mirror of
https://github.com/iperov/DeepFaceLab.git
synced 2025-07-05 20:42:11 -07:00
AMP fix
This commit is contained in:
parent
11a7993238
commit
e52b53f87c
2 changed files with 4 additions and 10 deletions
|
@ -333,7 +333,9 @@ def depth_to_space(x, size):
|
||||||
x = tf.reshape(x, (-1, oh, ow, oc, ))
|
x = tf.reshape(x, (-1, oh, ow, oc, ))
|
||||||
return x
|
return x
|
||||||
else:
|
else:
|
||||||
return tf.depth_to_space(x, size, data_format=nn.data_format)
|
cfg = nn.getCurrentDeviceConfig()
|
||||||
|
if not cfg.cpu_only:
|
||||||
|
return tf.depth_to_space(x, size, data_format=nn.data_format)
|
||||||
b,c,h,w = x.shape.as_list()
|
b,c,h,w = x.shape.as_list()
|
||||||
oh, ow = h * size, w * size
|
oh, ow = h * size, w * size
|
||||||
oc = c // (size * size)
|
oc = c // (size * size)
|
||||||
|
@ -344,11 +346,6 @@ def depth_to_space(x, size):
|
||||||
return x
|
return x
|
||||||
nn.depth_to_space = depth_to_space
|
nn.depth_to_space = depth_to_space
|
||||||
|
|
||||||
def pixel_norm(x, power = 1.0):
|
|
||||||
return x * power * tf.rsqrt(tf.reduce_mean(tf.square(x), axis=nn.conv2d_spatial_axes, keepdims=True) + 1e-06)
|
|
||||||
nn.pixel_norm = pixel_norm
|
|
||||||
|
|
||||||
|
|
||||||
def rgb_to_lab(srgb):
|
def rgb_to_lab(srgb):
|
||||||
srgb_pixels = tf.reshape(srgb, [-1, 3])
|
srgb_pixels = tf.reshape(srgb, [-1, 3])
|
||||||
linear_mask = tf.cast(srgb_pixels <= 0.04045, dtype=tf.float32)
|
linear_mask = tf.cast(srgb_pixels <= 0.04045, dtype=tf.float32)
|
||||||
|
|
|
@ -121,7 +121,7 @@ class AMPModel(ModelBase):
|
||||||
def on_initialize(self):
|
def on_initialize(self):
|
||||||
device_config = nn.getCurrentDeviceConfig()
|
device_config = nn.getCurrentDeviceConfig()
|
||||||
devices = device_config.devices
|
devices = device_config.devices
|
||||||
self.model_data_format = "NCHW"# if len(devices) != 0 and not self.is_debug() else "NHWC"
|
self.model_data_format = "NCHW"
|
||||||
nn.initialize(data_format=self.model_data_format)
|
nn.initialize(data_format=self.model_data_format)
|
||||||
tf = nn.tf
|
tf = nn.tf
|
||||||
|
|
||||||
|
@ -262,8 +262,6 @@ class AMPModel(ModelBase):
|
||||||
m = tf.nn.sigmoid(self.out_convm(m))
|
m = tf.nn.sigmoid(self.out_convm(m))
|
||||||
return x, m
|
return x, m
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
self.face_type = {'wf' : FaceType.WHOLE_FACE,
|
self.face_type = {'wf' : FaceType.WHOLE_FACE,
|
||||||
'head' : FaceType.HEAD}[ self.options['face_type'] ]
|
'head' : FaceType.HEAD}[ self.options['face_type'] ]
|
||||||
|
|
||||||
|
@ -287,7 +285,6 @@ class AMPModel(ModelBase):
|
||||||
if ct_mode == 'none':
|
if ct_mode == 'none':
|
||||||
ct_mode = None
|
ct_mode = None
|
||||||
|
|
||||||
|
|
||||||
models_opt_on_gpu = False if len(devices) == 0 else self.options['models_opt_on_gpu']
|
models_opt_on_gpu = False if len(devices) == 0 else self.options['models_opt_on_gpu']
|
||||||
models_opt_device = nn.tf_default_device_name if models_opt_on_gpu and self.is_training else '/CPU:0'
|
models_opt_device = nn.tf_default_device_name if models_opt_on_gpu and self.is_training else '/CPU:0'
|
||||||
optimizer_vars_on_cpu = models_opt_device=='/CPU:0'
|
optimizer_vars_on_cpu = models_opt_device=='/CPU:0'
|
||||||
|
|
Loading…
Add table
Add a link
Reference in a new issue