TensorFlow 1 version | View source on GitHub |
Generates fingerprint values.
tf.fingerprint(
data, method='farmhash64', name=None
)
Generates fingerprint values of data
.
Fingerprint op considers the first dimension of data
as the batch dimension,
and output[i]
contains the fingerprint value generated from contents in
data[i, ...]
for all i
.
Fingerprint op writes fingerprint values as byte arrays. For example, the
default method farmhash64
generates a 64-bit fingerprint value at a time.
This 8-byte value is written out as an tf.uint8
array of size 8, in
little-endian order.
For example, suppose that data
has data type tf.int32
and shape (2, 3, 4),
and that the fingerprint method is farmhash64
. In this case, the output
shape is (2, 8), where 2 is the batch dimension size of data
, and 8 is the
size of each fingerprint value in bytes. output[0, :]
is generated from
12 integers in data[0, :, :]
and similarly output[1, :]
is generated from
other 12 integers in data[1, :, :]
.
Note that this op fingerprints the raw underlying buffer, and it does not fingerprint Tensor's metadata such as data type and/or shape. For example, the fingerprint values are invariant under reshapes and bitcasts as long as the batch dimension remain the same:
tf.fingerprint(data) == tf.fingerprint(tf.reshape(data, ...))
tf.fingerprint(data) == tf.fingerprint(tf.bitcast(data, ...))
For string data, one should expect tf.fingerprint(data) !=
tf.fingerprint(tf.string.reduce_join(data))
in general.
Args | |
---|---|
data
|
A Tensor . Must have rank 1 or higher.
|
method
|
A Tensor of type tf.string . Fingerprint method used by this op.
Currently available method is farmhash64 .
|
name
|
A name for the operation (optional). |
Returns | |
---|---|
A two-dimensional Tensor of type tf.uint8 . The first dimension equals to
data 's first dimension, and the second dimension size depends on the
fingerprint algorithm.
|