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This file was autogenerated. Do not edit it by hand, since your modifications would be overwritten.
Modules
image
module: DO NOT EDIT.
linalg
module: DO NOT EDIT.
nn
module: DO NOT EDIT.
numpy
module: DO NOT EDIT.
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
.
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.
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 minium values along an axis.
argsort(...)
: Returns the indices that would sort a tensor.
array(...)
: Create a tensor.
average(...)
: Compute the weighted average along the specified axis.
average_pool(...)
: Average pooling operation.
batch_normalization(...)
: Normalizes x
by mean
and variance
.
binary_crossentropy(...)
: Computes binary cross-entropy loss between target and output tensor.
bincount(...)
: Count the number of occurrences of each value in a tensor of integers.
broadcast_to(...)
: Broadcast a tensor to a new shape.
cast(...)
: Cast a tensor to the desired dtype.
categorical_crossentropy(...)
: Computes categorical cross-entropy loss between target and output tensor.
ceil(...)
: Return the ceiling of the input, element-wise.
cholesky(...)
: Computes the Cholesky decomposition of a positive semi-definite matrix.
clip(...)
: Clip (limit) the values in a tensor.
concatenate(...)
: Join a sequence of tensors along an existing axis.
cond(...)
: Conditionally applies true_fn
or false_fn
.
conj(...)
: Shorthand for keras.ops.conjugate
.
conjugate(...)
: Returns the complex conjugate, element-wise.
conv(...)
: General N-D convolution.
conv_transpose(...)
: General N-D convolution transpose.
convert_to_numpy(...)
: Convert a tensor to a NumPy array.
convert_to_tensor(...)
: Convert a NumPy array to a tensor.
copy(...)
: Returns a copy of x
.
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.
ctc_decode(...)
: Decodes the output of a CTC model.
ctc_loss(...)
: CTC (Connectionist Temporal Classification) loss.
cumprod(...)
: Return the cumulative product of elements along a given axis.
cumsum(...)
: Returns the cumulative sum of elements along a given axis.
custom_gradient(...)
: Decorator to define a function with a custom gradient.
depthwise_conv(...)
: General N-D depthwise convolution.
det(...)
: Computes the determinant of a square tensor.
diag(...)
: Extract a diagonal or construct a diagonal array.
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.
eig(...)
: Computes the eigenvalues and eigenvectors of a square matrix.
eigh(...)
: Computes the eigenvalues and eigenvectors of a complex Hermitian.
einsum(...)
: Evaluates the Einstein summation convention on the operands.
elu(...)
: Exponential Linear Unit activation function.
empty(...)
: Return a tensor of given shape and type filled with uninitialized data.
equal(...)
: Returns (x1 == x2)
element-wise.
erf(...)
: Computes the error function of x
, element-wise.
erfinv(...)
: Computes the inverse error function of x
, element-wise.
exp(...)
: Calculate the 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.
extract_sequences(...)
: Expands the dimension of last axis into sequences of sequence_length
.
eye(...)
: Return a 2-D tensor with ones on the diagonal and zeros elsewhere.
fft(...)
: Computes the Fast Fourier Transform along last axis of input.
fft2(...)
: Computes the 2D Fast Fourier Transform along the last two axes of input.
flip(...)
: Reverse the order of elements in the tensor along the given axis.
floor(...)
: Return the floor of the input, element-wise.
floor_divide(...)
: Returns the largest integer smaller or equal to the division of inputs.
fori_loop(...)
: For loop implementation.
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.
gelu(...)
: Gaussian Error Linear Unit (GELU) activation function.
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.
hard_sigmoid(...)
: Hard sigmoid activation function.
hard_silu(...)
: Hard SiLU activation function, also known as Hard Swish.
hard_swish(...)
: Hard SiLU activation function, also known as Hard Swish.
hstack(...)
: Stack tensors in sequence horizontally (column wise).
identity(...)
: Return the identity tensor.
imag(...)
: Return the imaginary part of the complex argument.
in_top_k(...)
: Checks if the targets are in the top-k predictions.
inv(...)
: Computes the inverse of a square tensor.
irfft(...)
: Inverse real-valued Fast Fourier transform along the last axis.
is_tensor(...)
: Check whether the given object is a tensor.
isclose(...)
: Return whether two tensors are element-wise almost equal.
isfinite(...)
: Return whether a tensor is finite, element-wise.
isinf(...)
: Test element-wise for positive or negative infinity.
isnan(...)
: Test element-wise for NaN and return result as a boolean tensor.
istft(...)
: Inverse Short-Time Fourier Transform along the last axis of the input.
leaky_relu(...)
: Leaky version of a Rectified Linear Unit activation function.
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.
log_sigmoid(...)
: Logarithm of the sigmoid activation function.
log_softmax(...)
: Log-softmax activation function.
logaddexp(...)
: 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.
logsumexp(...)
