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torch.Tensor A torch.Tensor is a multi-dimensional matrix containing elements of a single data type. Torch defines 10 tensor types with CPU and GPU variants which are as follows: Data type dtype CPU tensor GPU tensor 32-bit floating point torch.float32 or torch.float torch.FloatTensor torch.cuda.FloatTensor 64-...
torch.tensors
torch.tensor(data, *, dtype=None, device=None, requires_grad=False, pin_memory=False) β†’ Tensor Constructs a tensor with data. Warning torch.tensor() always copies data. If you have a Tensor data and want to avoid a copy, use torch.Tensor.requires_grad_() or torch.Tensor.detach(). If you have a NumPy ndarray and want...
torch.generated.torch.tensor#torch.tensor
abs() β†’ Tensor See torch.abs()
torch.tensors#torch.Tensor.abs
absolute() β†’ Tensor Alias for abs()
torch.tensors#torch.Tensor.absolute
absolute_() β†’ Tensor In-place version of absolute() Alias for abs_()
torch.tensors#torch.Tensor.absolute_
abs_() β†’ Tensor In-place version of abs()
torch.tensors#torch.Tensor.abs_
acos() β†’ Tensor See torch.acos()
torch.tensors#torch.Tensor.acos
acosh() β†’ Tensor See torch.acosh()
torch.tensors#torch.Tensor.acosh
acosh_() β†’ Tensor In-place version of acosh()
torch.tensors#torch.Tensor.acosh_
acos_() β†’ Tensor In-place version of acos()
torch.tensors#torch.Tensor.acos_
add(other, *, alpha=1) β†’ Tensor Add a scalar or tensor to self tensor. If both alpha and other are specified, each element of other is scaled by alpha before being used. When other is a tensor, the shape of other must be broadcastable with the shape of the underlying tensor See torch.add()
torch.tensors#torch.Tensor.add
addbmm(batch1, batch2, *, beta=1, alpha=1) β†’ Tensor See torch.addbmm()
torch.tensors#torch.Tensor.addbmm
addbmm_(batch1, batch2, *, beta=1, alpha=1) β†’ Tensor In-place version of addbmm()
torch.tensors#torch.Tensor.addbmm_
addcdiv(tensor1, tensor2, *, value=1) β†’ Tensor See torch.addcdiv()
torch.tensors#torch.Tensor.addcdiv
addcdiv_(tensor1, tensor2, *, value=1) β†’ Tensor In-place version of addcdiv()
torch.tensors#torch.Tensor.addcdiv_
addcmul(tensor1, tensor2, *, value=1) β†’ Tensor See torch.addcmul()
torch.tensors#torch.Tensor.addcmul
addcmul_(tensor1, tensor2, *, value=1) β†’ Tensor In-place version of addcmul()
torch.tensors#torch.Tensor.addcmul_
addmm(mat1, mat2, *, beta=1, alpha=1) β†’ Tensor See torch.addmm()
torch.tensors#torch.Tensor.addmm
addmm_(mat1, mat2, *, beta=1, alpha=1) β†’ Tensor In-place version of addmm()
torch.tensors#torch.Tensor.addmm_
addmv(mat, vec, *, beta=1, alpha=1) β†’ Tensor See torch.addmv()
torch.tensors#torch.Tensor.addmv
addmv_(mat, vec, *, beta=1, alpha=1) β†’ Tensor In-place version of addmv()
torch.tensors#torch.Tensor.addmv_
addr(vec1, vec2, *, beta=1, alpha=1) β†’ Tensor See torch.addr()
torch.tensors#torch.Tensor.addr
addr_(vec1, vec2, *, beta=1, alpha=1) β†’ Tensor In-place version of addr()
torch.tensors#torch.Tensor.addr_
add_(other, *, alpha=1) β†’ Tensor In-place version of add()
torch.tensors#torch.Tensor.add_
align_as(other) β†’ Tensor Permutes the dimensions of the self tensor to match the dimension order in the other tensor, adding size-one dims for any new names. This operation is useful for explicit broadcasting by names (see examples). All of the dims of self must be named in order to use this method. The resulting ten...
