
'''simple docstring'''

import json
import os
import unittest

from transformers.models.fsmt.tokenization_fsmt import VOCAB_FILES_NAMES, FSMTTokenizer
from transformers.testing_utils import slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


# using a different tiny model than the one used for default params defined in init to ensure proper testing
UpperCAmelCase__				:	int					=						"stas/tiny-wmt19-en-ru"






class 				A       (		SCREAMING_SNAKE_CASE__					, unittest.TestCase      ):
	snake_case__ :Optional[int]				       =       FSMTTokenizer
	snake_case__ :Dict				       =       False





	def 							__SCREAMING_SNAKE_CASE					(   self     :    List[Any]							):


				"""simple docstring"""

				super().setUp()

				# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
				lowerCAmelCase__									=							[
				    "l",
				    "o",
				    "w",
				    "e",
				    "r",
				    "s",
				    "t",
				    "i",
				    "d",
				    "n",
				    "w</w>",
				    "r</w>",
				    "t</w>",
				    "lo",
				    "low",
				    "er</w>",
				    "low</w>",
				    "lowest</w>",
				    "newer</w>",
				    "wider</w>",
				    "<unk>",
				]
				lowerCAmelCase__									=							dict(zip(__magic_name__ ,							range(len(__magic_name__							)							)							)							)
				lowerCAmelCase__									=							["l o 123", "lo w 1456", "e r</w> 1789", ""]

				lowerCAmelCase__									=							["en", "ru"]
				lowerCAmelCase__									=							{
				    "langs": self.langs,
				    "src_vocab_size": 10,
				    "tgt_vocab_size": 20,
				}

				lowerCAmelCase__									=							os.path.join(self.tmpdirname ,							VOCAB_FILES_NAMES["src_vocab_file"]							)
				lowerCAmelCase__									=							os.path.join(self.tmpdirname ,							VOCAB_FILES_NAMES["tgt_vocab_file"]							)
				lowerCAmelCase__									=							os.path.join(self.tmpdirname ,							"tokenizer_config.json"							)
				lowerCAmelCase__									=							os.path.join(self.tmpdirname ,							VOCAB_FILES_NAMES["merges_file"]							)
				with open(self.src_vocab_file ,							"w"							) as fp:
							fp.write(json.dumps(__magic_name__							)							)
				with open(self.tgt_vocab_file ,							"w"							) as fp:
							fp.write(json.dumps(__magic_name__							)							)
				with open(self.merges_file ,							"w"							) as fp:
							fp.write("\n".join(__magic_name__							)							)
				with open(__magic_name__ ,							"w"							) as fp:
							fp.write(json.dumps(__magic_name__							)							)





	@cached_property
	def 							__SCREAMING_SNAKE_CASE					(   self     :    int							):


				"""simple docstring"""

				return FSMTTokenizer.from_pretrained("facebook/wmt19-ru-en"							)





	@cached_property
	def 							__SCREAMING_SNAKE_CASE					(   self     :    int							):


				"""simple docstring"""

				return FSMTTokenizer.from_pretrained("facebook/wmt19-en-ru"							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Any							):


				"""simple docstring"""

				lowerCAmelCase__									=							FSMTTokenizer.from_pretrained(__magic_name__							)
				self.assertListEqual([tokenizer.src_lang, tokenizer.tgt_lang] ,							["en", "ru"]							)
				self.assertEqual(tokenizer.src_vocab_size ,							21							)
				self.assertEqual(tokenizer.tgt_vocab_size ,							21							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Any							):


				"""simple docstring"""

				lowerCAmelCase__									=							FSMTTokenizer(self.langs ,							self.src_vocab_file ,							self.tgt_vocab_file ,							self.merges_file							)

				lowerCAmelCase__									=							"lower"
				lowerCAmelCase__									=							["low", "er</w>"]
				lowerCAmelCase__									=							tokenizer.tokenize(__magic_name__							)
				self.assertListEqual(__magic_name__ ,							__magic_name__							)

				lowerCAmelCase__									=							tokens + ["<unk>"]
				lowerCAmelCase__									=							[14, 15, 20]
				self.assertListEqual(tokenizer.convert_tokens_to_ids(__magic_name__							) ,							__magic_name__							)





	@slow
	def 							__SCREAMING_SNAKE_CASE					(   self     :    Any							):


				"""simple docstring"""

				lowerCAmelCase__									=							self.tokenizer_ru_en

				lowerCAmelCase__									=							tokenizer.encode("sequence builders" ,							add_special_tokens=__magic_name__							)
				lowerCAmelCase__									=							tokenizer.encode("multi-sequence build" ,							add_special_tokens=__magic_name__							)

				lowerCAmelCase__									=							tokenizer.build_inputs_with_special_tokens(__magic_name__							)
				lowerCAmelCase__									=							tokenizer.build_inputs_with_special_tokens(__magic_name__ ,							__magic_name__							)

				assert encoded_sentence == text + [2]
				assert encoded_pair == text + [2] + text_a + [2]





	@slow
	def 							__SCREAMING_SNAKE_CASE					(   self     :    Union[str, Any]							):


				"""simple docstring"""

				lowerCAmelCase__									=							self.tokenizer_en_ru
				lowerCAmelCase__									=							self.tokenizer_ru_en

				lowerCAmelCase__									=							[
				    [
				        "Here's a little song I wrote. Don't worry, be happy.",
				        [2470, 39, 11, 2349, 7222, 70, 5979, 7, 8450, 1050, 13160, 5, 26, 6445, 7, 2],
				    ],
				    ["This is it. No more. I'm done!", [132, 21, 37, 7, 1434, 86, 7, 70, 6476, 1305, 427, 2]],
				]

