pytorch学习手册【二】
九、Reduction Ops(规约/简化操作)
torch.
argmax
(input, dim=None, keepdim=False)
torch.argmin
(input, dim=None, keepdim=False)
torch.
cumprod
(input, dim, dtype=None) → Tensor
torch.
cumsum
(input, dim, out=None, dtype=None) → Tensor
torch.
dist
(input, other, p=2) → Tensor
torch.
logsumexp
(input, dim, keepdim=False, out=None)
torch.
mean
(input, dim, keepdim=False, out=None) → Tensor
torch.
median
()
torch.
median
(input) → Tensor
torch.
mode
(input, dim=-1, keepdim=False, values=None, indices=None) -> (Tensor, LongTensor)
torch.
norm
(input, p='fro', dim=None, keepdim=False, out=None)
torch.
prod
(input, dim, keepdim=False, dtype=None) → Tensor
torch.
std
()
torch.
std
(input, unbiased=True) → Tensor
torch.
std
(input, dim, keepdim=False, unbiased=True, out=None) → Tensor
torch.
sum
()
torch.
sum
(input, dtype=None) → Tensor
torch.
sum
(input, dim, keepdim=False, dtype=None) → Tensor
torch.
unique
(input, sorted=False, return_inverse=False, dim=None)[SOURCE]
torch.
var
()
torch.
var
(input, unbiased=True) → Tensor
torch.
var
(input, dim, keepdim=False, unbiased=True, out=None) → Tensor
十、Comparison Ops(比较操作)
torch.
allclose
(self, other, rtol=1e-05, atol=1e-08, equal_nan=False) → bool
torch.
argsort
(input, dim=None, descending=False)
torch.
eq
(input, other, out=None) → Tensor
torch.
equal
(tensor1, tensor2) → bool
torch.
ge
(input, other, out=None) → Tensor
torch.
gt
(input, other, out=None) → Tensor
torch.
isfinite
(tensor)
torch.
isinf
(tensor)
torch.
isnan
(tensor)
torch.
kthvalue
(input, k, dim=None, keepdim=False, out=None) -> (Tensor, LongTensor)
torch.
le
(input, other, out=None) → Tensor
torch.
lt
(input, other, out=None) → Tensor
torch.
max
()
torch.
max
(input) → Tensor
torch.
max
(input, dim, keepdim=False, out=None) -> (Tensor, LongTensor)
torch.
max
(input, other, out=None) → Tensor
torch.
min
()
torch.
min
(input) → Tensor
torch.
min
(input, dim, keepdim=False, out=None) -> (Tensor, LongTensor)
torch.
min
(input, other, out=None) → Tensor
torch.
ne
(input, other, out=None) → Tensor
torch.
sort
(input, dim=None, descending=False, out=None) -> (Tensor, LongTensor)
torch.
topk
(input, k, dim=None, largest=True, sorted=True, out=None) -> (Tensor, LongTensor)
十一、Spectral Ops(信号处理相关的谱运算)
torch.
fft
(input, signal_ndim, normalized=False) → Tensor
torch.
ifft
(input, signal_ndim, normalized=False) → Tensor
torch.
rfft
(input, signal_ndim, normalized=False, onesided=True) → Tensor
torch.
irfft
(input, signal_ndim, normalized=False, onesided=True, signal_sizes=None) → Tensor
torch.
stft
(input, n_fft, hop_length=None, win_length=None, window=None, center=True, pad_mode='reflect', normalized=False, onesided=True)
torch.
bartlett_window
(window_length, periodic=True, dtype=None, layout=torch.strided, device=None, requires_grad=False) → Tensor
torch.
blackman_window
(window_length, periodic=True, dtype=None, layout=torch.strided, device=None, requires_grad=False) → Tensor
torch.
hamming_window
(window_length, periodic=True, alpha=0.54, beta=0.46, dtype=None, layout=torch.strided, device=None, requires_grad=False) → Tensor
torch.
hann_window
(window_length, periodic=True, dtype=None, layout=torch.strided, device=None, requires_grad=False) → Tensor
十二、Other Operations(其他操作)
torch.
bincount
(self, weights=None, minlength=0) → Tensor
torch.
