text: import os, json, argparse
  from datetime import datetime
  
  from tqdm import tqdm
  
  
  class Distil:
      DATA_DIR = "{root_dir}/openwebtext"
      DATA_OUTPUT_PATH = "{root_dir}/openwebtext.txt"
      DATA_BINARIZED_OUTPUT_PATH = "{root_dir}/distil/openwebtext_binarized/{model_name}"
      DATA_TOKEN_COUNTS_OUTPUT_PATH = "{root_dir}/distil/openwebtext_token_counts/{model_name}"
      OUTPUT_PATH = "{root_dir}/distil/{model_name}/{timestamp}"
  
      def __init__(
          self,
          root_dir: str,
          model_type: str,
          model_name: str,
          config_file_path: str,
      ):
          self.root_dir = root_dir
          self.model_type = model_type
          self.model_name = model_name
          self.config_file_path = config_file_path
          self.config = json.load(open(config_file_path))
  
      def __call__(self):
          data_dir = self.DATA_DIR.format(root_dir=self.root_dir)
          if not os.path.exists(data_dir):
              os.mkdir(data_dir)
  
          data_output_path = self.DATA_OUTPUT_PATH.format(root_dir=self.root_dir)
          data_binarized_output_path = \
              self.DATA_BINARIZED_OUTPUT_PATH.format(
                  root_dir=self.root_dir,
                  model_name=self.model_name,
              )
          data_token_counts_output_path = \
              self.DATA_TOKEN_COUNTS_OUTPUT_PATH.format(
                  root_dir=self.root_dir,
                  model_name=self.model_name,
              )
  
          timestamp = str(datetime.now()).replace(" ", "_")
          output_path = self.OUTPUT_PATH.format(
              model_name=self.model_name,
              timestamp=timestamp,
              root_dir=self.root_dir,
          )
  
          if not os.path.exists(data_output_path):
              self.unzip_data(data_dir=data_dir)
              self.combine_data(
                  data_dir=data_dir,
                  data_output_path=data_output_path,
              )
  
          if not (os.path.exists(data_binarized_output_path) \
              and os.path.exists(data_token_counts_output_path)):
              self.process_data(
                  data_output_path=data_output_path,
                  data_binarized_output_path=data_binarized_output_path,
                  data_token_counts_output_path=data_token_counts_output_path,
              )
  
          self.train(
              data_binarized_output_path=data_binarized_output_path,
              data_token_counts_output_path=data_token_counts_output_path,
              output_path=output_path,
          )
  
      def unzip_data(self, data_dir: str):
          for p in tqdm(os.listdir(data_dir), desc="Unzipping"):
              path = os.path.join(data_dir, p)
              os.system(f"xz --decompress {path}")
  
      def combine_data(
          self,
          data_dir: str,
          data_output_path: str,
      ):
          sentences = []
          for p in tqdm(os.listdir(data_dir), desc="Combining"):
              path = os.path.join(data_dir, p)
              contents = open(path, "r").read().splitlines()
              contents = [c for c in contents if c]
              sentences.extend(contents)
  
          open(data_output_path, "w").write("\n".join(sentences))
  
      def process_data(
          self,
          data_output_path: str,
          data_binarized_output_path: str,
          data_token_counts_output_path: str,
      ):
          os.system(" ".join((
              "python scripts/binarized_data.py",
              f"--file_path {data_output_path}",
              f"--tokenizer_type {self.model_type}",
              f"--tokenizer_name {self.model_name}",
              f"--dump_file {data_binarized_output_path}",
          )))
  
          vocab_size = self.config["vocab_size"]
          os.system(" ".join((
              "python scripts/token_counts.py",
              f"--data_file {data_binarized_output_path}",
              f"--token_counts_dump {data_token_counts_output_path}",
              f"--vocab_size {vocab_size}",
          )))
  
      def train(
          self,
          data_binarized_output_path: str,
          data_token_counts_output_path: str,
          output_path: str,
      ):
          os.system(" ".join((
              "python train.py",
              f"--student_type {self.model_type}",
              f"--student_config {self.config_file_path}",
              f"--teacher_type {self.model_type}",
              f"--teacher_name {self.model_name}",
              "--alpha_ce 5.0 --alpha_mlm 2.0 --alpha_cos 1.0 --alpha_clm 0.0 --mlm",
              "--freeze_pos_embs",
              f"--dump_path {output_path}",
              f"--data_file {data_binarized_output_path}",
              f"--token_counts {data_token_counts_output_path}",
              "--force",
          )))
  
  
  if __name__ == "__main__":
      parser = argparse.ArgumentParser()
  
      parser.add_argument("-r", "--root_dir")
      parser.add_argument("-m", "--model_type")
      parser.add_argument("-n", "--model_name")
      parser.add_argument("-c", "--config_file_path")
  
      args = parser.parse_args()
  
      distil = Distil(
          args.root_dir,
          args.model_type,
          args.model_name,
          args.config_file_path
      )
      distil()
  