LossTrainer¶

class tfsnippet.LossTrainer(**kwargs)¶

Bases: tfsnippet.trainer.trainer.Trainer

A subclass of BaseTrainer, which optimizes a single loss.

Attributes Summary

`after_epochs`	Get the hooks run after epochs.
`after_steps`	Get the hooks run after steps.
`before_epochs`	Get the hooks run before epochs.
`before_steps`	Get the hooks run before steps.
`data_flow`	Get the training data flow.
`feed_dict`	Get the feed dict for training.
`hook_lists`	Get all the hook lists.
`inputs`	Get the input placeholders.
`loop`	Get the training loop object.
`loss`	Get the training loss.
`metric_name`	Get the metric name for collecting training loss.
`metrics`	Get the metrics to be computed along with train_op.
`summaries`	Get the summaries to be computed along with train_op.
`train_op`	Get the training operation.

Methods Summary

`anneal_after`(value[, epochs, steps])	Add an annealing hook to run after every few epochs or steps.
`anneal_after_epochs`(value, freq)	Add an annealing hook to run after every few epochs.
`anneal_after_steps`(value, freq)	Add an annealing hook to run after every few steps.
`evaluate_after`(evaluator[, epochs, steps])	Add an evaluation hook to run after every few epochs or steps.
`evaluate_after_epochs`(evaluator, freq)	Add an evaluation hook to run after every few epochs.
`evaluate_after_steps`(evaluator, freq)	Add an evaluation hook to run after every few steps.
`log_after`([epochs, steps])	Add a logging hook to run after every few epochs or steps.
`log_after_epochs`(freq)	Add a logging hook to run after every few epochs.
`log_after_steps`(freq)	Add a logging hook to run after every few steps.
`remove_annealing_hooks`()	Remove annealing hooks from all lists.
`remove_by_priority`(priority)	Remove hooks having the specified priority from all lists.
`remove_evaluation_hooks`()	Remove evaluation hooks from all lists.
`remove_log_hooks`()	Remove logging hooks from all lists.
`remove_validation_hooks`()	Remove evaluation hooks from all lists.
`run`(**kwargs)	Run training loop.
`validate_after`(evaluator[, epochs, steps])	Add an evaluation hook to run after every few epochs or steps.
`validate_after_epochs`(evaluator, freq)	Add an evaluation hook to run after every few epochs.
`validate_after_steps`(evaluator, freq)	Add an evaluation hook to run after every few steps.

Attributes Documentation

after_epochs¶

Get the hooks run after epochs.

Returns:	The hook list.
Return type:	HookList

after_steps¶

Get the hooks run after steps.

Returns:	The hook list.
Return type:	HookList

before_epochs¶

Get the hooks run before epochs.

Returns:	The hook list.
Return type:	HookList

before_steps¶

Get the hooks run before steps.

Returns:	The hook list.
Return type:	HookList

data_flow¶

Get the training data flow.

Returns:	The training data flow.
Return type:	DataFlow

feed_dict¶

Get the feed dict for training.

Returns:	The feed dict for training.
Return type:	dict[tf.Tensor, any]

hook_lists¶

Get all the hook lists.

Returns:	The tuple (self.before_epochs, self.before_steps, self.after_steps, self.after_epochs).
Return type:	tuple[HookList]

inputs¶

Get the input placeholders.

Returns:	The input placeholders.
Return type:	list[tf.Tensor]

loop¶

Get the training loop object.

Returns:	The training loop object.
Return type:	TrainLoop

loss¶: Get the training loss.

metric_name¶: Get the metric name for collecting training loss.

metrics¶: Get the metrics to be computed along with train_op.

summaries¶: Get the summaries to be computed along with train_op.

train_op¶: Get the training operation.

Methods Documentation

anneal_after(value, epochs=None, steps=None)¶

Add an annealing hook to run after every few epochs or steps.

