TensorFlow 1 version | View source on GitHub |
Outputs random values from a normal distribution.
tf.random.normal(
shape, mean=0.0, stddev=1.0, dtype=tf.dtypes.float32, seed=None, name=None
)
Example that generates a new set of random values every time:
tf.random.set_seed(5);
tf.random.normal([4], 0, 1, tf.float32)
<tf.Tensor: shape=(4,), dtype=float32, numpy=..., dtype=float32)>
Example that outputs a reproducible result:
tf.random.set_seed(5);
tf.random.normal([2,2], 0, 1, tf.float32, seed=1)
<tf.Tensor: shape=(2, 2), dtype=float32, numpy=
array([[-1.3768897 , -0.01258316],
[-0.169515 , 1.0824056 ]], dtype=float32)>
In this case, we are setting both the global and operation-level seed to
ensure this result is reproducible. See tf.random.set_seed
for more
information.
Args | |
---|---|
shape
|
A 1-D integer Tensor or Python array. The shape of the output tensor. |
mean
|
A Tensor or Python value of type dtype , broadcastable with stddev .
The mean of the normal distribution.
|
stddev
|
A Tensor or Python value of type dtype , broadcastable with mean .
The standard deviation of the normal distribution.
|
dtype
|
The type of the output. |
seed
|
A Python integer. Used to create a random seed for the distribution.
See
tf.random.set_seed
for behavior.
|
name
|
A name for the operation (optional). |
Returns | |
---|---|
A tensor of the specified shape filled with random normal values. |