Model

Model provide training functionality with model.fit(...) inspired from Keras

Examples:

model = Model(cnn)
model.compile("crossentropyloss", "adam", learning_rate=1e-3, metrics="accuracy")
model.fit(autodataset)

Parameters:

Name	Type	Description	Default
learner		Trainable model	required
accelerator_config		HuggingFace Accelerator config	required

compile(self, loss=None, optimizer=None, learning_rate=0.0003, metrics=None, loss_config=None, optimizer_config=None)

Examples:

model = Model(net)
model.compile(loss="crossentropyloss", optimizer="adam", learning_rate=1e-3, metrics="accuracy")

Parameters:

Name	Type	Description	Default
loss	Union[str, torch.nn.modules.loss._Loss]	name of loss or torch Loss class object. See available_losses()	None
optimizer	Union[str, torch.optim.optimizer.Optimizer]	optimizer name or torch.optim.Optimizer object	None
learning_rate	float	defaults to 1e-3	0.0003
metrics	Union[str, torchmetrics.metric.Metric, List[Union[str, torchmetrics.metric.Metric]]]	list of metrics to calculate. See available_metrics()	None
loss_config	Optional[dict]	Dict config if any to pass to loss function	None
optimizer_config	Optional[dict]	Dict config if any to pass to Optimizer	None

fit(self, autodataset, max_epochs=1, steps_per_epoch=None, callbacks=None, resume=True, show_progress=True, progress_kwargs=None)

Similar to Keras model.fit(...) it trains the model for specified epochs and returns Tracker object

Examples:

autodataset = AutoDataset(train_dataloader, val_dataloader)
model = Model(cnn)
model.compile("crossentropyloss", "adam", learning_rate=1e-3, metrics="accuracy")
model.fit(autodataset)

Parameters:

Name	Type	Description	Default
autodataset	AutoDataset	AutoDataset object encapsulate dataloader and datamodule	required
max_epochs	int	number of epochs to train	1
steps_per_epoch	Optional[int]	Number of steps trained in a single current_epoch	None
callbacks	Union[List[str], gradsflow.callbacks.callbacks.Callback]	Callback object or string	None
resume	bool	Resume training from the last current_epoch	True
show_progress	bool	Enable to show training progress	True
progress_kwargs		Arguments for rich.progress	None

Returns:

Type	Description
Tracker	Tracker object

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Last update: October 3, 2021

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