
"""simple docstring"""




import json
import os
import subprocess
import sys
import warnings
from argparse import ArgumentParser
from contextlib import AbstractContextManager
from typing import Dict, List, Optional

import requests

from ..utils import logging
from . import BaseTransformersCLICommand


snake_case			       =		logging.get_logger(__name__)  # pylint: disable=invalid-name


snake_case			       =		'lfs-multipart-upload'




class 					UpperCamelCase     (	_a				):

    """simple docstring"""



    @staticmethod
    def 							A (    lowercase__      )   ->   str:
         """simple docstring"""







         SCREAMING_SNAKE_CASE           =     parser.add_parser(
             'lfs-enable-largefiles'		,     help=(
                 'Deprecated: use `huggingface-cli` instead. Configure your repository to enable upload of files > 5GB.'
             )		,     )
         enable_parser.add_argument('path'		,     type=SCREAMING_SNAKE_CASE__		,     help='Local path to repository you want to configure.'      )
         enable_parser.set_defaults(func=lambda lowercase__      : LfsEnableCommand(SCREAMING_SNAKE_CASE__      )      )

         SCREAMING_SNAKE_CASE           =     parser.add_parser(
             SCREAMING_SNAKE_CASE__		,     help=(
                 'Deprecated: use `huggingface-cli` instead. '
                 'Command will get called by git-lfs, do not call it directly.'
             )		,     )
         upload_parser.set_defaults(func=lambda lowercase__      : LfsUploadCommand(SCREAMING_SNAKE_CASE__      )      )






class 					UpperCamelCase     :

    """simple docstring"""



    def __init__(    self		,     lowercase__      )   ->   List[Any]:
         """simple docstring"""







         SCREAMING_SNAKE_CASE           =     args




    def 							A (    self      )   ->   List[str]:
         """simple docstring"""







         warnings.warn(
             'Managing repositories through transformers-cli is deprecated. Please use `huggingface-cli` instead.'      )
         SCREAMING_SNAKE_CASE           =     os.path.abspath(self.args.path      )
         if not os.path.isdir(SCREAMING_SNAKE_CASE__      ):
              print('This does not look like a valid git repo.'      )
              exit(1      )
         subprocess.run(
             'git config lfs.customtransfer.multipart.path transformers-cli'.split()		,     check=SCREAMING_SNAKE_CASE__		,     cwd=SCREAMING_SNAKE_CASE__      )
         subprocess.run(
             f'''git config lfs.customtransfer.multipart.args {LFS_MULTIPART_UPLOAD_COMMAND}'''.split()		,     check=SCREAMING_SNAKE_CASE__		,     cwd=SCREAMING_SNAKE_CASE__		,     )
         print('Local repo set up for largefiles'      )






def   UpperCamelCase_  (		SCREAMING_SNAKE_CASE_      ):
     SCREAMING_SNAKE_CASE           =     json.dumps(SCREAMING_SNAKE_CASE_      ) + "\n"
     sys.stdout.write(SCREAMING_SNAKE_CASE_      )
     sys.stdout.flush()

def   UpperCamelCase_  (		):
     SCREAMING_SNAKE_CASE           =     json.loads(sys.stdin.readline().strip()      )

     if "terminate" in (msg.get('type'      ), msg.get('event'      )):
          # terminate message received
          return None

     if msg.get('event'      ) not in ("download", "upload"):
          logger.critical('Received unexpected message'      )
          sys.exit(1      )

     return msg




class 					UpperCamelCase     (	_a				):

    """simple docstring"""



    def __init__(    self		,     lowercase__		,     lowercase__		,     lowercase__      )   ->   Any:
         """simple docstring"""







         SCREAMING_SNAKE_CASE           =     filepath
         SCREAMING_SNAKE_CASE           =     seek_from
         SCREAMING_SNAKE_CASE           =     read_limit
         SCREAMING_SNAKE_CASE           =     0


    def __enter__(    self      )   ->   Optional[int]:
         """simple docstring"""







         SCREAMING_SNAKE_CASE           =     open(self.filepath		,     'rb'      )
         self.f.seek(self.seek_from      )
         return self


    def __len__(    self      )   ->   List[Any]:
         """simple docstring"""







