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update to 'partial' func

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iperov 2019-04-16 14:24:03 +04:00
commit a9d362844e
1 changed files with 12 additions and 39 deletions
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51
models/Model_SAE/Model.py
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@ -1,3 +1,4 @@
from functools import partial
import numpy as np import numpy as np
from nnlib import nnlib from nnlib import nnlib
@ -485,57 +486,29 @@ class SAEModel(ModelBase):
return x return x
SAEModel.ResidualBlock = ResidualBlock SAEModel.ResidualBlock = ResidualBlock
def ResidualBlock_pre (**base_kwargs):
def func(*args, **kwargs):
kwargs.update(base_kwargs)
return ResidualBlock(*args, **kwargs)
return func
SAEModel.ResidualBlock_pre = ResidualBlock_pre
def downscale (dim, padding='zero', norm='', act='', **kwargs): def downscale (dim, padding='zero', norm='', act='', **kwargs):
def func(x): def func(x):
return Norm(norm)( Act(act) (Conv2D(dim, kernel_size=5, strides=2, padding=padding)(x)) ) return Norm(norm)( Act(act) (Conv2D(dim, kernel_size=5, strides=2, padding=padding)(x)) )
return func return func
SAEModel.downscale = downscale SAEModel.downscale = downscale
def downscale_pre (**base_kwargs):
def func(*args, **kwargs):
kwargs.update(base_kwargs)
return downscale(*args, **kwargs)
return func
SAEModel.downscale_pre = downscale_pre
def upscale (dim, padding='zero', norm='', act='', **kwargs): def upscale (dim, padding='zero', norm='', act='', **kwargs):
def func(x): def func(x):
return SubpixelUpscaler()(Norm(norm)(Act(act)(Conv2D(dim * 4, kernel_size=3, strides=1, padding=padding)(x)))) return SubpixelUpscaler()(Norm(norm)(Act(act)(Conv2D(dim * 4, kernel_size=3, strides=1, padding=padding)(x))))
return func return func
SAEModel.upscale = upscale SAEModel.upscale = upscale
def upscale_pre (**base_kwargs):
def func(*args, **kwargs):
kwargs.update(base_kwargs)
return upscale(*args, **kwargs)
return func
SAEModel.upscale_pre = upscale_pre
def to_bgr (output_nc, padding='zero', **kwargs): def to_bgr (output_nc, padding='zero', **kwargs):
def func(x): def func(x):
return Conv2D(output_nc, kernel_size=5, padding=padding, activation='sigmoid')(x) return Conv2D(output_nc, kernel_size=5, padding=padding, activation='sigmoid')(x)
return func return func
SAEModel.to_bgr = to_bgr SAEModel.to_bgr = to_bgr
def to_bgr_pre (**base_kwargs):
def func(*args, **kwargs):
kwargs.update(base_kwargs)
return to_bgr(*args, **kwargs)
return func
SAEModel.to_bgr_pre = to_bgr_pre
@staticmethod @staticmethod
def LIAEEncFlow(resolution, ch_dims, **kwargs): def LIAEEncFlow(resolution, ch_dims, **kwargs):
exec (nnlib.import_all(), locals(), globals()) exec (nnlib.import_all(), locals(), globals())
upscale = SAEModel.upscale_pre(**kwargs) upscale = partial(SAEModel.upscale, **kwargs)
downscale = SAEModel.downscale_pre(**kwargs) downscale = partial(SAEModel.downscale, **kwargs)
def func(input): def func(input):
dims = K.int_shape(input)[-1]*ch_dims dims = K.int_shape(input)[-1]*ch_dims
@ -553,7 +526,7 @@ class SAEModel(ModelBase):
@staticmethod @staticmethod
def LIAEInterFlow(resolution, ae_dims=256, **kwargs): def LIAEInterFlow(resolution, ae_dims=256, **kwargs):
exec (nnlib.import_all(), locals(), globals()) exec (nnlib.import_all(), locals(), globals())
upscale = SAEModel.upscale_pre(**kwargs) upscale = partial(SAEModel.upscale, **kwargs)
lowest_dense_res=resolution // 16 lowest_dense_res=resolution // 16
def func(input): def func(input):
@ -568,10 +541,10 @@ class SAEModel(ModelBase):
@staticmethod @staticmethod
def LIAEDecFlow(output_nc,ch_dims, multiscale_count=1, add_residual_blocks=False, padding='zero', norm='', **kwargs): def LIAEDecFlow(output_nc,ch_dims, multiscale_count=1, add_residual_blocks=False, padding='zero', norm='', **kwargs):
exec (nnlib.import_all(), locals(), globals()) exec (nnlib.import_all(), locals(), globals())
upscale = SAEModel.upscale_pre(**kwargs) upscale = partial(SAEModel.upscale, **kwargs)
to_bgr = SAEModel.to_bgr_pre(**kwargs) to_bgr = partial(SAEModel.to_bgr, **kwargs)
dims = output_nc * ch_dims dims = output_nc * ch_dims
ResidualBlock = SAEModel.ResidualBlock_pre(**kwargs) ResidualBlock = partial(SAEModel.ResidualBlock, **kwargs)
def func(input): def func(input):
x = input[0] x = input[0]
@ -609,8 +582,8 @@ class SAEModel(ModelBase):
@staticmethod @staticmethod
def DFEncFlow(resolution, ae_dims, ch_dims, padding='zero', **kwargs): def DFEncFlow(resolution, ae_dims, ch_dims, padding='zero', **kwargs):
exec (nnlib.import_all(), locals(), globals()) exec (nnlib.import_all(), locals(), globals())
upscale = SAEModel.upscale_pre(padding=padding) upscale = partial(SAEModel.upscale, padding=padding)
downscale = SAEModel.downscale_pre(padding=padding) downscale = partial(SAEModel.downscale, padding=padding)
lowest_dense_res = resolution // 16 lowest_dense_res = resolution // 16
def func(input): def func(input):
@ -634,10 +607,10 @@ class SAEModel(ModelBase):
@staticmethod @staticmethod
def DFDecFlow(output_nc, ch_dims, multiscale_count=1, add_residual_blocks=False, padding='zero', **kwargs): def DFDecFlow(output_nc, ch_dims, multiscale_count=1, add_residual_blocks=False, padding='zero', **kwargs):
exec (nnlib.import_all(), locals(), globals()) exec (nnlib.import_all(), locals(), globals())
upscale = SAEModel.upscale_pre(padding=padding) upscale = partial(SAEModel.upscale, padding=padding)
to_bgr = SAEModel.to_bgr_pre(padding=padding) to_bgr = partial(SAEModel.to_bgr, padding=padding)
dims = output_nc * ch_dims dims = output_nc * ch_dims
ResidualBlock = SAEModel.ResidualBlock_pre(padding=padding) ResidualBlock = partial(SAEModel.ResidualBlock, padding=padding)
def func(input): def func(input):
x = input[0] x = input[0]