


"""simple docstring"""


from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional

from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand


try:
   from fastapi import Body, FastAPI, HTTPException
   from fastapi.routing import APIRoute
   from pydantic import BaseModel
   from starlette.responses import JSONResponse
   from uvicorn import run

   __snake_case    					=					True
except (ImportError, AttributeError):
   __snake_case    					=					object


   def    _lowerCamelCase   (     *lowerCamelCase__	:							List[Any]       ,		**lowerCamelCase__	:							str  ):
    pass






   __snake_case    					=					False


__snake_case    					=					logging.get_logger('transformers-cli/serving')


def    _lowerCamelCase   (     lowerCamelCase__	:							Namespace  ):
 lowercase__       :       Optional[int]				=						pipeline(
     task=args.task       ,		model=args.model if args.model else None       ,		config=args.config       ,		tokenizer=args.tokenizer       ,		device=args.device       ,		)
 return ServeCommand(lowerCamelCase__       ,		args.host       ,		args.port       ,		args.workers  )

class 				_SCREAMING_SNAKE_CASE				(							__UpperCAmelCase  ):
   """simple docstring"""



   _a   :       dict

class 				_SCREAMING_SNAKE_CASE				(							__UpperCAmelCase  ):
   """simple docstring"""



   _a   :       List[str]
   _a   :       Optional[List[int]]

class 				_SCREAMING_SNAKE_CASE				(							__UpperCAmelCase  ):
   """simple docstring"""



   _a   :       str

class 				_SCREAMING_SNAKE_CASE				(							__UpperCAmelCase  ):
   """simple docstring"""



   _a   :       Any

class 				_SCREAMING_SNAKE_CASE				(							__UpperCAmelCase  ):
   """simple docstring"""



   @staticmethod
   def 					UpperCAmelCase__(						lowerCamelCase__						)      ->							Dict:
    lowercase__       :       Optional[int]				=						parser.add_parser(
        """serve""" ,     help="""CLI tool to run inference requests through REST and GraphQL endpoints."""						)
    serve_parser.add_argument(
        """--task""" ,     type=lowerCamelCase__ ,     choices=get_supported_tasks() ,     help="""The task to run the pipeline on""" ,     )
    serve_parser.add_argument("""--host""" ,     type=lowerCamelCase__ ,     default="""localhost""" ,     help="""Interface the server will listen on."""						)
    serve_parser.add_argument("""--port""" ,     type=lowerCamelCase__ ,     default=8888 ,     help="""Port the serving will listen to."""						)
    serve_parser.add_argument("""--workers""" ,     type=lowerCamelCase__ ,     default=1 ,     help="""Number of http workers"""						)
    serve_parser.add_argument("""--model""" ,     type=lowerCamelCase__ ,     help="""Model's name or path to stored model."""						)
    serve_parser.add_argument("""--config""" ,     type=lowerCamelCase__ ,     help="""Model's config name or path to stored model."""						)
    serve_parser.add_argument("""--tokenizer""" ,     type=lowerCamelCase__ ,     help="""Tokenizer name to use."""						)
    serve_parser.add_argument(
        """--device""" ,     type=lowerCamelCase__ ,     default=-1 ,     help="""Indicate the device to run onto, -1 indicates CPU, >= 0 indicates GPU (default: -1)""" ,     )
    serve_parser.set_defaults(func=lowerCamelCase__						)


   def __init__(						self ,     lowerCamelCase__ ,     lowerCamelCase__ ,     lowerCamelCase__ ,     lowerCamelCase__						)      ->							Union[str, Any]:
    lowercase__       :       Tuple				=						pipeline

    lowercase__       :       Optional[int]				=						host
    lowercase__       :       Dict				=						port
    lowercase__       :       Any				=						workers

