mirror of https://github.com/hpcaitech/ColossalAI
38 lines
1006 B
Python
38 lines
1006 B
Python
#!/usr/bin/env python
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# -*- encoding: utf-8 -*-
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import torch.nn as nn
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from colossalai.builder import build_layer
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from colossalai.registry import LAYERS
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@LAYERS.register_module
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class LambdaWrapper(nn.Module):
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"""Wrap a function to nn.Module, which takes a config of layers and can fully access them
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:param func: User customed function
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:type func: Callable
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:param layers_cfg: Config of layers, defaults to None
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:type layers_cfg: dict, optional
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"""
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def __init__(self, func, layers_cfg: dict = None):
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super().__init__()
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self.func = func
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self.layers = self._build_layers(layers_cfg)
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def _build_layers(self, layers_cfg: dict):
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if layers_cfg is None:
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return None
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else:
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layers = []
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for cfg in layers_cfg:
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layer = build_layer(cfg)
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layers.append(layer)
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return layers
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def forward(self, *args, **kwargs):
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return self.func(self, *args, **kwargs)
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