373da2dac77ca1a4b0b1e580cf21d847d7676ae1,train.py,,run,#Any#Any#Any#Any#Any#Any#,42

Before Change

        // Save predictions
        filenames_evaluation = glob(os.path.join(eval_images_dir, "*.jpg"))
        exported_files_eval_dir = os.path.join(model_output_dir, "exported_eval_files", "epoch_{}".format(i))
        os.makedirs(exported_files_eval_dir, exist_ok=True)
        // Predict and save probs
        for filename in filenames_evaluation:  // tqdm(filenames_evaluation):

After Change

                                       params=_config))

        // Export model (filename, batch_size = 1) and predictions
        exported_path = estimator.export_savedmodel(os.path.join(model_output_dir, "export"),
                                                    input.serving_input_filename(training_params.input_resized_size))
        exported_path = exported_path.decode()
        timestamp_exported = exported_path.split("/")[-1]

        // Save predictions
        filenames_evaluation = glob(os.path.join(eval_images_dir, "*.jpg"))
        exported_files_eval_dir = os.path.join(model_output_dir, "eval",

Instances