


'''simple docstring'''







import inspect
import os
import unittest
from pathlib import Path

import torch

import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command


class  lowerCAmelCase_						(       unittest.TestCase      ):





  """simple docstring"""



  a_       :Optional[int]												=inspect.getfile(accelerate.test_utils      )
  a_       :int												=os.path.sep.join(mod_file.split(os.path.sep      )[:-1] + ["""scripts""", """test_cli.py"""]      )

  a_       :str												=["""accelerate""", """launch"""]
  a_       :Tuple												=Path.home() / """.cache/huggingface/accelerate"""
  a_       :List[str]												="""default_config.yaml"""
  a_       :Union[str, Any]												=config_folder / config_file
  a_       :Dict												=config_folder / """_default_config.yaml"""

  a_       :Any												=Path("""tests/test_configs"""      )

  @classmethod
  def __a						(					cls     :							List[Any]						):





       '''simple docstring'''

       if cls.config_path.is_file():
            cls.config_path.rename(cls.changed_path						)

  @classmethod
  def __a						(					cls     :							Dict						):





       '''simple docstring'''

       if cls.changed_path.is_file():
            cls.changed_path.rename(cls.config_path						)

  def __a						(					self     :							str						):





       '''simple docstring'''

       __a       =   self.base_cmd
       if torch.cuda.is_available() and (torch.cuda.device_count() > 1):
            cmd += ["--multi_gpu"]
       execute_subprocess_async(cmd + [self.test_file_path]				,							env=os.environ.copy()						)

  def __a						(					self     :							Union[str, Any]						):





       '''simple docstring'''

       for config in sorted(self.test_config_path.glob("""**/*.yaml"""						)						):
            with self.subTest(config_file=SCREAMING_SNAKE_CASE__						):
                 execute_subprocess_async(
                     self.base_cmd + ["""--config_file""", str(SCREAMING_SNAKE_CASE__						), self.test_file_path]				,							env=os.environ.copy()						)


  def __a						(					self     :							Union[str, Any]						):





       '''simple docstring'''

       execute_subprocess_async(["""accelerate""", """test"""]				,							env=os.environ.copy()						)


class  lowerCAmelCase_						(       unittest.TestCase      ):





  """simple docstring"""



  a_       :Any												="""test-tpu"""
  a_       :str												="""us-central1-a"""
  a_       :str												="""ls"""
  a_       :Any												=["""accelerate""", """tpu-config"""]
  a_       :str												="""cd /usr/share"""
  a_       :str												="""tests/test_samples/test_command_file.sh"""
  a_       :Optional[Any]												="""Running gcloud compute tpus tpu-vm ssh"""

  def __a						(					self     :							List[Any]						):





       '''simple docstring'''

       __a       =   run_command(
           self.cmd
           + ["""--command""", self.command, """--tpu_zone""", self.tpu_zone, """--tpu_name""", self.tpu_name, """--debug"""]				,							return_stdout=SCREAMING_SNAKE_CASE__				,							)
       self.assertIn(
           f'''{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all'''				,							SCREAMING_SNAKE_CASE__				,							)

  def __a						(					self     :							List[str]						):





       '''simple docstring'''

       __a       =   run_command(
           self.cmd
           + [
               """--config_file""",
               """tests/test_configs/0_12_0.yaml""",
               """--command""",
               self.command,
               """--tpu_zone""",
               self.tpu_zone,
               """--tpu_name""",
               self.tpu_name,
               """--debug""",
           ]				,							return_stdout=SCREAMING_SNAKE_CASE__				,							)
       self.assertIn(
           f'''{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all'''				,							SCREAMING_SNAKE_CASE__				,							)

  def __a						(					self     :							Any						):





       '''simple docstring'''

       __a       =   run_command(
           self.cmd + ["""--config_file""", """tests/test_configs/latest.yaml""", """--debug"""]				,							return_stdout=SCREAMING_SNAKE_CASE__						)
       self.assertIn(
           f'''{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; echo "hello world"; echo "this is a second command" --worker all'''				,							SCREAMING_SNAKE_CASE__				,							)

  def __a						(					self     :							Union[str, Any]						):





       '''simple docstring'''

