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# tensorflow::ops::CompareAndBitpack

`#include <math_ops.h>`

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

## Summary

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],
dtype=x.dtype,
initializer=tf.orthogonal_initializer())
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]
```

NOTE: Currently, the innermost dimension of the tensor must be divisible by 8.

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

Arguments:

• scope: A Scope object
• input: Values to compare against `threshold` and bitpack.
• threshold: Threshold to compare against.

Returns:

• `Output`: The bitpacked comparisons.

### Constructors and Destructors

`CompareAndBitpack(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input threshold)`

### Public attributes

`operation`
`Operation`
`output`
`::tensorflow::Output`

### Public functions

`node() const `
`::tensorflow::Node *`
`operator::tensorflow::Input() const `
``` ```
``` ```
`operator::tensorflow::Output() const `
``` ```
``` ```

## Public attributes

### operation

`Operation operation`

### output

`::tensorflow::Output output`

## Public functions

### CompareAndBitpack

``` CompareAndBitpack(
const ::tensorflow::Scope & scope,
::tensorflow::Input input,
::tensorflow::Input threshold
)```

### node

`::tensorflow::Node * node() const `

### operator::tensorflow::Input

` operator::tensorflow::Input() const `

### operator::tensorflow::Output

` operator::tensorflow::Output() const `