Add a Python fuzzer for tf.raw_ops.SparseCountSparseOutput.

PiperOrigin-RevId: 359381561
Change-Id: I546fd8791327fd9949b7b282b2f1d15fd7b47229

tensorflow/security/fuzzing/BUILD

@@ -166,3 +166,10 @@ tf_py_fuzz_target(
     tags = ["notap"],  # Run in OSS only.
     deps = [":python_fuzzing"],
 )
+
+tf_py_fuzz_target(
+    name = "sparseCountSparseOutput_fuzz",
+    srcs = ["sparseCountSparseOutput_fuzz.py"],
+    tags = ["notap"],  # Run in OSS only.
+    deps = [":python_fuzzing"],
+)

tensorflow/security/fuzzing/sparseCountSparseOutput_fuzz.py

@@ -0,0 +1,65 @@
+# 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 sys
+import atheris_no_libfuzzer as atheris
+from python_fuzzing import FuzzingHelper
+import tensorflow as tf
+
+
+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()