wehub-resource-sync
66 lines
2.4 KiB
Python
66 lines
2.4 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.distributed.auto_parallel.static.mix_to_dist_pass import (
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apply_mix2dist_pass,
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)
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paddle.enable_static()
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class TestStackGradSpmdRule(unittest.TestCase):
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def test_build_replicated_program(self):
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main_program = paddle.base.Program()
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with paddle.base.program_guard(main_program):
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mesh = dist.ProcessMesh([0, 1])
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x0 = paddle.static.data(name='x0', shape=[64, 36])
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x1 = paddle.static.data(name='x1', shape=[64, 36])
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x0.stop_gradient = False
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x1.stop_gradient = False
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y = paddle.static.data(name='y', shape=[2, 64, 36])
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dist_x0 = dist.shard_tensor(x0, mesh, [dist.Shard(0)])
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dist_x1 = dist.shard_tensor(x1, mesh, [dist.Shard(0)])
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dist_out = paddle.stack([dist_x0, dist_x1], axis=0)
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loss = paddle.mean(dist_out - y)
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dist_program = main_program.clone()
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apply_mix2dist_pass(dist_program)
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dist_loss_value = dist_program.global_block().ops[-1].result(0)
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with paddle.static.program_guard(dist_program):
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params_grads = paddle.autograd.ir_backward.append_backward(
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dist_loss_value
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)
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stack_grad_op = [
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op
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for op in dist_program.global_block().ops
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if op.name() == "pd_op.stack_grad"
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]
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stack_grad_op = stack_grad_op[0]
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out_grad = stack_grad_op.operand_source(1)
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x0_grad = dist_program.global_block().ops[-1].result(0)
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x1_grad = dist_program.global_block().ops[-1].result(1)
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self.assertEqual(out_grad.dist_attr().dims_mapping, [-1, 0, -1])
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self.assertEqual(x0_grad.dist_attr().dims_mapping, [0, -1])
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self.assertEqual(x1_grad.dist_attr().dims_mapping, [0, -1])
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if __name__ == "__main__":
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unittest.main()
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