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import torch.nn as nn |
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import torch |
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num_parallel = 1 |
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class ModuleParallel(nn.Module): |
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def __init__(self, module): |
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super(ModuleParallel, self).__init__() |
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self.module = module |
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def forward(self, x_parallel): |
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return [self.module(x) for x in x_parallel] |
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class LayerNormParallel(nn.Module): |
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def __init__(self, num_features): |
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super(LayerNormParallel, self).__init__() |
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for i in range(num_parallel): |
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setattr(self, 'ln_' + str(i), nn.LayerNorm(num_features, eps=1e-6)) |
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def forward(self, x_parallel): |
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return [getattr(self, 'ln_' + str(i))(x) for i, x in enumerate(x_parallel)] |