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https://github.com/zebrajr/pytorch.git
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20ac736200
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/44735 Reviewed By: mruberry Differential Revision: D23731306 Pulled By: ezyang fbshipit-source-id: 0ba009a99e475ddbe22981be8ac636f8a1c8b02f
25 lines
802 B
Python
25 lines
802 B
Python
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import copy
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import torch
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def fuse_conv_bn_eval(conv, bn):
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assert(not (conv.training or bn.training)), "Fusion only for eval!"
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fused_conv = copy.deepcopy(conv)
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fused_conv.weight, fused_conv.bias = \
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fuse_conv_bn_weights(fused_conv.weight, fused_conv.bias,
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bn.running_mean, bn.running_var, bn.eps, bn.weight, bn.bias)
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return fused_conv
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def fuse_conv_bn_weights(conv_w, conv_b, bn_rm, bn_rv, bn_eps, bn_w, bn_b):
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if conv_b is None:
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conv_b = bn_rm.new_zeros(bn_rm.shape)
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bn_var_rsqrt = torch.rsqrt(bn_rv + bn_eps)
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conv_w = conv_w * (bn_w * bn_var_rsqrt).reshape([-1] + [1] * (len(conv_w.shape) - 1))
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conv_b = (conv_b - bn_rm) * bn_var_rsqrt * bn_w + bn_b
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return torch.nn.Parameter(conv_w), torch.nn.Parameter(conv_b)
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