tf.compat.v1.math.log

Computes softmax activations. (deprecated arguments)

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Compat aliases for migration

tf.compat.v1.nn.softmax

tf.compat.v1.math.softmax(
    logits, axis=None, name=None, dim=None
)

Used in the notebooks

Used in the tutorials
Classify Flowers with Transfer Learning

This function performs the equivalent of

softmax = tf.exp(logits) / tf.reduce_sum(tf.exp(logits), axis)

See: https://en.wikipedia.org/wiki/Softmax_function

Example usage:

tf.nn.softmax([-1, 0., 1.])
<tf.Tensor: shape=(3,), dtype=float32,
numpy=array([0.09003057, 0.24472848, 0.66524094], dtype=float32)>

Args
`logits`	A non-empty `Tensor`, or an object whose type has a registered `Tensor` conversion function. Must be one of the following types: `half`,`float32`, `float64`. See also `convert_to_tensor`
`axis`	The dimension softmax would be performed on. The default is -1 which indicates the last dimension.
`name`	A name for the operation (optional).
`dim`	Deprecated alias for `axis`.

Returns
A `Tensor`. Has the same type and shape as `logits`.

Raises
`InvalidArgumentError`	if `logits` is empty or `axis` is beyond the last dimension of `logits`.
`TypeError`	If no conversion function is registered for `logits` to Tensor.
`RuntimeError`	If a registered conversion function returns an invalid value.

TensorFlow

tf.compat / v1 / v1.math.log_softmax

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Used in the notebooks

Example usage:

Args

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TensorFlow

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tf.compat / v1 / v1.math.log_softmax

View aliases

Used in the notebooks

Example usage:

Args

Returns

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