# Copyright (c) 2021 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. from __future__ import print_function import unittest import functools import operator import numpy as np import paddle import paddle.fluid as fluid import paddle.fluid.core as core import paddle.nn as nn import paddle.distributed as dist paddle.enable_static() def _flatten_nested_list(nested_list): result = functools.reduce(operator.iconcat, nested_list, []) return result def _append_attr_suffix(name): return name + core.kAutoParallelSuffix() LAST_PP_STAGE = 3 MASK = [[0, 1, 1], [0, 1, 1]] MESH = dist.ProcessMesh([[0, 1, 2], [3, 4, 5]]) class SimpleNet(nn.Layer): def __init__(self, vocab_size=128, hidden_size=4): super(SimpleNet, self).__init__() self.mesh = MESH self.mesh.set_placement([5, 4, 3, 2, 1, 0]) self.word_embeddings = nn.Embedding(vocab_size, hidden_size) self.dense1 = nn.Linear(hidden_size, hidden_size) self.dense2 = nn.Linear(hidden_size, hidden_size // 2) def forward(self, x, y): x = dist.shard_tensor(x, self.mesh, dim_mapping=[0, -1]) x = dist.set_shard_mask(x, MASK) emb_out = self.word_embeddings(x) dist.set_pipeline_stage(LAST_PP_STAGE) y = dist.shard_tensor(y, self.mesh, dim_mapping=[0, -1]) dist.set_offload_device(y, "cpu") linear1 = self.dense1(y) out = self.dense2(linear1) return x, y, self.mesh class TestAutoParallelAPI(unittest.TestCase): def test_api(self): net = SimpleNet() data1 = fluid.layers.fill_constant(shape=[2, 4], value=1, dtype="int64") data2 = fluid.layers.fill_constant( shape=[2, 4], value=2, dtype="float32") data3 = fluid.layers.fill_constant( shape=[2, 4], value=4, dtype="float32") x, y, mesh = net.forward(data1, data2) mesh_attr = _append_attr_suffix('mesh_id') x_mesh_id = x._get_attr(mesh_attr) self.assertEqual(x_mesh_id, mesh._id) x_mesh = x.process_mesh allatts = x.attr_names self.assertEqual(x_mesh, mesh) shard_mask_attr = _append_attr_suffix('mask') self.assertEqual( x._get_attr(shard_mask_attr), _flatten_nested_list(MASK)) self.assertEqual(x.shard_mask, _flatten_nested_list(MASK)) offload_attr = _append_attr_suffix('offload_device') self.assertEqual(y._get_attr(offload_attr), "cpu") self.assertEqual(y.desc.has_attr(offload_attr), True) self.assertEqual(y.offload_device, "cpu") y._remove_attr(offload_attr) self.assertEqual(y._has_attr(offload_attr), False) ops = paddle.static.default_main_program().block(0).ops first_op = ops[0] last_op = ops[-1] self.assertEqual(last_op.pipeline_stage, LAST_PP_STAGE) DIMS_MAPPING1 = [0, 1, -1] DIMS_MAPPING2 = [-1, 2, 0] kwargs = {'x': data2, 'y': data3} dist.shard_op( paddle.add, mesh=mesh, dim_mapping_dict={ data2.name: DIMS_MAPPING1, data3.name: DIMS_MAPPING2 }, **kwargs) ops = paddle.static.default_main_program().block(0).ops last_op = ops[-1] self.assertEqual(last_op.process_mesh, mesh) attr_name = "IN_" + data2.name attr_name = _append_attr_suffix(attr_name) self.assertEqual(last_op.attr(attr_name), DIMS_MAPPING1) attr_name = "IN_" + data3.name attr_name = _append_attr_suffix(attr_name) self.assertEqual(last_op.attr(attr_name), DIMS_MAPPING2) def test_process_mesh(self): mesh1 = dist.ProcessMesh([[0, 1, 2], [3, 4, 5]], parent=MESH) mesh2 = dist.ProcessMesh([[0, 1, 2], [3, 4, 5]], parent=mesh1) mesh3 = dist.ProcessMesh([[0, 1], [2, 3]], parent=mesh1) mesh4 = dist.ProcessMesh([[2, 3], [4, 5]], parent=mesh1) self.assertEqual(MESH.parent, None) self.assertEqual(mesh1.parent, MESH) self.assertEqual(mesh1._desc.parent, MESH._id) self.assertEqual(mesh3.parent, mesh1) self.assertEqual(mesh4.parent, mesh1) self.assertEqual(mesh1, mesh2) self.assertNotEqual(mesh3, mesh4) self.assertEqual(mesh2._id, mesh2._desc.id) self.assertEqual(mesh3.topology, mesh3._desc.topology) self.assertEqual(mesh3.topology, [2, 2]) self.assertEqual(mesh3.process_group, [0, 1, 2, 3]) self.assertEqual(mesh4.process_group, mesh4._desc.process_group) if __name__ == '__main__': unittest.main()