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Diffstat (limited to 'tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.contrib.distributions.LaplaceWithSoftplusScale.md')
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diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.contrib.distributions.LaplaceWithSoftplusScale.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.contrib.distributions.LaplaceWithSoftplusScale.md index cebf30a19a..49fe6c601f 100644 --- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.contrib.distributions.LaplaceWithSoftplusScale.md +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.contrib.distributions.LaplaceWithSoftplusScale.md @@ -277,54 +277,6 @@ a more accurate answer than simply taking the logarithm of the `cdf` when - - - -#### `tf.contrib.distributions.LaplaceWithSoftplusScale.log_pdf(value, name='log_pdf')` {#LaplaceWithSoftplusScale.log_pdf} - -Log probability density function. - -##### Args: - - -* <b>`value`</b>: `float` or `double` `Tensor`. -* <b>`name`</b>: The name to give this op. - -##### Returns: - - -* <b>`log_prob`</b>: a `Tensor` of shape `sample_shape(x) + self.batch_shape` with - values of type `self.dtype`. - -##### Raises: - - -* <b>`TypeError`</b>: if not `is_continuous`. - - -- - - - -#### `tf.contrib.distributions.LaplaceWithSoftplusScale.log_pmf(value, name='log_pmf')` {#LaplaceWithSoftplusScale.log_pmf} - -Log probability mass function. - -##### Args: - - -* <b>`value`</b>: `float` or `double` `Tensor`. -* <b>`name`</b>: The name to give this op. - -##### Returns: - - -* <b>`log_pmf`</b>: a `Tensor` of shape `sample_shape(x) + self.batch_shape` with - values of type `self.dtype`. - -##### Raises: - - -* <b>`TypeError`</b>: if `is_continuous`. - - -- - - - #### `tf.contrib.distributions.LaplaceWithSoftplusScale.log_prob(value, name='log_prob')` {#LaplaceWithSoftplusScale.log_prob} Log probability density/mass function (depending on `is_continuous`). @@ -455,54 +407,6 @@ Dictionary of parameters used to instantiate this `Distribution`. - - - -#### `tf.contrib.distributions.LaplaceWithSoftplusScale.pdf(value, name='pdf')` {#LaplaceWithSoftplusScale.pdf} - -Probability density function. - -##### Args: - - -* <b>`value`</b>: `float` or `double` `Tensor`. -* <b>`name`</b>: The name to give this op. - -##### Returns: - - -* <b>`prob`</b>: a `Tensor` of shape `sample_shape(x) + self.batch_shape` with - values of type `self.dtype`. - -##### Raises: - - -* <b>`TypeError`</b>: if not `is_continuous`. - - -- - - - -#### `tf.contrib.distributions.LaplaceWithSoftplusScale.pmf(value, name='pmf')` {#LaplaceWithSoftplusScale.pmf} - -Probability mass function. - -##### Args: - - -* <b>`value`</b>: `float` or `double` `Tensor`. -* <b>`name`</b>: The name to give this op. - -##### Returns: - - -* <b>`pmf`</b>: a `Tensor` of shape `sample_shape(x) + self.batch_shape` with - values of type `self.dtype`. - -##### Raises: - - -* <b>`TypeError`</b>: if `is_continuous`. - - -- - - - #### `tf.contrib.distributions.LaplaceWithSoftplusScale.prob(value, name='prob')` {#LaplaceWithSoftplusScale.prob} Probability density/mass function (depending on `is_continuous`). |