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Quick fix to TF summarization example (#14401)

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Matt 2021-11-15 13:45:51 +00:00 committed by GitHub
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examples/tensorflow/summarization/run_summarization.py
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@ -577,7 +577,7 @@ def main():
# region Optimizer, loss and LR scheduling # region Optimizer, loss and LR scheduling
# Scheduler and math around the number of training steps. # Scheduler and math around the number of training steps.
num_update_steps_per_epoch = len(train_dataset) // training_args.per_device_train_batch_size num_update_steps_per_epoch = len(train_dataset) // total_train_batch_size
num_train_steps = training_args.num_train_epochs * num_update_steps_per_epoch num_train_steps = training_args.num_train_epochs * num_update_steps_per_epoch
optimizer, lr_schedule = create_optimizer( optimizer, lr_schedule = create_optimizer(
init_lr=training_args.learning_rate, num_train_steps=num_train_steps, num_warmup_steps=0 init_lr=training_args.learning_rate, num_train_steps=num_train_steps, num_warmup_steps=0