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90 lines
2.4 KiB
Python
90 lines
2.4 KiB
Python
# Copyright (c) 2025, NVIDIA CORPORATION. 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 os
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import tempfile
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import pytest
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import torch
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from nemo.core.classes.module import NeuralModule
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class TempModule(NeuralModule):
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def __init__(self):
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super().__init__()
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self.layer1 = torch.nn.Linear(10, 10, bias=False)
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self.layer2 = torch.nn.Linear(10, 10, bias=False)
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class TestNeuralModule:
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@pytest.mark.unit
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def test_num_weights(self):
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module = TempModule()
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assert module.num_weights == 200
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@pytest.mark.unit
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def test_freeze(self):
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module = TempModule()
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module.freeze()
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for p in module.parameters():
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assert not p.requires_grad
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@pytest.mark.unit
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def test_unfreeze(self):
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module = TempModule()
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module.freeze()
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module.unfreeze()
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for p in module.parameters():
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assert p.requires_grad
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@pytest.mark.unit
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def test_as_frozen(self):
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module = TempModule()
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for p in module.parameters():
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assert p.requires_grad
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with module.as_frozen():
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for p in module.parameters():
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assert not p.requires_grad
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for p in module.parameters():
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assert p.requires_grad
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@pytest.mark.unit
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def test_partial_unfreeze(self):
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module = TempModule()
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for param in module.layer1.parameters():
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param.requires_grad = False
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module.freeze()
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for param in module.layer1.parameters():
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assert not param.requires_grad
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assert module._frozen_grad_map is not None
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assert len(module._frozen_grad_map) == 2
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assert module._frozen_grad_map['layer1.weight'] is False
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module.unfreeze(partial=True)
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# layer1 should still be frozen due to partial unfreeze
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assert module.layer1.weight.requires_grad is False
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assert not hasattr(module, '_frozen_grad_map')
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