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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 | 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 float type of the output: float16, bfloat16, float32, float64. Defaults to float32. |
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. |
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