sparseCountSparseOutput_fuzz.py

# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""This is a Python API fuzzer for tf.raw_ops.SparseCountSparseOutput."""
import atheris
with atheris.instrument_imports():
  import sys
  from python_fuzzing import FuzzingHelper
  import tensorflow as tf


@atheris.instrument_func
def TestOneInput(input_bytes):
  """Test randomized integer fuzzing input for tf.raw_ops.SparseCountSparseOutput."""
  fh = FuzzingHelper(input_bytes)

  shape1 = fh.get_int_list(min_length=0, max_length=8, min_int=0, max_int=8)
  shape2 = fh.get_int_list(min_length=0, max_length=8, min_int=0, max_int=8)
  shape3 = fh.get_int_list(min_length=0, max_length=8, min_int=0, max_int=8)
  shape4 = fh.get_int_list(min_length=0, max_length=8, min_int=0, max_int=8)

  seed = fh.get_int()
  indices = tf.random.uniform(
      shape=shape1, minval=0, maxval=1000, dtype=tf.int64, seed=seed)
  values = tf.random.uniform(
      shape=shape2, minval=0, maxval=1000, dtype=tf.int64, seed=seed)
  dense_shape = tf.random.uniform(
      shape=shape3, minval=0, maxval=1000, dtype=tf.int64, seed=seed)
  weights = tf.random.uniform(
      shape=shape4, minval=0, maxval=1000, dtype=tf.int64, seed=seed)

  binary_output = fh.get_bool()
  minlength = fh.get_int()
  maxlength = fh.get_int()
  name = fh.get_string()
  try:
    _, _, _, = tf.raw_ops.SparseCountSparseOutput(
        indices=indices,
        values=values,
        dense_shape=dense_shape,
        weights=weights,
        binary_output=binary_output,
        minlength=minlength,
        maxlength=maxlength,
        name=name)
  except tf.errors.InvalidArgumentError:
    pass


def main():
  atheris.Setup(sys.argv, TestOneInput, enable_python_coverage=True)
  atheris.Fuzz()


if __name__ == "__main__":
  main()