tf.contrib.training.weighted_resample

Performs an approximate weighted resampling of inputs.

tf.contrib.training.weighted_resample(
    inputs, weights, overall_rate, scope=None, mean_decay=0.999, seed=None
)

This method chooses elements from inputs where each item's rate of selection is proportional to its value in weights, and the average rate of selection across all inputs (and many invocations!) is overall_rate.

Args
inputs	A list of tensors whose first dimension is batch_size.
weights	A [batch_size]-shaped tensor with each batch member's weight.
overall_rate	Desired overall rate of resampling.
scope	Scope to use for the op.
mean_decay	How quickly to decay the running estimate of the mean weight.
seed	Random seed.

Returns
A list of tensors exactly like inputs, but with an unknown (and possibly zero) first dimension. A tensor containing the effective resampling rate used for each output.