tf.random_gamma
tf.random_gamma
tf.random_gamma
random_gamma( shape, alpha, beta=None, dtype=tf.float32, seed=None, name=None )
Defined in tensorflow/python/ops/random_ops.py
.
See the guide: Constants, Sequences, and Random Values > Random Tensors
Draws shape
samples from each of the given Gamma distribution(s).
alpha
is the shape parameter describing the distribution(s), and beta
is the inverse scale parameter(s).
Example:
samples = tf.random_gamma([10], [0.5, 1.5]) # samples has shape [10, 2], where each slice [:, 0] and [:, 1] represents # the samples drawn from each distribution
samples = tf.random_gamma([7, 5], [0.5, 1.5]) # samples has shape [7, 5, 2], where each slice [:, :, 0] and [:, :, 1] # represents the 7x5 samples drawn from each of the two distributions
samples = tf.random_gamma([30], [[1.],[3.],[5.]], beta=[[3., 4.]]) # samples has shape [30, 3, 2], with 30 samples each of 3x2 distributions.
Note: Because internal calculations are done using float64
and casting has floor
semantics, we must manually map zero outcomes to the smallest possible positive floating-point value, i.e., np.finfo(dtype).tiny
. This means that np.finfo(dtype).tiny
occurs more frequently than it otherwise should. This bias can only happen for small values of alpha
, i.e., alpha << 1
or large values of beta
, i.e., beta >> 1
.
Args:
-
shape
: A 1-D integer Tensor or Python array. The shape of the output samples to be drawn per alpha/beta-parameterized distribution. -
alpha
: A Tensor or Python value or N-D array of typedtype
.alpha
provides the shape parameter(s) describing the gamma distribution(s) to sample. Must be broadcastable withbeta
. -
beta
: A Tensor or Python value or N-D array of typedtype
. Defaults to 1.beta
provides the inverse scale parameter(s) of the gamma distribution(s) to sample. Must be broadcastable withalpha
. -
dtype
: The type of alpha, beta, and the output:float16
,float32
, orfloat64
. -
seed
: A Python integer. Used to create a random seed for the distributions. Seetf.set_random_seed
for behavior. -
name
: Optional name for the operation.
Returns:
-
samples
: aTensor
of shapetf.concat(shape, tf.shape(alpha + beta))
with values of typedtype
.
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/random_gamma