





'''simple docstring'''

import subprocess
import sys

from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch

class       UpperCAmelCase (						_lowercase  ):




		@require_torch
		def 				UpperCAmelCase__   (self      :	Union[str, Any]				)					-> List[str]:
						# this test is a bit tricky since TRANSFORMERS_OFFLINE can only be changed before
						# `transformers` is loaded, and it's too late for inside pytest - so we are changing it
						# while running an external program

						# python one-liner segments

						# this must be loaded before socket.socket is monkey-patched
						lowercase         = "\nfrom transformers import BertConfig, BertModel, BertTokenizer, pipeline\n        "

						lowercase         = "\nmname = \"hf-internal-testing/tiny-random-bert\"\nBertConfig.from_pretrained(mname)\nBertModel.from_pretrained(mname)\nBertTokenizer.from_pretrained(mname)\npipe = pipeline(task=\"fill-mask\", model=mname)\nprint(\"success\")\n        "

						lowercase         = "\nimport socket\ndef offline_socket(*args, **kwargs): raise RuntimeError(\"Offline mode is enabled, we shouldn't access internet\")\nsocket.socket = offline_socket\n        "

						# Force fetching the files so that we can use the cache
						lowercase         = "hf-internal-testing/tiny-random-bert"
						BertConfig.from_pretrained(A__				)
						BertModel.from_pretrained(A__				)
						BertTokenizer.from_pretrained(A__				)
						pipeline(task="fill-mask"							,			model=A__				)

						# baseline - just load from_pretrained with normal network
						lowercase         = [sys.executable, "-c", "\n".join([load, run, mock]				)]

						# should succeed
						lowercase         = self.get_env()
						# should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
						lowercase         = "1"
						lowercase         = subprocess.run(A__							,			env=A__							,			check=A__							,			capture_output=A__				)
						self.assertEqual(result.returncode							,			0							,			result.stderr				)
						self.assertIn("success"							,			result.stdout.decode()				)




		@require_torch
		def 				UpperCAmelCase__   (self      :	Any				)					-> Tuple:
						# python one-liner segments
						# this must be loaded before socket.socket is monkey-patched
						lowercase         = "\nfrom transformers import BertConfig, BertModel, BertTokenizer, pipeline\n        "

						lowercase         = "\nmname = \"hf-internal-testing/tiny-random-bert\"\nBertConfig.from_pretrained(mname)\nBertModel.from_pretrained(mname)\nBertTokenizer.from_pretrained(mname)\npipe = pipeline(task=\"fill-mask\", model=mname)\nprint(\"success\")\n        "

						lowercase         = "\nimport socket\ndef offline_socket(*args, **kwargs): raise socket.error(\"Faking flaky internet\")\nsocket.socket = offline_socket\n        "

						# Force fetching the files so that we can use the cache
						lowercase         = "hf-internal-testing/tiny-random-bert"
						BertConfig.from_pretrained(A__				)
						BertModel.from_pretrained(A__				)
						BertTokenizer.from_pretrained(A__				)
						pipeline(task="fill-mask"							,			model=A__				)

						# baseline - just load from_pretrained with normal network
						lowercase         = [sys.executable, "-c", "\n".join([load, run, mock]				)]

						# should succeed
						lowercase         = self.get_env()
						lowercase         = subprocess.run(A__							,			env=A__							,			check=A__							,			capture_output=A__				)
						self.assertEqual(result.returncode							,			0							,			result.stderr				)
						self.assertIn("success"							,			result.stdout.decode()				)




		@require_torch
		def 				UpperCAmelCase__   (self      :	Optional[Any]				)					-> int:
						# this test is a bit tricky since TRANSFORMERS_OFFLINE can only be changed before
						# `transformers` is loaded, and it's too late for inside pytest - so we are changing it
						# while running an external program

						# python one-liner segments

						# this must be loaded before socket.socket is monkey-patched
						lowercase         = "\nfrom transformers import BertConfig, BertModel, BertTokenizer\n        "

						lowercase         = "\nmname = \"hf-internal-testing/tiny-random-bert-sharded\"\nBertConfig.from_pretrained(mname)\nBertModel.from_pretrained(mname)\nprint(\"success\")\n        "

						lowercase         = "\nimport socket\ndef offline_socket(*args, **kwargs): raise ValueError(\"Offline mode is enabled\")\nsocket.socket = offline_socket\n        "

						# baseline - just load from_pretrained with normal network
						lowercase         = [sys.executable, "-c", "\n".join([load, run]				)]

