Validator¶

class tfsnippet.Validator(**kwargs)¶

Bases: tfsnippet.trainer.evaluator.Evaluator

Class to compute validation loss and other metrics.

Attributes Summary

`batch_weight_func`	Get the function to compute the metric weight for each mini-batch.
`data_flow`	Get the validation data flow.
`events`	Get the event source object.
`feed_dict`	Get the fixed feed dict.
`inputs`	Get the input placeholders.
`last_metrics_dict`	Get the metric values from last evaluation.
`loop`	Get the training loop object.
`metrics`	Get the metrics to compute.
`time_metric_name`	Get the metric name for collecting evaluation time usage.

Methods Summary

run([feed_dict]) Run evaluation.

Attributes Documentation

batch_weight_func¶: Get the function to compute the metric weight for each mini-batch.

data_flow¶

Get the validation data flow.

Returns:	The validation data flow.
Return type:	DataFlow

events¶

Get the event source object.

Returns:	The event source object.
Return type:	EventSource

feed_dict¶

Get the fixed feed dict.

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

inputs¶

Get the input placeholders.

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

last_metrics_dict¶

Get the metric values from last evaluation.

Returns:	The metric values dict.
Return type:	dict[str, any]

loop¶

Get the training loop object.

Returns:	The training loop object.
Return type:	TrainLoop

metrics¶

Get the metrics to compute.

Returns:	The metrics to compute.
Return type:	OrderedDict[str, tf.Tensor]

time_metric_name¶: Get the metric name for collecting evaluation time usage.

Methods Documentation

run(feed_dict=None)¶

Run evaluation.

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