       __a       =   run_command(
           self.cmd + ["""--config_file""", """tests/test_configs/latest.yaml""", """--command""", self.command, """--debug"""]				,							return_stdout=SCREAMING_SNAKE_CASE__				,							)
       self.assertIn(
           f'''{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all'''				,							SCREAMING_SNAKE_CASE__				,							)

  def __a						(					self     :							Optional[int]						):





       '''simple docstring'''

       __a       =   run_command(
           self.cmd
           + [
               """--config_file""",
               """tests/test_configs/latest.yaml""",
               """--command""",
               self.command,
               """--command""",
               """echo \"Hello World\"""",
               """--debug""",
           ]				,							return_stdout=SCREAMING_SNAKE_CASE__				,							)
       self.assertIn(
           f'''{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls; echo "Hello World" --worker all'''				,							SCREAMING_SNAKE_CASE__				,							)

  def __a						(					self     :							Dict						):





       '''simple docstring'''

       __a       =   run_command(
           self.cmd
           + ["""--config_file""", """tests/test_configs/latest.yaml""", """--command_file""", self.command_file, """--debug"""]				,							return_stdout=SCREAMING_SNAKE_CASE__				,							)
       self.assertIn(
           f'''{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; echo "hello world"; echo "this is a second command" --worker all'''				,							SCREAMING_SNAKE_CASE__				,							)

  def __a						(					self     :							List[Any]						):





       '''simple docstring'''

       __a       =   run_command(
           self.cmd
           + [
               """--config_file""",
               """tests/test_configs/0_12_0.yaml""",
               """--command_file""",
               self.command_file,
               """--tpu_zone""",
               self.tpu_zone,
               """--tpu_name""",
               self.tpu_name,
               """--debug""",
           ]				,							return_stdout=SCREAMING_SNAKE_CASE__				,							)
       self.assertIn(
           f'''{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; echo "hello world"; echo "this is a second command" --worker all'''				,							SCREAMING_SNAKE_CASE__				,							)

  def __a						(					self     :							Any						):





       '''simple docstring'''

       __a       =   run_command(
           self.cmd + ["""--config_file""", """tests/test_configs/latest.yaml""", """--install_accelerate""", """--debug"""]				,							return_stdout=SCREAMING_SNAKE_CASE__				,							)
       self.assertIn(
           f'''{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; pip install accelerate -U; echo "hello world"; echo "this is a second command" --worker all'''				,							SCREAMING_SNAKE_CASE__				,							)


  def __a						(					self     :							Optional[int]						):





       '''simple docstring'''

       __a       =   run_command(
           self.cmd
           + [
               """--config_file""",
               """tests/test_configs/latest.yaml""",
               """--install_accelerate""",
               """--accelerate_version""",
               """12.0.0""",
               """--debug""",
           ]				,							return_stdout=SCREAMING_SNAKE_CASE__				,							)
       self.assertIn(
           f'''{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; pip install accelerate==12.0.0; echo "hello world"; echo "this is a second command" --worker all'''				,							SCREAMING_SNAKE_CASE__				,							)










'''simple docstring'''







import unittest

from transformers import (
    MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
    TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
    TextClassificationPipeline,
    pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow

from .test_pipelines_common import ANY


# These 2 model types require different inputs than those of the usual text models.
SCREAMING_SNAKE_CASE_      =			{'LayoutLMv2Config', 'LayoutLMv3Config'}


@is_pipeline_test
class  lowerCAmelCase_						(       unittest.TestCase      ):





  """simple docstring"""



  a_       :List[Any]												=MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING
  a_       :List[Any]												=TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING

  if model_mapping is not None:
    a_       :List[Any]												={config: model for config, model in model_mapping.items() if config.__name__ not in _TO_SKIP}
  if tf_model_mapping is not None:
    a_       :Tuple												={
        config: model for config, model in tf_model_mapping.items() if config.__name__ not in _TO_SKIP
    }

  @require_torch
  def __a						(					self     :							int						):





       '''simple docstring'''

       __a       =   pipeline(
           task="""text-classification"""				,							model="""hf-internal-testing/tiny-random-distilbert"""				,							framework="""pt"""						)