    if not _serve_dependencies_installed:
     raise RuntimeError(
         """Using serve command requires FastAPI and uvicorn. """
         """Please install transformers with [serving]: pip install \"transformers[serving]\"."""
         """Or install FastAPI and uvicorn separately."""						)
    else:
     logger.info(F'''Serving model over {host}:{port}'''						)
     lowercase__       :       Dict				=						FastAPI(
         routes=[
             APIRoute(
                 """/""" ,     self.model_info ,     response_model=lowerCamelCase__ ,     response_class=lowerCamelCase__ ,     methods=["""GET"""] ,     ),
             APIRoute(
                 """/tokenize""" ,     self.tokenize ,     response_model=lowerCamelCase__ ,     response_class=lowerCamelCase__ ,     methods=["""POST"""] ,     ),
             APIRoute(
                 """/detokenize""" ,     self.detokenize ,     response_model=lowerCamelCase__ ,     response_class=lowerCamelCase__ ,     methods=["""POST"""] ,     ),
             APIRoute(
                 """/forward""" ,     self.forward ,     response_model=lowerCamelCase__ ,     response_class=lowerCamelCase__ ,     methods=["""POST"""] ,     ),
         ] ,     timeout=600 ,     )


   def 					UpperCAmelCase__(						self						)      ->							List[str]:
    run(self._app ,     host=self.host ,     port=self.port ,     workers=self.workers						)


   def 					UpperCAmelCase__(						self						)      ->							Optional[int]:
    return ServeModelInfoResult(infos=vars(self._pipeline.model.config						)						)


   def 					UpperCAmelCase__(						self ,     lowerCamelCase__ = Body(lowerCamelCase__ ,     embed=lowerCamelCase__						) ,     lowerCamelCase__ = Body(lowerCamelCase__ ,     embed=lowerCamelCase__						)						)      ->							Union[str, Any]:
    try:
     lowercase__       :       int				=						self._pipeline.tokenizer.tokenize(lowerCamelCase__						)

     if return_ids:
      lowercase__       :       Optional[int]				=						self._pipeline.tokenizer.convert_tokens_to_ids(lowerCamelCase__						)
      return ServeTokenizeResult(tokens=lowerCamelCase__ ,     tokens_ids=lowerCamelCase__						)
     else:
      return ServeTokenizeResult(tokens=lowerCamelCase__						)

    except Exception as e:
     raise HTTPException(status_code=500 ,     detail={"""model""": """""", """error""": str(lowerCamelCase__						)}						)


   def 					UpperCAmelCase__(						self ,     lowerCamelCase__ = Body(lowerCamelCase__ ,     embed=lowerCamelCase__						) ,     lowerCamelCase__ = Body(lowerCamelCase__ ,     embed=lowerCamelCase__						) ,     lowerCamelCase__ = Body(lowerCamelCase__ ,     embed=lowerCamelCase__						) ,     )      ->							Union[str, Any]:
    try:
     lowercase__       :       List[str]				=						self._pipeline.tokenizer.decode(lowerCamelCase__ ,     lowerCamelCase__ ,     lowerCamelCase__						)
     return ServeDeTokenizeResult(model="""""" ,     text=lowerCamelCase__						)
    except Exception as e:
     raise HTTPException(status_code=500 ,     detail={"""model""": """""", """error""": str(lowerCamelCase__						)}						)







   async def 					UpperCAmelCase__(						self ,     lowerCamelCase__=Body(lowerCamelCase__ ,     embed=lowerCamelCase__						)						)      ->							Optional[Any]:

    # Check we don't have empty string
    if len(lowerCamelCase__						) == 0:
     return ServeForwardResult(output=[] ,     attention=[]						)

    try:
     # Forward through the model
     lowercase__       :       List[Any]				=						self._pipeline(lowerCamelCase__						)
     return ServeForwardResult(output=lowerCamelCase__						)
    except Exception as e:
     raise HTTPException(500 ,     {"""error""": str(lowerCamelCase__						)}						)



"""simple docstring"""


import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import AutoConfig, BertConfig, GPTaConfig
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test


sys.path.append(str(Path(__file__).parent.parent / 'utils'))

