Operations#

abs(a, /, *[, stream])

Element-wise absolute value.

add(a, b[, stream])

Element-wise addition.

all(a, /[, axis, keepdims, stream])

An and reduction over the given axes.

allclose(a, b, /[, rtol, atol, stream])

Approximate comparison of two arrays.

any(a, /[, axis, keepdims, stream])

An or reduction over the given axes.

arange(start, stop, step[, dtype, stream])

Generates ranges of numbers.

arccos(a, /, *[, stream])

Element-wise inverse cosine.

arccosh(a, /, *[, stream])

Element-wise inverse hyperbolic cosine.

arcsin(a, /, *[, stream])

Element-wise inverse sine.

arcsinh(a, /, *[, stream])

Element-wise inverse hyperbolic sine.

arctan(a, /, *[, stream])

Element-wise inverse tangent.

arctanh(a, /, *[, stream])

Element-wise inverse hyperbolic tangent.

argmax(a, /[, axis, keepdims, stream])

Indices of the maximum values along the axis.

argmin(a, /[, axis, keepdims, stream])

Indices of the minimum values along the axis.

argpartition(a, /, kth[, axis, stream])

Returns the indices that partition the array.

argsort(a, /[, axis, stream])

Returns the indices that sort the array.

array_equal(a, b[, equal_nan, stream])

Array equality check.

broadcast_to(a, /, shape, *[, stream])

Broadcast an array to the given shape.

concatenate(arrays[, axis, stream])

Concatenate the arrays along the given axis.

convolve(a, v, /[, mode, stream])

The discrete convolution of 1D arrays.

conv1d(input, weight, /[, stride, padding, ...])

1D convolution over an input with several channels

conv2d(input, weight, /[, stride, padding, ...])

2D convolution over an input with several channels

cos(a, /, *[, stream])

Element-wise cosine.

cosh(a, /, *[, stream])

Element-wise hyperbolic cosine.

divide(a, b[, stream])

Element-wise division.

equal(a, b[, stream])

Element-wise equality.

erf(a, /, *[, stream])

Element-wise error function.

erfinv(a, /, *[, stream])

Element-wise inverse of erf().

exp(a, /, *[, stream])

Element-wise exponential.

expand_dims(a, /, axis, *[, stream])

Add a size one dimension at the given axis.

eye(n[, m, k, dtype, stream])

Create an identity matrix or a general diagonal matrix.

full(shape, vals[, dtype, stream])

Construct an array with the given value.

greater(a, b[, stream])

Element-wise greater than.

greater_equal(a, b[, stream])

Element-wise greater or equal.

identity(n[, dtype, stream])

Create a square identity matrix.

less(a, b[, stream])

Element-wise less than.

less_equal(a, b[, stream])

Element-wise less than or equal.

load(file, /, *[, stream])

Load array(s) from a binary file in .npy or .npz format.

log(a, /, *[, stream])

Element-wise natural logarithm.

log2(a, /, *[, stream])

Element-wise base-2 logarithm.

log10(a, /, *[, stream])

Element-wise base-10 logarithm.

log1p(a, /, *[, stream])

Element-wise natural log of one plus the array.

logaddexp(a, b, /, *[, stream])

Element-wise log-add-exp.

logical_not(a, /, *[, stream])

Element-wise logical not.

logsumexp(a, /[, axis, keepdims, stream])

A log-sum-exp reduction over the given axes.

matmul(a, b, /, *[, stream])

Matrix multiplication.

max(a, /[, axis, keepdims, stream])

An max reduction over the given axes.

maximum(a, b, /, *[, stream])

Element-wise maximum.

mean(a, /[, axis, keepdims, stream])

Compute the mean(s) over the given axes.

min(a, /[, axis, keepdims, stream])

An min reduction over the given axes.

minimum(a, b, /, *[, stream])

Element-wise minimum.

multiply(a, b[, stream])

Element-wise multiplication.

negative(a, /, *[, stream])

Element-wise negation.

ones(shape[, dtype, stream])

Construct an array of ones.

ones_like(a, /, *[, stream])

An array of ones like the input.

partition(a, /, kth[, axis, stream])

Returns a partitioned copy of the array such that the smaller kth elements are first.

pad(a, pad_with[, constant_values, stream])

Pad an array with a constant value

prod(a, /[, axis, keepdims, stream])

An product reduction over the given axes.

reciprocal(a, /, *[, stream])

Element-wise reciprocal.

reshape(a, /, shape, *[, stream])

Reshape an array while preserving the size.

rsqrt(a, /, *[, stream])

Element-wise reciprocal and square root.

save(file, arr, /[, retain_graph])

Save the array to a binary file in .npy format.

savez(file, *args, **kwargs)

Save several arrays to a binary file in uncompressed .npz format.

savez_compressed(file, *args, **kwargs)

Save several arrays to a binary file in compressed .npz format.

sigmoid(a, /, *[, stream])

Element-wise logistic sigmoid.

sign(a, /, *[, stream])

Element-wise sign.

sin(a, /, *[, stream])

Element-wise sine.

sinh(a, /, *[, stream])

Element-wise hyperbolic sine.

softmax(a, /[, axis, stream])

Perform the softmax along the given axis.

sort(a, /[, axis, stream])

Returns a sorted copy of the array.

split(a, /, indices_or_sections[, axis, stream])

Split an array along a given axis.

sqrt(a, /, *[, stream])

Element-wise square root.

square(a, /, *[, stream])

Element-wise square.

squeeze(a, /[, axis, stream])

Remove length one axes from an array.

stop_gradient(a, /, *[, stream])

Stop gradients from being computed.

subtract(a, b[, stream])

Element-wise subtraction.

sum(a, /[, axis, keepdims, stream])

Sum reduce the array over the given axes.

take(a, /, indices[, axis, stream])

Take elements along an axis.

take_along_axis(a, /, indices[, axis, stream])

Take values along an axis at the specified indices.

tan(a, /, *[, stream])

Element-wise tangent.

tanh(a, /, *[, stream])

Element-wise hyperbolic tangent.

transpose(a, /[, axes, stream])

Transpose the dimensions of the array.

var(a, /[, axis, keepdims, ddof, stream])

Compute the variance(s) over the given axes.

where(condition, x, y, /, *[, stream])

Select from x or y according to condition.

zeros(shape[, dtype, stream])

Construct an array of zeros.

zeros_like(a, /, *[, stream])

An array of zeros like the input.