import tensorflow as tf
import numpy as np


def uniform(shape, scale=0.05, name=None):
    """Uniform init."""
    initial = tf.random_uniform(shape, minval=-scale, maxval=scale, dtype=tf.float32)
    return tf.Variable(initial, name=name)


def glorot(shape, name=None):
    """Glorot & Bengio (AISTATS 2010) init."""
    if len(shape) == 2:
        init_range = np.sqrt(6.0 / (shape[0] + shape[1]))
    elif len(shape) == 1:
        init_range = np.sqrt(6.0 / shape[0])
    initial = tf.random_uniform(shape, minval=-init_range, maxval=init_range, dtype=tf.float32)
    return tf.get_variable(initializer=initial, name=name)


def zeros(shape, name=None):
    """All zeros."""
    initial = tf.zeros(shape, dtype=tf.float32)
    return tf.Variable(initial, name=name)


def ones(shape, name=None):
    """All ones."""
    initial = tf.ones(shape, dtype=tf.float32)
    return tf.Variable(initial, name=name)