       __a       =   text_classifier("""This is great !"""						)
       self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[{"""label""": """LABEL_0""", """score""": 0.5_0_4}]						)

       __a       =   text_classifier("""This is great !"""				,							top_k=2						)
       self.assertEqual(
           nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[{"""label""": """LABEL_0""", """score""": 0.5_0_4}, {"""label""": """LABEL_1""", """score""": 0.4_9_6}]						)

       __a       =   text_classifier(["""This is great !""", """This is bad"""]				,							top_k=2						)
       self.assertEqual(
           nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[
               [{"""label""": """LABEL_0""", """score""": 0.5_0_4}, {"""label""": """LABEL_1""", """score""": 0.4_9_6}],
               [{"""label""": """LABEL_0""", """score""": 0.5_0_4}, {"""label""": """LABEL_1""", """score""": 0.4_9_6}],
           ]				,							)

       __a       =   text_classifier("""This is great !"""				,							top_k=1						)
       self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[{"""label""": """LABEL_0""", """score""": 0.5_0_4}]						)

       # Legacy behavior
       __a       =   text_classifier("""This is great !"""				,							return_all_scores=SCREAMING_SNAKE_CASE__						)
       self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[{"""label""": """LABEL_0""", """score""": 0.5_0_4}]						)

       __a       =   text_classifier("""This is great !"""				,							return_all_scores=SCREAMING_SNAKE_CASE__						)
       self.assertEqual(
           nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[[{"""label""": """LABEL_0""", """score""": 0.5_0_4}, {"""label""": """LABEL_1""", """score""": 0.4_9_6}]]						)

       __a       =   text_classifier(["""This is great !""", """Something else"""]				,							return_all_scores=SCREAMING_SNAKE_CASE__						)
       self.assertEqual(
           nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[
               [{"""label""": """LABEL_0""", """score""": 0.5_0_4}, {"""label""": """LABEL_1""", """score""": 0.4_9_6}],
               [{"""label""": """LABEL_0""", """score""": 0.5_0_4}, {"""label""": """LABEL_1""", """score""": 0.4_9_6}],
           ]				,							)

       __a       =   text_classifier(["""This is great !""", """Something else"""]				,							return_all_scores=SCREAMING_SNAKE_CASE__						)
       self.assertEqual(
           nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[
               {"""label""": """LABEL_0""", """score""": 0.5_0_4},
               {"""label""": """LABEL_0""", """score""": 0.5_0_4},
           ]				,							)

  @require_torch
  def __a						(					self     :							Optional[int]						):





       '''simple docstring'''

       import torch

       __a       =   pipeline(
           task="""text-classification"""				,							model="""hf-internal-testing/tiny-random-distilbert"""				,							framework="""pt"""				,							device=torch.device("""cpu"""						)				,							)

       __a       =   text_classifier("""This is great !"""						)
       self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[{"""label""": """LABEL_0""", """score""": 0.5_0_4}]						)

  @require_tf
  def __a						(					self     :							List[str]						):





       '''simple docstring'''

       __a       =   pipeline(
           task="""text-classification"""				,							model="""hf-internal-testing/tiny-random-distilbert"""				,							framework="""tf"""						)

       __a       =   text_classifier("""This is great !"""						)
       self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[{"""label""": """LABEL_0""", """score""": 0.5_0_4}]						)

  @slow
  @require_torch
  def __a						(					self     :							int						):





       '''simple docstring'''

       __a       =   pipeline("""text-classification"""						)

       __a       =   text_classifier("""This is great !"""						)
       self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[{"""label""": """POSITIVE""", """score""": 1.0}]						)
       __a       =   text_classifier("""This is bad !"""						)
       self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[{"""label""": """NEGATIVE""", """score""": 1.0}]						)
       __a       =   text_classifier("""Birds are a type of animal"""						)
       self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[{"""label""": """POSITIVE""", """score""": 0.9_8_8}]						)

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





       '''simple docstring'''

