abs
Computes the absolute value of each element in input.
absolute
Alias for torch.abs()
acos
Computes the inverse cosine of each element in input.
arccos
Alias for torch.acos().
acosh
Returns a new tensor with the inverse hyperbolic cosine of the elements of input.
arccosh
Alias for torch.acosh().
add
Adds other, scaled by alpha, to input.
addcdiv
Performs the element-wise division of tensor1 by tensor2, multiplies the result by the scalar value and adds it to input.
addcmul
Performs the element-wise multiplication of tensor1 by tensor2, multiplies the result by the scalar value and adds it to input.
angle
Computes the element-wise angle (in radians) of the given input tensor.
asin
Returns a new tensor with the arcsine of the elements of input.
arcsin
Alias for torch.asin().
asinh
Returns a new tensor with the inverse hyperbolic sine of the elements of input.
arcsinh
Alias for torch.asinh().
atan
Returns a new tensor with the arctangent of the elements of input.
arctan
Alias for torch.atan().
atanh
Returns a new tensor with the inverse hyperbolic tangent of the elements of input.
arctanh
Alias for torch.atanh().
atan2
Element-wise arctangent of input i / other i \text{input}_{i} / \text{other}_{i} inputi/otheri with consideration of the quadrant.
arctan2
Alias for torch.atan2().
bitwise_not
Computes the bitwise NOT of the given input tensor.
bitwise_and
Computes the bitwise AND of input and other.
bitwise_or
Computes the bitwise OR of input and other.
bitwise_xor
Computes the bitwise XOR of input and other.
bitwise_left_shift
Computes the left arithmetic shift of input by other bits.
bitwise_right_shift
Computes the right arithmetic shift of input by other bits.
ceil
Returns a new tensor with the ceil of the elements of input, the smallest integer greater than or equal to each element.
clamp
Clamps all elements in input into the range [ min, max ].
clip
Alias for torch.clamp().
conj_physical
Computes the element-wise conjugate of the given input tensor.
copysign
Create a new floating-point tensor with the magnitude of input and the sign of other, elementwise.
cos
Returns a new tensor with the cosine of the elements of input.
cosh
Returns a new tensor with the hyperbolic cosine of the elements of input.
deg2rad
Returns a new tensor with each of the elements of input converted from angles in degrees to radians.
div
Divides each element of the input input by the corresponding element of other.
divide
Alias for torch.div().
digamma
Alias for torch.special.digamma().
erf
Alias for torch.special.erf().
erfc
Alias for torch.special.erfc().
erfinv
Alias for torch.special.erfinv().
exp
Returns a new tensor with the exponential of the elements of the input tensor input.
exp2
Alias for torch.special.exp2().
expm1
Alias for torch.special.expm1().
fake_quantize_per_channel_affine
Returns a new tensor with the data in input fake quantized per channel using scale, zero_point, quant_min and quant_max, across the channel specified by axis.
fake_quantize_per_tensor_affine
Returns a new tensor with the data in input fake quantized using scale, zero_point, quant_min and quant_max.
fix
Alias for torch.trunc()
float_power
Raises input to the power of exponent, elementwise, in double precision.
floor
Returns a new tensor with the floor of the elements of input, the largest integer less than or equal to each element.
floor_divide fmod
Applies C++'s std::fmod entrywise.
frac
Computes the fractional portion of each element in input.
frexp
Decomposes input into mantissa and exponent tensors such that input = mantissa × 2exponent \text{input} = \text{mantissa} \times 2^{\text{exponent}} input=mantissa×2exponent.
gradient
Estimates the gradient of a function g : Rn → R g : \mathbb{R}^n \rightarrow \mathbb{R} g:Rn→R in one or more dimensions using the second-order accurate central differences method and either first or second order estimates at the boundaries.
imag
Returns a new tensor containing imaginary values of the self tensor.
ldexp
Multiplies input by 2 ** other.
lerp
Does a linear interpolation of two tensors start (given by input) and end based on a scalar or tensor weight and returns the resulting out tensor.
lgamma
Computes the natural logarithm of the absolute value of the gamma function on input.
log
Returns a new tensor with the natural logarithm of the elements of input.
log10
Returns a new tensor with the logarithm to the base 10 of the elements of input.
log1p
Returns a new tensor with the natural logarithm of (1 + input).
log2
Returns a new tensor with the logarithm to the base 2 of the elements of input.
logaddexp
Logarithm of the sum of exponentiations of the inputs.
logaddexp2
Logarithm of the sum of exponentiations of the inputs in base-2.
logical_and
Computes the element-wise logical AND of the given input tensors.
logical_not
Computes the element-wise logical NOT of the given input tensor.
logical_or
Computes the element-wise logical OR of the given input tensors.
logical_xor
Computes the element-wise logical XOR of the given input tensors.
logit
Alias for torch.special.logit().
hypot
Given the legs of a right triangle, return its hypotenuse.
i0
Alias for torch.special.i0().
igamma
Alias for torch.special.gammainc().
igammac
Alias for torch.special.gammaincc().
mul
Multiplies input by other.
multiply
Alias for torch.mul().
mvlgamma
Alias for torch.special.multigammaln().
nan_to_num
Replaces NaN, positive infinity, and negative infinity values in input with the values specified by nan, posinf, and neginf, respectively.
neg
Returns a new tensor with the negative of the elements of input.
negative
Alias for torch.neg()
nextafter
Return the next floating-point value after input towards other, elementwise.
polygamma
Alias for torch.special.polygamma().
positive
Returns input.
pow
Takes the power of each element in input with exponent and returns a tensor with the result.
quantized_batch_norm
Applies batch normalization on a 4D (NCHW) quantized tensor.
quantized_max_pool1d
Applies a 1D max pooling over an input quantized tensor composed of several input planes.
quantized_max_pool2d
Applies a 2D max pooling over an input quantized tensor composed of several input planes.
rad2deg
Returns a new tensor with each of the elements of input converted from angles in radians to degrees.
real
Returns a new tensor containing real values of the self tensor.
reciprocal
Returns a new tensor with the reciprocal of the elements of input
remainder
Computes Python's modulus operation entrywise.
round
Rounds elements of input to the nearest integer.
rsqrt
Returns a new tensor with the reciprocal of the square-root of each of the elements of input.
sigmoid
Alias for torch.special.expit().
sign
Returns a new tensor with the signs of the elements of input.
sgn
This function is an extension of torch.sign() to complex tensors.
signbit
Tests if each element of input has its sign bit set or not.
sin
Returns a new tensor with the sine of the elements of input.
sinc
Alias for torch.special.sinc().
sinh
Returns a new tensor with the hyperbolic sine of the elements of input.
softmax
Alias for torch.nn.functional.softmax().
sqrt
Returns a new tensor with the square-root of the elements of input.
square
Returns a new tensor with the square of the elements of input.
sub
Subtracts other, scaled by alpha, from input.
subtract
Alias for torch.sub().
tan
Returns a new tensor with the tangent of the elements of input.
tanh
Returns a new tensor with the hyperbolic tangent of the elements of input.
true_divide
Alias for torch.div() with rounding_mode=None.
trunc
Returns a new tensor with the truncated integer values of the elements of input.
xlogy
Alias for torch.special.xlogy().
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