torch.named_tensor#torch.Tensor.align_as
align_to(*names) [source] Permutes the dimensions of the self tensor to match the order specified in names, adding size-one dims for any new names. All of the dims of self must be named in order to use this method. The resulting tensor is a view on the original tensor. All dimension names of self must be present in n...
torch.named_tensor#torch.Tensor.align_to
all(dim=None, keepdim=False) β†’ Tensor See torch.all()
torch.tensors#torch.Tensor.all
allclose(other, rtol=1e-05, atol=1e-08, equal_nan=False) β†’ Tensor See torch.allclose()
torch.tensors#torch.Tensor.allclose
amax(dim=None, keepdim=False) β†’ Tensor See torch.amax()
torch.tensors#torch.Tensor.amax
amin(dim=None, keepdim=False) β†’ Tensor See torch.amin()
torch.tensors#torch.Tensor.amin
angle() β†’ Tensor See torch.angle()
torch.tensors#torch.Tensor.angle
any(dim=None, keepdim=False) β†’ Tensor See torch.any()
torch.tensors#torch.Tensor.any
apply_(callable) β†’ Tensor Applies the function callable to each element in the tensor, replacing each element with the value returned by callable. Note This function only works with CPU tensors and should not be used in code sections that require high performance.
torch.tensors#torch.Tensor.apply_
arccos() β†’ Tensor See torch.arccos()
torch.tensors#torch.Tensor.arccos
arccosh() acosh() -> Tensor See torch.arccosh()
torch.tensors#torch.Tensor.arccosh
arccosh_() acosh_() -> Tensor In-place version of arccosh()
torch.tensors#torch.Tensor.arccosh_
arccos_() β†’ Tensor In-place version of arccos()
torch.tensors#torch.Tensor.arccos_
arcsin() β†’ Tensor See torch.arcsin()
torch.tensors#torch.Tensor.arcsin
arcsinh() β†’ Tensor See torch.arcsinh()
torch.tensors#torch.Tensor.arcsinh
arcsinh_() β†’ Tensor In-place version of arcsinh()
torch.tensors#torch.Tensor.arcsinh_
arcsin_() β†’ Tensor In-place version of arcsin()
torch.tensors#torch.Tensor.arcsin_
arctan() β†’ Tensor See torch.arctan()
torch.tensors#torch.Tensor.arctan
arctanh() β†’ Tensor See torch.arctanh()
torch.tensors#torch.Tensor.arctanh
arctanh_(other) β†’ Tensor In-place version of arctanh()
torch.tensors#torch.Tensor.arctanh_
arctan_() β†’ Tensor In-place version of arctan()
torch.tensors#torch.Tensor.arctan_
argmax(dim=None, keepdim=False) β†’ LongTensor See torch.argmax()
torch.tensors#torch.Tensor.argmax
argmin(dim=None, keepdim=False) β†’ LongTensor See torch.argmin()
torch.tensors#torch.Tensor.argmin
argsort(dim=-1, descending=False) β†’ LongTensor See torch.argsort()
torch.tensors#torch.Tensor.argsort
asin() β†’ Tensor See torch.asin()
torch.tensors#torch.Tensor.asin
asinh() β†’ Tensor See torch.asinh()
torch.tensors#torch.Tensor.asinh
asinh_() β†’ Tensor In-place version of asinh()
torch.tensors#torch.Tensor.asinh_
asin_() β†’ Tensor In-place version of asin()
torch.tensors#torch.Tensor.asin_
as_strided(size, stride, storage_offset=0) β†’ Tensor See torch.as_strided()
torch.tensors#torch.Tensor.as_strided
as_subclass(cls) β†’ Tensor Makes a cls instance with the same data pointer as self. Changes in the output mirror changes in self, and the output stays attached to the autograd graph. cls must be a subclass of Tensor.
