|  | # Lint as: python3 | 
|  | # Copyright 2020 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. | 
|  | """Test concat op.""" | 
|  |  | 
|  | from absl import app | 
|  | import numpy as np | 
|  | from pyiree.tf.support import tf_test_utils | 
|  | from pyiree.tf.support import tf_utils | 
|  | import tensorflow.compat.v2 as tf | 
|  |  | 
|  |  | 
|  | class ConcatOpsModule(tf.Module): | 
|  |  | 
|  | @tf.function(input_signature=[ | 
|  | tf.TensorSpec([1, 5, 0], tf.float32), | 
|  | tf.TensorSpec([1, 5, 1], tf.float32), | 
|  | ]) | 
|  | def concat_zero_dim(self, a, b): | 
|  | return tf.concat([a, b], axis=2) | 
|  |  | 
|  | @tf.function(input_signature=[ | 
|  | tf.TensorSpec([1, 5, 1], tf.float32), | 
|  | tf.TensorSpec([1, 5, 1], tf.float32), | 
|  | ]) | 
|  | def concat0axis(self, a, b): | 
|  | return tf.concat([a, b], axis=0) | 
|  |  | 
|  | @tf.function(input_signature=[ | 
|  | tf.TensorSpec([1, 5, 1], tf.float32), | 
|  | tf.TensorSpec([1, 5, 1], tf.float32), | 
|  | ]) | 
|  | def concat1axis(self, a, b): | 
|  | return tf.concat([a, b], axis=1) | 
|  |  | 
|  | @tf.function(input_signature=[ | 
|  | tf.TensorSpec([1, 5, 1], tf.float32), | 
|  | tf.TensorSpec([1, 5, 1], tf.float32), | 
|  | ]) | 
|  | def concat2axis(self, a, b): | 
|  | return tf.concat([a, b], axis=2) | 
|  |  | 
|  |  | 
|  | class ConcatOpsTest(tf_test_utils.TracedModuleTestCase): | 
|  |  | 
|  | def __init__(self, *args, **kwargs): | 
|  | super().__init__(*args, **kwargs) | 
|  | self._modules = tf_test_utils.compile_tf_module(ConcatOpsModule) | 
|  |  | 
|  | def test_concat_zero_dim(self): | 
|  |  | 
|  | def concat_zero_dim(module): | 
|  | a = tf_utils.uniform([1, 5, 0]) | 
|  | b = tf_utils.uniform([1, 5, 1]) | 
|  | module.concat_zero_dim(a, b) | 
|  |  | 
|  | self.compare_backends(concat_zero_dim, self._modules) | 
|  |  | 
|  | def test_concat0axis(self): | 
|  |  | 
|  | def concat0axis(module): | 
|  | a = tf_utils.uniform([1, 5, 1]) | 
|  | b = tf_utils.uniform([1, 5, 1]) | 
|  | module.concat0axis(a, b) | 
|  |  | 
|  | self.compare_backends(concat0axis, self._modules) | 
|  |  | 
|  | def test_concat1axis(self): | 
|  |  | 
|  | def concat1axis(module): | 
|  | a = tf_utils.uniform([1, 5, 1]) | 
|  | b = tf_utils.uniform([1, 5, 1]) | 
|  | module.concat1axis(a, b) | 
|  |  | 
|  | self.compare_backends(concat1axis, self._modules) | 
|  |  | 
|  | def test_concat2axis(self): | 
|  |  | 
|  | def concat2axis(module): | 
|  | a = tf_utils.uniform([1, 5, 1]) | 
|  | b = tf_utils.uniform([1, 5, 1]) | 
|  | module.concat2axis(a, b) | 
|  |  | 
|  | self.compare_backends(concat2axis, 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) |