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
)
Used in the notebooks
| Used in the guide | Used in the tutorials |
|---|---|
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
mean
dtype, broadcastable with stddev.
The mean of the normal distribution.
stddev
dtype, broadcastable with mean.
The standard deviation of the normal distribution.
dtype
float16, bfloat16, float32,
float64. Defaults to float32.
seed
tf.random.set_seed
for behavior.
name
Returns | |
|---|---|
| A tensor of the specified shape filled with random normal values. |
View source on GitHub