# tf.truncated_normal(shape, mean=0.0, stddev=1.0, dtype=tf.float32, seed=None, name=None)

### tf.truncated_normal(shape, mean=0.0, stddev=1.0, dtype=tf.float32, seed=None, name=None)

See the guide: Constants, Sequences, and Random Values > Random Tensors

Outputs random values from a truncated normal distribution.

The generated values follow a normal distribution with specified mean and standard deviation, except that values whose magnitude is more than 2 standard deviations from the mean are dropped and re-picked.

#### Args:

• shape: A 1-D integer Tensor or Python array. The shape of the output tensor.
• mean: A 0-D Tensor or Python value of type dtype. The mean of the truncated normal distribution.
• stddev: A 0-D Tensor or Python value of type dtype. The standard deviation of the truncated normal distribution.
• dtype: The type of the output.
• seed: A Python integer. Used to create a random seed for the distribution. See tf.set_random_seed for behavior.
• name: A name for the operation (optional).

#### Returns:

A tensor of the specified shape filled with random truncated normal values.