tf.contrib.gan.features.tensor_pool(
input_values,
pool_size=50,
pooling_probability=0.5,
name='tensor_pool'
)
Defined in tensorflow/contrib/gan/python/features/python/random_tensor_pool_impl.py
.
Queue storing input values and returning random previously stored ones.
Every time the returned output_value
is evaluated, input_value
is
evaluated and its value either directly returned (with
1-pooling_probability
) or stored in the pool and a random one of the samples
currently in the pool is popped and returned. As long as the pool in not fully
filled, the input_value is always directly returned, as well as stored in the
pool. Note during inference / testing, it may be appropriate to set
pool_size
= 0 or pooling_probability
= 0.
Args:
input_values
: An arbitrarily nested structure oftf.Tensors
, from which to read values to be pooled.pool_size
: An integer specifying the maximum size of the pool. Defaults to 50.pooling_probability
: A floatTensor
specifying the probability of getting a value from the pool, as opposed to just the current input.name
: A string prefix for the name scope for all tensorflow ops.
Returns:
A nested structure of Tensor
objects with the same structure as
input_values
. With the given probability, the Tensor values are either the
same as in input_values
or a randomly chosen sample that was previously
inserted in the pool.
Raises:
ValueError
: Ifpool_size
is negative.