|  | # 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 scatter update behavior for tensorflow.""" | 
|  |  | 
|  | from absl import app | 
|  | import numpy as np | 
|  | from pyiree.tf.support import tf_test_utils | 
|  | import tensorflow.compat.v2 as tf | 
|  |  | 
|  |  | 
|  | class ScatterUpdateModule(tf.Module): | 
|  |  | 
|  | def __init__(self): | 
|  | pass | 
|  |  | 
|  | @tf.function(input_signature=[ | 
|  | tf.TensorSpec([8], tf.int32), | 
|  | tf.TensorSpec([3, 1], tf.int32), | 
|  | tf.TensorSpec([3], tf.int32) | 
|  | ]) | 
|  | def scatter_update_1D(self, tensor, indices, updates): | 
|  | return tf.tensor_scatter_nd_update(tensor, indices, updates) | 
|  |  | 
|  | @tf.function(input_signature=[ | 
|  | tf.TensorSpec([4, 3], tf.int32), | 
|  | tf.TensorSpec([3, 2], tf.int32), | 
|  | tf.TensorSpec([3], tf.int32) | 
|  | ]) | 
|  | def scatter_update_2D(self, tensor, indices, updates): | 
|  | return tf.tensor_scatter_nd_update(tensor, indices, updates) | 
|  |  | 
|  | @tf.function(input_signature=[ | 
|  | tf.TensorSpec([4, 3], tf.int32), | 
|  | tf.TensorSpec([1, 1], tf.int32), | 
|  | tf.TensorSpec([1, 3], tf.int32) | 
|  | ]) | 
|  | def scatter_update_2D_slice(self, tensor, indices, updates): | 
|  | return tf.tensor_scatter_nd_update(tensor, indices, updates) | 
|  |  | 
|  |  | 
|  | class ScatterUpdateTest(tf_test_utils.TracedModuleTestCase): | 
|  |  | 
|  | def __init__(self, *args, **kwargs): | 
|  | super(ScatterUpdateTest, self).__init__(*args, **kwargs) | 
|  | self._modules = tf_test_utils.compile_tf_module(ScatterUpdateModule) | 
|  |  | 
|  | # yapf: disable | 
|  | def test_scatter_update_1D(self): | 
|  | def scatter_update_1D(module): | 
|  | tensor = np.ones([8], dtype=np.int32) | 
|  | indices = np.array([[4], [5], [6]], dtype=np.int32) | 
|  | updates = np.array([9, 10, 11], dtype=np.int32) | 
|  | module.scatter_update_1D(tensor, indices, updates) | 
|  | self.compare_backends(scatter_update_1D, self._modules) | 
|  |  | 
|  | def test_scatter_update_2D(self): | 
|  | def scatter_update_2D(module): | 
|  | tensor = np.ones([4, 3], dtype=np.int32) | 
|  | indices = np.array([[1, 0], [2, 1], [3, 2]], dtype=np.int32) | 
|  | updates = np.array([2, 5, 8], dtype=np.int32) | 
|  | module.scatter_update_2D(tensor, indices, updates) | 
|  | self.compare_backends(scatter_update_2D, self._modules) | 
|  |  | 
|  | def test_scatter_update_2D_slice(self): | 
|  | def scatter_update_2D_slice(module): | 
|  | tensor = np.ones([4, 3], dtype=np.int32) | 
|  | indices = np.array([[1]], dtype=np.int32) | 
|  | updates = np.array([[2, 3, 4]], dtype=np.int32) | 
|  | module.scatter_update_2D_slice(tensor, indices, updates) | 
|  | self.compare_backends(scatter_update_2D_slice, 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) |