add substitution for functional linear #1266
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elad-c
reviewed
Nov 14, 2024
| from model_compression_toolkit.logger import Logger | ||
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| class FunctionalLinear(common.BaseSubstitution): |
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just import BaseSubstitution from common
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| class FunctionalLinear(common.BaseSubstitution): | ||
| """ | ||
| Replace functional layer_norm with LayerNorm. |
| Logger.critical(f'Weight input missing for node {func_node.name}.') # pragma: no cover | ||
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| weight = func_node.weights[1] | ||
| bias = func_node.weights.get(2, None) |
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make sure the bias positional weight is saved as 2 even when the linear is called with bias as kwarg
| name=func_node.name, | ||
| framework_attr=framework_attr, | ||
| input_shape=func_node.input_shape[0], | ||
| output_shape=tuple(func_node.output_shape[0]), |
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why not just output_shape=func_node.output_shape?
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| def forward(self, x): | ||
| x = F.linear(x, self.fc1.weight, self.fc1.bias) | ||
| y = F.linear(x, self.fc2.weight, self.fc2.bias) |
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change to:
y = F.linear(x, bias=self.fc2.bias, weight=self.fc2.weight)
to make sure everything still works
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