
"""simple docstring"""



import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest

from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import ArrayaD, ClassLabel, Features, Image, Value
from datasets.features.features import ArrayaDExtensionType, cast_to_python_objects
from datasets.keyhash import DuplicatedKeysError, InvalidKeyError

from .utils import require_pil





class 				a			(					lowercase      ):



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      Optional[Any]     							=					pa.array(TypedSequence([1, 2, 3]      )      )
          self.assertEqual(arr.type     ,	pa.intaa()      )



      def  __snake_case							(   self      ):
          with self.assertRaises(UpperCamelCase_      ):
              UpperCAmelCase__	:      Optional[Any]     							=					pa.array(TypedSequence([1, 2, 3]      )     ,	type=pa.intaa()      )



      def  __snake_case							(   self      ):
          with self.assertRaises(UpperCamelCase_      ):
              UpperCAmelCase__	:      List[Any]     							=					pa.array(TypedSequence([1, 2, 3]     ,	try_type=Value('bool'      )     ,	type=Value('int64'      )      )      )



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      str     							=					pa.array(TypedSequence([1, 2, 3]     ,	type=Value('int32'      )      )      )
          self.assertEqual(arr.type     ,	pa.intaa()      )



      def  __snake_case							(   self      ):
          with self.assertRaises((TypeError, pa.lib.ArrowInvalid)      ):
              UpperCAmelCase__	:      List[str]     							=					pa.array(TypedSequence(['foo', 'bar']     ,	type=Value('int64'      )      )      )



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      int     							=					pa.array(TypedSequence([1, 2, 3]     ,	try_type=Value('int32'      )      )      )
          self.assertEqual(arr.type     ,	pa.intaa()      )



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      Any     							=					pa.array(TypedSequence(['foo', 'bar']     ,	try_type=Value('int64'      )      )      )
          self.assertEqual(arr.type     ,	pa.string()      )



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      int     							=					pa.array(TypedSequence([[[1, 2, 3]]]     ,	type=ArrayaD((1, 3)     ,	'int64'      )      )      )
          self.assertEqual(arr.type     ,	ArrayaDExtensionType((1, 3)     ,	'int64'      )      )



      def  __snake_case							(   self      ):
          with self.assertRaises((TypeError, pa.lib.ArrowInvalid)      ):
              UpperCAmelCase__	:      int     							=					pa.array(TypedSequence(['foo', 'bar']     ,	type=ArrayaD((1, 3)     ,	'int64'      )      )      )



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      str     							=					pa.array(TypedSequence([[[1, 2, 3]]]     ,	try_type=ArrayaD((1, 3)     ,	'int64'      )      )      )
          self.assertEqual(arr.type     ,	ArrayaDExtensionType((1, 3)     ,	'int64'      )      )



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      List[Any]     							=					pa.array(TypedSequence(['foo', 'bar']     ,	try_type=ArrayaD((1, 3)     ,	'int64'      )      )      )
          self.assertEqual(arr.type     ,	pa.string()      )



      @require_pil
      def  __snake_case							(   self      ):
          import PIL.Image

          UpperCAmelCase__	:      Tuple     							=					PIL.Image.fromarray(np.arange(10     ,	dtype=np.uinta      ).reshape(2     ,	5      )      )
          with patch(
              'datasets.arrow_writer.cast_to_python_objects'     ,	side_effect=UpperCamelCase_      ) as mock_cast_to_python_objects:
              UpperCAmelCase__	:      List[str]     							=					pa.array(TypedSequence([{'path': None, 'bytes': b'image_bytes'}, pil_image]     ,	type=Image()      )      )
              UpperCAmelCase__							,							UpperCAmelCase__	:      Any     							=					mock_cast_to_python_objects.call_args_list[-1]
              self.assertIn('optimize_list_casting'     ,	UpperCamelCase_      )
              self.assertFalse(kwargs['optimize_list_casting']      )