						# should succeed
						lowercase         = self.get_env()
						lowercase         = subprocess.run(A__							,			env=A__							,			check=A__							,			capture_output=A__				)
						self.assertEqual(result.returncode							,			0							,			result.stderr				)
						self.assertIn("success"							,			result.stdout.decode()				)

						# next emulate no network
						lowercase         = [sys.executable, "-c", "\n".join([load, mock, run]				)]

						# Doesn't fail anymore since the model is in the cache due to other tests, so commenting this.
						# env["TRANSFORMERS_OFFLINE"] = "0"
						# result = subprocess.run(cmd, env=env, check=False, capture_output=True)
						# self.assertEqual(result.returncode, 1, result.stderr)

						# should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
						lowercase         = "1"
						lowercase         = subprocess.run(A__							,			env=A__							,			check=A__							,			capture_output=A__				)
						self.assertEqual(result.returncode							,			0							,			result.stderr				)
						self.assertIn("success"							,			result.stdout.decode()				)




		@require_torch
		def 				UpperCAmelCase__   (self      :	Dict				)					-> int:
						lowercase         = "\nfrom transformers import pipeline\n        "
						lowercase         = "\nmname = \"hf-internal-testing/tiny-random-bert\"\npipe = pipeline(model=mname)\n        "

						lowercase         = "\nimport socket\ndef offline_socket(*args, **kwargs): raise socket.error(\"Offline mode is enabled\")\nsocket.socket = offline_socket\n        "
						lowercase         = self.get_env()
						lowercase         = "1"
						lowercase         = [sys.executable, "-c", "\n".join([load, mock, run]				)]
						lowercase         = subprocess.run(A__							,			env=A__							,			check=A__							,			capture_output=A__				)
						self.assertEqual(result.returncode							,			1							,			result.stderr				)
						self.assertIn(
						    "You cannot infer task automatically within `pipeline` when using offline mode"							,			result.stderr.decode().replace("\n"							,			""				)							,			)





		@require_torch
		def 				UpperCAmelCase__   (self      :	int				)					-> Tuple:
						lowercase         = "\nfrom transformers import AutoModel\n        "
						lowercase         = "\nmname = \"hf-internal-testing/test_dynamic_model\"\nAutoModel.from_pretrained(mname, trust_remote_code=True)\nprint(\"success\")\n        "

						# baseline - just load from_pretrained with normal network
						lowercase         = [sys.executable, "-c", "\n".join([load, run]				)]

						# should succeed
						lowercase         = self.get_env()
						lowercase         = subprocess.run(A__							,			env=A__							,			check=A__							,			capture_output=A__				)
						self.assertEqual(result.returncode							,			0							,			result.stderr				)
						self.assertIn("success"							,			result.stdout.decode()				)

						# should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
						lowercase         = "1"
						lowercase         = subprocess.run(A__							,			env=A__							,			check=A__							,			capture_output=A__				)
						self.assertEqual(result.returncode							,			0							,			result.stderr				)
						self.assertIn("success"							,			result.stdout.decode()				)











'''simple docstring'''

import functools







def 							UpperCAmelCase_    (	lowerCAmelCase_		,							lowerCAmelCase_							):

				"""simple docstring"""






				if not isinstance(lowerCAmelCase_		,							lowerCAmelCase_							) or not all(isinstance(lowerCAmelCase_		,							lowerCAmelCase_							) for day in days							):
								raise ValueError("The parameter days should be a list of integers"							)

				if len(lowerCAmelCase_							) != 3 or not all(isinstance(lowerCAmelCase_		,							lowerCAmelCase_							) for cost in costs							):
								raise ValueError("The parameter costs should be a list of three integers"							)

				if len(lowerCAmelCase_							) == 0:
								return 0

				if min(lowerCAmelCase_							) <= 0:
								raise ValueError("All days elements should be greater than 0"							)

				if max(lowerCAmelCase_							) >= 366:
								raise ValueError("All days elements should be less than 366"							)

				lowercase         = set(lowerCAmelCase_							)

				@functools.cache
				def dynamic_programming(lowerCAmelCase_							) -> int:
								if index > 365:
												return 0

								if index not in days_set:
												return dynamic_programming(index + 1							)

								return min(
								    costs[0] + dynamic_programming(index + 1							)		,							costs[1] + dynamic_programming(index + 7							)		,							costs[2] + dynamic_programming(index + 30							)		,							)

				return dynamic_programming(1							)


if __name__ == "__main__":
			import doctest

			doctest.testmod()




