fix: docstring and kwargs

templates/gan/trainers.py

@@ -34,17 +34,28 @@ def train_function(
 
  Parameters
  ----------
- - config: config object
- - engine: Engine instance
- - batch: batch in current iteration
- - netD: discriminator model
- - netG: generator model
- - loss_fn: nn.Module loss
- - optimizerD: discriminator optimizer
- - optimizerG: generator optimizer
- - device: device to use for training
- - real_labels: real label tensor
- - fake_labels: fake label tensor
+ config
+ config object
+ engine
+ Engine instance
+ batch
+ batch in current iteration
+ netD
+ discriminator model
+ netG
+ generator model
+ loss_fn
+ nn.Module loss
+ optimizerD
+ discriminator optimizer
+ optimizerG
+ generator optimizer
+ device
+ device to use for training
+ real_labels
+ real label tensor
+ fake_labels
+ fake label tensor
 
  Returns
  -------

templates/gan/utils.py

@@ -37,8 +37,10 @@ def initialize(
 
  Parameters
  ----------
- config:
+ config
  config object
+ num_channels
+ number of channels for Generator
 
  Returns
  -------

templates/image_classification/trainers.py

@@ -31,13 +31,20 @@ def train_function(
 
  Parameters
  ----------
- - config: config object
- - engine: Engine instance
- - batch: batch in current iteration
- - model: nn.Module model
- - loss_fn: nn.Module loss
- - optimizer: torch optimizer
- - device: device to use for training
+ config
+ config object
+ engine
+ Engine instance
+ batch
+ batch in current iteration
+ model
+ nn.Module model
+ loss_fn
+ nn.Module loss
+ optimizer
+ torch optimizer
+ device
+ device to use for training
 
  Returns
  -------
@@ -86,12 +93,16 @@ def evaluate_function(
 
  Parameters
  ----------
- - config: config object
- - engine: Engine instance
- - batch: batch in current iteration
- - model: nn.Module model
- - loss_fn: nn.Module loss
- - device: device to use for training
+ config
+ config object
+ engine
+ Engine instance
+ batch
+ batch in current iteration
+ model
+ nn.Module model
+ device
+ device to use for training
 
  Returns
  -------
@@ -129,6 +140,7 @@ def create_trainers(**kwargs) -> Tuple[Engine, Engine]:
  **kwargs,
  )
  )
+ kwargs.pop('optimizer')
  eval_engine = Engine(
  lambda e, b: evaluate_function(
  engine=e,

templates/single/trainers.py

@@ -31,13 +31,20 @@ def train_function(
 
  Parameters
  ----------
- - config: config object
- - engine: Engine instance
- - batch: batch in current iteration
- - model: nn.Module model
- - loss_fn: nn.Module loss
- - optimizer: torch optimizer
- - device: device to use for training
+ config
+ config object
+ engine
+ Engine instance
+ batch
+ batch in current iteration
+ model
+ nn.Module model
+ loss_fn
+ nn.Module loss
+ optimizer
+ torch optimizer
+ device
+ device to use for training
 
  Returns
  -------
@@ -87,12 +94,18 @@ def evaluate_function(
 
  Parameters
  ----------
- - config: config object
- - engine: Engine instance
- - batch: batch in current iteration
- - model: nn.Module model
- - loss_fn: nn.Module loss
- - device: device to use for training
+ config
+ config object
+ engine
+ Engine instance
+ batch
+ batch in current iteration
+ model
+ nn.Module model
+ loss_fn
+ nn.Module loss
+ device
+ device to use for training
 
  Returns
  -------
@@ -133,6 +146,7 @@ def create_trainers(**kwargs) -> Tuple[Engine, Engine]:
  **kwargs,
  )
  )
+ kwargs.pop('optimizer')
  eval_engine = Engine(
  lambda e, b: evaluate_function(
  engine=e,