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