       __a       =   pipeline("""text-classification"""				,							framework="""tf"""						)

       __a       =   text_classifier("""This is great !"""						)
       self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[{"""label""": """POSITIVE""", """score""": 1.0}]						)
       __a       =   text_classifier("""This is bad !"""						)
       self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[{"""label""": """NEGATIVE""", """score""": 1.0}]						)
       __a       =   text_classifier("""Birds are a type of animal"""						)
       self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[{"""label""": """POSITIVE""", """score""": 0.9_8_8}]						)

  def __a						(					self     :							Tuple				,							SCREAMING_SNAKE_CASE__     :							int				,							SCREAMING_SNAKE_CASE__     :							str				,							SCREAMING_SNAKE_CASE__     :							Tuple						):





       '''simple docstring'''

       __a       =   TextClassificationPipeline(model=SCREAMING_SNAKE_CASE__				,							tokenizer=SCREAMING_SNAKE_CASE__						)
       return text_classifier, ["HuggingFace is in", "This is another test"]


  def __a						(					self     :							Any				,							SCREAMING_SNAKE_CASE__     :							Any				,							SCREAMING_SNAKE_CASE__     :							Tuple						):





       '''simple docstring'''

       __a       =   text_classifier.model
       # Small inputs because BartTokenizer tiny has maximum position embeddings = 22
       __a       =   """HuggingFace is in"""
       __a       =   text_classifier(SCREAMING_SNAKE_CASE__						)

       self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[{"""label""": ANY(SCREAMING_SNAKE_CASE__						), """score""": ANY(SCREAMING_SNAKE_CASE__						)}]						)
       self.assertTrue(outputs[0]["""label"""] in model.config.idalabel.values()						)

       __a       =   ["""HuggingFace is in """, """Paris is in France"""]
       __a       =   text_classifier(SCREAMING_SNAKE_CASE__						)
       self.assertEqual(
           nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[{"""label""": ANY(SCREAMING_SNAKE_CASE__						), """score""": ANY(SCREAMING_SNAKE_CASE__						)}, {"""label""": ANY(SCREAMING_SNAKE_CASE__						), """score""": ANY(SCREAMING_SNAKE_CASE__						)}]				,							)
       self.assertTrue(outputs[0]["""label"""] in model.config.idalabel.values()						)
       self.assertTrue(outputs[1]["""label"""] in model.config.idalabel.values()						)

       # Forcing to get all results with `top_k=None`
       # This is NOT the legacy format
       __a       =   text_classifier(SCREAMING_SNAKE_CASE__				,							top_k=SCREAMING_SNAKE_CASE__						)
       __a       =   len(model.config.idalabel.values()						)
       self.assertEqual(
           nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[[{"""label""": ANY(SCREAMING_SNAKE_CASE__						), """score""": ANY(SCREAMING_SNAKE_CASE__						)}] * N, [{"""label""": ANY(SCREAMING_SNAKE_CASE__						), """score""": ANY(SCREAMING_SNAKE_CASE__						)}] * N]				,							)

       __a       =   {"""text""": """HuggingFace is in """, """text_pair""": """Paris is in France"""}
       __a       =   text_classifier(SCREAMING_SNAKE_CASE__						)
       self.assertEqual(
           nested_simplify(SCREAMING_SNAKE_CASE__						)				,							{"""label""": ANY(SCREAMING_SNAKE_CASE__						), """score""": ANY(SCREAMING_SNAKE_CASE__						)}				,							)
       self.assertTrue(outputs["""label"""] in model.config.idalabel.values()						)

       # This might be used a text pair, but tokenizer + pipe interaction
       # makes it hard to understand that it's not using the pair properly
       # https://github.com/huggingface/transformers/issues/17305
       # We disabled this usage instead as it was outputting wrong outputs.
       __a       =   [["""HuggingFace is in """, """Paris is in France"""]]
       with self.assertRaises(SCREAMING_SNAKE_CASE__						):
            text_classifier(SCREAMING_SNAKE_CASE__						)

       # This used to be valid for doing text pairs
       # We're keeping it working because of backward compatibility
       __a       =   text_classifier([[["""HuggingFace is in """, """Paris is in France"""]]]						)
       self.assertEqual(
           nested_simplify(SCREAMING_SNAKE_CASE__						)				,							[{"""label""": ANY(SCREAMING_SNAKE_CASE__						), """score""": ANY(SCREAMING_SNAKE_CASE__						)}]				,							)
       self.assertTrue(outputs[0]["""label"""] in model.config.idalabel.values()						)






