# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved. # # 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 # # http://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. import unittest from paddle.distributed.auto_parallel.static.completion import get_spmd_rule from paddle.distributed.auto_parallel.static.dist_attribute import ( DistTensorSpec, TensorDistAttr, ) from paddle.distributed.fleet import auto class TestReductionSPMDRule(unittest.TestCase): """ Unit tests for reduction spmd rule. """ def setUp(self): self.rule = get_spmd_rule("max") x_shape = [64, 32] process_mesh = auto.ProcessMesh(mesh=[0, 1, 2, 3]) x_tensor_dist_attr = TensorDistAttr() x_tensor_dist_attr.dims_mapping = [1, 0] x_tensor_dist_attr.process_mesh = process_mesh self.x_dist_tensor_spec = DistTensorSpec(x_shape, x_tensor_dist_attr) self.attrs = { 'keep_dim': False, 'axis': [0], 'linearity': False, } def test_single_mesh_dim(self): # reduce on dim 0, keep_dim = false # [0, -1] --> [0, -1], [-1], partial_on_dim:[0] self.attrs['keep_dim'] = False self.attrs['axis'] = [0] self.x_dist_tensor_spec.set_dims_mapping([0, -1]) result_dist_attrs = self.rule.infer_forward( [self.x_dist_tensor_spec], self.attrs ) infered_input_dist_attrs = result_dist_attrs[0] infered_output_dist_attrs = result_dist_attrs[1] self.assertEqual(len(result_dist_attrs), 2) self.assertEqual(len(infered_input_dist_attrs), 1) self.assertEqual(len(infered_output_dist_attrs), 1) self.assertEqual(infered_input_dist_attrs[0].dims_mapping, [0, -1]) self.assertEqual(infered_output_dist_attrs[0].dims_mapping, [-1]) # reduce on dim 0, keep_dim = true # [0, -1] --> [0, -1], [-1, -1], partial_on_dim:[0] self.attrs['keep_dim'] = True self.attrs['axis'] = [0] self.x_dist_tensor_spec.set_dims_mapping([0, -1]) result_dist_attrs = self.rule.infer_forward( [self.x_dist_tensor_spec], self.attrs ) infered_input_dist_attrs = result_dist_attrs[0] infered_output_dist_attrs = result_dist_attrs[1] self.assertEqual(infered_input_dist_attrs[0].dims_mapping, [0, -1]) self.assertEqual(infered_output_dist_attrs[0].dims_mapping, [-1, -1]) # reduce on dim 1, keep_dim = false # [0, -1] --> [0, -1], [0], partial_on_dim:[] self.attrs['keep_dim'] = False self.attrs['axis'] = [1] self.x_dist_tensor_spec.set_dims_mapping([0, -1]) result_dist_attrs = self.rule.infer_forward( [self.x_dist_tensor_spec], self.attrs ) infered_input_dist_attrs = result_dist_attrs[0] infered_output_dist_attrs = result_dist_attrs[1] self.assertEqual(infered_input_dist_attrs[0].dims_mapping, [0, -1]) self.assertEqual(infered_output_dist_attrs[0].dims_mapping, [0]) # reduce on dim 1, keep_dim = true # [0, -1] --> [0, -1], [0, -1], partial_on_dim:[] self.attrs['keep_dim'] = True self.attrs['axis'] = [1] self.x_dist_tensor_spec.set_dims_mapping([0, -1]) result_dist_attrs = self.rule.infer_forward( [self.x_dist_tensor_spec], self.attrs ) infered_input_dist_attrs = result_dist_attrs[0] infered_output_dist_attrs = result_dist_attrs[1] self.assertEqual(infered_input_dist_attrs[0].dims_mapping, [0, -1]) self.assertEqual(infered_output_dist_attrs[0].dims_mapping, [0, -1]) # reduce on dim 0 and 1, keep_dim = false # [0, -1] --> [0, -1], [], partial_on_dim:[0] self.attrs['keep_dim'] = False self.attrs['axis'] = [0, 1] self.x_dist_tensor_spec.set_dims_mapping([0, -1]) result_dist_attrs = self.rule.infer_forward( [self.x_dist_tensor_spec], self.attrs ) infered_input_dist_attrs = result_dist_attrs[0] infered_output_dist_attrs = result_dist_attrs[1] self.assertEqual(infered_input_dist_attrs[0].dims_mapping, [0, -1]) self.assertEqual(infered_output_dist_attrs[0].dims_mapping, []) # reduce