Module: tfp.experimental.distributions.marginal_fns.ps

Operations that use static values when possible.

Modules

dtype_util module: Utility functions for dtypes.

tensorshape_util module: Utility functions for TensorShape.

Functions

abs(...): Computes the absolute value of a tensor.

add(...): Returns x + y element-wise.

argmax(...): Returns the index with the largest value across axes of a tensor.

argmin(...): Returns the index with the smallest value across axes of a tensor.

argsort(...): Returns the indices of a tensor that give its sorted order along an axis.

broadcast_shape(...): Computes the shape of a broadcast.

broadcast_to(...): Broadcast an array for a compatible shape.

case(...): Like tf.case, except attempts to statically evaluate predicates.

cast(...): Casts a tensor to a new type.

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

concat(...): Concatenates tensors along one dimension.

cond(...): Return either true_fn() if predicate pred is true else false_fn().

constant(...): Creates a constant tensor from a tensor-like object.

convert_to_shape_tensor(...): Converts the given value to a Tensor.

cumprod(...): Compute the cumulative product of the tensor x along axis.

cumsum(...): Compute the cumulative sum of the tensor x along axis.

dimension_size(...): Equivalent to shape(x)[idx], but robust to partially-known shapes.

equal(...): Returns the truth value of (x == y) element-wise.

expand_dims(...): Returns a tensor with a length 1 axis inserted at index axis.

expm1(...): Computes exp(x) - 1 element-wise.

eye(...): Construct an identity matrix, or a batch of matrices.

fill(...): Creates a tensor filled with a scalar value.

floor(...): Returns element-wise largest integer not greater than x.

gather(...): Gather slices from params axis axis according to indices. (deprecated arguments)

greater(...): Returns the truth value of (x > y) element-wise.

identity(...): Return a Tensor with the same shape and contents as input.

invert_permutation(...): Computes the inverse permutation of a tensor.

is_finite(...): Returns which elements of x are finite.

is_inf(...): Returns which elements of x are Inf.

is_nan(...): Returns which elements of x are NaN.

is_numpy(...): Returns true if x is a numpy object.

less(...): Returns the truth value of (x < y) element-wise.

linspace(...): Generates evenly-spaced values in an interval along a given axis.

log(...): Computes natural logarithm of x element-wise.

log1p(...): Computes natural logarithm of (1 + x) element-wise.

logical_and(...): Returns the truth value of x AND y element-wise.

logical_not(...): Returns the truth value of NOT x element-wise.

logical_or(...): Returns the truth value of x OR y element-wise.

maximum(...): Returns the max of x and y (i.e. x > y ? x : y) element-wise.

minimum(...): Returns the min of x and y (i.e. x < y ? x : y) element-wise.

nextafter(...): Returns the next representable value of x1 in the direction of x2, element-wise.

non_negative_axis(...): Make (possibly negatively indexed) axis argument non-negative.

not_equal(...): Returns the truth value of (x != y) element-wise.

one_hot(...): Returns a one-hot tensor.

ones(...): Creates a tensor with all elements set to one (1).

ones_like(...): Creates a tensor of all ones that has the same shape as the input.

pad(...): Pads a tensor.

pow(...): Computes the power of one value to another.

range(...): Creates a sequence of numbers.

rank(...): Returns the rank of a tensor.

rank_from_shape(...): Computes rank given a Tensor's shape.

reduce_all(...): Computes tf.math.logical_and of elements across dimensions of a tensor.

reduce_any(...): Computes tf.math.logical_or of elements across dimensions of a tensor.

reduce_max(...): Computes tf.math.maximum of elements across dimensions of a tensor.

reduce_min(...): Computes the tf.math.minimum of elements across dimensions of a tensor.

reduce_prod(...): Computes tf.math.multiply of elements across dimensions of a tensor.

reduce_sum(...): Computes the sum of elements across dimensions of a tensor.

repeat(...): Repeat elements of input.

reshape(...): Reshapes a tensor.

reverse(...): Reverses specific dimensions of a tensor.

round(...): Rounds the values of a tensor to the nearest integer, element-wise.

rsqrt(...): Computes reciprocal of square root of x element-wise.

setdiff1d(...): Compute set difference of elements in last dimension of a and b.

shape(...): Returns a tensor containing the shape of the input tensor.

shape_slice(...): Equivalent to shape(x)[slice_], but robust to partially-known shapes.

size(...): Returns the size of a tensor.

size0(...): Returns the size of the first dimension (0 if scalar).

slice(...): Extracts a slice from a tensor.

smart_where(...): As tf.where, but only calls x_fn/y_fn when condition not statically known.

sort(...): Sorts a tensor.

split(...): Splits a tensor value into a list of sub tensors.

sqrt(...): Computes element-wise square root of the input tensor.

stack(...): Stacks a list of rank-R tensors into one rank-(R+1) tensor.

tensor_scatter_nd_add(...): Adds sparse updates to an existing tensor according to indices.

tensor_scatter_nd_sub(...): Subtracts sparse updates from an existing tensor according to indices.

tensor_scatter_nd_update(...): Scatter updates into an existing tensor according to indices.

tile(...): Constructs a tensor by tiling a given tensor.

top_k(...): Finds values and indices of the k largest entries for the last dimension.

unique(...): Finds unique elements in a 1-D tensor.

unstack(...): Unpacks the given dimension of a rank-R tensor into rank-(R-1) tensors.

where(...): Returns the indices of non-zero elements, or multiplexes x and y.

zeros(...): Creates a tensor with all elements set to zero.

zeros_like(...): Creates a tensor with all elements set to zero.

JAX_MODE False