tf.math.log_sigmoid
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Computes log sigmoid of x element-wise.
tf.math.log_sigmoid(
x, name=None
)
Specifically, y = log(1 / (1 + exp(-x))). For numerical stability,
we use y = -tf.nn.softplus(-x).
Args |
|---|
x
|
A Tensor with type float32 or float64.
|
name
|
A name for the operation (optional).
|
Returns |
|---|
A Tensor with the same type as x.
|
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Last updated 2020-10-01 UTC.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.math.log_sigmoid\n\n\u003cbr /\u003e\n\n|-----------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 1 version](/versions/r1.15/api_docs/python/tf/math/log_sigmoid) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.0.0/tensorflow/python/ops/math_ops.py#L3135-L3153) |\n\nComputes log sigmoid of `x` element-wise.\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.log_sigmoid`](/api_docs/python/tf/math/log_sigmoid), [`tf.compat.v1.math.log_sigmoid`](/api_docs/python/tf/math/log_sigmoid)\n\n\u003cbr /\u003e\n\n tf.math.log_sigmoid(\n x, name=None\n )\n\nSpecifically, `y = log(1 / (1 + exp(-x)))`. For numerical stability,\nwe use `y = -tf.nn.softplus(-x)`.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|--------|--------------------------------------------|\n| `x` | A Tensor with type `float32` or `float64`. |\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 with the same type as `x`. ||\n\n\u003cbr /\u003e"]]
TensorFlow 1 version
View source on GitHub