| # 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 | |
| from iree.tf.support import tf_test_utils | |
| from iree.tf.support import tf_utils | |
| import numpy as np | |
| 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) |