





'''simple docstring'''

from __future__ import annotations

from enum import Enum, unique
from typing import TypeVar

# Create a generic variable that can be 'Enum', or any subclass.
lowerCAmelCase__	:					Optional[int]	     =       TypeVar("T", bound="Enum")


@unique
class 			SCREAMING_SNAKE_CASE__	(					A_						):







					"""simple docstring"""






					SCREAMING_SNAKE_CASE				=     80
					SCREAMING_SNAKE_CASE				=     70
					SCREAMING_SNAKE_CASE				=     60
					SCREAMING_SNAKE_CASE				=     50
					SCREAMING_SNAKE_CASE				=     40
					SCREAMING_SNAKE_CASE				=     30
					SCREAMING_SNAKE_CASE				=     20
					SCREAMING_SNAKE_CASE				=     10






@unique
class 			SCREAMING_SNAKE_CASE__	(					A_						):







					"""simple docstring"""






					SCREAMING_SNAKE_CASE				=     24
					SCREAMING_SNAKE_CASE				=     21
					SCREAMING_SNAKE_CASE				=     18
					SCREAMING_SNAKE_CASE				=     15
					SCREAMING_SNAKE_CASE				=     12
					SCREAMING_SNAKE_CASE				=     9
					SCREAMING_SNAKE_CASE				=     6
					SCREAMING_SNAKE_CASE				=     3
					SCREAMING_SNAKE_CASE				=     2
					SCREAMING_SNAKE_CASE				=     1
					SCREAMING_SNAKE_CASE				=     -1
					SCREAMING_SNAKE_CASE				=     -2
					SCREAMING_SNAKE_CASE				=     -3
					SCREAMING_SNAKE_CASE				=     -6
					SCREAMING_SNAKE_CASE				=     -9
					SCREAMING_SNAKE_CASE				=     -12
					SCREAMING_SNAKE_CASE				=     -15
					SCREAMING_SNAKE_CASE				=     -18
					SCREAMING_SNAKE_CASE				=     -21
					SCREAMING_SNAKE_CASE				=     -24
					@classmethod
					def 						lowerCamelCase_					(					cls    :	type[T]						):







							"""simple docstring"""
							return {unit.name: unit.value for unit in cls if unit.value > 0}






					@classmethod
					def 						lowerCamelCase_					(					cls    :	type[T]						):







							"""simple docstring"""
							return {unit.name: unit.value for unit in cls if unit.value < 0}






def 		__UpperCamelCase		(       _UpperCAmelCase   ):
		__UpperCAmelCase     :				Dict					   =			SIUnit.get_positive() if value > 0 else SIUnit.get_negative()
		for name_prefix, value_prefix in prefixes.items():
				__UpperCAmelCase     :				Optional[Any]					   =			value / (10**value_prefix)
				if numerical_part > 1:
						return F"{numerical_part!s} {name_prefix}"
		return str(A__   )


def 		__UpperCamelCase		(       _UpperCAmelCase   ):

		for prefix in BinaryUnit:
				__UpperCAmelCase     :				Optional[Any]					   =			value / (2**prefix.value)
				if numerical_part > 1:
						return F"{numerical_part!s} {prefix.name}"
		return str(A__   )


if __name__ == "__main__":
			import doctest

			doctest.testmod()






import os
import shutil
import unittest
from unittest.mock import patch

from transformers.testing_utils import CaptureStd, is_pt_tf_cross_test, require_torch







class      lowerCamelCase		(  unittest.TestCase  ):





     @patch("sys.argv"				,    ["fakeprogrampath", "env"]   )
     def 		UpperCAmelCase(self      :    Optional[Any]   )						->						Dict:
         # test transformers-cli env
         import transformers.commands.transformers_cli

         with CaptureStd() as cs:
             transformers.commands.transformers_cli.main()
         self.assertIn("Python version"				,    cs.out   )
         self.assertIn("Platform"				,    cs.out   )
         self.assertIn("Using distributed or parallel set-up in script?"				,    cs.out   )





     @is_pt_tf_cross_test
     @patch(
         "sys.argv"				,    ["fakeprogrampath", "pt-to-tf", "--model-name", "hf-internal-testing/tiny-random-gptj", "--no-pr"]   )
     def 		UpperCAmelCase(self      :    Any   )						->						int:
         import transformers.commands.transformers_cli

         shutil.rmtree("/tmp/hf-internal-testing/tiny-random-gptj"				,    ignore_errors=_A   )  # cleans potential past runs
         transformers.commands.transformers_cli.main()

         # The original repo has no TF weights -- if they exist, they were created by the CLI
         self.assertTrue(os.path.exists("/tmp/hf-internal-testing/tiny-random-gptj/tf_model.h5"   )   )





     @require_torch
     @patch("sys.argv"				,    ["fakeprogrampath", "download", "hf-internal-testing/tiny-random-gptj", "--cache-dir", "/tmp"]   )
     def 		UpperCAmelCase(self      :    Dict   )						->						List[Any]:
         import transformers.commands.transformers_cli

         # # remove any previously downloaded model to start clean
         shutil.rmtree("/tmp/models--hf-internal-testing--tiny-random-gptj"				,    ignore_errors=_A   )

         # run the command
         transformers.commands.transformers_cli.main()

         # check if the model files are downloaded correctly on /tmp/models--hf-internal-testing--tiny-random-gptj
         self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--tiny-random-gptj/blobs"   )   )
         self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--tiny-random-gptj/refs"   )   )
         self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--tiny-random-gptj/snapshots"   )   )





     @require_torch
     @patch(
         "sys.argv"				,    [
             "fakeprogrampath",
             "download",
             "hf-internal-testing/test_dynamic_model_with_tokenizer",
             "--trust-remote-code",
             "--cache-dir",
             "/tmp",
         ]				,    )
     def 		UpperCAmelCase(self      :    Any   )						->						List[str]:
         import transformers.commands.transformers_cli

         # # remove any previously downloaded model to start clean
         shutil.rmtree("/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer"				,    ignore_errors=_A   )

         # run the command
         transformers.commands.transformers_cli.main()

         # check if the model files are downloaded correctly on /tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer
         self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/blobs"   )   )
         self.assertTrue(os.path.exists("/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/refs"   )   )
         self.assertTrue(
             os.path.exists("/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/snapshots"   )   )

