




'''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


_SCREAMING_SNAKE_CASE							:   Optional[Any]      		= {
    "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, 1.0_1),
    "suppress_tokens": [0, 1],
    "begin_suppress_tokens": 2,
    "task_specific_params": {"translation": "some_params"},
    "problem_type": "regression",
}




@is_staging_test
class  _snake_case		(	unittest.TestCase							):




			@classmethod
			def    lowerCAmelCase__				(					cls							)				->				Union[str, Any]:

										'''simple docstring'''




										snake_case_						=      TOKEN
										HfFolder.save_token(a__							)




			@classmethod
			def    lowerCAmelCase__				(					cls							)				->				str:

										'''simple docstring'''




										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    lowerCAmelCase__				(					self							)				->				List[str]:

										'''simple docstring'''




										snake_case_						=      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							)

										snake_case_						=      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							)

										snake_case_						=      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    lowerCAmelCase__				(					self							)				->				Optional[int]:

										'''simple docstring'''




										snake_case_						=      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							)

										snake_case_						=      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							)

										snake_case_						=      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    lowerCAmelCase__				(					self							)				->				Tuple:

										'''simple docstring'''




										CustomConfig.register_for_auto_class()
										snake_case_						=      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"}							)

										snake_case_						=      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  _snake_case		(	unittest.TestCase							):




			def    lowerCAmelCase__				(					self							)				->				Optional[Any]:

										'''simple docstring'''




										snake_case_						=      GPTaConfig()

										# attempt to modify each of int/float/bool/str config records and verify they were updated
										snake_case_						=      c.n_embd + 1  # int
										snake_case_						=      c.resid_pdrop + 1.0  # float
										snake_case_						=      not c.scale_attn_weights  # bool
										snake_case_						=      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    lowerCAmelCase__				(					self							)				->				Union[str, Any]:

										'''simple docstring'''




										snake_case_						=      PretrainedConfig()
										snake_case_						=      [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"]							)
										snake_case_						=      [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    lowerCAmelCase__				(					self							)				->				Optional[int]:

										'''simple docstring'''




										with self.assertRaises(a__							):
																	# config is in subfolder, the following should not work without specifying the subfolder
																	snake_case_						=      BertConfig.from_pretrained("hf-internal-testing/tiny-random-bert-subfolder"							)

										snake_case_						=      BertConfig.from_pretrained("hf-internal-testing/tiny-random-bert-subfolder"				,							subfolder="bert"							)

										self.assertIsNotNone(a__							)




			def    lowerCAmelCase__				(					self							)				->				List[str]:

										'''simple docstring'''




										snake_case_						=      mock.Mock()
										snake_case_						=      500
										snake_case_						=      {}
										snake_case_						=      HTTPError
										snake_case_						=      {}

										# Download this model to make sure it's in the cache.
										snake_case_						=      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:
																	snake_case_						=      BertConfig.from_pretrained("hf-internal-testing/tiny-random-bert"							)
																	# This check we did call the fake head request
																	mock_head.assert_called()




			def    lowerCAmelCase__				(					self							)				->				Optional[Any]:

										'''simple docstring'''




										snake_case_						=      BertConfig.from_pretrained(
										    "https://huggingface.co/hf-internal-testing/tiny-random-bert/resolve/main/config.json"							)




			def    lowerCAmelCase__				(					self							)				->				List[Any]:

										'''simple docstring'''




										snake_case_						=      AutoConfig.from_pretrained("bert-base-cased"							)
										snake_case_						=      ["config.4.0.0.json"]

										with tempfile.TemporaryDirectory() as tmp_dir:
																	configuration.save_pretrained(a__							)
																	snake_case_						=      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
																	snake_case_						=      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
																	snake_case_						=      ["config.42.0.0.json"]
																	snake_case_						=      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"							)							)
																	snake_case_						=      AutoConfig.from_pretrained(a__							)
																	self.assertEqual(new_configuration.hidden_size				,							768							)




			def    lowerCAmelCase__				(					self							)				->				Optional[int]:

										'''simple docstring'''




										snake_case_						=      "hf-internal-testing/test-two-configs"

										import transformers as new_transformers

										snake_case_						=      "v4.0.0"
										snake_case_					,      snake_case_						=      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

										snake_case_						=      "v3.0.0"
										snake_case_						=      old_transformers.models.auto.AutoConfig.from_pretrained(a__							)
										self.assertEqual(old_configuration.hidden_size				,							768							)






from __future__ import annotations

import os
from collections.abc import Mapping

_UpperCAmelCase					: Tuple      =       tuple[int, int]


class 				lowercase					:



		def __init__( self				,      A_				,      A_       )  ->					None:
				"""simple docstring"""
				UpperCamelCase		=     vertices
				UpperCamelCase		=     {
				    (min(A_       ), max(A_       )): weight for edge, weight in edges.items()
				}



		def __UpperCamelCase ( self				,      A_				,      A_       )  ->					None:
				"""simple docstring"""
				self.vertices.add(edge[0]       )
				self.vertices.add(edge[1]       )
				UpperCamelCase		=     weight



		def __UpperCamelCase ( self       )  ->					Graph:
				"""simple docstring"""
				UpperCamelCase		=     Graph({min(self.vertices       )}				,      {}       )
				UpperCamelCase		=     42
				UpperCamelCase		=     42
				UpperCamelCase		=     42
				UpperCamelCase		=     42

				while len(subgraph.vertices       ) < len(self.vertices       ):
						UpperCamelCase		=     max(self.edges.values()       ) + 1
						for edge, weight in self.edges.items():
								if (edge[0] in subgraph.vertices) ^ (edge[1] in subgraph.vertices):
										if weight < min_weight:
												UpperCamelCase		=     edge
												UpperCamelCase		=     weight

						subgraph.add_edge(A_				,      A_       )

				return subgraph






def       A       (					lowercase = "p107_network.txt" )   ->  int:
		'''simple docstring'''

		UpperCamelCase		=     os.path.abspath(os.path.dirname(lowercase ) )
		UpperCamelCase		=     os.path.join(lowercase    ,       lowercase )
		UpperCamelCase		=     {}
		UpperCamelCase		=     42
		UpperCamelCase		=     42
		UpperCamelCase		=     42

		with open(lowercase ) as f:
				UpperCamelCase		=     f.read().strip().split('\n' )

		UpperCamelCase		=     [line.split(',' ) for line in data]

		for edgea in range(1    ,       len(lowercase ) ):
				for edgea in range(lowercase ):
						if adjaceny_matrix[edgea][edgea] != "-":
								UpperCamelCase		=     int(adjaceny_matrix[edgea][edgea] )

		UpperCamelCase		=     Graph(set(range(len(lowercase ) ) )    ,       lowercase )

		UpperCamelCase		=     graph.prims_algorithm()

		UpperCamelCase		=     sum(graph.edges.values() )
		UpperCamelCase		=     sum(subgraph.edges.values() )

		return initial_total - optimal_total


if __name__ == "__main__":
					print(F'''{solution() = }''')