         SCREAMING_SNAKE_CASE           =     os.fstat(self.f.fileno()      ).st_size
         return min(self.read_limit		,     total_length - self.seek_from      )


    def 							A (    self		,     lowercase__=-1      )   ->   List[Any]:
         """simple docstring"""







         if self.n_seen >= self.read_limit:
              return b""
         SCREAMING_SNAKE_CASE           =     self.read_limit - self.n_seen
         SCREAMING_SNAKE_CASE           =     self.f.read(remaining_amount if n < 0 else min(SCREAMING_SNAKE_CASE__		,     SCREAMING_SNAKE_CASE__      )      )
         self.n_seen += len(SCREAMING_SNAKE_CASE__      )
         return data


    def __iter__(    self      )   ->   str:
         """simple docstring"""







         yield self.read(n=4 * 1024 * 1024      )




    def __exit__(    self		,     *lowercase__      )   ->   List[Any]:
         """simple docstring"""







         self.f.close()






class 					UpperCamelCase     :

    """simple docstring"""



    def __init__(    self		,     lowercase__      )   ->   Any:
         """simple docstring"""







         SCREAMING_SNAKE_CASE           =     args




    def 							A (    self      )   ->   Tuple:
         """simple docstring"""







         SCREAMING_SNAKE_CASE           =     json.loads(sys.stdin.readline().strip()      )
         if not (init_msg.get('event'      ) == "init" and init_msg.get('operation'      ) == "upload"):
              write_msg({'error': {'code': 32, 'message': 'Wrong lfs init operation'}}      )
              sys.exit(1      )

         # The transfer process should use the information it needs from the
         # initiation structure, and also perform any one-off setup tasks it
         # needs to do. It should then respond on stdout with a simple empty
         # confirmation structure, as follows:
         write_msg({}      )

         # After the initiation exchange, git-lfs will send any number of
         # transfer requests to the stdin of the transfer process, in a serial sequence.
         while True:
              SCREAMING_SNAKE_CASE           =     read_msg()
              if msg is None:
                   # When all transfers have been processed, git-lfs will send
                   # a terminate event to the stdin of the transfer process.
                   # On receiving this message the transfer process should
                   # clean up and terminate. No response is expected.
                   sys.exit(0      )

              SCREAMING_SNAKE_CASE           =     msg["oid"]
              SCREAMING_SNAKE_CASE           =     msg["path"]
              SCREAMING_SNAKE_CASE           =     msg["action"]["href"]
              SCREAMING_SNAKE_CASE           =     msg["action"]["header"]
              SCREAMING_SNAKE_CASE           =     int(header.pop('chunk_size'      )      )
              SCREAMING_SNAKE_CASE           =     list(header.values()      )

              SCREAMING_SNAKE_CASE           =     []
              for i, presigned_url in enumerate(SCREAMING_SNAKE_CASE__      ):
                   with FileSlice(SCREAMING_SNAKE_CASE__		,     seek_from=i * chunk_size		,     read_limit=SCREAMING_SNAKE_CASE__      ) as data:
                        SCREAMING_SNAKE_CASE           =     requests.put(SCREAMING_SNAKE_CASE__		,     data=SCREAMING_SNAKE_CASE__      )
                        r.raise_for_status()
                        parts.append(
                            {
                                'etag': r.headers.get('etag'      ),
                                'partNumber': i + 1,
                            }      )
                        # In order to support progress reporting while data is uploading / downloading,
                        # the transfer process should post messages to stdout
                        write_msg(
                            {
                                'event': 'progress',
                                'oid': oid,
                                'bytesSoFar': (i + 1) * chunk_size,
                                'bytesSinceLast': chunk_size,
                            }      )
                        # Not precise but that's ok.

