mirror of https://github.com/hpcaitech/ColossalAI
50 lines
1.4 KiB
Python
50 lines
1.4 KiB
Python
#!/usr/bin/env python
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import torch
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import torch.nn as nn
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from colossalai.legacy.nn import CheckpointModule
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from .registry import non_distributed_component_funcs
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from .utils.dummy_data_generator import DummyDataGenerator
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class NetWithRepeatedlyComputedLayers(CheckpointModule):
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"""
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This model is to test with layers which go through forward pass multiple times.
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In this model, the fc1 and fc2 call forward twice
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"""
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def __init__(self, checkpoint=False) -> None:
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super().__init__(checkpoint=checkpoint)
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self.fc1 = nn.Linear(5, 5)
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self.fc2 = nn.Linear(5, 5)
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self.fc3 = nn.Linear(5, 2)
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self.layers = [self.fc1, self.fc2, self.fc1, self.fc2, self.fc3]
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def forward(self, x):
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for layer in self.layers:
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x = layer(x)
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return x
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class DummyDataLoader(DummyDataGenerator):
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def generate(self):
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data = torch.rand(16, 5)
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label = torch.randint(low=0, high=2, size=(16,))
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return data, label
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@non_distributed_component_funcs.register(name='repeated_computed_layers')
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def get_training_components():
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def model_builder(checkpoint=False):
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return NetWithRepeatedlyComputedLayers(checkpoint)
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trainloader = DummyDataLoader()
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testloader = DummyDataLoader()
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criterion = torch.nn.CrossEntropyLoss()
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return model_builder, trainloader, testloader, torch.optim.Adam, criterion
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