tf.keras.initializers.RandomNormal
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Initializer that generates tensors with a normal distribution.
Inherits From: random_normal_initializer
tf.keras.initializers.RandomNormal(
mean=0.0, stddev=0.05, seed=None, dtype=tf.dtypes.float32
)
Args |
|---|
mean
|
a python scalar or a scalar tensor. Mean of the random values to
generate. Defaults to 0.
|
stddev
|
a python scalar or a scalar tensor. Standard deviation of the random
values to generate. Defaults to 0.05.
|
seed
|
A Python integer. Used to create random seeds. See
tf.compat.v1.set_random_seed for behavior.
|
dtype
|
The data type. Only floating point types are supported.
|
Returns |
|---|
|
RandomNormal instance.
|
Methods
from_config
View source
@classmethod
from_config(
config
)
Instantiates an initializer from a configuration dictionary.
Example:
initializer = RandomUniform(-1, 1)
config = initializer.get_config()
initializer = RandomUniform.from_config(config)
| Args |
|---|
config
|
A Python dictionary. It will typically be the output of
get_config.
|
| Returns |
|---|
|
An Initializer instance.
|
get_config
View source
get_config()
Returns the configuration of the initializer as a JSON-serializable dict.
| Returns |
|---|
|
A JSON-serializable Python dict.
|
__call__
View source
__call__(
shape, dtype=None, partition_info=None
)
Returns a tensor object initialized as specified by the initializer.
| Args |
|---|
shape
|
Shape of the tensor.
|
dtype
|
Optional dtype of the tensor. If not provided use the initializer
dtype.
|
partition_info
|
Optional information about the possible partitioning of a
tensor.
|
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Last updated 2020-10-01 UTC.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.keras.initializers.RandomNormal\n\n\u003cbr /\u003e\n\n|-----------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 2 version](/api_docs/python/tf/keras/initializers/RandomNormal) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/keras/initializers.py#L125-L143) |\n\nInitializer that generates tensors with a normal distribution.\n\nInherits From: [`random_normal_initializer`](../../../tf/random_normal_initializer)\n\n#### View aliases\n\n\n**Main aliases**\n\n\\`tf.keras.initializers.normal\\`, [`tf.keras.initializers.random_normal`](/api_docs/python/tf/keras/initializers/RandomNormal)\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.keras.initializers.RandomNormal`](/api_docs/python/tf/compat/v1/keras/initializers/RandomNormal), [`tf.compat.v1.keras.initializers.normal`](/api_docs/python/tf/compat/v1/keras/initializers/RandomNormal), [`tf.compat.v1.keras.initializers.random_normal`](/api_docs/python/tf/compat/v1/keras/initializers/RandomNormal)\n\n\u003cbr /\u003e\n\n tf.keras.initializers.RandomNormal(\n mean=0.0, stddev=0.05, seed=None, dtype=tf.dtypes.float32\n )\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------|---------------------------------------------------------------------------------------------------------------------------------------|\n| `mean` | a python scalar or a scalar tensor. Mean of the random values to generate. Defaults to 0. |\n| `stddev` | a python scalar or a scalar tensor. Standard deviation of the random values to generate. Defaults to 0.05. |\n| `seed` | A Python integer. Used to create random seeds. See [`tf.compat.v1.set_random_seed`](../../../tf/random/set_random_seed) for behavior. |\n| `dtype` | The data type. Only floating point types are supported. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| RandomNormal instance. ||\n\n\u003cbr /\u003e\n\nMethods\n-------\n\n### `from_config`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/ops/init_ops.py#L78-L97) \n\n @classmethod\n from_config(\n config\n )\n\nInstantiates an initializer from a configuration dictionary.\n\n#### Example:\n\n initializer = RandomUniform(-1, 1)\n config = initializer.get_config()\n initializer = RandomUniform.from_config(config)\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|----------|-----------------------------------------------------------------------|\n| `config` | A Python dictionary. It will typically be the output of `get_config`. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| An Initializer instance. ||\n\n\u003cbr /\u003e\n\n### `get_config`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/ops/init_ops.py#L325-L331) \n\n get_config()\n\nReturns the configuration of the initializer as a JSON-serializable dict.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| A JSON-serializable Python dict. ||\n\n\u003cbr /\u003e\n\n### `__call__`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/ops/init_ops.py#L319-L323) \n\n __call__(\n shape, dtype=None, partition_info=None\n )\n\nReturns a tensor object initialized as specified by the initializer.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|------------------|--------------------------------------------------------------------------|\n| `shape` | Shape of the tensor. |\n| `dtype` | Optional dtype of the tensor. If not provided use the initializer dtype. |\n| `partition_info` | Optional information about the possible partitioning of a tensor. |\n\n\u003cbr /\u003e"]]
TensorFlow 2 version
View source on GitHub