethod:: atan

.. automethod:: atan2

.. automethod:: atan2_

.. automethod:: atan_

.. automethod:: baddbmm

.. automethod:: baddbmm_

.. automethod:: bernoulli

.. automethod:: bernoulli_

.. automethod:: bmm

.. automethod:: byte

.. automethod:: cauchy_

.. automethod:: ceil

.. automethod:: ceil_

.. automethod:: char

.. automethod:: chunk

.. automethod:: clamp

.. automethod:: clamp_

.. automethod:: clone

.. automethod:: contiguous

.. automethod:: copy_

.. automethod:: cos

.. automethod:: cos_

.. automethod:: cosh

.. automethod:: cosh_

.. automethod:: cpu

.. automethod:: cross

.. automethod:: cuda

.. automethod:: cumprod

.. automethod:: cumsum

.. automethod:: data_ptr

.. automethod:: diag

.. automethod:: dim

.. automethod:: dist

.. automethod:: div

.. automethod:: div_

.. automethod:: dot

.. automethod:: double

.. automethod:: eig

.. automethod:: element_size

.. automethod:: eq

.. automethod:: eq_

.. automethod:: equal

.. automethod:: exp

.. automethod:: exp_

.. automethod:: expand

.. automethod:: expand_as

.. automethod:: exponential_

.. automethod:: fill_

.. automethod:: float

.. automethod:: floor

.. automethod:: floor_

.. automethod:: fmod

.. automethod:: fmod_

.. automethod:: frac

.. automethod:: frac_

.. automethod:: gather

.. automethod:: ge

.. automethod:: ge_

.. automethod:: gels

.. automethod:: geometric_

.. automethod:: geqrf

.. automethod:: ger

.. automethod:: gesv

.. automethod:: gt

.. automethod:: gt_

.. automethod:: half

.. automethod:: histc

.. automethod:: index

.. automethod:: index_add_

.. automethod:: index_copy_

.. automethod:: index_fill_

.. automethod:: index_select

.. automethod:: int

.. automethod:: inverse

.. automethod:: is_contiguous

.. autoattribute:: is_cuda
   :annotation:

.. automethod:: is_pinned

.. automethod:: is_set_to

.. automethod:: is_signed

.. automethod:: kthvalue

.. automethod:: le

.. automethod:: le_

.. automethod:: lerp

.. automethod:: lerp_

.. automethod:: log

.. automethod:: log1p

.. automethod:: log1p_

.. automethod:: log_

.. automethod:: log_normal_

.. automethod:: long

.. automethod:: lt

.. automethod:: lt_

.. automethod:: map_

.. automethod:: masked_copy_

.. automethod:: masked_fill_

.. automethod:: masked_select

.. automethod:: max

.. automethod:: mean

.. automethod:: median

.. automethod:: min

.. automethod:: mm

.. automethod:: mode

.. automethod:: mul

.. automethod:: mul_

.. automethod:: multinomial

.. automethod:: mv

.. automethod:: narrow

.. automethod:: ndimension

.. automethod:: ne

.. automethod:: ne_

.. automethod:: neg

.. automethod:: neg_

.. automethod:: nelement

.. automethod:: new

.. automethod:: nonzero

.. automethod:: norm

.. automethod:: normal_

.. automethod:: numel

.. automethod:: numpy

.. automethod:: orgqr

.. automethod:: ormqr

.. automethod:: permute

.. automethod:: pin_memory

.. automethod:: potrf

.. automethod:: potri

.. automethod:: potrs

.. automethod:: pow

.. automethod:: pow_

.. automethod:: prod

.. automethod:: pstrf

.. automethod:: qr

.. automethod:: random_

.. automethod:: reciprocal

.. automethod:: reciprocal_

.. automethod:: remainder

.. automethod:: remainder_

.. automethod:: renorm

.. automethod:: renorm_

.. automethod:: repeat

.. automethod:: resize_

.. automethod:: resize_as_

.. automethod:: round

.. automethod:: round_

.. automethod:: rsqrt

.. automethod:: rsqrt_

.. automethod:: scatter_

.. automethod:: select

.. automethod:: set_

.. automethod:: share_memory_

.. automethod:: short

.. automethod:: sigmoid

.. automethod:: sigmoid_

.. automethod:: sign

.. automethod:: sign_

.. automethod:: sin

.. automethod:: sin_

.. automethod:: sinh

.. automethod:: sinh_

.. automethod:: size

.. automethod:: sort

.. automethod:: split

.. automethod:: sqrt

.. automethod:: sqrt_

.. automethod:: squeeze

.. automethod:: squeeze_

.. automethod:: std

.. automethod:: storage

.. automethod:: storage_offset

.. automethod:: storage_type

.. automethod:: stride

.. automethod:: sub

.. automethod:: sub_

.. automethod:: sum

.. automethod:: svd

.. automethod:: symeig

.. automethod:: t

.. automethod:: t_

.. automethod:: tan

.. automethod:: tan_

.. automethod:: tanh

.. automethod:: tanh_

.. automethod:: tolist

.. automethod:: topk

.. automethod:: trace

.. automethod:: transpose

.. automethod:: transpose_

.. automethod:: tril

.. automethod:: tril_

.. automethod:: triu

.. automethod:: triu_

.. automethod:: trtrs

.. automethod:: trunc

.. automethod:: trunc_

.. automethod:: type

.. automethod:: type_as

.. automethod:: unfold

.. automethod:: uniform_

.. automethod:: unsqueeze

.. automethod:: unsqueeze_

.. automethod:: var

.. automethod:: view

.. automethod:: view_as

.. automethod:: zero_