from test_module.custom_configuration import CustomConfig  # noqa E402


__snake_case    					=					{
    'return_dict': False,
    'output_hidden_states': True,
    'output_attentions': True,
    'torchscript': True,
    'torch_dtype': 'float16',
    'use_bfloat16': True,
    'tf_legacy_loss': True,
    'pruned_heads': {'a': 1},
    'tie_word_embeddings': False,
    'is_decoder': True,
    'cross_attention_hidden_size': 128,
    'add_cross_attention': True,
    'tie_encoder_decoder': True,
    'max_length': 50,
    'min_length': 3,
    'do_sample': True,
    'early_stopping': True,
    'num_beams': 3,
    'num_beam_groups': 3,
    'diversity_penalty': 0.5,
    'temperature': 2.0,
    'top_k': 10,
    'top_p': 0.7,
    'typical_p': 0.2,
    'repetition_penalty': 0.8,
    'length_penalty': 0.8,
    'no_repeat_ngram_size': 5,
    'encoder_no_repeat_ngram_size': 5,
    'bad_words_ids': [1, 2, 3],
    'num_return_sequences': 3,
    'chunk_size_feed_forward': 5,
    'output_scores': True,
    'return_dict_in_generate': True,
    'forced_bos_token_id': 2,
    'forced_eos_token_id': 3,
    'remove_invalid_values': True,
    'architectures': ['BertModel'],
    'finetuning_task': 'translation',
    'id2label': {0: 'label'},
    'label2id': {'label': '0'},
    'tokenizer_class': 'BertTokenizerFast',
    'prefix': 'prefix',
    'bos_token_id': 6,
    'pad_token_id': 7,
    'eos_token_id': 8,
    'sep_token_id': 9,
    'decoder_start_token_id': 10,
    'exponential_decay_length_penalty': (5, 1.01),
    'suppress_tokens': [0, 1],
    'begin_suppress_tokens': 2,
    'task_specific_params': {'translation': 'some_params'},
    'problem_type': 'regression',
}

@is_staging_test
class 				_SCREAMING_SNAKE_CASE				(							unittest.TestCase  ):
   """simple docstring"""



   @classmethod
   def 					UpperCAmelCase__(						cls						)      ->							Dict:
    lowercase__       :       str				=						TOKEN
    HfFolder.save_token(lowerCamelCase__						)


   @classmethod
   def 					UpperCAmelCase__(						cls						)      ->							Optional[Any]:
    try:
     delete_repo(token=cls._token ,     repo_id="""test-config"""						)
    except HTTPError:
     pass

    try:
     delete_repo(token=cls._token ,     repo_id="""valid_org/test-config-org"""						)
    except HTTPError:
     pass

    try:
     delete_repo(token=cls._token ,     repo_id="""test-dynamic-config"""						)
    except HTTPError:
     pass


   def 					UpperCAmelCase__(						self						)      ->							List[str]:
    lowercase__       :       Union[str, Any]				=						BertConfig(
        vocab_size=99 ,     hidden_size=32 ,     num_hidden_layers=5 ,     num_attention_heads=4 ,     intermediate_size=37						)
    config.push_to_hub("""test-config""" ,     use_auth_token=self._token						)

    lowercase__       :       Union[str, Any]				=						BertConfig.from_pretrained(F'''{USER}/test-config'''						)
    for k, v in config.to_dict().items():
     if k != "transformers_version":
      self.assertEqual(lowerCamelCase__ ,     getattr(lowerCamelCase__ ,     lowerCamelCase__						)						)

        # Reset repo
    delete_repo(token=self._token ,     repo_id="""test-config"""						)

    # Push to hub via save_pretrained
    with tempfile.TemporaryDirectory() as tmp_dir:
     config.save_pretrained(lowerCamelCase__ ,     repo_id="""test-config""" ,     push_to_hub=lowerCamelCase__ ,     use_auth_token=self._token						)

    lowercase__       :       Optional[Any]				=						BertConfig.from_pretrained(F'''{USER}/test-config'''						)
    for k, v in config.to_dict().items():
     if k != "transformers_version":
      self.assertEqual(lowerCamelCase__ ,     getattr(lowerCamelCase__ ,     lowerCamelCase__						)						)


   def 					UpperCAmelCase__(						self						)      ->							Optional[Any]:
    lowercase__       :       int				=						BertConfig(
        vocab_size=99 ,     hidden_size=32 ,     num_hidden_layers=5 ,     num_attention_heads=4 ,     intermediate_size=37						)
    config.push_to_hub("""valid_org/test-config-org""" ,     use_auth_token=self._token						)

    lowercase__       :       List[str]				=						BertConfig.from_pretrained("""valid_org/test-config-org"""						)
    for k, v in config.to_dict().items():
     if k != "transformers_version":
      self.assertEqual(lowerCamelCase__ ,     getattr(lowerCamelCase__ ,     lowerCamelCase__						)						)