              SCREAMING_SNAKE_CASE           =     requests.post(
                  SCREAMING_SNAKE_CASE__		,     json={
                      'oid': oid,
                      'parts': parts,
                  }		,     )
              r.raise_for_status()

              write_msg({'event': 'complete', 'oid': oid}      )


"""simple docstring"""




import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available


if is_torch_available():
	from transformers.pytorch_utils import is_torch_greater_or_equal_than_1_11
else:
	snake_case			       =		False

if is_vision_available():
	from PIL import Image

	from transformers import (
	    AutoProcessor,
	    PixaStructImageProcessor,
	    PixaStructProcessor,
	    PreTrainedTokenizerFast,
	    TaTokenizer,
	)




@unittest.skipIf(
    not is_torch_greater_or_equal_than_1_11  ,				reason="`Pix2StructImageProcessor` requires `torch>=1.11.0`."  ,				)
@require_vision
@require_torch
class 					UpperCamelCase     (	unittest.TestCase				):

				"""simple docstring"""



				def 							A (    self      )   ->   Any:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     tempfile.mkdtemp()

									SCREAMING_SNAKE_CASE           =     PixaStructImageProcessor()
									SCREAMING_SNAKE_CASE           =     TaTokenizer.from_pretrained('t5-small'      )

									SCREAMING_SNAKE_CASE           =     PixaStructProcessor(lowercase__		,     lowercase__      )

									processor.save_pretrained(self.tmpdirname      )


				def 							A (    self		,     **lowercase__      )   ->   Dict:
									"""simple docstring"""







									return AutoProcessor.from_pretrained(self.tmpdirname		,     **lowercase__      ).tokenizer


				def 							A (    self		,     **lowercase__      )   ->   Union[str, Any]:
									"""simple docstring"""







									return AutoProcessor.from_pretrained(self.tmpdirname		,     **lowercase__      ).image_processor


				def 							A (    self      )   ->   Optional[int]:
									"""simple docstring"""







									shutil.rmtree(self.tmpdirname      )


				def 							A (    self      )   ->   int:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     [np.random.randint(255		,     size=(3, 30, 400)		,     dtype=np.uinta      )]

									SCREAMING_SNAKE_CASE           =     [Image.fromarray(np.moveaxis(lowercase__		,     0		,     -1      )      ) for x in image_inputs]

									return image_inputs


				def 							A (    self      )   ->   int:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     PixaStructProcessor(tokenizer=self.get_tokenizer()		,     image_processor=self.get_image_processor()      )
									processor.save_pretrained(self.tmpdirname      )

									SCREAMING_SNAKE_CASE           =     self.get_tokenizer(bos_token='(BOS)'		,     eos_token='(EOS)'      )
									SCREAMING_SNAKE_CASE           =     self.get_image_processor(do_normalize=lowercase__		,     padding_value=1.0      )

									SCREAMING_SNAKE_CASE           =     PixaStructProcessor.from_pretrained(
									    self.tmpdirname		,     bos_token='(BOS)'		,     eos_token='(EOS)'		,     do_normalize=lowercase__		,     padding_value=1.0      )

									self.assertEqual(processor.tokenizer.get_vocab()		,     tokenizer_add_kwargs.get_vocab()      )
									self.assertIsInstance(processor.tokenizer		,     lowercase__      )

									self.assertEqual(processor.image_processor.to_json_string()		,     image_processor_add_kwargs.to_json_string()      )
									self.assertIsInstance(processor.image_processor		,     lowercase__      )


				def 							A (    self      )   ->   int:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self.get_image_processor()
									SCREAMING_SNAKE_CASE           =     self.get_tokenizer()

									SCREAMING_SNAKE_CASE           =     PixaStructProcessor(tokenizer=lowercase__		,     image_processor=lowercase__      )

									SCREAMING_SNAKE_CASE           =     self.prepare_image_inputs()

									SCREAMING_SNAKE_CASE           =     image_processor(lowercase__		,     return_tensors='np'      )
									SCREAMING_SNAKE_CASE           =     processor(images=lowercase__		,     return_tensors='np'      )

									for key in input_feat_extract.keys():
														self.assertAlmostEqual(input_feat_extract[key].sum()		,     input_processor[key].sum()		,     delta=1E-2      )


				def 							A (    self      )   ->   List[Any]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self.get_image_processor()
									SCREAMING_SNAKE_CASE           =     self.get_tokenizer()

									SCREAMING_SNAKE_CASE           =     PixaStructProcessor(tokenizer=lowercase__		,     image_processor=lowercase__      )

									SCREAMING_SNAKE_CASE           =     'lower newer'

									SCREAMING_SNAKE_CASE           =     processor(text=lowercase__      )

