Module: tf.compat.v1.math   Math Operations. 
Note: Functions taking Tensor arguments can also take anything accepted by tf.convert_to_tensor.


Note: Elementwise binary operations in TensorFlow follow numpy-style broadcasting.
 TensorFlow provides a variety of math functions including:  Basic arithmetic operators and trigonometric functions. Special math functions (like: tf.math.igamma and tf.math.zeta) Complex number functions (like: tf.math.imag and tf.math.angle) Reductions and scans (like: tf.math.reduce_mean and tf.math.cumsum) Segment functions (like: tf.math.segment_sum)  See: tf.linalg for matrix and tensor functions. About Segmentation TensorFlow provides several operations that you can use to perform common math computations on tensor segments. Here a segmentation is a partitioning of a tensor along the first dimension, i.e. it defines a mapping from the first dimension onto segment_ids. The segment_ids tensor should be the size of the first dimension, d0, with consecutive IDs in the range 0 to k, where k<d0. In particular, a segmentation of a matrix tensor is a mapping of rows to segments. For example: c = tf.constant([[1,2,3,4], [-1,-2,-3,-4], [5,6,7,8]])
tf.math.segment_sum(c, tf.constant([0, 0, 1]))
#  ==>  [[0 0 0 0]
#        [5 6 7 8]]
 The standard segment_* functions assert that the segment indices are sorted. If you have unsorted indices use the equivalent unsorted_segment_ function. These functions take an additional argument num_segments so that the output tensor can be efficiently allocated. c = tf.constant([[1,2,3,4], [-1,-2,-3,-4], [5,6,7,8]])
tf.math.unsorted_segment_sum(c, tf.constant([0, 1, 0]), num_segments=2)
# ==> [[ 6,  8, 10, 12],
#       [-1, -2, -3, -4]]
 Modules special module: Public API for tf.math.special namespace. Functions abs(...): Computes the absolute value of a tensor. accumulate_n(...): Returns the element-wise sum of a list of tensors. acos(...): Computes acos of x element-wise. acosh(...): Computes inverse hyperbolic cosine of x element-wise. add(...): Returns x + y element-wise. add_n(...): Adds all input tensors element-wise. angle(...): Returns the element-wise argument of a complex (or real) tensor. argmax(...): Returns the index with the largest value across axes of a tensor. (deprecated arguments) argmin(...): Returns the index with the smallest value across axes of a tensor. (deprecated arguments) asin(...): Computes the trignometric inverse sine of x element-wise. asinh(...): Computes inverse hyperbolic sine of x element-wise. atan(...): Computes the trignometric inverse tangent of x element-wise. atan2(...): Computes arctangent of y/x element-wise, respecting signs of the arguments. atanh(...): Computes inverse hyperbolic tangent of x element-wise. bessel_i0(...): Computes the Bessel i0 function of x element-wise. bessel_i0e(...): Computes the Bessel i0e function of x element-wise. bessel_i1(...): Computes the Bessel i1 function of x element-wise. bessel_i1e(...): Computes the Bessel i1e function of x element-wise. betainc(...): Compute the regularized incomplete beta integral \(I_x(a, b)\). bincount(...): Counts the number of occurrences of each value in an integer array. ceil(...): Return the ceiling of the input, element-wise. confusion_matrix(...): Computes the confusion matrix from predictions and labels. conj(...): Returns the complex conjugate of a complex number. cos(...): Computes cos of x element-wise. cosh(...): Computes hyperbolic cosine of x element-wise. count_nonzero(...): Computes number of nonzero elements across dimensions of a tensor. (deprecated arguments) (deprecated arguments) cumprod(...): Compute the cumulative product of the tensor x along axis. cumsum(...): Compute the cumulative sum of the tensor x along axis. cumulative_logsumexp(...): Compute the cumulative log-sum-exp of the tensor x along axis. digamma(...): Computes Psi, the derivative of Lgamma (the log of the absolute value of divide(...): Computes Python style division of x by y. divide_no_nan(...): Computes a safe divide which returns 0 if the y is zero. equal(...): Returns the truth value of (x == y) element-wise. erf(...): Computes the Gauss error function of x element-wise. erfc(...): Computes the complementary error function of x element-wise. erfcinv(...): Computes the inverse of complementary error function. erfinv(...): Compute inverse error function. exp(...): Computes exponential of x element-wise. \(y = e^x\). expm1(...): Computes exp(x) - 1 element-wise. floor(...): Returns element-wise largest integer not greater than x. floordiv(...): Divides x / y elementwise, rounding toward the most negative integer. floormod(...): Returns element-wise remainder of division. When x < 0 xor y < 0 is greater(...): Returns the truth value of (x > y) element-wise. greater_equal(...): Returns the truth value of (x >= y) element-wise. igamma(...): Compute the lower regularized incomplete Gamma function P(a, x). igammac(...): Compute the upper regularized incomplete Gamma function Q(a, x). imag(...): Returns the imaginary part of a complex (or real) tensor. in_top_k(...): Says whether the targets are in the top K predictions. 