blob: 180f2dac1f2938949a4557f68bb7e6d5ff043ea4 [file] [log] [blame]
# Copyright 2019 Google LLC
#
# 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
#
# https://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.
from absl import app
import numpy as np
from pyiree.tf.support import tf_test_utils
import tensorflow.compat.v2 as tf
class ControlFlowModule(tf.Module):
def __init__(self):
pass
@tf.function(input_signature=[tf.TensorSpec([], tf.float32)])
def collatz(self, a):
i = 0.
while a > 1.:
i = i + 1.
if (a % 2.) > 0.:
a = 3. * a + 1.
else:
a = a / 2.
return i
class ControlFlowTest(tf_test_utils.TracedModuleTestCase):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self._modules = tf_test_utils.compile_tf_module(ControlFlowModule)
def test_short_sequence(self):
def short_sequence(module):
input_array = np.array(9., dtype=np.float32)
module.collatz(input_array)
self.compare_backends(short_sequence, self._modules)
def test_long_sequence(self):
def long_sequence(module):
input_array = np.array(178., dtype=np.float32)
module.collatz(input_array)
self.compare_backends(long_sequence, self._modules)
def main(argv):
del argv # Unused
if hasattr(tf, 'enable_v2_behavior'):
tf.enable_v2_behavior()
tf.test.main()
if __name__ == '__main__':
app.run(main)