
# as due to their complexity multi-gpu tests could impact other tests, and to aid debug we have those in a separate module.

import os
import sys

from transformers.testing_utils import TestCasePlus, execute_subprocess_async, get_gpu_count, require_torch_gpu, slow

from .utils import load_json




class    _SCREAMING_SNAKE_CASE					( __UpperCamelCase	):
      @classmethod
      def A_     (     cls	):
          return cls



      @slow
      @require_torch_gpu
      def A_     (     self	):
          snake_case__  =			self.get_auto_remove_tmp_dir()
          snake_case__  =			F"""
            --model_name Helsinki-NLP/opus-mt-en-ro
            --save_dir {output_dir}
            --data_dir {self.test_file_dir_str}/test_data/wmt_en_ro
            --num_beams 2
            --task translation
        """.split()

          # we want this test to run even if there is only one GPU, but if there are more we use them all
          snake_case__  =			get_gpu_count()
          snake_case__  =			F"""
            -m torch.distributed.launch
            --nproc_per_node={n_gpu}
            {self.test_file_dir}/run_distributed_eval.py
        """.split()
          snake_case__  =			[sys.executable] + distributed_args + args
          execute_subprocess_async(lowerCamelCase						,		env=self.get_env()	)

          snake_case__  =			os.path.join(lowerCamelCase						,		"test_bleu.json"	)
          snake_case__  =			load_json(lowerCamelCase	)
          # print(metrics)
          self.assertGreaterEqual(metrics["bleu"]						,		25	)





import os
import tempfile
import unittest
from typing import List

from transformers.models.esm.tokenization_esm import VOCAB_FILES_NAMES, EsmTokenizer
from transformers.testing_utils import require_tokenizers
from transformers.tokenization_utils import PreTrainedTokenizer
from transformers.tokenization_utils_base import PreTrainedTokenizerBase




@require_tokenizers
class    _SCREAMING_SNAKE_CASE					( unittest.TestCase	):
      _A  :						Optional[Any]      		=       EsmTokenizer
      def A_     (     self	):
          super().setUp()
          snake_case__  =			tempfile.mkdtemp()
          # fmt: off
          snake_case__  =			["<cls>", "<pad>", "<eos>", "<unk>", "L", "A", "G", "V", "S", "E", "R", "T", "I", "D", "P", "K", "Q", "N", "F", "Y", "M", "H", "W", "C", "X", "B", "U", "Z", "O", ".", "-", "<null_1>", "<mask>"]  # noqa: E501
          # fmt: on
          snake_case__  =			os.path.join(self.tmpdirname						,		VOCAB_FILES_NAMES["vocab_file"]	)
          with open(self.vocab_file						,		"w"						,		encoding="utf-8"	) as vocab_writer:
              vocab_writer.write("".join([x + "\n" for x in vocab_tokens]	)	)
      def A_     (     self						,		**lowerCamelCase	):
          return [self.get_tokenizer(**lowerCamelCase	)]
      def A_     (     self						,		**lowerCamelCase	):
          return self.tokenizer_class.from_pretrained(self.tmpdirname						,		**lowerCamelCase	)
      def A_     (     self	):
          snake_case__  =			self.tokenizer_class(self.vocab_file	)

          snake_case__  =			tokenizer.tokenize("LAGVS"	)
          self.assertListEqual(lowerCamelCase						,		["L", "A", "G", "V", "S"]	)
          self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase	)						,		[4, 5, 6, 7, 8]	)
      def A_     (     self	):
          snake_case__  =			self.tokenizer_class(self.vocab_file	)

          snake_case__  =			"LAGVS"
          self.assertListEqual(tokenizer.encode(lowerCamelCase	)						,		[0, 4, 5, 6, 7, 8, 2]	)
      def A_     (     self	):
          snake_case__  =			self.tokenizer_class(self.vocab_file	)

          snake_case__  =			["LAGVS", "WCB"]
          snake_case__  =			tokenizer(lowerCamelCase						,		padding=lowerCamelCase	)["input_ids"]

          self.assertListEqual(lowerCamelCase						,		[[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2]]	)
      def A_     (     self	):
          snake_case__  =			self.tokenizer_class(self.vocab_file	)

          snake_case__  =			["LAGVS", "WCB"]
          snake_case__  =			tokenizer(lowerCamelCase						,		padding=lowerCamelCase	)["input_ids"]

          self.assertListEqual(lowerCamelCase						,		[[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2, 1, 1]]	)



      def A_     (     self	):
          snake_case__  =			self.get_tokenizers(fast=lowerCamelCase	)
          for tokenizer in tokenizers:
              with self.subTest(F"""{tokenizer.__class__.__name__}"""	):
                  snake_case__  =			"<unk>"
                  snake_case__  =			"<mask>"

                  snake_case__  =			tokenizer.tokenize(lowerCamelCase	)
                  snake_case__  =			tokenizer.tokenize(lowerCamelCase	)

                  self.assertEqual(len(lowerCamelCase	)						,		1	)
                  self.assertEqual(len(lowerCamelCase	)						,		1	)
                  self.assertEqual(token_a[0]						,		lowerCamelCase	)
                  self.assertEqual(token_a[0]						,		lowerCamelCase	)