def 					lowerCamelCase   (     _snake_case    ,_snake_case ):
    UpperCAmelCase__	:      str     							=					pa.BufferReader(_snake_case ) if isinstance(_snake_case    ,pa.Buffer ) else pa.memory_map(_snake_case )
    UpperCAmelCase__	:      Any     							=					pa.ipc.open_stream(_snake_case )
    UpperCAmelCase__	:      pa.Table     							=					f.read_all()
    assert len(pa_table.to_batches() ) == expected_num_chunks
    assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}
    del pa_table
@pytest.mark.parametrize('writer_batch_size'    ,[None, 1, 10] )
@pytest.mark.parametrize(
    'fields'    ,[None, {'col_1': pa.string(), 'col_2': pa.intaa()}, {'col_1': pa.string(), 'col_2': pa.intaa()}] )
def 					lowerCamelCase   (     _snake_case    ,_snake_case ):
    UpperCAmelCase__	:      Optional[Any]     							=					pa.BufferOutputStream()
    UpperCAmelCase__	:      List[str]     							=					pa.schema(_snake_case ) if fields else None
    with ArrowWriter(stream=_snake_case    ,schema=_snake_case    ,writer_batch_size=_snake_case ) as writer:
        writer.write({'col_1': 'foo', 'col_2': 1} )
        writer.write({'col_1': 'bar', 'col_2': 2} )
        UpperCAmelCase__							,							UpperCAmelCase__	:      Any     							=					writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    if not fields:
        UpperCAmelCase__	:      Optional[Any]     							=					{'col_1': pa.string(), 'col_2': pa.intaa()}
    assert writer._schema == pa.schema(_snake_case    ,metadata=writer._schema.metadata )
    _check_output(output.getvalue()    ,expected_num_chunks=num_examples if writer_batch_size == 1 else 1 )
def 					lowerCamelCase   (     ):
    UpperCAmelCase__	:      Tuple     							=					pa.BufferOutputStream()
    UpperCAmelCase__	:      Optional[Any]     							=					Features({'labels': ClassLabel(names=['neg', 'pos'] )} )
    with ArrowWriter(stream=_snake_case    ,features=_snake_case ) as writer:
        writer.write({'labels': 0} )
        writer.write({'labels': 1} )
        UpperCAmelCase__							,							UpperCAmelCase__	:      Tuple     							=					writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    assert writer._schema == features.arrow_schema
    assert writer._schema.metadata == features.arrow_schema.metadata
    UpperCAmelCase__	:      List[str]     							=					pa.BufferReader(output.getvalue() )
    UpperCAmelCase__	:      Optional[Any]     							=					pa.ipc.open_stream(_snake_case )
    UpperCAmelCase__	:      pa.Table     							=					f.read_all()
    UpperCAmelCase__	:      List[Any]     							=					pa_table.schema
    assert pa_table.num_rows == 2
    assert schema == features.arrow_schema
    assert schema.metadata == features.arrow_schema.metadata
    assert features == Features.from_arrow_schema(_snake_case )
@pytest.mark.parametrize('writer_batch_size'    ,[None, 1, 10] )
def 					lowerCamelCase   (     _snake_case ):
    UpperCAmelCase__	:      Optional[int]     							=					pa.BufferOutputStream()
    with ArrowWriter(
        stream=_snake_case    ,writer_batch_size=_snake_case    ,hash_salt='split_name'    ,check_duplicates=_snake_case    ,) as writer:
        with pytest.raises(_snake_case ):
            writer.write({'col_1': 'foo', 'col_2': 1}    ,key=[1, 2] )
            UpperCAmelCase__							,							UpperCAmelCase__	:      str     							=					writer.finalize()
@pytest.mark.parametrize('writer_batch_size'    ,[None, 2, 10] )
def 					lowerCamelCase   (     _snake_case ):
    UpperCAmelCase__	:      Union[str, Any]     							=					pa.BufferOutputStream()
    with ArrowWriter(
        stream=_snake_case    ,writer_batch_size=_snake_case    ,hash_salt='split_name'    ,check_duplicates=_snake_case    ,) as writer:
        with pytest.raises(_snake_case ):
            writer.write({'col_1': 'foo', 'col_2': 1}    ,key=10 )
            writer.write({'col_1': 'bar', 'col_2': 2}    ,key=10 )
            UpperCAmelCase__							,							UpperCAmelCase__	:      List[str]     							=					writer.finalize()
@pytest.mark.parametrize('writer_batch_size'    ,[None, 2, 10] )
def 					lowerCamelCase   (     _snake_case ):
    UpperCAmelCase__	:      int     							=					pa.BufferOutputStream()
    with ArrowWriter(
        stream=_snake_case    ,writer_batch_size=_snake_case    ,hash_salt='split_name'    ,check_duplicates=_snake_case    ,) as writer:
        writer.write({'col_1': 'foo', 'col_2': 1}    ,key=1 )
        writer.write({'col_1': 'bar', 'col_2': 2}    ,key=2 )
        UpperCAmelCase__							,							UpperCAmelCase__	:      List[str]     							=					writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    _check_output(output.getvalue()    ,expected_num_chunks=num_examples if writer_batch_size == 1 else 1 )
@pytest.mark.parametrize('writer_batch_size'    ,[None, 1, 10] )
@pytest.mark.parametrize(
    'fields'    ,[None, {'col_1': pa.string(), 'col_2': pa.intaa()}, {'col_1': pa.string(), 'col_2': pa.intaa()}] )
def 					lowerCamelCase   (     _snake_case    ,_snake_case ):
    UpperCAmelCase__	:      List[Any]     							=					pa.BufferOutputStream()
    UpperCAmelCase__	:      Tuple     							=					pa.schema(_snake_case ) if fields else None
    with ArrowWriter(stream=_snake_case    ,schema=_snake_case    ,writer_batch_size=_snake_case ) as writer:
