80 lines
2.5 KiB
Python
80 lines
2.5 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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import torch
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from vllm.model_executor.models.utils import AutoWeightsLoader
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class ModuleWithBatchNorm(torch.nn.Module):
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def __init__(self):
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super().__init__()
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self.bn = torch.nn.BatchNorm1d(2)
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def forward(self, x):
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return self.bn(x)
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class ModuleWithNestedBatchNorm(torch.nn.Module):
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def __init__(self):
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super().__init__()
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self.nested_mod = ModuleWithBatchNorm()
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def forward(self, x):
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return self.nested_mod(x)
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def test_module_with_batchnorm_can_load():
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"""Ensure the auto weight loader can load batchnorm stats."""
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mod = ModuleWithBatchNorm()
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# Run some data through the module with batchnorm
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mod(torch.Tensor([[1, 2], [3, 4]]))
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# Try to load the weights to a new instance
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def weight_generator():
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yield from mod.state_dict().items()
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new_mod = ModuleWithBatchNorm()
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assert not torch.all(new_mod.bn.running_mean == mod.bn.running_mean)
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assert not torch.all(new_mod.bn.running_var == mod.bn.running_var)
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assert new_mod.bn.num_batches_tracked.item() == 0
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loader = AutoWeightsLoader(new_mod)
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loader.load_weights(weight_generator())
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# Ensure the stats are updated
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assert torch.all(new_mod.bn.running_mean == mod.bn.running_mean)
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assert torch.all(new_mod.bn.running_var == mod.bn.running_var)
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assert new_mod.bn.num_batches_tracked.item() == 1
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def test_module_with_child_containing_batchnorm_can_autoload():
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"""Ensure the auto weight loader can load nested modules batchnorm stats."""
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mod = ModuleWithNestedBatchNorm()
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# Run some data through the module with batchnorm
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mod(torch.Tensor([[1, 2], [3, 4]]))
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# Try to load the weights to a new instance
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def weight_generator():
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yield from mod.state_dict().items()
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new_mod = ModuleWithNestedBatchNorm()
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assert not torch.all(
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new_mod.nested_mod.bn.running_mean == mod.nested_mod.bn.running_mean)
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assert not torch.all(
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new_mod.nested_mod.bn.running_var == mod.nested_mod.bn.running_var)
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assert new_mod.nested_mod.bn.num_batches_tracked.item() == 0
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loader = AutoWeightsLoader(new_mod)
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loader.load_weights(weight_generator())
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# Ensure the stats are updated
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assert torch.all(
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new_mod.nested_mod.bn.running_mean == mod.nested_mod.bn.running_mean)
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assert torch.all(
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new_mod.nested_mod.bn.running_var == mod.nested_mod.bn.running_var)
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assert new_mod.nested_mod.bn.num_batches_tracked.item() == 1
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