tf.contrib.training.resample_at_rate(
inputs,
rates,
scope=None,
seed=None,
back_prop=False
)
Defined in tensorflow/contrib/training/python/training/resample.py.
Given inputs tensors, stochastically resamples each at a given rate.
For example, if the inputs are [[a1, a2], [b1, b2]] and the rates
tensor contains [3, 1], then the return value may look like [[a1,
a2, a1, a1], [b1, b2, b1, b1]]. However, many other outputs are
possible, since this is stochastic -- averaged over many repeated
calls, each set of inputs should appear in the output rate times
the number of invocations.
Args:
inputs: A list of tensors, each of which has a shape of[batch_size, ...]rates: A tensor of shape[batch_size]containing the resampling rates for each input.scope: Scope for the op.seed: Random seed to use.back_prop: Whether to allow back-propagation through this op.
Returns:
Selections from the input tensors.