        # Reset repo
    delete_repo(token=self._token ,     repo_id="""valid_org/test-config-org"""						)

    # Push to hub via save_pretrained
    with tempfile.TemporaryDirectory() as tmp_dir:
     config.save_pretrained(
         lowerCamelCase__ ,     repo_id="""valid_org/test-config-org""" ,     push_to_hub=lowerCamelCase__ ,     use_auth_token=self._token						)

    lowercase__       :       Optional[Any]				=						BertConfig.from_pretrained("""valid_org/test-config-org"""						)
    for k, v in config.to_dict().items():
     if k != "transformers_version":
      self.assertEqual(lowerCamelCase__ ,     getattr(lowerCamelCase__ ,     lowerCamelCase__						)						)







   def 					UpperCAmelCase__(						self						)      ->							Dict:
    CustomConfig.register_for_auto_class()
    lowercase__       :       int				=						CustomConfig(attribute=42						)

    config.push_to_hub("""test-dynamic-config""" ,     use_auth_token=self._token						)

    # This has added the proper auto_map field to the config
    self.assertDictEqual(config.auto_map ,     {"""AutoConfig""": """custom_configuration.CustomConfig"""}						)

    lowercase__       :       Any				=						AutoConfig.from_pretrained(F'''{USER}/test-dynamic-config''' ,     trust_remote_code=lowerCamelCase__						)
    # Can't make an isinstance check because the new_config is from the FakeConfig class of a dynamic module
    self.assertEqual(new_config.__class__.__name__ ,     """CustomConfig"""						)
    self.assertEqual(new_config.attribute ,     42						)

class 				_SCREAMING_SNAKE_CASE				(							unittest.TestCase  ):
   """simple docstring"""



   def 					UpperCAmelCase__(						self						)      ->							Tuple:
    lowercase__       :       str				=						GPTaConfig()

    # attempt to modify each of int/float/bool/str config records and verify they were updated
    lowercase__       :       List[str]				=						c.n_embd + 1  # int
    lowercase__       :       Union[str, Any]				=						c.resid_pdrop + 1.0  # float
    lowercase__       :       int				=						not c.scale_attn_weights  # bool
    lowercase__       :       Optional[int]				=						c.summary_type + """foo"""  # str
    c.update_from_string(
        F'''n_embd={n_embd},resid_pdrop={resid_pdrop},scale_attn_weights={scale_attn_weights},summary_type={summary_type}'''						)
    self.assertEqual(lowerCamelCase__ ,     c.n_embd ,     """mismatch for key: n_embd"""						)
    self.assertEqual(lowerCamelCase__ ,     c.resid_pdrop ,     """mismatch for key: resid_pdrop"""						)
    self.assertEqual(lowerCamelCase__ ,     c.scale_attn_weights ,     """mismatch for key: scale_attn_weights"""						)
    self.assertEqual(lowerCamelCase__ ,     c.summary_type ,     """mismatch for key: summary_type"""						)


   def 					UpperCAmelCase__(						self						)      ->							Optional[int]:
    lowercase__       :       List[str]				=						PretrainedConfig()
    lowercase__       :       Union[str, Any]				=						[key for key in base_config.__dict__ if key not in config_common_kwargs]
    # If this part of the test fails, you have arguments to addin config_common_kwargs above.
    self.assertListEqual(
        lowerCamelCase__ ,     ["""is_encoder_decoder""", """_name_or_path""", """_commit_hash""", """transformers_version"""]						)
    lowercase__       :       List[Any]				=						[key for key, value in config_common_kwargs.items() if value == getattr(lowerCamelCase__ ,     lowerCamelCase__						)]
    if len(lowerCamelCase__						) > 0:
     raise ValueError(
         """The following keys are set with the default values in"""
         """ `test_configuration_common.config_common_kwargs` pick another value for them:"""
         F''' {', '.join(lowerCamelCase__						)}.'''						)


   def 					UpperCAmelCase__(						self						)      ->							Optional[Any]:
    with self.assertRaises(lowerCamelCase__						):
     # config is in subfolder, the following should not work without specifying the subfolder
     lowercase__       :       str				=						BertConfig.from_pretrained("""hf-internal-testing/tiny-random-bert-subfolder"""						)

