Reporting

reporting.Reporter is used to collect values that users want to watch. The reporter object holds a mapping from value names to the actually observed values. We call this mapping observations.

When a value is passed to the reporter, an object called observer can be optionally attached. In this case, the name of the observer is added as the prefix of the value name. The observer name should be registered beforehand.

import pytorch_pfn_extras as ppe

reporter = ppe.reporting.Reporter()
observer = object()
reporter.add_observer('my_observer', observer)
observation = {}

with reporter.scope(observation):
    reporter.report({'x': 1}, observer)

print(observation)
# outputs: {'my_observer/x': 1}

There is also a global API to add values:

import pytorch_pfn_extras as ppe

reporter = ppe.reporting.Reporter()
observer = object()
reporter.add_observer('my_observer', observer)

observation = {}
with reporter:
    with ppe.reporting.report_scope(observation):
         ppe.reporting.report({'x': 1}, observer)

print(observation)
# outputs: {'my_observer/x': 1}

The most important application of Reporter is to report observed values from different parts of the model in the training and validation procedures. ExtensionsManager objects hold their own Reporter object with the parameters of the target module registered as observers. report() can be used inside the modules to report the observed values (e.g., training loss, accuracy, activation statistics, etc.).