LossTrainer¶
-
class
tfsnippet.
LossTrainer
(**kwargs)¶ Bases:
tfsnippet.trainer.trainer.Trainer
A subclass of
BaseTrainer
, which optimizes a single loss.Attributes Summary
data_flow
Get the training data flow. events
Get the event source object. feed_dict
Get the feed dict for training. 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_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
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events
¶ Get the event source object.
Returns: The event source object. Return type: EventSource
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feed_dict
¶ Get the feed dict for training.
Returns: The feed dict for training. Return type: dict[tf.Tensor, any]
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loss
¶ Get the training loss.
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metric_name
¶ Get the metric name for collecting training loss.
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metrics
¶ Get the metrics to be computed along with train_op.
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summaries
¶ Get the summaries to be computed along with train_op.
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train_op
¶ Get the training operation.
Methods Documentation
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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.- value (AnnealingVariable or () -> any) – An annealing variable
(which has
-
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.
- value (AnnealingVariable or () -> any) – An annealing variable
(which has
-
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.
- value (AnnealingVariable or () -> any) – An annealing variable
(which has
-
evaluate_after
(evaluator, epochs=None, steps=None)¶ Add an evaluation hook to run after every few epochs or steps.
Parameters: Raises: ValueError
– If both epochs and steps are specified, or neither is specified.
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evaluate_after_epochs
(evaluator, freq)¶ Add an evaluation hook to run after every few epochs.
Parameters:
-
evaluate_after_steps
(evaluator, freq)¶ Add an evaluation hook to run after every few steps.
Parameters:
-
log_after
(epochs=None, steps=None)¶ Add a logging hook to run after every few epochs or steps.
Parameters: Raises: ValueError
– If both epochs and steps are specified, or neither is specified.
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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
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remove_evaluation_hooks
()¶ Remove evaluation hooks from all lists.
Returns: The number of removed hooks. Return type: int
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remove_log_hooks
()¶ Remove logging hooks from all lists.
Returns: The number of removed hooks. Return type: int
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remove_validation_hooks
()¶ Remove evaluation hooks from all lists.
Returns: The number of removed hooks. Return type: int
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run
(**kwargs)¶ Run training loop.
Parameters: feed_dict – DEPRECATED. The extra feed dict to be merged with the already configured dict. (default None
)
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validate_after
(evaluator, epochs=None, steps=None)¶ Add an evaluation hook to run after every few epochs or steps.
Parameters: 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:
-