broadcast_tensors
(*tensors) → List of Tensors[SOURCE]
torch.
cross
(input, other, dim=-1, out=None) → Tensor
torch.
diag
(input, diagonal=0, out=None) → Tensor
torch.diagonal()
always returns the diagonal of its input.
torch.diagflat()
always constructs a tensor with diagonal elements specified by the input.
torch.
diag_embed
(input, offset=0, dim1=-2, dim2=-1) → Tensor
torch.
diagflat
(input, diagonal=0) → Tensor
torch.
diagonal
(input, offset=0, dim1=0, dim2=1) → Tensor
torch.
einsum
(equation, *operands) → Tensor[SOURCE]
torch.
flatten
(input, start_dim=0, end_dim=-1) → Tensor
torch.
flip
(input, dims) → Tensor
torch.
histc
(input, bins=100, min=0, max=0, out=None) → Tensor
torch.
meshgrid
(*tensors, **kwargs)[SOURCE]
torch.
renorm
(input, p, dim, maxnorm, out=None) → Tensor
torch.
roll
(input, shifts, dims=None) → Tensor
torch.
tensordot
(a, b, dims=2)[SOURCE]
torch.
trace
(input) → Tensor
torch.
tril
(input, diagonal=0, out=None) → Tensor
torch.
triu
(input, diagonal=0, out=None) → Tensor
十三、BLAS and LAPACK Operations(线性代数相关的运算)
BLAS即 basic linear algebra subprogram
LAPACK即 Linear Algebra PACKage
torch.
addbmm
(beta=1, mat, alpha=1, batch1, batch2, out=None) → Tensor
torch.
addmm
(beta=1, mat, alpha=1, mat1, mat2, out=None) → Tensor
torch.
addmv
(beta=1, tensor, alpha=1, mat, vec, out=None) → Tensor
torch.
addr
(beta=1, mat, alpha=1, vec1, vec2, out=None) → Tensor
torch.
baddbmm
(beta=1, mat, alpha=1, batch1, batch2, out=None) → Tensor
torch.
bmm
(batch1, batch2, out=None) → Tensor
torch.
btrifact
(A, info=None, pivot=True)
torch.
btrifact_with_info
(A, pivot=True) -> (Tensor, IntTensor, IntTensor)
torch.
btrisolve
(b, LU_data, LU_pivots) → Tensor
torch.
btriunpack
(LU_data, LU_pivots, unpack_data=True, unpack_pivots=True)
torch.
chain_matmul
(*matrices)
torch.
cholesky
(A, upper=False, out=None) → Tensor
torch.
dot
(tensor1, tensor2) → Tensor
torch.
eig
(a, eigenvectors=False, out=None) -> (Tensor, Tensor)
torch.
gels
(B, A, out=None) → Tensor
torch.
geqrf
(input, out=None) -> (Tensor, Tensor)
torch.
ger
(vec1, vec2, out=None) → Tensor
torch.
gesv
(B, A) -> (Tensor, Tensor)
torch.
inverse
(input, out=None) → Tensor
torch.
det
(A) → Tensor
torch.
logdet
(A) → Tensor
torch.
slogdet
(A) -> (Tensor, Tensor)
torch.
matmul
(tensor1, tensor2, out=None) → Tensor
torch.
matrix_power
(input, n) → Tensor
torch.
matrix_rank
(input, tol=None, bool symmetric=False) → Tensor
torch.
mm
(mat1, mat2, out=None) → Tensor
torch.
mv
(mat, vec, out=None) → Tensor
torch.
orgqr
(a, tau) → Tensor
torch.
pinverse
(input, rcond=1e-15) → Tensor
torch.
potrf
(a, upper=True, out=None)
torch.
potrs
(b, u, upper=True, out=None) → Tensor
torch.
pstrf
(a, upper=True, out=None) -> (Tensor, Tensor)
torch.
qr
(input, out=None) -> (Tensor, Tensor)
torch.
svd
(input, some=True, compute_uv=True, out=None) -> (Tensor, Tensor, Tensor)
torch.
symeig
(input, eigenvectors=False, upper=True, out=None) -> (Tensor, Tensor)
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