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_non_decreasing(...): Returns True if x is non-decreasing. is_strictly_increasing(...): Returns True if x is strictly increasing. l2_normalize(...): Normalizes along dimension axis using an L2 norm. (deprecated arguments) lbeta(...): Computes \(ln(|Beta(x)|)\), reducing along the last dimension. less(...): Returns the truth value of (x < y) element-wise. less_equal(...): Returns the truth value of (x <= y) element-wise. lgamma(...): Computes the log of the absolute value of Gamma(x) element-wise. log(...): Computes natural logarithm of x element-wise. log1p(...): Computes natural logarithm of (1 + x) element-wise. log_sigmoid(...): Computes log sigmoid of x element-wise. log_softmax(...): Computes log softmax activations. (deprecated arguments) logical_and(...): Logical AND function. logical_not(...): Returns the truth value of NOT x element-wise. logical_or(...): Returns the truth value of x OR y element-wise. logical_xor(...): Logical XOR function. 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. mod(...): Returns element-wise remainder of division. When x < 0 xor y < 0 is multiply(...): Returns an element-wise x * y. multiply_no_nan(...): Computes the product of x and y and returns 0 if the y is zero, even if x is NaN or infinite. ndtri(...): Compute quantile of Standard Normal. negative(...): Computes numerical negative value element-wise. nextafter(...): Returns the next representable value of x1 in the direction of x2, element-wise. not_equal(...): Returns the truth value of (x != y) element-wise. polygamma(...): Compute the polygamma function \(\psi^{(n)}(x)\). polyval(...): Computes the elementwise value of a polynomial. pow(...): Computes the power of one value to another. real(...): Returns the real part of a complex (or real) tensor. reciprocal(...): Computes the reciprocal of x element-wise. reciprocal_no_nan(...): Performs a safe reciprocal operation, element wise. reduce_all(...): Computes the "logical and" of elements across dimensions of a tensor. (deprecated arguments) reduce_any(...): Computes the "logical or" of elements across dimensions of a tensor. (deprecated arguments) reduce_euclidean_norm(...): Computes the Euclidean norm of elements across dimensions of a tensor. reduce_logsumexp(...): Computes log(sum(exp(elements across dimensions of a tensor))). (deprecated arguments) reduce_max(...): Computes the maximum of elements across dimensions of a tensor. (deprecated arguments) reduce_mean(...): Computes the mean of elements across dimensions of a tensor. reduce_min(...): Computes the minimum of elements across dimensions of a tensor. (deprecated arguments) reduce_prod(...): Computes the product of elements across dimensions of a tensor. (deprecated arguments) reduce_std(...): Computes the standard deviation of elements across dimensions of a tensor. reduce_sum(...): Computes the sum of elements across dimensions of a tensor. (deprecated arguments) reduce_variance(...): Computes the variance of elements across dimensions of a tensor. rint(...): Returns element-wise integer closest to x. round(...): Rounds the values of a tensor to the nearest integer, element-wise. rsqrt(...): Computes reciprocal of square root of x element-wise. scalar_mul(...): Multiplies a scalar times a Tensor or IndexedSlices object. segment_max(...): Computes the maximum along segments of a tensor. segment_mean(...): Computes the mean along segments of a tensor. segment_min(...): Computes the minimum along segments of a tensor. segment_prod(...): Computes the product along segments of a tensor. segment_sum(...): Computes the sum along segments of a tensor. sigmoid(...): Computes sigmoid of x element-wise. sign(...): Returns an element-wise indication of the sign of a number. sin(...): Computes sine of x element-wise. sinh(...): Computes hyperbolic sine of x element-wise. sobol_sample(...): Generates points from the Sobol sequence. softmax(...): Computes softmax activations. (deprecated arguments) softplus(...): Computes softplus: log(exp(features) + 1). softsign(...): Computes softsign: features / (abs(features) + 1). sqrt(...): Computes element-wise square root of the input tensor. square(...): Computes square of x element-wise. squared_difference(...): Returns conj(x - y)(x - y) element-wise. subtract(...): Returns x - y element-wise. tan(...): Computes tan of x element-wise. tanh(...): Computes hyperbolic tangent of x element-wise. top_k(...): Finds values and indices of the k largest entries for the last dimension. truediv(...): Divides x / y elementwise (using Python 3 division operator semantics). unsorted_segment_max(...): Computes the maximum along segments of a tensor. unsorted_segment_mean(...): Computes the mean along segments of a tensor. unsorted_segment_min(...): Computes the minimum along segments of a tensor. unsorted_segment_prod(...): Computes the product along segments of a tensor. unsorted_segment_sqrt_n(...): Computes the sum along segments of a tensor divided by the sqrt(N). unsorted_segment_sum(...): Computes the sum along segments of a tensor. xdivy(...): Returns 0 if x == 0, and x / y otherwise, elementwise. xlog1py(...): Compute x * log1p(y). xlogy(...): Returns 0 if x == 0, and x * log(y) otherwise, elementwise. zero_fraction(...): Returns the fraction of zeros in value. zeta(...): Compute the Hurwitz zeta function \(\zeta(x, q)\).