				# if data needs to be recreated or added, run:
				# import torch
				# model = torch.hub.load("pytorch/fairseq", "transformer.wmt19.en-ru", checkpoint_file="model4.pt", tokenizer="moses", bpe="fastbpe")
				# for src_text, _ in targets: print(f"""[\n"{src_text}",\n {model.encode(src_text).tolist()}\n],""")

				for src_text, tgt_input_ids in targets:
							lowerCAmelCase__									=							tokenizer_enc.encode(__magic_name__ ,							return_tensors=__magic_name__							)
							self.assertListEqual(__magic_name__ ,							__magic_name__							)

							# and decode backward, using the reversed languages model
							lowerCAmelCase__									=							tokenizer_dec.decode(__magic_name__ ,							skip_special_tokens=__magic_name__							)
							self.assertEqual(__magic_name__ ,							__magic_name__							)





	@slow
	def 							__SCREAMING_SNAKE_CASE					(   self     :    Dict							):


				"""simple docstring"""

				lowerCAmelCase__									=							FSMTTokenizer.from_pretrained("facebook/wmt19-ru-en" ,							do_lower_case=__magic_name__							)
				lowerCAmelCase__									=							tokenizer.tokenize("USA is United States of America"							)
				lowerCAmelCase__									=							["us", "a</w>", "is</w>", "un", "i", "ted</w>", "st", "ates</w>", "of</w>", "am", "er", "ica</w>"]
				self.assertListEqual(__magic_name__ ,							__magic_name__							)





	@unittest.skip("FSMTConfig.__init__  requires non-optional args"							)
	def 							__SCREAMING_SNAKE_CASE					(   self     :    Union[str, Any]							):


				"""simple docstring"""

				pass







	@unittest.skip("FSMTConfig.__init__  requires non-optional args"							)
	def 							__SCREAMING_SNAKE_CASE					(   self     :    int							):


				"""simple docstring"""

				pass







'''simple docstring'''

import unittest

from transformers import load_tool
from transformers.tools.agent_types import AGENT_TYPE_MAPPING

from .test_tools_common import ToolTesterMixin, output_types






class 				A       (		unittest.TestCase					, SCREAMING_SNAKE_CASE__      ):





	def 							__SCREAMING_SNAKE_CASE					(   self     :    List[Any]							):


				"""simple docstring"""

				lowerCAmelCase__									=							load_tool("translation"							)
				self.tool.setup()
				lowerCAmelCase__									=							load_tool("translation" ,							remote=__magic_name__							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Tuple							):


				"""simple docstring"""

				lowerCAmelCase__									=							self.tool("Hey, what's up?" ,							src_lang="English" ,							tgt_lang="French"							)
				self.assertEqual(__magic_name__ ,							"- Hé, comment ça va?"							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Optional[int]							):


				"""simple docstring"""

				lowerCAmelCase__									=							self.remote_tool("Hey, what's up?" ,							src_lang="English" ,							tgt_lang="French"							)
				self.assertEqual(__magic_name__ ,							"- Hé, comment ça va?"							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    List[Any]							):


				"""simple docstring"""

				lowerCAmelCase__									=							self.tool(text="Hey, what's up?" ,							src_lang="English" ,							tgt_lang="French"							)
				self.assertEqual(__magic_name__ ,							"- Hé, comment ça va?"							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    int							):


				"""simple docstring"""

				lowerCAmelCase__									=							self.remote_tool(text="Hey, what's up?" ,							src_lang="English" ,							tgt_lang="French"							)
				self.assertEqual(__magic_name__ ,							"- Hé, comment ça va?"							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    int							):


				"""simple docstring"""

				lowerCAmelCase__									=							["Hey, what's up?", "English", "Spanish"]
				lowerCAmelCase__									=							self.tool(*__magic_name__							)

				# There is a single output
				if len(self.tool.outputs							) == 1:
							lowerCAmelCase__									=							[outputs]

				self.assertListEqual(output_types(__magic_name__							) ,							self.tool.outputs							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    str							):


				"""simple docstring"""

				lowerCAmelCase__									=							["Hey, what's up?", "English", "Spanish"]
				lowerCAmelCase__									=							self.tool(*__magic_name__							)

				if not isinstance(__magic_name__ ,							__magic_name__							):
							lowerCAmelCase__									=							[outputs]

				self.assertEqual(len(__magic_name__							) ,							len(self.tool.outputs							)							)

				for output, output_type in zip(__magic_name__ ,							self.tool.outputs							):
							lowerCAmelCase__									=							AGENT_TYPE_MAPPING[output_type]
							self.assertTrue(isinstance(__magic_name__ ,							__magic_name__							)							)







	def 							__SCREAMING_SNAKE_CASE					(   self     :    int							):


				"""simple docstring"""

				lowerCAmelCase__									=							["Hey, what's up?", "English", "Spanish"]

				lowerCAmelCase__									=							[]

				for _input, input_type in zip(__magic_name__ ,							self.tool.inputs							):
							if isinstance(__magic_name__ ,							__magic_name__							):
										_inputs.append([AGENT_TYPE_MAPPING[_input_type](_input							) for _input_type in input_type]							)
							else:
										_inputs.append(AGENT_TYPE_MAPPING[input_type](_input							)							)

        # Should not raise an error
				lowerCAmelCase__									=							self.tool(*__magic_name__							)

				if not isinstance(__magic_name__ ,							__magic_name__							):
							lowerCAmelCase__									=							[outputs]

				self.assertEqual(len(__magic_name__							) ,							len(self.tool.outputs							)							)





