




import platform
from argparse import ArgumentParser

import huggingface_hub
import pandas
import pyarrow

from datasets import __version__ as version
from datasets.commands import BaseDatasetsCLICommand


def 							__SCREAMING_SNAKE_CASE						(    snake_case_		):

						'''simple docstring'''


						return EnvironmentCommand()






class 					__lowerCAmelCase				( UpperCAmelCase__				):







			@staticmethod
			def UpperCamelCase    ( snake_case__					:    ArgumentParser   ):




									"""simple docstring"""


									_UpperCAmelCase									=  parser.add_parser("env"					,					help="Print relevant system environment info."   )
									download_parser.set_defaults(func=snake_case__   )







			def UpperCamelCase    ( self					:    List[str]   ):




									"""simple docstring"""


									_UpperCAmelCase									=  {
									    "`datasets` version": version,
									    "Platform": platform.platform(),
									    "Python version": platform.python_version(),
									    "Huggingface_hub version": huggingface_hub.__version__,
									    "PyArrow version": pyarrow.__version__,
									    "Pandas version": pandas.__version__,
									}

									print("\nCopy-and-paste the text below in your GitHub issue.\n"   )
									print(self.format_dict(snake_case__   )   )

									return info







			@staticmethod
			def UpperCamelCase    ( snake_case__					:    Tuple   ):




									"""simple docstring"""


									return "\n".join([F"""- {prop}: {val}""" for prop, val in d.items()]   ) + "\n"










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					:    List[str]   ):




									"""simple docstring"""


									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					:    Optional[Any]   ):




									"""simple docstring"""


									import transformers.commands.transformers_cli

									shutil.rmtree("/tmp/hf-internal-testing/tiny-random-gptj"					,					ignore_errors=snake_case__   )  # 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					:    Any   ):




									"""simple docstring"""


									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=snake_case__   )

									# 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					:    int   ):




									"""simple docstring"""


									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=snake_case__   )

									# 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"   )   )




