




"""simple docstring"""
import qiskit





def 						UpperCAmelCase				(			A__:    int = 2     )  ->     qiskit.result.counts.Counts:
			__lowerCamelCase					:	Tuple	       =				qubits

			# Using Aer's simulator
			__lowerCamelCase					:	Optional[Any]	       =				qiskit.Aer.get_backend('aer_simulator'     )

			# Creating a Quantum Circuit acting on the q register
			__lowerCamelCase					:	Optional[int]	       =				qiskit.QuantumCircuit(A__							,				A__     )

			# Adding a H gate on qubit 0 (now q0 in superposition)
			circuit.h(0     )

			for i in range(1							,				A__     ):
						# Adding CX (CNOT) gate
						circuit.cx(i - 1							,				A__     )

			# Mapping the quantum measurement to the classical bits
			circuit.measure(list(range(A__     )     )							,				list(range(A__     )     )     )

			# Now measuring any one qubit would affect other qubits to collapse
			# their super position and have same state as the measured one.

			# Executing the circuit on the simulator
			__lowerCamelCase					:	str	       =				qiskit.execute(A__							,				A__							,				shots=1000     )

			return job.result().get_counts(A__     )


if __name__ == "__main__":
					print(F"""Total count for various states are: {quantum_entanglement(3)}""")









"""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


a_				:    Optional[int]										=     {
    '''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, 1.0_1),
    '''suppress_tokens''': [0, 1],
    '''begin_suppress_tokens''': 2,
    '''task_specific_params''': {'''translation''': '''some_params'''},
    '''problem_type''': '''regression''',
}

@is_staging_test
class __lowercase(      unittest.TestCase				):




					'''simple docstring'''


					@classmethod
					def     snake_case_				(    cls     ):
								__lowerCamelCase					:	Tuple	       =				TOKEN
								HfFolder.save_token(__a     )
					@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     ):
								__lowerCamelCase					:	List[str]	       =				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     )

								__lowerCamelCase					:	Any	       =				BertConfig.from_pretrained(f'''{USER}/test-config'''     )
								for k, v in config.to_dict().items():
											if k != "transformers_version":
														self.assertEqual(__a						,	getattr(__a						,	__a     )     )

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

								__lowerCamelCase					:	Any	       =				BertConfig.from_pretrained(f'''{USER}/test-config'''     )
								for k, v in config.to_dict().items():
											if k != "transformers_version":
														self.assertEqual(__a						,	getattr(__a						,	__a     )     )
					def     snake_case_				(    self     ):
								__lowerCamelCase					:	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     )

								__lowerCamelCase					:	Tuple	       =				BertConfig.from_pretrained('valid_org/test-config-org'     )
								for k, v in config.to_dict().items():
											if k != "transformers_version":
														self.assertEqual(__a						,	getattr(__a						,	__a     )     )

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

								__lowerCamelCase					:	Tuple	       =				BertConfig.from_pretrained('valid_org/test-config-org'     )
								for k, v in config.to_dict().items():
											if k != "transformers_version":
														self.assertEqual(__a						,	getattr(__a						,	__a     )     )





					def     snake_case_				(    self     ):
								CustomConfig.register_for_auto_class()
								__lowerCamelCase					:	Optional[Any]	       =				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'}     )

								__lowerCamelCase					:	Tuple	       =				AutoConfig.from_pretrained(f'''{USER}/test-dynamic-config'''						,	trust_remote_code=__a     )
								# 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 __lowercase(      unittest.TestCase				):




					'''simple docstring'''


					def     snake_case_				(    self     ):
								__lowerCamelCase					:	Tuple	       =				GPTaConfig()