torch.tensors#torch.Tensor.as_subclass
atan() β†’ Tensor See torch.atan()
torch.tensors#torch.Tensor.atan
atan2(other) β†’ Tensor See torch.atan2()
torch.tensors#torch.Tensor.atan2
atan2_(other) β†’ Tensor In-place version of atan2()
torch.tensors#torch.Tensor.atan2_
atanh() β†’ Tensor See torch.atanh()
torch.tensors#torch.Tensor.atanh
atanh_(other) β†’ Tensor In-place version of atanh()
torch.tensors#torch.Tensor.atanh_
atan_() β†’ Tensor In-place version of atan()
torch.tensors#torch.Tensor.atan_
backward(gradient=None, retain_graph=None, create_graph=False, inputs=None) [source] Computes the gradient of current tensor w.r.t. graph leaves. The graph is differentiated using the chain rule. If the tensor is non-scalar (i.e. its data has more than one element) and requires gradient, the function additionally req...
torch.autograd#torch.Tensor.backward
baddbmm(batch1, batch2, *, beta=1, alpha=1) β†’ Tensor See torch.baddbmm()
torch.tensors#torch.Tensor.baddbmm
baddbmm_(batch1, batch2, *, beta=1, alpha=1) β†’ Tensor In-place version of baddbmm()
torch.tensors#torch.Tensor.baddbmm_
bernoulli(*, generator=None) β†’ Tensor Returns a result tensor where each result[i]\texttt{result[i]} is independently sampled from Bernoulli(self[i])\text{Bernoulli}(\texttt{self[i]}) . self must have floating point dtype, and the result will have the same dtype. See torch.bernoulli()
torch.tensors#torch.Tensor.bernoulli
bernoulli_() bernoulli_(p=0.5, *, generator=None) β†’ Tensor Fills each location of self with an independent sample from Bernoulli(p)\text{Bernoulli}(\texttt{p}) . self can have integral dtype. bernoulli_(p_tensor, *, generator=None) β†’ Tensor p_tensor should be a tensor containing probabilities to be used for...
torch.tensors#torch.Tensor.bernoulli_
bfloat16(memory_format=torch.preserve_format) β†’ Tensor self.bfloat16() is equivalent to self.to(torch.bfloat16). See to(). Parameters memory_format (torch.memory_format, optional) – the desired memory format of returned Tensor. Default: torch.preserve_format.
torch.tensors#torch.Tensor.bfloat16
bincount(weights=None, minlength=0) β†’ Tensor See torch.bincount()
torch.tensors#torch.Tensor.bincount
bitwise_and() β†’ Tensor See torch.bitwise_and()
torch.tensors#torch.Tensor.bitwise_and
bitwise_and_() β†’ Tensor In-place version of bitwise_and()
torch.tensors#torch.Tensor.bitwise_and_
bitwise_not() β†’ Tensor See torch.bitwise_not()
torch.tensors#torch.Tensor.bitwise_not
bitwise_not_() β†’ Tensor In-place version of bitwise_not()
torch.tensors#torch.Tensor.bitwise_not_
bitwise_or() β†’ Tensor See torch.bitwise_or()
torch.tensors#torch.Tensor.bitwise_or
bitwise_or_() β†’ Tensor In-place version of bitwise_or()
torch.tensors#torch.Tensor.bitwise_or_
bitwise_xor() β†’ Tensor See torch.bitwise_xor()
torch.tensors#torch.Tensor.bitwise_xor
bitwise_xor_() β†’ Tensor In-place version of bitwise_xor()
torch.tensors#torch.Tensor.bitwise_xor_
bmm(batch2) β†’ Tensor See torch.bmm()
torch.tensors#torch.Tensor.bmm
bool(memory_format=torch.preserve_format) β†’ Tensor self.bool() is equivalent to self.to(torch.bool). See to(). Parameters memory_format (torch.memory_format, optional) – the desired memory format of returned Tensor. Default: torch.preserve_format.