        writer.write_batch({'col_1': ['foo', 'bar'], 'col_2': [1, 2]} )
        writer.write_batch({'col_1': [], 'col_2': []} )
        UpperCAmelCase__							,							UpperCAmelCase__	:      List[str]     							=					writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    if not fields:
        UpperCAmelCase__	:      Any     							=					{'col_1': pa.string(), 'col_2': pa.intaa()}
    assert writer._schema == pa.schema(_snake_case    ,metadata=writer._schema.metadata )
    _check_output(output.getvalue()    ,expected_num_chunks=num_examples if writer_batch_size == 1 else 1 )
@pytest.mark.parametrize('writer_batch_size'    ,[None, 1, 10] )
@pytest.mark.parametrize(
    'fields'    ,[None, {'col_1': pa.string(), 'col_2': pa.intaa()}, {'col_1': pa.string(), 'col_2': pa.intaa()}] )
def 					lowerCamelCase   (     _snake_case    ,_snake_case ):
    UpperCAmelCase__	:      List[Any]     							=					pa.BufferOutputStream()
    UpperCAmelCase__	:      Tuple     							=					pa.schema(_snake_case ) if fields else None
    with ArrowWriter(stream=_snake_case    ,schema=_snake_case    ,writer_batch_size=_snake_case ) as writer:
        writer.write_table(pa.Table.from_pydict({'col_1': ['foo', 'bar'], 'col_2': [1, 2]} ) )
        UpperCAmelCase__							,							UpperCAmelCase__	:      Optional[int]     							=					writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    if not fields:
        UpperCAmelCase__	:      Optional[int]     							=					{'col_1': pa.string(), 'col_2': pa.intaa()}
    assert writer._schema == pa.schema(_snake_case    ,metadata=writer._schema.metadata )
    _check_output(output.getvalue()    ,expected_num_chunks=num_examples if writer_batch_size == 1 else 1 )
@pytest.mark.parametrize('writer_batch_size'    ,[None, 1, 10] )
@pytest.mark.parametrize(
    'fields'    ,[None, {'col_1': pa.string(), 'col_2': pa.intaa()}, {'col_1': pa.string(), 'col_2': pa.intaa()}] )
def 					lowerCamelCase   (     _snake_case    ,_snake_case ):
    UpperCAmelCase__	:      List[str]     							=					pa.BufferOutputStream()
    UpperCAmelCase__	:      List[str]     							=					pa.schema(_snake_case ) if fields else None
    with ArrowWriter(stream=_snake_case    ,schema=_snake_case    ,writer_batch_size=_snake_case ) as writer:
        writer.write_row(pa.Table.from_pydict({'col_1': ['foo'], 'col_2': [1]} ) )
        writer.write_row(pa.Table.from_pydict({'col_1': ['bar'], 'col_2': [2]} ) )
        UpperCAmelCase__							,							UpperCAmelCase__	:      Dict     							=					writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    if not fields:
        UpperCAmelCase__	:      Optional[int]     							=					{'col_1': pa.string(), 'col_2': pa.intaa()}
    assert writer._schema == pa.schema(_snake_case    ,metadata=writer._schema.metadata )
    _check_output(output.getvalue()    ,expected_num_chunks=num_examples if writer_batch_size == 1 else 1 )
def 					lowerCamelCase   (     ):
    with tempfile.TemporaryDirectory() as tmp_dir:
        UpperCAmelCase__	:      Optional[int]     							=					{'col_1': pa.string(), 'col_2': pa.intaa()}
        UpperCAmelCase__	:      Optional[int]     							=					os.path.join(_snake_case    ,'test.arrow' )
        with ArrowWriter(path=_snake_case    ,schema=pa.schema(_snake_case ) ) as writer:
            writer.write_batch({'col_1': ['foo', 'bar'], 'col_2': [1, 2]} )
            UpperCAmelCase__							,							UpperCAmelCase__	:      Dict     							=					writer.finalize()
        assert num_examples == 2
        assert num_bytes > 0
        assert writer._schema == pa.schema(_snake_case    ,metadata=writer._schema.metadata )
        _check_output(_snake_case    ,1 )
def 					lowerCamelCase   (     _snake_case ):
    if pa.types.is_list(_snake_case ):
        return get_base_dtype(arr_type.value_type )
    else:
        return arr_type
def 					lowerCamelCase   (     _snake_case    ,_snake_case ):
    if isinstance(lst[0]    ,_snake_case ):
        change_first_primitive_element_in_list(lst[0]    ,_snake_case )
    else:
        UpperCAmelCase__	:      Optional[int]     							=					value
@pytest.mark.parametrize('optimized_int_type, expected_dtype'    ,[(None, pa.intaa()), (Value('int32' ), pa.intaa())] )
@pytest.mark.parametrize('sequence'    ,[[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]] )
def 					lowerCamelCase   (     _snake_case    ,_snake_case    ,_snake_case ):
    UpperCAmelCase__	:      Any     							=					pa.array(TypedSequence(_snake_case    ,optimized_int_type=_snake_case ) )
    assert get_base_dtype(arr.type ) == expected_dtype
@pytest.mark.parametrize(
    'col, expected_dtype'    ,[
        ('attention_mask', pa.inta()),
        ('special_tokens_mask', pa.inta()),
        ('token_type_ids', pa.inta()),
        ('input_ids', pa.intaa()),
        ('other', pa.intaa()),
    ]    ,)
@pytest.mark.parametrize('sequence'    ,[[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]] )
def 					lowerCamelCase   (     _snake_case    ,_snake_case    ,_snake_case ):
    # in range
    UpperCAmelCase__	:      List[str]     							=					pa.array(OptimizedTypedSequence(_snake_case    ,col=_snake_case ) )
    assert get_base_dtype(arr.type ) == expected_dtype

