tf.contrib.training.resample_at_rate

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Given inputs tensors, stochastically resamples each at a given rate.

tf.contrib.training.resample_at_rate(
    inputs, rates, scope=None, seed=None, back_prop=False
)

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.

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.

Selections from the input tensors.