tf.random.normal
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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
)
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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Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tf.random.normal\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/ops/random_ops.py#L42-L98) |\n\nOutputs random values from a normal distribution.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.random.normal`](https://www.tensorflow.org/api_docs/python/tf/random/normal), [`tf.compat.v1.random_normal`](https://www.tensorflow.org/api_docs/python/tf/random/normal)\n\n\u003cbr /\u003e\n\n tf.random.normal(\n shape,\n mean=0.0,\n stddev=1.0,\n dtype=../../tf/dtypes#float32,\n seed=None,\n name=None\n )\n\nExample that generates a new set of random values every time: \n\n tf.random.set_seed(5);\n tf.random.normal([4], 0, 1, tf.float32)\n \u003ctf.Tensor: shape=(4,), dtype=float32, numpy=..., dtype=float32)\u003e\n\nExample that outputs a reproducible result: \n\n tf.random.set_seed(5);\n tf.random.normal([2,2], 0, 1, tf.float32, seed=1)\n \u003ctf.Tensor: shape=(2, 2), dtype=float32, numpy=\n array([[-1.3768897 , -0.01258316],\n [-0.169515 , 1.0824056 ]], dtype=float32)\u003e\n\nIn this case, we are setting both the global and operation-level seed to\nensure this result is reproducible. See [`tf.random.set_seed`](../../tf/random/set_seed) for more\ninformation.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------|-----------------------------------------------------------------------------------------------------------------------------------------|\n| `shape` | A 1-D integer Tensor or Python array. The shape of the output tensor. |\n| `mean` | A Tensor or Python value of type `dtype`, broadcastable with `stddev`. The mean of the normal distribution. |\n| `stddev` | A Tensor or Python value of type `dtype`, broadcastable with `mean`. The standard deviation of the normal distribution. |\n| `dtype` | The float type of the output: `float16`, `bfloat16`, `float32`, `float64`. Defaults to `float32`. |\n| `seed` | A Python integer. Used to create a random seed for the distribution. See [`tf.random.set_seed`](../../tf/random/set_seed) for behavior. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A tensor of the specified shape filled with random normal values. ||\n\n\u003cbr /\u003e"]]
View source on GitHub