Module: tf.keras.ops.numpy

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Functions

abs(...): Shorthand for keras.ops.absolute.

absolute(...): Compute the absolute value element-wise.

add(...): Add arguments element-wise.

all(...): Test whether all array elements along a given axis evaluate to True.

allclose(...): Returns True if two arrays are element-wise equal within a tolerance.

amax(...): Returns the maximum of an array or maximum value along an axis.

amin(...): Returns the minimum of an array or minimum value along an axis.

angle(...): Element-wise angle of a complex tensor.

any(...): Test whether any array element along a given axis evaluates to True.

append(...): Append tensor x2 to the end of tensor x1.

arange(...): Return evenly spaced values within a given interval.

arccos(...): Trigonometric inverse cosine, element-wise.

arccosh(...): Inverse hyperbolic cosine, element-wise.

arcsin(...): Inverse sine, element-wise.

arcsinh(...): Inverse hyperbolic sine, element-wise.

arctan(...): Trigonometric inverse tangent, element-wise.

arctan2(...): Element-wise arc tangent of x1/x2 choosing the quadrant correctly.

arctanh(...): Inverse hyperbolic tangent, element-wise.

argmax(...): Returns the indices of the maximum values along an axis.

argmin(...): Returns the indices of the minimum values along an axis.

argpartition(...): Performs an indirect partition along the given axis.

argsort(...): Returns the indices that would sort a tensor.

array(...): Create a tensor.

array_split(...): Splits an array into multiple sub-arrays (unevenly).

average(...): Compute the weighted average along the specified axis.

bartlett(...): Bartlett window function.

bincount(...): Count the number of occurrences of each value in a tensor of integers.

bitwise_and(...): Compute the bit-wise AND of two arrays element-wise.

bitwise_invert(...): Compute bit-wise inversion, or bit-wise NOT, element-wise.

bitwise_left_shift(...): Shift the bits of an integer to the left.

bitwise_not(...): Compute bit-wise inversion, or bit-wise NOT, element-wise.

bitwise_or(...): Compute the bit-wise OR of two arrays element-wise.

bitwise_right_shift(...): Shift the bits of an integer to the right.

bitwise_xor(...): Compute the bit-wise XOR of two arrays element-wise.

blackman(...): Blackman window function.

broadcast_to(...): Broadcast a tensor to a new shape.

cbrt(...): Computes the cube root of the input tensor, element-wise.

ceil(...): Return the ceiling of the input, element-wise.

clip(...): Clip (limit) the values in a tensor.

concatenate(...): Join a sequence of tensors along an existing axis.

conj(...): Shorthand for keras.ops.conjugate.

conjugate(...): Returns the complex conjugate, element-wise.

copy(...): Returns a copy of x.

corrcoef(...): Compute the Pearson correlation coefficient matrix.

correlate(...): Compute the cross-correlation of two 1-dimensional tensors.

cos(...): Cosine, element-wise.

cosh(...): Hyperbolic cosine, element-wise.

count_nonzero(...): Counts the number of non-zero values in x along the given axis.

cross(...): Returns the cross product of two (arrays of) vectors.

cumprod(...): Return the cumulative product of elements along a given axis.

cumsum(...): Returns the cumulative sum of elements along a given axis.

deg2rad(...): Convert angles from degrees to radians.

diag(...): Extract a diagonal or construct a diagonal array.

diagflat(...): Create a two-dimensional array with the flattened input on the k-th diagonal.

diagonal(...): Return specified diagonals.

diff(...): Calculate the n-th discrete difference along the given axis.

digitize(...): Returns the indices of the bins to which each value in x belongs.

divide(...): Divide arguments element-wise.

divide_no_nan(...): Safe element-wise division which returns 0 where the denominator is 0.

dot(...): Dot product of two tensors.

dsplit(...): Split an array into multiple sub-arrays depth-wise.

dstack(...): Stack tensors in sequence depth wise (along third axis).

einsum(...): Evaluates the Einstein summation convention on the operands.

empty(...): Return a tensor of given shape and type filled with uninitialized data.

empty_like(...): Return a new uninitialized tensor with the same shape and dtype as x.

equal(...): Returns (x1 == x2) element-wise.

exp(...): Calculate the exponential of all elements in the input tensor.

exp2(...): Calculate the base-2 exponential of all elements in the input tensor.

expand_dims(...): Expand the shape of a tensor.

expm1(...): Calculate exp(x) - 1 for all elements in the tensor.

eye(...): Return a 2-D tensor with ones on the diagonal and zeros elsewhere.

fabs(...): Compute the absolute values element-wise.

flip(...): Reverse the order of elements in the tensor along the given axis.