: Computes the logarithm of sum of exponentials of elements in a tensor.
lu_factor(...)
: Computes the lower-upper decomposition of a square matrix.
matmul(...)
: Matrix product of two tensors.
max(...)
: Return the maximum of a tensor or maximum along an axis.
max_pool(...)
: Max pooling operation.
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.
moments(...)
: Calculates the mean and variance of x
.
moveaxis(...)
: Move axes of a tensor to new positions.
multi_hot(...)
: Encodes integer labels as multi-hot vectors.
multiply(...)
: Multiply arguments element-wise.
nan_to_num(...)
: Replace NaN with zero and infinity with large finite numbers.
ndim(...)
: Return the number of dimensions of a tensor.
negative(...)
: Numerical negative, element-wise.
nonzero(...)
: Return the indices of the elements that are non-zero.
norm(...)
: Matrix or vector norm.
normalize(...)
: Normalizes x
over the specified axis.
not_equal(...)
: Return (x1 != x2)
element-wise.
one_hot(...)
: Converts integer tensor x
into a one-hot tensor.
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.
power(...)
: First tensor elements raised to powers from second tensor, element-wise.
prod(...)
: Return the product of tensor elements over a given axis.
psnr(...)
: Peak Signal-to-Noise Ratio (PSNR) function.
qr(...)
: Computes the QR decomposition of a tensor.
quantile(...)
: Compute the q-th quantile(s) of the data along the specified axis.
ravel(...)
: Return a contiguous flattened tensor.
real(...)
: Return the real part of the complex argument.
reciprocal(...)
: Return the reciprocal of the argument, element-wise.
relu(...)
: Rectified linear unit activation function.
relu6(...)
: Rectified linear unit activation function with upper bound of 6.
repeat(...)
: Repeat each element of a tensor after themselves.
reshape(...)
: Gives a new shape to a tensor without changing its data.
rfft(...)
: Real-valued Fast Fourier Transform along the last axis of the input.
roll(...)
: Roll tensor elements along a given axis.
round(...)
: Evenly round to the given number of decimals.
rsqrt(...)
: Computes reciprocal of square root of x element-wise.
scatter(...)
: Returns a tensor of shape shape
where indices
are set to values
.
scatter_update(...)
: Update inputs via updates at scattered (sparse) indices.
segment_max(...)
: Computes the max of segments in a tensor.
segment_sum(...)
: Computes the sum of segments in a tensor.
select(...)
: Return elements from choicelist
, based on conditions in condlist
.
selu(...)
: Scaled Exponential Linear Unit (SELU) activation function.
separable_conv(...)
: General N-D separable convolution.
shape(...)
: Gets the shape of the tensor input.
sigmoid(...)
: Sigmoid activation function.
sign(...)
: Returns a tensor with the signs of the elements of x
.
silu(...)
: Sigmoid Linear Unit (SiLU) activation function, also known as Swish.
sin(...)
: Trigonometric sine, element-wise.
sinh(...)
: Hyperbolic sine, element-wise.
size(...)
: Return the number of elements in a tensor.
slice(...)
: Return a slice of an input tensor.
slice_update(...)
: Update an input by slicing in a tensor of updated values.
slogdet(...)
: Compute the sign and natural logarithm of the determinant of a matrix.
softmax(...)
: Softmax activation function.
softplus(...)
: Softplus activation function.
softsign(...)
: Softsign activation function.
solve(...)
: Solves a linear system of equations given by a x = b
.
solve_triangular(...)
: Solves a linear system of equations given by a x = b
.
sort(...)
: Sorts the elements of x
along a given axis in ascending order.
sparse_categorical_crossentropy(...)
: Computes sparse categorical cross-entropy loss.
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.
stft(...)
: Short-Time Fourier Transform along the last axis of the input.
stop_gradient(...)
: Stops gradient computation.
subtract(...)
: Subtract arguments element-wise.
sum(...)
: Sum of a tensor over the given axes.
svd(...)
: Computes the singular value decomposition of a matrix.
swapaxes(...)
: Interchange two axes of a tensor.
swish(...)
: Sigmoid Linear Unit (SiLU) activation function, also known as Swish.
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
.
top_k(...)
: Finds the top-k values and their indices in a tensor.
trace(...)
: Return the sum along diagonals of the tensor.
transpose(...)
: Returns a tensor with axes
transposed.
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
.
unstack(...)
: Unpacks the given dimension of a rank-R tensor into rank-(R-1) tensors.
var(...)
: Compute the variance along the specified axes.
vdot(...)
: Return the dot product of two vectors.
vectorize(...)
: Turn a function into a vectorized function.
vectorized_map(...)
: Parallel map of function
on axis 0 of tensor(s) elements
.
vstack(...)
: Stack tensors in sequence vertically (row wise).
where(...)
: Return elements chosen from x1
or x2
depending on condition
.
while_loop(...)
: While loop implementation.
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
.