    lowercase__       :       Union[str, Any]				=						BertConfig.from_pretrained("""hf-internal-testing/tiny-random-bert-subfolder""" ,     subfolder="""bert"""						)

    self.assertIsNotNone(lowerCamelCase__						)


   def 					UpperCAmelCase__(						self						)      ->							Union[str, Any]:
    # A mock response for an HTTP head request to emulate server down
    lowercase__       :       Dict				=						mock.Mock()
    lowercase__       :       str				=						500
    lowercase__       :       int				=						{}
    lowercase__       :       Optional[int]				=						HTTPError
    lowercase__       :       Dict				=						{}

    # Download this model to make sure it's in the cache.
    lowercase__       :       Any				=						BertConfig.from_pretrained("""hf-internal-testing/tiny-random-bert"""						)

    # Under the mock environment we get a 500 error when trying to reach the model.
    with mock.patch("""requests.Session.request""" ,     return_value=lowerCamelCase__						) as mock_head:
     lowercase__       :       int				=						BertConfig.from_pretrained("""hf-internal-testing/tiny-random-bert"""						)
     # This check we did call the fake head request
     mock_head.assert_called()


   def 					UpperCAmelCase__(						self						)      ->							int:
    # This test is for deprecated behavior and can be removed in v5
    lowercase__       :       Optional[Any]				=						BertConfig.from_pretrained(
        """https://huggingface.co/hf-internal-testing/tiny-random-bert/resolve/main/config.json"""						)


   def 					UpperCAmelCase__(						self						)      ->							List[Any]:
    lowercase__       :       Optional[int]				=						AutoConfig.from_pretrained("""bert-base-cased"""						)
    lowercase__       :       Union[str, Any]				=						["""config.4.0.0.json"""]

    with tempfile.TemporaryDirectory() as tmp_dir:
     configuration.save_pretrained(lowerCamelCase__						)
     lowercase__       :       Optional[Any]				=						2
     json.dump(configuration.to_dict() ,     open(os.path.join(lowerCamelCase__ ,     """config.4.0.0.json"""						) ,     """w"""						)						)

     # This should pick the new configuration file as the version of Transformers is > 4.0.0
     lowercase__       :       Optional[int]				=						AutoConfig.from_pretrained(lowerCamelCase__						)
     self.assertEqual(new_configuration.hidden_size ,     2						)

     # Will need to be adjusted if we reach v42 and this test is still here.
     # Should pick the old configuration file as the version of Transformers is < 4.42.0
     lowercase__       :       Optional[int]				=						["""config.42.0.0.json"""]
     lowercase__       :       Optional[int]				=						768
     configuration.save_pretrained(lowerCamelCase__						)
     shutil.move(os.path.join(lowerCamelCase__ ,     """config.4.0.0.json"""						) ,     os.path.join(lowerCamelCase__ ,     """config.42.0.0.json"""						)						)
     lowercase__       :       Dict				=						AutoConfig.from_pretrained(lowerCamelCase__						)
     self.assertEqual(new_configuration.hidden_size ,     768						)







   def 					UpperCAmelCase__(						self						)      ->							List[Any]:
    # This repo has two configuration files, one for v4.0.0 and above with a different hidden size.
    lowercase__       :       Any				=						"""hf-internal-testing/test-two-configs"""

    import transformers as new_transformers

    lowercase__       :       Union[str, Any]				=						"""v4.0.0"""
    lowercase__	,       lowercase__       :       int				=						new_transformers.models.auto.AutoConfig.from_pretrained(
        lowerCamelCase__ ,     return_unused_kwargs=lowerCamelCase__						)
    self.assertEqual(new_configuration.hidden_size ,     2						)
    # This checks `_configuration_file` ia not kept in the kwargs by mistake.
    self.assertDictEqual(lowerCamelCase__ ,     {}						)

    # Testing an older version by monkey-patching the version in the module it's used.
    import transformers as old_transformers

    lowercase__       :       str				=						"""v3.0.0"""
    lowercase__       :       int				=						old_transformers.models.auto.AutoConfig.from_pretrained(lowerCamelCase__						)
    self.assertEqual(old_configuration.hidden_size ,     768						)