    # not in range
    if col != "other":
        # avoids errors due to in-place modifications
        UpperCAmelCase__	:      Union[str, Any]     							=					copy.deepcopy(_snake_case )
        UpperCAmelCase__	:      Tuple     							=					np.iinfo(expected_dtype.to_pandas_dtype() ).max + 1
        change_first_primitive_element_in_list(_snake_case    ,_snake_case )
        UpperCAmelCase__	:      Optional[Any]     							=					pa.array(OptimizedTypedSequence(_snake_case    ,col=_snake_case ) )
        assert get_base_dtype(arr.type ) == pa.intaa()
@pytest.mark.parametrize('raise_exception'    ,[False, True] )
def 					lowerCamelCase   (     _snake_case    ,_snake_case ):
    UpperCAmelCase__	:      str     							=					str(tmp_path / 'dataset-train.arrow' )
    try:
        with ArrowWriter(path=_snake_case ) as writer:
            if raise_exception:
                raise pa.lib.ArrowInvalid()
            else:
                writer.stream.close()
    except pa.lib.ArrowInvalid:
        pass
    finally:
        assert writer.stream.closed
def 					lowerCamelCase   (     _snake_case ):
    UpperCAmelCase__	:      Dict     							=					'mock://dataset-train.arrow'
    with ArrowWriter(path=_snake_case    ,storage_options=mockfs.storage_options ) as writer:
        assert isinstance(writer._fs    ,type(_snake_case ) )
        assert writer._fs.storage_options == mockfs.storage_options
        writer.write({'col_1': 'foo', 'col_2': 1} )
        writer.write({'col_1': 'bar', 'col_2': 2} )
        UpperCAmelCase__							,							UpperCAmelCase__	:      List[Any]     							=					writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    assert mockfs.exists(_snake_case )
def 					lowerCamelCase   (     ):
    UpperCAmelCase__	:      Union[str, Any]     							=					pa.BufferOutputStream()
    with ParquetWriter(stream=_snake_case ) as writer:
        writer.write({'col_1': 'foo', 'col_2': 1} )
        writer.write({'col_1': 'bar', 'col_2': 2} )
        UpperCAmelCase__							,							UpperCAmelCase__	:      Union[str, Any]     							=					writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    UpperCAmelCase__	:      Optional[Any]     							=					pa.BufferReader(output.getvalue() )
    UpperCAmelCase__	:      pa.Table     							=					pq.read_table(_snake_case )
    assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}
@require_pil
@pytest.mark.parametrize('embed_local_files'    ,[False, True] )
def 					lowerCamelCase   (     _snake_case    ,_snake_case ):
    import PIL.Image

