wehub-resource-sync
153 lines
5.0 KiB
Python
153 lines
5.0 KiB
Python
# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import paddle
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import paddle.distributed as dist
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from paddle.base.framework import (
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auto_complete_op_role,
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pir_chunk_id_guard,
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pir_op_role_guard,
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)
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from paddle.distributed import Replicate, Shard
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from paddle.distributed.auto_parallel.static.mix_to_dist_pass import (
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apply_mix2dist_pass,
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)
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from paddle.distributed.auto_parallel.static.pir_pass import (
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ReshardPasses,
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apply_partition_pass,
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)
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class TestOpRole(unittest.TestCase):
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def test_single(self):
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paddle.enable_static()
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with paddle.pir_utils.IrGuard():
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main_program = paddle.base.Program()
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with paddle.base.program_guard(main_program):
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# op_role = -1
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x0 = paddle.static.data(name='x0', shape=[1, 128, 512])
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x1 = paddle.nn.functional.relu(x0)
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x2 = paddle.nn.functional.relu(x1)
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with pir_op_role_guard(1), pir_chunk_id_guard(2):
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y0 = paddle.static.data(name='y0', shape=[1, 128, 512])
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y1 = paddle.nn.functional.relu(y0)
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z0 = paddle.add(y1, x2)
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z0 = z0 * 3.0
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with pir_op_role_guard(3), pir_chunk_id_guard(1):
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z1 = paddle.nn.functional.relu(z0)
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z2 = paddle.add(y0, z1)
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z4 = paddle.split(z0, num_or_sections=[8, 100, 20], axis=1)
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with pir_op_role_guard(0), pir_chunk_id_guard(3):
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z3 = paddle.add(y1, z2)
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# op_role = -1
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z4 = paddle.add(y0, z3)
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# check global shape
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std_ops = [
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"pd_op.data:-1:-1",
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"pd_op.data:1:2",
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"pd_op.relu:-1:-1",
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"pd_op.relu:-1:-1",
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"pd_op.relu:1:2",
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"pd_op.add:1:2",
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"pd_op.full:1:2",
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"pd_op.scale:1:2",
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"pd_op.relu:3:1",
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"pd_op.add:3:1",
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"pd_op.full_int_array:3:1",
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"pd_op.full:3:1",
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"pd_op.split:3:1",
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"builtin.split:3:1",
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"pd_op.add:0:3",
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"pd_op.add:-1:-1",
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]
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cur_ops = [
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f"{op.name()}:{op.op_role}:{op.chunk_id}"
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for op in main_program.global_block().ops
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]
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self.assertEqual(cur_ops, std_ops)
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def test_dist(self):
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paddle.enable_static()
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mesh = dist.ProcessMesh([[0, 1], [2, 3]], dim_names=["x", "y"])
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with paddle.pir_utils.IrGuard():
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main_program = paddle.base.Program()
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with (
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paddle.base.program_guard(main_program),
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auto_complete_op_role(main_program, 0),
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):
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x0 = paddle.static.data(name='x0', shape=[1, 128, 512])
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x0 = dist.shard_tensor(
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x0, mesh, [Shard(1), Replicate()], stop_gradient=False
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)
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x1 = x0 / 2.0
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with pir_op_role_guard(3):
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x2 = dist.reshard(x1, mesh, [Shard(2), Replicate()])
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with pir_op_role_guard(1):
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x3 = dist.reshard(x2, mesh, [Replicate(), Replicate()])
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x4 = dist.reshard(x3, mesh, [Shard(1), Replicate()])
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x5 = dist.reshard(x4, mesh, [Replicate(), Replicate()])
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apply_mix2dist_pass(main_program)
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apply_partition_pass(main_program)
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ReshardPasses.apply_reshard_pass(main_program)
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std_ops = [
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'pd_op.data:0',
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'pd_op.full:0',
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'pd_op.scale:0',
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'pd_op.all_gather:3',
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'pd_op.full:3',
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'pd_op.split_with_num:3',
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'pd_op.full:3',
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'pd_op.concat:3',
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'pd_op.full_int_array:3',
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'pd_op.full_int_array:3',
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'pd_op.slice:3',
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'pd_op.all_gather:1',
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'pd_op.full:1',
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'pd_op.split_with_num:1',
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'pd_op.full:1',
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'pd_op.concat:1',
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'pd_op.full_int_array:3',
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'pd_op.full_int_array:3',
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'pd_op.slice:3',
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'pd_op.all_gather:0',
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'pd_op.full:0',
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'pd_op.split_with_num:0',
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'pd_op.full:0',
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'pd_op.concat:0',
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]
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cur_ops = [
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f"{op.name()}:{op.op_role}"
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for op in main_program.global_block().ops
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]
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self.assertEqual(cur_ops, std_ops)
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if __name__ == "__main__":
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unittest.main()
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