Parameters:	value (AnnealingVariable or () -> any) – An annealing variable (which has `.anneal()`), or any callable object. epochs (None or int) – Run validation after every this few epochs. steps (None or int) – Run validation after every this few steps.
Raises:	`ValueError` – If both epochs and steps are specified, or neither is specified.

anneal_after_epochs(value, freq)¶

Add an annealing hook to run after every few epochs.

Parameters:	value (AnnealingVariable or () -> any) – An annealing variable (which has `.anneal()`), or any callable object. freq (int) – The frequency for this annealing hook to run.

anneal_after_steps(value, freq)¶

Add an annealing hook to run after every few steps.

Parameters:	value (AnnealingVariable or () -> any) – An annealing variable (which has `.anneal()`), or any callable object. freq (int) – The frequency for this annealing hook to run.

evaluate_after(evaluator, epochs=None, steps=None)¶

Add an evaluation hook to run after every few epochs or steps.

Parameters:	evaluator (Evaluator or () -> any) – A evaluator object (which has `.run()`), or any callable object. epochs (None or int) – Run validation after every this few epochs. steps (None or int) – Run validation after every this few steps.
Raises:	`ValueError` – If both epochs and steps are specified, or neither is specified.

evaluate_after_epochs(evaluator, freq)¶

Add an evaluation hook to run after every few epochs.

Parameters:	evaluator (Evaluator or () -> any) – A evaluator object (which has `.run()`), or any callable object. freq (int) – The frequency for this evaluation hook to run.

evaluate_after_steps(evaluator, freq)¶

Add an evaluation hook to run after every few steps.

Parameters:	evaluator (Evaluator or () -> any) – A evaluator object (which has `.run()`), or any callable object. freq (int) – The frequency for this evaluation hook to run.

log_after(epochs=None, steps=None)¶

Add a logging hook to run after every few epochs or steps.

Parameters:	epochs (None or int) – Run validation after every this few epochs. steps (None or int) – Run validation after every this few steps.
Raises:	`ValueError` – If both epochs and steps are specified, or neither is specified.

log_after_epochs(freq)¶

Add a logging hook to run after every few epochs.

Parameters:	freq (int) – The frequency for this logging hook to run.

log_after_steps(freq)¶

Add a logging hook to run after every few steps.

Parameters:	freq (int) – The frequency for this logging hook to run.

remove_annealing_hooks()¶

Remove annealing hooks from all lists.

Returns:	The number of removed hooks.
Return type:	int

remove_by_priority(priority)¶

Remove hooks having the specified priority from all lists.

Parameters:	priority – The priority of the hooks to be removed.
Returns:	The number of removed hooks.
Return type:	int

remove_evaluation_hooks()¶

Remove evaluation hooks from all lists.

Returns:	The number of removed hooks.
Return type:	int

remove_log_hooks()¶

Remove logging hooks from all lists.

Returns:	The number of removed hooks.
Return type:	int

remove_validation_hooks()¶

Remove evaluation hooks from all lists.

Returns:	The number of removed hooks.
Return type:	int

run(**kwargs)¶

Run training loop.

Parameters:	feed_dict – DEPRECATED. The extra feed dict to be merged with the already configured dict. (default `None`)

validate_after(evaluator, epochs=None, steps=None)¶

Add an evaluation hook to run after every few epochs or steps.

Parameters:	evaluator (Evaluator or () -> any) – A evaluator object (which has `.run()`), or any callable object. epochs (None or int) – Run validation after every this few epochs. steps (None or int) – Run validation after every this few steps.
Raises:	`ValueError` – If both epochs and steps are specified, or neither is specified.

validate_after_epochs(evaluator, freq)¶

Add an evaluation hook to run after every few epochs.

Parameters:	evaluator (Evaluator or () -> any) – A evaluator object (which has `.run()`), or any callable object. freq (int) – The frequency for this evaluation hook to run.

validate_after_steps(evaluator, freq)¶

Add an evaluation hook to run after every few steps.

Parameters:	evaluator (Evaluator or () -> any) – A evaluator object (which has `.run()`), or any callable object. freq (int) – The frequency for this evaluation hook to run.