									SCREAMING_SNAKE_CASE           =     tokenizer(lowercase__		,     return_token_type_ids=lowercase__		,     add_special_tokens=lowercase__      )

									for key in encoded_tok.keys():
														self.assertListEqual(encoded_tok[key]		,     encoded_processor[key]      )


				def 							A (    self      )   ->   List[Any]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self.get_image_processor()
									SCREAMING_SNAKE_CASE           =     self.get_tokenizer()

									SCREAMING_SNAKE_CASE           =     PixaStructProcessor(tokenizer=lowercase__		,     image_processor=lowercase__      )

									SCREAMING_SNAKE_CASE           =     'lower newer'
									SCREAMING_SNAKE_CASE           =     self.prepare_image_inputs()

									SCREAMING_SNAKE_CASE           =     processor(text=lowercase__		,     images=lowercase__      )

									self.assertListEqual(
									    list(inputs.keys()      )		,     ['flattened_patches', 'attention_mask', 'decoder_attention_mask', 'decoder_input_ids']      )

									# test if it raises when no input is passed
									with pytest.raises(lowercase__      ):
														processor()


				def 							A (    self      )   ->   Union[str, Any]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self.get_image_processor()
									SCREAMING_SNAKE_CASE           =     self.get_tokenizer()

									SCREAMING_SNAKE_CASE           =     PixaStructProcessor(tokenizer=lowercase__		,     image_processor=lowercase__      )

									SCREAMING_SNAKE_CASE           =     'lower newer'
									SCREAMING_SNAKE_CASE           =     self.prepare_image_inputs()

									SCREAMING_SNAKE_CASE           =     processor(text=lowercase__		,     images=lowercase__      )

									SCREAMING_SNAKE_CASE           =     [512, 1024, 2048, 4096]
									SCREAMING_SNAKE_CASE           =     [770, 770, 770, 770]
									# with text
									for i, max_patch in enumerate(lowercase__      ):
														SCREAMING_SNAKE_CASE           =     processor(text=lowercase__		,     images=lowercase__		,     max_patches=lowercase__      )
														self.assertEqual(inputs['flattened_patches'][0].shape[0]		,     lowercase__      )
														self.assertEqual(inputs['flattened_patches'][0].shape[1]		,     expected_hidden_size[i]      )

									# without text input
									for i, max_patch in enumerate(lowercase__      ):
														SCREAMING_SNAKE_CASE           =     processor(images=lowercase__		,     max_patches=lowercase__      )
														self.assertEqual(inputs['flattened_patches'][0].shape[0]		,     lowercase__      )
														self.assertEqual(inputs['flattened_patches'][0].shape[1]		,     expected_hidden_size[i]      )


				def 							A (    self      )   ->   Tuple:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self.get_image_processor()
									SCREAMING_SNAKE_CASE           =     self.get_tokenizer()

									SCREAMING_SNAKE_CASE           =     PixaStructProcessor(tokenizer=lowercase__		,     image_processor=lowercase__      )

									SCREAMING_SNAKE_CASE           =     [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

									SCREAMING_SNAKE_CASE           =     processor.batch_decode(lowercase__      )
									SCREAMING_SNAKE_CASE           =     tokenizer.batch_decode(lowercase__      )

									self.assertListEqual(lowercase__		,     lowercase__      )




				def 							A (    self      )   ->   Optional[Any]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self.get_image_processor()
									SCREAMING_SNAKE_CASE           =     self.get_tokenizer()

									SCREAMING_SNAKE_CASE           =     PixaStructProcessor(tokenizer=lowercase__		,     image_processor=lowercase__      )

									SCREAMING_SNAKE_CASE           =     'lower newer'
									SCREAMING_SNAKE_CASE           =     self.prepare_image_inputs()

									SCREAMING_SNAKE_CASE           =     processor(text=lowercase__		,     images=lowercase__      )

									# For now the processor supports only ["flattened_patches", "input_ids", "attention_mask", "decoder_attention_mask"]
									self.assertListEqual(
									    list(inputs.keys()      )		,     ['flattened_patches', 'attention_mask', 'decoder_attention_mask', 'decoder_input_ids']      )

									SCREAMING_SNAKE_CASE           =     processor(text=lowercase__      )

									# For now the processor supports only ["flattened_patches", "input_ids", "attention_mask", "decoder_attention_mask"]
									self.assertListEqual(list(inputs.keys()      )		,     ['input_ids', 'attention_mask']      )
