# 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 TestReshapeSPMDRule(unittest.TestCase): def setUp(self): self.rule = get_spmd_rule("reshape") x_shape = [6, 12, 48, 24] process_mesh = auto.ProcessMesh(mesh=[[0, 1, 2], [3, 4, 5]]) x_tensor_dist_attr = TensorDistAttr() x_tensor_dist_attr.dims_mapping = [-1, -1] x_tensor_dist_attr.process_mesh = process_mesh self.x_dist_tensor_spec = DistTensorSpec(x_shape, x_tensor_dist_attr) self.attrs = {"shape": [1, 72, 48, 4, 6]} def test_reshape_infer_forward(self): # shape: [6, 12, 48, 24] --> [1, 72, 48, 4, 6] # dims_mapping: [0, -1, 1, -1] --> [0, -1, 1, -1] [-1, 0, 1, -1, -1] self.x_dist_tensor_spec.set_dims_mapping([0, -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(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, -1] ) self.assertEqual( infered_output_dist_attrs[0].dims_mapping, [-1, 0, 1, -1, -1] ) # shape: [6, 12, 48, 24] --> [1, 72, 48, 4, 6] # dims_mapping: [-1, 0, -1, 1] --> [-1, -1, -1, -1] [-1, -1, -1, -1, -1] self.x_dist_tensor_spec.set_dims_mapping([-1, 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, [-1, -1, -1, -1] ) self.assertEqual( infered_output_dist_attrs[0].dims_mapping, [-1, -1, -1, -1, -1] ) # shape: [6, 12, 48, 24] --> [1, 72, 48, 4, 6] # dims_mapping: [1, -1, -1, 0] --> [1, -1, -1, 0] [-1, 1, -1, 0, -1] self.x_dist_tensor_spec.set_dims_mapping([1, -1, -1, 0]) 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, 0] ) self.assertEqual( infered_output_dist_attrs[0].dims_mapping, [-1, 1, -1, 0, -1] ) # shape: [6, 12, 48, 24] --> [3, 24, 6, 8, 24] # dims_mapping: [0, 1, -1, -1] --> [-1, -1, -1, -1] [-1, -1, -1, -1, -1] self.attrs["shape"] = [3, 24, 6, 8, 24] self.x_dist_tensor_spec.set_dims_mapping([0, 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, -1] ) self.assertEqual( infered_output_dist_attrs[0].dims_mapping, [-1, -1, -1, -1, -1] ) # shape: [6, 12, 48, 24] --> [3, 24, 6, 8, 24] # dims_mapping: [1, -1, -1, 0] --> [1, -1, -1, 0] [1, -1, -1, -1, 0] self.x_dist_tensor_spec.set_dims_mapping([1, -1, -1, 0]) 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, 0] ) self.assertEqual( infered_output_dist_attrs[0].dims_mapping, [1, -1, -1, -1, 0] ) # shape: [6, 12, 48, 24] --> [3, 24, 6, -1, 24] # dims_mapping: [-1, -1, 0, 1] --> [-1, -1, 0, 1], [-1, -1, 0, -1, 1] self.attrs["shape"] = [3, 24, 6, -1, 24] self.x_dist_tensor_spec.set_dims_mapping([-1, -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, -1, 0, 1] ) self.assertEqual( infered_output_dist_attrs[0].dims_mapping, [-1, -1, 0, -1, 1] ) # shape: [6, 12, 48, 24] --> [1, 72, 0, 4, 6] # dims_mapping: [1, -1, -1, 0] --> [1, -1, -1, 0] [-1, 1, -1, 0, -1] self.attrs["shape"] = [1, 72, 0, 4, 6] self.x_dist_tensor_spec.set_dims_mapping([1, -1, -1, 0]) 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, 0] ) self.assertEqual( infered_output_dist_attrs[0].dims_mapping, [-1, 1, -1, 0, -1] ) # shape: [6, 12, 48, 24] --> [6, 12, 48, 24] # dims_mapping: [-1, -1, 0, 1] --> [-1, -1, 0, 1], [-1, -1, 0, 1] self.attrs["shape"] = [6, 12, 48, 24] self.x_dist_tensor_spec.set_dims_mapping([-1, -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, -1, 0, 1] ) self.assertEqual( infered_output_dist_attrs[0].dims_mapping, [-1, -1, 0, 1] ) # shape: [6, 12, 48, 24] --> [72, 3, 16, 24] # dims_mapping: [0, -1, 1, -1] --> [0, -1, 1, -1], [0, 1, -1, -1] self.attrs["shape"] = [72, 3, 16, 24] self.x_dist_tensor_spec.set_dims_mapping([0, -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, [0, -1, 1, -1] ) self.assertEqual( infered_output_dist_attrs[0].dims_mapping, [0, 1, -1, -1] ) # shape: [6, 12, 48, 24] --> [72, 3, 16, 24] # dims_mapping: [1, -1, 0, -1] --> [1, -1, -1, -1], [1, -1, -1, -1] self.attrs["shape"] = [72, 3, 16, 24] self.x_dist_tensor_spec.set_dims_mapping([1, -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, -1, -1, -1] ) self.assertEqual( infered_output_dist_attrs[0].dims_mapping, [1, -1, -1, -1] ) # shape: [6, 12, 48, 24] --> [3, 24, 6, -1, -1] # raise error self.attrs["shape"] = [3, 24, 6, -1, -1] with self.assertRaises(BaseException): self.rule.infer_forward([self.x_dist_tensor_spec], self.attrs) if __name__ == "__main__": unittest.main()