mirror of
https://github.com/iperov/DeepFaceLab.git
synced 2024-12-25 23:41:12 -08:00
61472cdaf7
removed support of extracted(aligned) PNG faces. Use old builds to convert from PNG to JPG. fanseg model file in facelib/ is renamed
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
from core.leras import nn
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tf = nn.tf
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class InstanceNorm2D(nn.LayerBase):
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def __init__(self, in_ch, dtype=None, **kwargs):
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self.in_ch = in_ch
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if dtype is None:
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dtype = nn.floatx
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self.dtype = dtype
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super().__init__(**kwargs)
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def build_weights(self):
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kernel_initializer = tf.initializers.glorot_uniform(dtype=self.dtype)
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self.weight = tf.get_variable("weight", (self.in_ch,), dtype=self.dtype, initializer=kernel_initializer )
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self.bias = tf.get_variable("bias", (self.in_ch,), dtype=self.dtype, initializer=tf.initializers.zeros() )
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def get_weights(self):
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return [self.weight, self.bias]
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def forward(self, x):
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if nn.data_format == "NHWC":
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shape = (1,1,1,self.in_ch)
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else:
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shape = (1,self.in_ch,1,1)
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weight = tf.reshape ( self.weight , shape )
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bias = tf.reshape ( self.bias , shape )
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x_mean = tf.reduce_mean(x, axis=nn.conv2d_spatial_axes, keepdims=True )
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x_std = tf.math.reduce_std(x, axis=nn.conv2d_spatial_axes, keepdims=True ) + 1e-5
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x = (x - x_mean) / x_std
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x *= weight
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x += bias
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return x
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nn.InstanceNorm2D = InstanceNorm2D |