Compare values of input to threshold and pack resulting bits into a uint8.

Each comparison returns a boolean true (if input_value > threshold) or and false otherwise.

This operation is useful for Locality-Sensitive-Hashing (LSH) and other algorithms that use hashing approximations of cosine and L2 distances; codes can be generated from an input via:

codebook_size = 50
codebook_bits = codebook_size * 32
codebook = tf.get_variable('codebook', [x.shape[-1].value, codebook_bits],
codes = compare_and_threshold(tf.matmul(x, codebook), threshold=0.)
codes = tf.bitcast(codes, tf.int32)  # go from uint8 to int32
# now codes has shape x.shape[:-1] + [codebook_size]

Given an input shaped [s0, s1, ..., s_n], the output is a uint8 tensor shaped [s0, s1, ..., s_n / 8].

input A Tensor. Must be one of the following types: bool, half, float32, float64, int8, int16, int32, int64. Values to compare against threshold and bitpack.
threshold A Tensor. Must have the same type as input. Threshold to compare against.
name A name for the operation (optional).

A Tensor of type uint8.