def _test_fitting(self, params, logs, has_valid=True):
self.assertEqual(len(logs), params['epochs'])
train_dict = dict(zip(self.metrics_names, self.metrics_values), loss=ANY)
if has_valid:
val_metrics_names = ['val_' + metric_name for metric_name in self.metrics_names]
val_dict = dict(zip(val_metrics_names, self.metrics_values), val_loss=ANY)
log_dict = {**train_dict, **val_dict}
else:
log_dict = train_dict
for epoch, log in enumerate(logs, 1):
self.assertEqual(log, dict(log_dict, epoch=epoch))
call_list = []
call_list.append(call.on_train_begin({}))
for epoch in range(1, params['epochs']+1):
call_list.append(call.on_epoch_begin(epoch, {}))
for step in range(1, params['steps']+1):
call_list.append(call.on_batch_begin(step, {}))
call_list.append(call.on_backward_end(step))
call_list.append(call.on_batch_end(step, {'batch': step, 'size': ANY, **train_dict}))
call_list.append(call.on_epoch_end(epoch, {'epoch': epoch, **log_dict}))
call_list.append(call.on_train_end({}))
method_calls = self.mock_callback.method_calls
self.assertIn(call.set_model(self.model), method_calls[:2])
self.assertIn(call.set_params(params), method_calls[:2])
self.assertEqual(len(method_calls), len(call_list) + 2)
self.assertEqual(method_calls[2:], call_list)
def _test_batch_delay(self, epoch_delay, batch_in_epoch_delay):
batch_delay = epoch_delay*DelayCallbackTest.steps_per_epoch + batch_in_epoch_delay
delay_callback = DelayCallback(self.mock_callback, batch_delay=batch_delay)
train_generator = some_data_generator(DelayCallbackTest.batch_size)
valid_generator = some_data_generator(DelayCallbackTest.batch_size)
logs = self.model.fit_generator(train_generator, valid_generator, epochs=DelayCallbackTest.epochs, steps_per_epoch=DelayCallbackTest.steps_per_epoch, validation_steps=DelayCallbackTest.steps_per_epoch, callbacks=[delay_callback])
params = {'epochs': DelayCallbackTest.epochs, 'steps': DelayCallbackTest.steps_per_epoch}
call_list = []
call_list.append(call.on_train_begin({}))
for epoch in range(epoch_delay + 1, DelayCallbackTest.epochs+1):
call_list.append(call.on_epoch_begin(epoch, {}))
start_step = batch_in_epoch_delay + 1 if epoch == epoch_delay + 1 else 1
for step in range(start_step, params['steps']+1):
call_list.append(call.on_batch_begin(step, {}))
call_list.append(call.on_backward_end(step))
call_list.append(call.on_batch_end(step, {'batch': step, 'size': DelayCallbackTest.batch_size, **self.train_dict}))
call_list.append(call.on_epoch_end(epoch, {'epoch': epoch, **self.log_dict}))
call_list.append(call.on_train_end({}))
method_calls = self.mock_callback.method_calls
self.assertIn(call.set_model(self.model), method_calls[:2])
self.assertIn(call.set_params(params), method_calls[:2])
self.assertEqual(len(method_calls), len(call_list) + 2)
self.assertEqual(method_calls[2:], call_list)