torch.tensors#torch.Tensor.bool
broadcast_to(shape) β†’ Tensor See torch.broadcast_to().
torch.tensors#torch.Tensor.broadcast_to
byte(memory_format=torch.preserve_format) β†’ Tensor self.byte() is equivalent to self.to(torch.uint8). See to(). Parameters memory_format (torch.memory_format, optional) – the desired memory format of returned Tensor. Default: torch.preserve_format.
torch.tensors#torch.Tensor.byte
cauchy_(median=0, sigma=1, *, generator=None) β†’ Tensor Fills the tensor with numbers drawn from the Cauchy distribution: f(x)=1πσ(xβˆ’median)2+Οƒ2f(x) = \dfrac{1}{\pi} \dfrac{\sigma}{(x - \text{median})^2 + \sigma^2}
torch.tensors#torch.Tensor.cauchy_
ceil() β†’ Tensor See torch.ceil()
torch.tensors#torch.Tensor.ceil
ceil_() β†’ Tensor In-place version of ceil()
torch.tensors#torch.Tensor.ceil_
char(memory_format=torch.preserve_format) β†’ Tensor self.char() is equivalent to self.to(torch.int8). See to(). Parameters memory_format (torch.memory_format, optional) – the desired memory format of returned Tensor. Default: torch.preserve_format.
torch.tensors#torch.Tensor.char
cholesky(upper=False) β†’ Tensor See torch.cholesky()
torch.tensors#torch.Tensor.cholesky
cholesky_inverse(upper=False) β†’ Tensor See torch.cholesky_inverse()
torch.tensors#torch.Tensor.cholesky_inverse
cholesky_solve(input2, upper=False) β†’ Tensor See torch.cholesky_solve()
torch.tensors#torch.Tensor.cholesky_solve
chunk(chunks, dim=0) β†’ List of Tensors See torch.chunk()
torch.tensors#torch.Tensor.chunk
clamp(min, max) β†’ Tensor See torch.clamp()
torch.tensors#torch.Tensor.clamp
clamp_(min, max) β†’ Tensor In-place version of clamp()
torch.tensors#torch.Tensor.clamp_
clip(min, max) β†’ Tensor Alias for clamp().
torch.tensors#torch.Tensor.clip
clip_(min, max) β†’ Tensor Alias for clamp_().
torch.tensors#torch.Tensor.clip_
clone(*, memory_format=torch.preserve_format) β†’ Tensor See torch.clone()
torch.tensors#torch.Tensor.clone
coalesce() β†’ Tensor Returns a coalesced copy of self if self is an uncoalesced tensor. Returns self if self is a coalesced tensor. Warning Throws an error if self is not a sparse COO tensor.
torch.sparse#torch.Tensor.coalesce
conj() β†’ Tensor See torch.conj()
torch.tensors#torch.Tensor.conj
contiguous(memory_format=torch.contiguous_format) β†’ Tensor Returns a contiguous in memory tensor containing the same data as self tensor. If self tensor is already in the specified memory format, this function returns the self tensor. Parameters memory_format (torch.memory_format, optional) – the desired memory for...
torch.tensors#torch.Tensor.contiguous
copysign(other) β†’ Tensor See torch.copysign()
torch.tensors#torch.Tensor.copysign
copysign_(other) β†’ Tensor In-place version of copysign()
torch.tensors#torch.Tensor.copysign_
copy_(src, non_blocking=False) β†’ Tensor Copies the elements from src into self tensor and returns self. The src tensor must be broadcastable with the self tensor. It may be of a different data type or reside on a different device. Parameters src (Tensor) – the source tensor to copy from non_blocking (bool) – if ...
torch.tensors#torch.Tensor.copy_
cos() β†’ Tensor See torch.cos()
torch.tensors#torch.Tensor.cos
cosh() β†’ Tensor See torch.cosh()
torch.tensors#torch.Tensor.cosh