benchmarks/fp8/transformer_engine/ddp.py [117:142]:
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    assert trained_model_results["accuracy"] > base_model_results["accuracy"], (
        f"Accuracy should be higher for the trained model: {trained_model_results['accuracy']} > {base_model_results['accuracy']}"
    )
    assert trained_model_results["f1"] > base_model_results["f1"], (
        f"F1 score should be higher for the trained model: {trained_model_results['f1']} > {base_model_results['f1']}"
    )

    return base_model_results, trained_model_results


if __name__ == "__main__":
    baseline_not_trained, baseline_trained = train_baseline()
    accelerator_not_trained, accelerator_trained = train_integration()

    assert baseline_not_trained["accuracy"] == accelerator_not_trained["accuracy"], (
        f"Accuracy should be the same for the baseline and accelerator: {baseline_not_trained['accuracy']} == {accelerator_not_trained['accuracy']}"
    )
    assert baseline_not_trained["f1"] == accelerator_not_trained["f1"], (
        f"F1 score should be the same for the baseline and accelerator: {baseline_not_trained['f1']} == {accelerator_not_trained['f1']}"
    )
    assert baseline_trained["accuracy"] == accelerator_trained["accuracy"], (
        f"Accuracy should be the same for the baseline and accelerator: {baseline_trained['accuracy']} == {accelerator_trained['accuracy']}"
    )
    assert baseline_trained["f1"] == accelerator_trained["f1"], (
        f"F1 score should be the same for the baseline and accelerator: {baseline_trained['f1']} == {accelerator_trained['f1']}"
    )
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