								# attempt to modify each of int/float/bool/str config records and verify they were updated
								__lowerCamelCase					:	List[str]	       =				c.n_embd + 1  # int
								__lowerCamelCase					:	Dict	       =				c.resid_pdrop + 1.0  # float
								__lowerCamelCase					:	int	       =				not c.scale_attn_weights  # bool
								__lowerCamelCase					:	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(__a						,	c.n_embd						,	'mismatch for key: n_embd'     )
								self.assertEqual(__a						,	c.resid_pdrop						,	'mismatch for key: resid_pdrop'     )
								self.assertEqual(__a						,	c.scale_attn_weights						,	'mismatch for key: scale_attn_weights'     )
								self.assertEqual(__a						,	c.summary_type						,	'mismatch for key: summary_type'     )
					def     snake_case_				(    self     ):
								__lowerCamelCase					:	Tuple	       =				PretrainedConfig()
								__lowerCamelCase					:	Dict	       =				[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(
								    __a						,	['is_encoder_decoder', '_name_or_path', '_commit_hash', 'transformers_version']     )
								__lowerCamelCase					:	int	       =				[key for key, value in config_common_kwargs.items() if value == getattr(__a						,	__a     )]
								if len(__a     ) > 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(__a     )}.'''     )
					def     snake_case_				(    self     ):
								with self.assertRaises(__a     ):
											# config is in subfolder, the following should not work without specifying the subfolder
											__lowerCamelCase					:	int	       =				BertConfig.from_pretrained('hf-internal-testing/tiny-random-bert-subfolder'     )

								__lowerCamelCase					:	Optional[int]	       =				BertConfig.from_pretrained('hf-internal-testing/tiny-random-bert-subfolder'						,	subfolder='bert'     )

								self.assertIsNotNone(__a     )
					def     snake_case_				(    self     ):
								# A mock response for an HTTP head request to emulate server down
								__lowerCamelCase					:	List[str]	       =				mock.Mock()
								__lowerCamelCase					:	Tuple	       =				500
								__lowerCamelCase					:	Tuple	       =				{}
								__lowerCamelCase					:	Optional[Any]	       =				HTTPError
								__lowerCamelCase					:	str	       =				{}

								# Download this model to make sure it's in the cache.
								__lowerCamelCase					:	Optional[int]	       =				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=__a     ) as mock_head:
											__lowerCamelCase					:	Union[str, 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
								__lowerCamelCase					:	Optional[Any]	       =				BertConfig.from_pretrained(
								    'https://huggingface.co/hf-internal-testing/tiny-random-bert/resolve/main/config.json'     )
					def     snake_case_				(    self     ):
								__lowerCamelCase					:	List[Any]	       =				AutoConfig.from_pretrained('bert-base-cased'     )
								__lowerCamelCase					:	str	       =				['config.4.0.0.json']

								with tempfile.TemporaryDirectory() as tmp_dir:
											configuration.save_pretrained(__a     )
											__lowerCamelCase					:	Optional[int]	       =				2
											json.dump(configuration.to_dict()						,	open(os.path.join(__a						,	'config.4.0.0.json'     )						,	'w'     )     )

											# This should pick the new configuration file as the version of Transformers is > 4.0.0
											__lowerCamelCase					:	Any	       =				AutoConfig.from_pretrained(__a     )
											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
											__lowerCamelCase					:	Any	       =				['config.42.0.0.json']
											__lowerCamelCase					:	Tuple	       =				768
											configuration.save_pretrained(__a     )
											shutil.move(os.path.join(__a						,	'config.4.0.0.json'     )						,	os.path.join(__a						,	'config.42.0.0.json'     )     )
											__lowerCamelCase					:	Dict	       =				AutoConfig.from_pretrained(__a     )
											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.
								__lowerCamelCase					:	List[str]	       =				'hf-internal-testing/test-two-configs'

								import transformers as new_transformers

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

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

								__lowerCamelCase					:	Union[str, Any]	       =				'v3.0.0'
								__lowerCamelCase					:	Optional[int]	       =				old_transformers.models.auto.AutoConfig.from_pretrained(__a     )
								self.assertEqual(old_configuration.hidden_size						,	768     )



