[examples] Cleanup summarization docs (#4876)

examples/summarization/README.md

 ### Get CNN Data
-Both types of models do require CNN data and follow different procedures of obtaining so.
-
-#### For BART models
 To be able to reproduce the authors' results on the CNN/Daily Mail dataset you first need to download both CNN and Daily Mail datasets [from Kyunghyun Cho's website](https://cs.nyu.edu/~kcho/DMQA/) (the links next to "Stories") in the same folder. Then uncompress the archives by running:
 
 ```bash
@@ -12,40 +9,17 @@ tar -xzvf cnn_dm.tgz
 this should make a directory called cnn_dm/ with files like `test.source`.
 To use your own data, copy that files format. Each article to be summarized is on its own line.
 
-#### For T5 models
-First, you need to download the CNN data. It's about ~400 MB and can be downloaded by
-running
-
-```bash
-python download_cnn_daily_mail.py cnn_articles_input_data.txt cnn_articles_reference_summaries.txt
-```
-
-You should confirm that each file has 11490 lines:
-
-```bash
-wc -l cnn_articles_input_data.txt # should print 11490
-wc -l cnn_articles_reference_summaries.txt # should print 11490
-```
-
 ### Evaluation
 
 To create summaries for each article in dataset, run:
 ```bash
-python evaluate_cnn.py <path_to_test.source> test_generations.txt <model-name>
+python evaluate_cnn.py <path_to_test.source> test_generations.txt <model-name>  --score_path rouge_scores.txt
 ```
 The default batch size, 8, fits in 16GB GPU memory, but may need to be adjusted to fit your system.
 
 ### Training
 Run/modify `finetune_bart.sh` or `finetune_t5.sh`
 
-## (WIP) Rouge Scores
-
-To create summaries for each article in dataset and also calculate rouge scores run:
-```bash
-python evaluate_cnn.py <path_to_test.source> test_generations.txt <model-name> --reference_path <path_to_correct_summaries> --score_path <path_to_save_rouge_scores>
-```
-The rouge scores "rouge1, rouge2, rougeL" are automatically created and saved in ``<path_to_save_rouge_scores>``.
-
 ### Stanford CoreNLP Setup
 ```
 ptb_tokenize () {

examples/summarization/download_cnn_daily_mail.py

-# -*- coding: utf-8 -*-
-import argparse
-from pathlib import Path
-
-import tensorflow_datasets as tfds
-
-
-def main(input_path, reference_path, data_dir):
-    cnn_ds = tfds.load("cnn_dailymail", split="test", shuffle_files=False, data_dir=data_dir)
-    cnn_ds_iter = tfds.as_numpy(cnn_ds)
-
-    test_articles_file = Path(input_path).open("w", encoding="utf-8")
-    test_summaries_file = Path(reference_path).open("w", encoding="utf-8")
-
-    for example in cnn_ds_iter:
-        test_articles_file.write(example["article"].decode("utf-8") + "\n")
-        test_articles_file.flush()
-        test_summaries_file.write(example["highlights"].decode("utf-8").replace("\n", " ") + "\n")
-        test_summaries_file.flush()
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument("input_path", type=str, help="where to save the articles input data")
-    parser.add_argument(
-        "reference_path", type=str, help="where to save the reference summaries",
-    )
-    parser.add_argument(
-        "--data_dir", type=str, default="~/tensorflow_datasets", help="where to save the tensorflow datasets.",
-    )
-    args = parser.parse_args()
-    main(args.input_path, args.reference_path, args.data_dir)

examples/summarization/finetune_bart.sh

@@ -6,7 +6,7 @@ export OUTPUT_DIR=${CURRENT_DIR}/${OUTPUT_DIR_NAME}
 mkdir -p $OUTPUT_DIR
 
 # Add parent directory to python path to access lightning_base.py
-export PYTHONPATH="../../":"${PYTHONPATH}"
+export PYTHONPATH="../":"${PYTHONPATH}"
 
 python finetune.py \
 --data_dir=./cnn-dailymail/cnn_dm \

examples/summarization/finetune_bart_tiny.sh

@@ -13,7 +13,7 @@ export OUTPUT_DIR=${CURRENT_DIR}/${OUTPUT_DIR_NAME}
 mkdir -p $OUTPUT_DIR
 
 # Add parent directory to python path to access lightning_base.py and utils.py
-export PYTHONPATH="../../":"${PYTHONPATH}"
+export PYTHONPATH="../":"${PYTHONPATH}"
 python finetune.py \
 --data_dir=cnn_tiny/ \
 --model_type=bart \

examples/summarization/finetune_t5.sh

@@ -6,7 +6,7 @@ export OUTPUT_DIR=${CURRENT_DIR}/${OUTPUT_DIR_NAME}
 mkdir -p $OUTPUT_DIR
 
 # Add parent directory to python path to access lightning_base.py
-export PYTHONPATH="../../":"${PYTHONPATH}"
+export PYTHONPATH="../":"${PYTHONPATH}"
 
 python finetune.py \
 --data_dir=./cnn-dailymail/cnn_dm \