tf.random.stateless_normal
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Outputs deterministic pseudorandom values from a normal distribution.
tf.random.stateless_normal(
shape,
seed,
mean=0.0,
stddev=1.0,
dtype=tf.dtypes.float32,
name=None,
alg='auto_select'
)
This is a stateless version of tf.random.normal: if run twice with the
same seeds and shapes, it will produce the same pseudorandom numbers. The
output is consistent across multiple runs on the same hardware (and between
CPU and GPU), but may change between versions of TensorFlow or on non-CPU/GPU
hardware.
Args |
|---|
shape
|
A 1-D integer Tensor or Python array. The shape of the output tensor.
|
seed
|
A shape [2] Tensor, the seed to the random number generator. Must have
dtype int32 or int64. (When using XLA, only int32 is allowed.)
|
mean
|
A 0-D Tensor or Python value of type dtype. The mean of the normal
distribution.
|
stddev
|
A 0-D Tensor or Python value of type dtype. The standard deviation
of the normal distribution.
|
dtype
|
The float type of the output: float16, bfloat16, float32,
float64. Defaults to float32.
|
name
|
A name for the operation (optional).
|
alg
|
The RNG algorithm used to generate the random numbers. See
tf.random.stateless_uniform for a detailed explanation.
|
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.stateless_normal\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/ops/stateless_random_ops.py#L764-L808) |\n\nOutputs deterministic pseudorandom 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.stateless_normal`](https://www.tensorflow.org/api_docs/python/tf/random/stateless_normal)\n\n\u003cbr /\u003e\n\n tf.random.stateless_normal(\n shape,\n seed,\n mean=0.0,\n stddev=1.0,\n dtype=../../tf/dtypes#float32,\n name=None,\n alg='auto_select'\n )\n\nThis is a stateless version of [`tf.random.normal`](../../tf/random/normal): if run twice with the\nsame seeds and shapes, it will produce the same pseudorandom numbers. The\noutput is consistent across multiple runs on the same hardware (and between\nCPU and GPU), but may change between versions of TensorFlow or on non-CPU/GPU\nhardware.\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| `seed` | A shape \\[2\\] Tensor, the seed to the random number generator. Must have dtype `int32` or `int64`. (When using XLA, only `int32` is allowed.) |\n| `mean` | A 0-D Tensor or Python value of type `dtype`. The mean of the normal distribution. |\n| `stddev` | A 0-D Tensor or Python value of type `dtype`. The standard deviation of the normal distribution. |\n| `dtype` | The float type of the output: `float16`, `bfloat16`, `float32`, `float64`. Defaults to `float32`. |\n| `name` | A name for the operation (optional). |\n| `alg` | The RNG algorithm used to generate the random numbers. See [`tf.random.stateless_uniform`](../../tf/random/stateless_uniform) for a detailed explanation. |\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