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Fix warnings during GAN training #3334

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Fix warnings during GAN training #3334

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aed39ae
Fix warnings during GAN training
AndreyYashkin Apr 22, 2021
e2fb23f
Update fix
AndreyYashkin May 14, 2021
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18 changes: 9 additions & 9 deletions fastai/vision/gan.py
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Expand Up @@ -138,8 +138,8 @@ def __init__(self, switch_eval=False, clip=None, beta=0.98, gen_first=False, sho
self.gen_loss,self.crit_loss = AvgSmoothLoss(beta=beta),AvgSmoothLoss(beta=beta)

def _set_trainable(self):
train_model = self.generator if self.gen_mode else self.critic
loss_model = self.generator if not self.gen_mode else self.critic
train_model = self.gan_generator if self.gan_gen_mode else self.gan_critic
loss_model = self.gan_generator if not self.gan_gen_mode else self.gan_critic
set_freeze_model(train_model, True)
set_freeze_model(loss_model, False)
if self.switch_eval:
Expand All @@ -148,9 +148,9 @@ def _set_trainable(self):

def before_fit(self):
"Initialize smootheners."
self.generator,self.critic = self.model.generator,self.model.critic
self.gen_mode = self.gen_first
self.switch(self.gen_mode)
self.gan_generator,self.gan_critic = self.model.generator,self.model.critic
self.learn.gan_gen_mode = self.gen_first
self.switch(self.gan_gen_mode)
self.crit_losses,self.gen_losses = [],[]
self.gen_loss.reset() ; self.crit_loss.reset()
#self.recorder.no_val=True
Expand All @@ -165,13 +165,13 @@ def before_batch(self):
"Clamp the weights with `self.clip` if it's not None, set the correct input/target."
if self.training and self.clip is not None:
for p in self.critic.parameters(): p.data.clamp_(-self.clip, self.clip)
if not self.gen_mode:
if not self.gan_gen_mode:
(self.learn.xb,self.learn.yb) = (self.yb,self.xb)

def after_batch(self):
"Record `last_loss` in the proper list."
if not self.training: return
if self.gen_mode:
if self.gan_gen_mode:
self.gen_loss.accumulate(self.learn)
self.gen_losses.append(self.gen_loss.value)
self.last_gen = self.learn.to_detach(self.pred)
Expand All @@ -181,7 +181,7 @@ def after_batch(self):

def before_epoch(self):
"Put the critic or the generator back to eval if necessary."
self.switch(self.gen_mode)
self.switch(self.gan_gen_mode)

#def after_epoch(self):
# "Show a sample image."
Expand All @@ -198,7 +198,7 @@ def before_epoch(self):

def switch(self, gen_mode=None):
"Switch the model and loss function, if `gen_mode` is provided, in the desired mode."
self.gen_mode = (not self.gen_mode) if gen_mode is None else gen_mode
self.learn.gan_gen_mode = (not self.gen_mode) if gen_mode is None else gen_mode
self._set_trainable()
self.model.switch(gen_mode)
self.loss_func.switch(gen_mode)
Expand Down
18 changes: 9 additions & 9 deletions nbs/24_vision.gan.ipynb
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Expand Up @@ -394,8 +394,8 @@
" self.gen_loss,self.crit_loss = AvgSmoothLoss(beta=beta),AvgSmoothLoss(beta=beta)\n",
"\n",
" def _set_trainable(self):\n",
" train_model = self.generator if self.gen_mode else self.critic\n",
" loss_model = self.generator if not self.gen_mode else self.critic\n",
" train_model = self.gan_generator if self.gan_gen_mode else self.gan_critic\n",
" loss_model = self.gan_generator if not self.gan_gen_mode else self.gan_critic\n",
" set_freeze_model(train_model, True)\n",
" set_freeze_model(loss_model, False)\n",
" if self.switch_eval:\n",
Expand All @@ -404,9 +404,9 @@
"\n",
" def before_fit(self):\n",
" \"Initialize smootheners.\"\n",
" self.generator,self.critic = self.model.generator,self.model.critic\n",
" self.gen_mode = self.gen_first\n",
" self.switch(self.gen_mode)\n",
" self.gan_generator,self.gan_critic = self.model.generator,self.model.critic\n",
" self.learn.gan_gen_mode = self.gen_first\n",
" self.switch(self.gan_gen_mode)\n",
" self.crit_losses,self.gen_losses = [],[]\n",
" self.gen_loss.reset() ; self.crit_loss.reset()\n",
" #self.recorder.no_val=True\n",
Expand All @@ -421,13 +421,13 @@
" \"Clamp the weights with `self.clip` if it's not None, set the correct input/target.\"\n",
" if self.training and self.clip is not None:\n",
" for p in self.critic.parameters(): p.data.clamp_(-self.clip, self.clip)\n",
" if not self.gen_mode:\n",
" if not self.gan_gen_mode:\n",
" (self.learn.xb,self.learn.yb) = (self.yb,self.xb)\n",
"\n",
" def after_batch(self):\n",
" \"Record `last_loss` in the proper list.\"\n",
" if not self.training: return\n",
" if self.gen_mode:\n",
" if self.gan_gen_mode:\n",
" self.gen_loss.accumulate(self.learn)\n",
" self.gen_losses.append(self.gen_loss.value)\n",
" self.last_gen = self.learn.to_detach(self.pred)\n",
Expand All @@ -437,7 +437,7 @@
"\n",
" def before_epoch(self):\n",
" \"Put the critic or the generator back to eval if necessary.\"\n",
" self.switch(self.gen_mode)\n",
" self.switch(self.gan_gen_mode)\n",
"\n",
" #def after_epoch(self):\n",
" # \"Show a sample image.\"\n",
Expand All @@ -454,7 +454,7 @@
"\n",
" def switch(self, gen_mode=None):\n",
" \"Switch the model and loss function, if `gen_mode` is provided, in the desired mode.\"\n",
" self.gen_mode = (not self.gen_mode) if gen_mode is None else gen_mode\n",
" self.learn.gan_gen_mode = (not self.gen_mode) if gen_mode is None else gen_mode\n",
" self._set_trainable()\n",
" self.model.switch(gen_mode)\n",
" self.loss_func.switch(gen_mode)"
Expand Down