"""Math operations that are specific to extremely quantized networks."""

import tensorflow as tf


def sign(x):
    r"""A sign function that will never be zero
    \\[
    f(x) = \begin{cases}
      -1 & x < 0 \\\
      1 & x \geq 0
    \end{cases}
    \\]

    This function is similar to
    [`tf.math.sign`](https://www.tensorflow.org/api_docs/python/tf/math/sign) but will
    return a binary value and will never be zero.

    # Arguments
        `x`: Input Tensor

    # Returns
        A Tensor with same type as `x`.
    """
    return tf.sign(tf.sign(x) + 0.1)


def heaviside(x):
    r"""Heaviside step function with output values 0 and 1.

    \\[
    q(x) = \begin{cases}
    +1 & x > 0 \\\
    0 & x \leq 0
    \end{cases}
    \\]

    # Arguments
        `x`: Input Tensor

    # Returns
        A Tensor with same type as `x`.
    """
    return tf.sign(tf.nn.relu(x))

"""Math operations that are specific to extremely quantized networks."""

import tensorflow as tf


def sign(x):
    r"""A sign function that will never be zero
    \\[
    f(x) = \begin{cases}
      -1 & x < 0 \\\
      \hphantom{-}1 & x \geq 0
    \end{cases}
    \\]

    This function is similar to
    [`tf.math.sign`](https://www.tensorflow.org/api_docs/python/tf/math/sign) but will
    return a binary value and will never be zero.

    # Arguments
        `x`: Input Tensor

    # Returns
        A Tensor with same type as `x`.
    """
    return tf.sign(tf.sign(x) + 0.1)


def heaviside(x):
    r"""Heaviside step function with output values 0 and 1.

    \\[
    q(x) = \begin{cases}
    +1 & x > 0 \\\
    \hphantom{+}0 & x \leq 0
    \end{cases}
    \\]

    # Arguments
        `x`: Input Tensor

    # Returns
        A Tensor with same type as `x`.
    """
    return tf.sign(tf.nn.relu(x))

Improve alignment of LaTeX formulas (#501)