    UpperCAmelCase__	:      str     							=					str(tmp_path / 'test_image_rgb.jpg' )
    PIL.Image.fromarray(np.zeros((5, 5)    ,dtype=np.uinta ) ).save(_snake_case    ,format='png' )
    UpperCAmelCase__	:      Any     							=					pa.BufferOutputStream()
    with ParquetWriter(
        stream=_snake_case    ,features=Features({'image': Image()} )    ,embed_local_files=_snake_case ) as writer:
        writer.write({'image': image_path} )
        writer.finalize()
    UpperCAmelCase__	:      str     							=					pa.BufferReader(output.getvalue() )
    UpperCAmelCase__	:      pa.Table     							=					pq.read_table(_snake_case )
    UpperCAmelCase__	:      List[str]     							=					pa_table.to_pydict()
    if embed_local_files:
        assert isinstance(out['image'][0]['path']    ,_snake_case )
        with open(_snake_case    ,'rb' ) as f:
            assert out["image"][0]["bytes"] == f.read()
    else:
        assert out["image"][0]["path"] == image_path
        assert out["image"][0]["bytes"] is None

def 					lowerCamelCase   (     ):
    UpperCAmelCase__	:      Union[str, Any]     							=					pa.schema([pa.field('col_1'    ,pa.string()    ,nullable=_snake_case )] )
    UpperCAmelCase__	:      Optional[Any]     							=					pa.BufferOutputStream()
    with ArrowWriter(stream=_snake_case ) as writer:
        writer._build_writer(inferred_schema=_snake_case )
        assert writer._schema == pa.schema([pa.field('col_1'    ,pa.string() )] )



"""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


UpperCamelCase__          =	{
    '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': 1_28,
    '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 				a			(					unittest.TestCase      ):



      @classmethod
      def  __snake_case							(   cls      ):
          UpperCAmelCase__	:      List[str]     							=					TOKEN
          HfFolder.save_token(UpperCamelCase_      )



      @classmethod
      def  __snake_case							(   cls      ):
          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  __snake_case							(   self      ):
          UpperCAmelCase__	:      Optional[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      )

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

        # 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(UpperCamelCase_     ,	repo_id='test-config'     ,	push_to_hub=UpperCamelCase_     ,	use_auth_token=self._token      )

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



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      List[Any]     							=					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      )

          UpperCAmelCase__	:      Union[str, Any]     							=					BertConfig.from_pretrained('valid_org/test-config-org'      )
          for k, v in config.to_dict().items():
              if k != "transformers_version":
                  self.assertEqual(UpperCamelCase_     ,	getattr(UpperCamelCase_     ,	UpperCamelCase_      )      )

        # 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(
                  UpperCamelCase_     ,	repo_id='valid_org/test-config-org'     ,	push_to_hub=UpperCamelCase_     ,	use_auth_token=self._token      )

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



      def  __snake_case							(   self      ):
          CustomConfig.register_for_auto_class()
          UpperCAmelCase__	:      Dict     							=					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'}      )