on dim 0 and 1, keep_dim = true # [0, -1] --> [0, -1], [-1, -1], partial_on_dim:[0] self.attrs['keep_dim'] = True self.attrs['axis'] = [0, 1] self.x_dist_tensor_spec.set_dims_mapping([0, -1]) result_dist_attrs = self.rule.infer_forward( [self.x_dist_tensor_spec], self.attrs ) infered_input_dist_attrs = result_dist_attrs[0] infered_output_dist_attrs = result_dist_attrs[1] self.assertEqual(infered_input_dist_attrs[0].dims_mapping, [0, -1]) self.assertEqual(infered_output_dist_attrs[0].dims_mapping, [-1, -1]) def test_multi_mesh_dim(self): process_mesh = auto.ProcessMesh(mesh=[[0, 1, 2], [3, 4, 5]]) self.x_dist_tensor_spec.set_process_mesh(process_mesh) self.x_dist_tensor_spec.shape = [96, 24, 48] # reduce on dim 1, 2, keep_dim = false # [0, -1, -1] --> [0, -1, -1], [0], partial_on_dim:[] self.attrs['keep_dim'] = False self.attrs['axis'] = [1, 2] self.x_dist_tensor_spec.set_dims_mapping([0, -1, -1]) result_dist_attrs = self.rule.infer_forward( [self.x_dist_tensor_spec], self.attrs ) infered_input_dist_attrs = result_dist_attrs[0] infered_output_dist_attrs = result_dist_attrs[1] self.assertEqual(len(result_dist_attrs), 2) self.assertEqual(len(infered_input_dist_attrs), 1) self.assertEqual(len(infered_output_dist_attrs), 1) self.assertEqual(infered_input_dist_attrs[0].dims_mapping, [0, -1, -1]) self.assertEqual(infered_output_dist_attrs[0].dims_mapping, [0]) # reduce on dim 1, 2, keep_dim = false # [-1, 0, 1] --> [-1, 0, 1], [-1], partial_on_dim:[0, 1] self.attrs['keep_dim'] = False self.attrs['axis'] = [1, 2] self.x_dist_tensor_spec.set_dims_mapping([-1, 0, 1]) result_dist_attrs = self.rule.infer_forward( [self.x_dist_tensor_spec], self.attrs ) infered_input_dist_attrs = result_dist_attrs[0] infered_output_dist_attrs = result_dist_attrs[1] self.assertEqual(infered_input_dist_attrs[0].dims_mapping, [-1, 0, 1]) self.assertEqual(infered_output_dist_attrs[0].dims_mapping, [-1]) # reduction on dim 1, 2, keep_dim = false # [1, -1, -1] --> [1, -1, -1], [1], partial_on_dim:[] self.attrs['keep_dim'] = False self.attrs['axis'] = [1, 2] self.x_dist_tensor_spec.set_dims_mapping([1, -1, -1]) result_dist_attrs = self.rule.infer_forward( [self.x_dist_tensor_spec], self.attrs ) infered_input_dist_attrs = result_dist_attrs[0] infered_output_dist_attrs = result_dist_attrs[1] self.assertEqual(infered_input_dist_attrs[0].dims_mapping, [1, -1, -1]) self.assertEqual(infered_output_dist_attrs[0].dims_mapping, [1]) # reduction on dim 1, 2, keep_dim = false # [0, 1, -1] --> [0, 1, -1], [0], partial_on_dim:[1] self.attrs['keep_dim'] = False self.attrs['axis'] = [1, 2] self.x_dist_tensor_spec.set_dims_mapping([0, 1, -1]) result_dist_attrs = self.rule.infer_forward( [self.x_dist_tensor_spec], self.attrs ) infered_input_dist_attrs = result_dist_attrs[0] infered_output_dist_attrs = result_dist_attrs[1] self.assertEqual(infered_input_dist_attrs[0].dims_mapping, [0, 1, -1]) self.assertEqual(infered_output_dist_attrs[0].dims_mapping, [0]) # reduction on dim 1, 2, keep_dim = true # [0, 1, -1] --> [0, 1, -1], [0, -1, -1], partial_on_dim:[1] self.attrs['keep_dim'] = True self.attrs['axis'] = [1, 2] self.x_dist_tensor_spec.set_dims_mapping([0, 1, -1]) result_dist_attrs = self.rule.infer_forward( [self.x_dist_tensor_spec], self.attrs ) infered_input_dist_attrs = result_dist_attrs[0] infered_output_dist_attrs = result_dist_attrs[1] self.assertEqual(infered_input_dist_attrs[0].dims_mapping, [0, 1, -1]) self.assertEqual(infered_output_dist_attrs[0].dims_mapping, [0, -1, -1]) if __name__ == "__main__": unittest.main()