fliplr(...): Reverse the order of elements along axis 1 (left/right).

flipud(...): Reverse the order of elements along axis 0 (up/down).

floor(...): Return the floor of the input, element-wise.

floor_divide(...): Returns the largest integer smaller or equal to the division of inputs.

fmax(...): Element-wise maximum of tensor elements, ignoring NaNs.

fmin(...): Element-wise minimum of tensor elements, ignoring NaNs.

fmod(...): Returns the element-wise remainder of division with truncation.

full(...): Return a new tensor of given shape and type, filled with fill_value.

full_like(...): Return a full tensor with the same shape and type as the given tensor.

gcd(...): Greatest common divisor of x1 and x2, element-wise.

geomspace(...): Returns numbers spaced evenly on a log scale (a geometric progression).

get_item(...): Return x[key].

greater(...): Return the truth value of x1 > x2 element-wise.

greater_equal(...): Return the truth value of x1 >= x2 element-wise.

hamming(...): Hamming window function.

hanning(...): Hanning window function.

heaviside(...): Heaviside step function.

histogram(...): Computes a histogram of the data tensor x.

hsplit(...): Split an array into multiple sub-arrays horizontally (column-wise).

hstack(...): Stack tensors in sequence horizontally (column wise).

hypot(...): Element-wise hypotenuse of right triangles with legs x1 and x2.

i0(...): Modified Bessel function of the first kind, order 0.

identity(...): Return the identity tensor.

imag(...): Return the imaginary part of the complex argument.

inner(...): Return the inner product of two tensors.

isclose(...): Return whether two tensors are element-wise almost equal.

isfinite(...): Return whether a tensor is finite, element-wise.

isin(...): Test whether each element of x1 is present in x2.

isinf(...): Test element-wise for positive or negative infinity.

isnan(...): Test element-wise for NaN and return result as a boolean tensor.

isneginf(...): Test element-wise for negative infinity.

isposinf(...): Test element-wise for positive infinity.

isreal(...): Test element-wise for real numbers.

kaiser(...): Kaiser window function.

kron(...): Kronecker product of x1 and x2.

lcm(...): Least common multiple of x1 and x2, element-wise.

ldexp(...): Multiply x1 by 2 raised to the power of x2, element-wise.

left_shift(...): Shift the bits of an integer to the left.

less(...): Return the truth value of x1 < x2 element-wise.

less_equal(...): Return the truth value of x1 <= x2 element-wise.

linspace(...): Return evenly spaced numbers over a specified interval.

log(...): Natural logarithm, element-wise.

log10(...): Return the base 10 logarithm of the input tensor, element-wise.

log1p(...): Returns the natural logarithm of one plus the x, element-wise.

log2(...): Base-2 logarithm of x, element-wise.

logaddexp(...): Logarithm of the sum of exponentiations of the inputs.

logaddexp2(...): Base-2 logarithm of the sum of exponentiations of the inputs.

logical_and(...): Computes the element-wise logical AND of the given input tensors.

logical_not(...): Computes the element-wise NOT of the given input tensor.

logical_or(...): Computes the element-wise logical OR of the given input tensors.

logical_xor(...): Compute the truth value of x1 XOR x2, element-wise.

logspace(...): Returns numbers spaced evenly on a log scale.

matmul(...): Matrix product of two tensors.

max(...): Return the maximum of a tensor or maximum along an axis.

maximum(...): Element-wise maximum of x1 and x2.

mean(...): Compute the arithmetic mean along the specified axes.

median(...): Compute the median along the specified axis.

meshgrid(...): Creates grids of coordinates from coordinate vectors.

min(...): Return the minimum of a tensor or minimum along an axis.

minimum(...): Element-wise minimum of x1 and x2.

mod(...): Returns the element-wise remainder of division.

moveaxis(...): Move axes of a tensor to new positions.

multiply(...): Multiply arguments element-wise.

nan_to_num(...): Replace NaN with zero and infinity with large finite numbers.

nanargmax(...): Returns the indices of the maximum values along an axis, ignoring NaNs.

nanargmin(...): Returns the indices of the minimum values along an axis, ignoring NaNs.

nancumprod(...): Returns the cumulative product of elements along a given axis, treating NaNs as one.

nancumsum(...): Returns the cumulative sum of elements along a given axis, treating NaNs as zero.

nanmax(...): Maximum of a tensor over the given axes, ignoring NaNs.

nanmean(...): Mean of a tensor over the given axes, ignoring NaNs.

nanmedian(...): Median of a tensor over the given axes, ignoring NaNs.

nanmin(...): Minimum of a tensor over the given axes, ignoring NaNs.

