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Added new features in leras

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This commit is contained in:
Cioscos 2021-10-02 15:30:07 +02:00
commit c0ddc6fc5d
3 changed files with 19 additions and 8 deletions
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15
core/leras/archis/DeepFakeArchi.py
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@ -21,6 +21,13 @@ class DeepFakeArchi(nn.ArchiBase):
conv_dtype = tf.float16 if use_fp16 else tf.float32 conv_dtype = tf.float16 if use_fp16 else tf.float32
if 'c' in opts:
def act(x, alpha=0.1):
return tf.nn.relu(x)
else:
def act(x, alpha=0.1):
return tf.nn.leaky_relu(x, alpha)
if mod is None: if mod is None:
class Downscale(nn.ModelBase): class Downscale(nn.ModelBase):
def __init__(self, in_ch, out_ch, kernel_size=5, *kwargs ): def __init__(self, in_ch, out_ch, kernel_size=5, *kwargs ):
@ -34,7 +41,7 @@ class DeepFakeArchi(nn.ArchiBase):
def forward(self, x): def forward(self, x):
x = self.conv1(x) x = self.conv1(x)
x = tf.nn.leaky_relu(x, 0.1) x = act(x, 0.1)
return x return x
def get_out_ch(self): def get_out_ch(self):
@ -62,7 +69,7 @@ class DeepFakeArchi(nn.ArchiBase):
def forward(self, x): def forward(self, x):
x = self.conv1(x) x = self.conv1(x)
x = tf.nn.leaky_relu(x, 0.1) x = act(x, 0.1)
x = nn.depth_to_space(x, 2) x = nn.depth_to_space(x, 2)
return x return x
@ -73,9 +80,9 @@ class DeepFakeArchi(nn.ArchiBase):
def forward(self, inp): def forward(self, inp):
x = self.conv1(inp) x = self.conv1(inp)
x = tf.nn.leaky_relu(x, 0.2) x = act(x, 0.2)
x = self.conv2(x) x = self.conv2(x)
x = tf.nn.leaky_relu(inp + x, 0.2) x = act(inp + x, 0.2)
return x return x
class Encoder(nn.ModelBase): class Encoder(nn.ModelBase):

1
core/leras/layers/__init__.py
View file

@ -8,6 +8,7 @@ from .Dense import *
from .BlurPool import * from .BlurPool import *
from .BatchNorm2D import * from .BatchNorm2D import *
from .InstanceNorm2D import *
from .FRNorm2D import * from .FRNorm2D import *
from .TLU import * from .TLU import *

11
core/leras/ops/__init__.py
View file

@ -108,10 +108,13 @@ nn.gelu = gelu
def upsample2d(x, size=2): def upsample2d(x, size=2):
if nn.data_format == "NCHW": if nn.data_format == "NCHW":
b,c,h,w = x.shape.as_list() x = tf.transpose(x, (0,2,3,1))
x = tf.reshape (x, (-1,c,h,1,w,1) ) x = tf.image.resize_nearest_neighbor(x, (x.shape[1]*size, x.shape[2]*size) )
x = tf.tile(x, (1,1,1,size,1,size) ) x = tf.transpose(x, (0,3,1,2))
x = tf.reshape (x, (-1,c,h*size,w*size) ) #b,c,h,w = x.shape.as_list()
#x = tf.reshape (x, (-1,c,h,1,w,1) )
#x = tf.tile(x, (1,1,1,size,1,size) )
#x = tf.reshape (x, (-1,c,h*size,w*size) )
return x return x
else: else:
return tf.image.resize_nearest_neighbor(x, (x.shape[1]*size, x.shape[2]*size) ) return tf.image.resize_nearest_neighbor(x, (x.shape[1]*size, x.shape[2]*size) )