|  | # 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 matrix ops.""" | 
|  |  | 
|  | from absl import app | 
|  | from pyiree.tf.support import tf_test_utils | 
|  | from pyiree.tf.support import tf_utils | 
|  | import tensorflow.compat.v2 as tf | 
|  |  | 
|  |  | 
|  | class MatrixOpsDynamicModule(tf.Module): | 
|  |  | 
|  | @tf.function(input_signature=[ | 
|  | tf.TensorSpec([None, None, 4, 2], tf.float32), | 
|  | tf.TensorSpec([None, None, 2, 4], tf.float32), | 
|  | ]) | 
|  | def matmul_high_rank_batch(self, lhs, rhs): | 
|  | return tf.matmul(lhs, rhs) | 
|  |  | 
|  | @tf.function(input_signature=[ | 
|  | tf.TensorSpec([None, None, None], tf.float32), | 
|  | tf.TensorSpec([None, None, None], tf.float32), | 
|  | ]) | 
|  | def matmul_dynamic(self, lhs, rhs): | 
|  | return tf.matmul(lhs, rhs) | 
|  |  | 
|  | @tf.function(input_signature=[ | 
|  | tf.TensorSpec([None, None, None], tf.float32), | 
|  | tf.TensorSpec([None, None], tf.float32), | 
|  | ]) | 
|  | def matmul_dynamic_lhs_batch(self, lhs, rhs): | 
|  | return tf.matmul(lhs, rhs) | 
|  |  | 
|  |  | 
|  | class MatrixOpsDynamicTest(tf_test_utils.TracedModuleTestCase): | 
|  |  | 
|  | def __init__(self, *args, **kwargs): | 
|  | super().__init__(*args, **kwargs) | 
|  | self._modules = tf_test_utils.compile_tf_module(MatrixOpsDynamicModule) | 
|  |  | 
|  | # yapf: disable | 
|  | def test_matmul_high_rank_batch(self): | 
|  | def matmul_high_rank_batch(module): | 
|  | module.matmul_high_rank_batch( | 
|  | tf_utils.uniform([1, 7, 4, 2]), tf_utils.uniform([7, 1, 2, 4])) | 
|  | self.compare_backends(matmul_high_rank_batch, self._modules) | 
|  |  | 
|  | def test_matmul_dynamic_matching_batch(self): | 
|  | def matmul_dynamic_matching_batch(module): | 
|  | module.matmul_dynamic( | 
|  | tf_utils.uniform([2, 2, 3]), tf_utils.uniform([2, 3, 4])) | 
|  | self.compare_backends(matmul_dynamic_matching_batch, self._modules) | 
|  |  | 
|  | def test_matmul_dynamic_broadcast_lhs(self): | 
|  | def matmul_dynamic_broadcast_lhs(module): | 
|  | module.matmul_dynamic( | 
|  | tf_utils.uniform([1, 2, 3]), tf_utils.uniform([2, 3, 4])) | 
|  | self.compare_backends(matmul_dynamic_broadcast_lhs, self._modules) | 
|  |  | 
|  | def test_matmul_dynamic_broadcast_rhs(self): | 
|  | def matmul_dynamic_broadcast_rhs(module): | 
|  | module.matmul_dynamic( | 
|  | tf_utils.uniform([2, 2, 3]), tf_utils.uniform([1, 3, 4])) | 
|  | self.compare_backends(matmul_dynamic_broadcast_rhs, self._modules) | 
|  |  | 
|  | def test_matmul_dynamic_rank_broadcasting(self): | 
|  | def matmul_dynamic_rank_broadcasting(module): | 
|  | module.matmul_dynamic_lhs_batch( | 
|  | tf_utils.uniform([7, 2, 3]), tf_utils.uniform([3, 4])) | 
|  | self.compare_backends(matmul_dynamic_rank_broadcasting, self._modules) | 
|  | # yapf: enable | 
|  |  | 
|  |  | 
|  | 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) |