nanpercentile(...): Compute the q-th percentile(s) of the data along the specified axis, while ignoring NaNs.

nanprod(...): Product of a tensor over the given axes, ignoring NaNs.

nanquantile(...): Compute the q-th quantile(s) of the data along the specified axis, while ignoring NaNs.

nanstd(...): Compute the standard deviation along the specified axes, ignoring NaNs.

nansum(...): Sum of a tensor over the given axes, ignoring NaNs.

nanvar(...): Compute the variance along the specified axes, ignoring NaNs.

ndim(...): Return the number of dimensions of a tensor.

negative(...): Numerical negative, element-wise.

nextafter(...): Return the next representable floating-point value after x1 towards x2.

nonzero(...): Return the indices of the elements that are non-zero.

not_equal(...): Return (x1 != x2) element-wise.

ones(...): Return a new tensor of given shape and type, filled with ones.

ones_like(...): Return a tensor of ones with the same shape and type of x.

outer(...): Compute the outer product of two vectors.

pad(...): Pad a tensor.

percentile(...): Compute the q-th percentile(s) of the data along the specified axis.

power(...): First tensor elements raised to powers from second tensor, element-wise.

prod(...): Return the product of tensor elements over a given axis.

ptp(...): Return the peak-to-peak (max - min) value of tensor elements over a given axis.

quantile(...): Compute the q-th quantile(s) of the data along the specified axis.

rad2deg(...): Convert angles from radians to degrees.

ravel(...): Return a contiguous flattened tensor.

real(...): Return the real part of the complex argument.

reciprocal(...): Return the reciprocal of the argument, element-wise.

repeat(...): Repeat each element of a tensor after themselves.

reshape(...): Gives a new shape to a tensor without changing its data.

right_shift(...): Shift the bits of an integer to the right.

roll(...): Roll tensor elements along a given axis.

rot90(...): Rotate an array by 90 degrees in the plane specified by axes.

round(...): Evenly round to the given number of decimals.

searchsorted(...): Perform a binary search, returning indices for insertion of values into sorted_sequence that maintain the sorting order.

select(...): Return elements from choicelist, based on conditions in condlist.

sign(...): Returns a tensor with the signs of the elements of x.

signbit(...): Return the sign bit of the elements of x.

sin(...): Trigonometric sine, element-wise.

sinc(...): Return the normalized sinc function.

sinh(...): Hyperbolic sine, element-wise.

size(...): Return the number of elements in a tensor.

slogdet(...): Compute the sign and natural logarithm of the determinant of a matrix.

sort(...): Sorts the elements of x along a given axis in ascending order.

split(...): Split a tensor into chunks.

sqrt(...): Return the non-negative square root of a tensor, element-wise.

square(...): Return the element-wise square of the input.

squeeze(...): Remove axes of length one from x.

stack(...): Join a sequence of tensors along a new axis.

std(...): Compute the standard deviation along the specified axis.

subtract(...): Subtract arguments element-wise.

sum(...): Sum of a tensor over the given axes.

swapaxes(...): Interchange two axes of a tensor.

take(...): Take elements from a tensor along an axis.

take_along_axis(...): Select values from x at the 1-D indices along the given axis.

tan(...): Compute tangent, element-wise.

tanh(...): Hyperbolic tangent, element-wise.

tensordot(...): Compute the tensor dot product along specified axes.

tile(...): Repeat x the number of times given by repeats.

trace(...): Return the sum along diagonals of the tensor.

transpose(...): Returns a tensor with axes transposed.

trapezoid(...): Integrate along the given axis using the composite trapezoidal rule.

tri(...): Return a tensor with ones at and below a diagonal and zeros elsewhere.

tril(...): Return lower triangle of a tensor.

triu(...): Return upper triangle of a tensor.

true_divide(...): Alias for keras.ops.divide.

trunc(...): Return the truncated value of the input, element-wise.

unique(...): Finds the unique elements of a tensor.

unravel_index(...): Convert flat indices to coordinate arrays in a given array shape.

vander(...): Generate a Vandermonde matrix.

var(...): Compute the variance along the specified axes.

vdot(...): Return the dot product of two vectors.

vectorize(...): Turn a function into a vectorized function.

view(...): Create a new bitwise view of the same data with the specified dtype.

vsplit(...): Split an array into multiple sub-arrays vertically (row-wise).

vstack(...): Stack tensors in sequence vertically (row wise).

where(...): Return elements chosen from x1 or x2 depending on condition.

zeros(...): Return a new tensor of given shape and type, filled with zeros.

zeros_like(...): Return a tensor of zeros with the same shape and type as x.