wehub-resource-sync
90 lines
3.1 KiB
Python
90 lines
3.1 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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from legacy_test.test_parallel_dygraph_dataparallel import (
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TestMultipleAccelerators,
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)
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class TestMuonParallel(TestMultipleAccelerators):
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def test_muon_sharding_optimizer(self):
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"""MuonSharding test: iterate ns_coeff_type combinations.
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Test logic is in hybrid_parallel_sharding_muon_model.py,
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iterating 4 ns_coeff_types. fp32 matmul is auto-selected on V100.
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"""
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self.run_mnist_2accelerators(
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'hybrid_parallel_sharding_muon_model.py',
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need_envs={"MULTI_PRECISION": "1"},
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)
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def test_muon_sharding_fused_gradient(self):
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"""MuonSharding test with FLAGS_shard_fused_gradient=1.
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Covers muon_sharding_optimizer.py L627-635 (comm_buffer_2d reduce)
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and L665-667 (comm_buffer_2d scale_grads).
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"""
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self.run_mnist_2accelerators(
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'hybrid_parallel_sharding_muon_model.py',
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need_envs={
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"FLAGS_shard_fused_gradient": "1",
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"MULTI_PRECISION": "1",
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},
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)
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def test_muon_sharding_fuse_optimizer_states(self):
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"""MuonSharding test with enable_fuse_optimizer_states=True.
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Covers muon_sharding_optimizer.py L125 (use_fusion_storage).
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"""
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self.run_mnist_2accelerators(
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'hybrid_parallel_sharding_muon_model.py',
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need_envs={
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"ENABLE_FUSE_OPTIMIZER_STATES": "1",
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"MULTI_PRECISION": "1",
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},
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)
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def test_muon_sharding_release_grads_fused(self):
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"""MuonSharding test with fused gradient + release_gradients.
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Covers muon_sharding_optimizer.py L633-635 (sd_release_grads path
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in fused gradient reduce: copy_grad_to_buffer when grad_storage is None).
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"""
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self.run_mnist_2accelerators(
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'hybrid_parallel_sharding_muon_model.py',
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need_envs={
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"FLAGS_shard_fused_gradient": "1",
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"RELEASE_GRADIENTS": "1",
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"MULTI_PRECISION": "1",
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},
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)
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def test_muon_sharding_multi_precision(self):
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"""MuonSharding test with multi_precision=True.
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Covers muon.py L575 (master_weight.scale_ with weight_decay),
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L582-583 (master_weight.subtract_ + assign back to param).
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"""
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self.run_mnist_2accelerators(
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'hybrid_parallel_sharding_muon_model.py',
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need_envs={"MULTI_PRECISION": "1"},
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)
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if __name__ == "__main__":
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unittest.main()
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