          UpperCAmelCase__	:      Any     							=					AutoConfig.from_pretrained(F'''{USER}/test-dynamic-config'''     ,	trust_remote_code=UpperCamelCase_      )
          # 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 				a			(					unittest.TestCase      ):



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      List[str]     							=					GPTaConfig()

          # attempt to modify each of int/float/bool/str config records and verify they were updated
          UpperCAmelCase__	:      List[str]     							=					c.n_embd + 1  # int
          UpperCAmelCase__	:      Optional[int]     							=					c.resid_pdrop + 1.0  # float
          UpperCAmelCase__	:      Optional[int]     							=					not c.scale_attn_weights  # bool
          UpperCAmelCase__	:      str     							=					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(UpperCamelCase_     ,	c.n_embd     ,	'mismatch for key: n_embd'      )
          self.assertEqual(UpperCamelCase_     ,	c.resid_pdrop     ,	'mismatch for key: resid_pdrop'      )
          self.assertEqual(UpperCamelCase_     ,	c.scale_attn_weights     ,	'mismatch for key: scale_attn_weights'      )
          self.assertEqual(UpperCamelCase_     ,	c.summary_type     ,	'mismatch for key: summary_type'      )



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      Dict     							=					PretrainedConfig()
          UpperCAmelCase__	:      str     							=					[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(
              UpperCamelCase_     ,	['is_encoder_decoder', '_name_or_path', '_commit_hash', 'transformers_version']      )
          UpperCAmelCase__	:      int     							=					[key for key, value in config_common_kwargs.items() if value == getattr(UpperCamelCase_     ,	UpperCamelCase_      )]
          if len(UpperCamelCase_      ) > 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(UpperCamelCase_      )}.'''      )



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

          UpperCAmelCase__	:      str     							=					BertConfig.from_pretrained('hf-internal-testing/tiny-random-bert-subfolder'     ,	subfolder='bert'      )

          self.assertIsNotNone(UpperCamelCase_      )



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

          # Download this model to make sure it's in the cache.
          UpperCAmelCase__	:      List[str]     							=					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=UpperCamelCase_      ) as mock_head:
              UpperCAmelCase__	:      Optional[Any]     							=					BertConfig.from_pretrained('hf-internal-testing/tiny-random-bert'      )
              # This check we did call the fake head request
              mock_head.assert_called()



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



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      int     							=					AutoConfig.from_pretrained('bert-base-cased'      )
          UpperCAmelCase__	:      str     							=					['config.4.0.0.json']

          with tempfile.TemporaryDirectory() as tmp_dir:
              configuration.save_pretrained(UpperCamelCase_      )
              UpperCAmelCase__	:      List[str]     							=					2
              json.dump(configuration.to_dict()     ,	open(os.path.join(UpperCamelCase_     ,	'config.4.0.0.json'      )     ,	'w'      )      )

              # This should pick the new configuration file as the version of Transformers is > 4.0.0
              UpperCAmelCase__	:      Any     							=					AutoConfig.from_pretrained(UpperCamelCase_      )
              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
              UpperCAmelCase__	:      Tuple     							=					['config.42.0.0.json']
              UpperCAmelCase__	:      Tuple     							=					768
              configuration.save_pretrained(UpperCamelCase_      )
              shutil.move(os.path.join(UpperCamelCase_     ,	'config.4.0.0.json'      )     ,	os.path.join(UpperCamelCase_     ,	'config.42.0.0.json'      )      )
              UpperCAmelCase__	:      Any     							=					AutoConfig.from_pretrained(UpperCamelCase_      )
              self.assertEqual(new_configuration.hidden_size     ,	768      )



      def  __snake_case							(   self      ):
          # This repo has two configuration files, one for v4.0.0 and above with a different hidden size.
          UpperCAmelCase__	:      Tuple     							=					'hf-internal-testing/test-two-configs'

          import transformers as new_transformers

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

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

          UpperCAmelCase__	:      List[Any]     							=					'v3.0.0'
          UpperCAmelCase__	:      Union[str, Any]     							=					old_transformers.models.auto.AutoConfig.from_pretrained(UpperCamelCase_      )
          self.assertEqual(old_configuration.hidden_size     ,	768      )

