


import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock

import torch

from ..state import AcceleratorState, PartialState
from ..utils import (
    gather,
    is_bnb_available,
    is_comet_ml_available,
    is_datasets_available,
    is_deepspeed_available,
    is_mps_available,
    is_safetensors_available,
    is_tensorboard_available,
    is_torch_version,
    is_tpu_available,
    is_transformers_available,
    is_wandb_available,
    is_xpu_available,
)


def     lowercase	(    a     , a=False ):



		'''simple docstring'''




		try:
				SCREAMING_SNAKE_CASE_				:Tuple				     =						os.environ[key]
		except KeyError:
				# KEY isn't set, default to `default`.
				SCREAMING_SNAKE_CASE_				:Any				     =						default
		else:
				# KEY is set, convert it to True or False.
				try:
						SCREAMING_SNAKE_CASE_				:Optional[int]				     =						strtobool(a )
				except ValueError:
						# More values are supported, but let's keep the message simple.
						raise ValueError(F"If set, {key} must be yes or no." )
		return _value


SCREAMING_SNAKE_CASE__     					=			parse_flag_from_env("RUN_SLOW", default=False)


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skip("Test was skipped" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(_run_slow_tests     , "test is slow" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(not torch.cuda.is_available()     , "test requires only a CPU" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(torch.cuda.is_available()     , "test requires a GPU" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(is_xpu_available()     , "test requires a XPU" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(is_mps_available()     , "test requires a `mps` backend support in `torch`" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(
		    is_transformers_available() and is_datasets_available()     , "test requires the Hugging Face suite" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(is_bnb_available()     , "test requires the bitsandbytes library" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(is_tpu_available()     , "test requires TPU" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(torch.cuda.device_count() == 1     , "test requires a GPU" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(torch.xpu.device_count() == 1     , "test requires a XPU" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(torch.cuda.device_count() > 1     , "test requires multiple GPUs" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(torch.xpu.device_count() > 1     , "test requires multiple XPUs" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(is_safetensors_available()     , "test requires safetensors" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(is_deepspeed_available()     , "test requires DeepSpeed" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(is_torch_version(">="     , "1.12.0" )     , "test requires torch version >= 1.12.0" )(a )


def     lowercase	(    a=None     , a=None ):



		'''simple docstring'''




		if test_case is None:
				return partial(a     , version=a )
		return unittest.skipUnless(is_torch_version(">="     , a )     , F"test requires torch version >= {version}" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(is_tensorboard_available()     , "test requires Tensorboard" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(is_wandb_available()     , "test requires wandb" )(a )


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(is_comet_ml_available()     , "test requires comet_ml" )(a )


SCREAMING_SNAKE_CASE__     					=			(
    any([is_wandb_available(), is_tensorboard_available()]) and not is_comet_ml_available()
)


def     lowercase	(    a ):



		'''simple docstring'''




		return unittest.skipUnless(
		    _atleast_one_tracker_available     , "test requires at least one tracker to be available and for `comet_ml` to not be installed"     , )(a )



class 						_UpperCAmelCase      (     unittest.TestCase							):
		lowerCamelCase_	:			str       			=  True






		@classmethod
		def _snake_case		(						cls				:     Union[str, Any]):
				SCREAMING_SNAKE_CASE_				:List[str]				     =						tempfile.mkdtemp()






		@classmethod
		def _snake_case		(						cls				:     Union[str, Any]):
				if os.path.exists(cls.tmpdir):
						shutil.rmtree(cls.tmpdir)







		def _snake_case		(						self				:     int):
				if self.clear_on_setup:
						for path in Path(self.tmpdir).glob("**/*"):
								if path.is_file():
										path.unlink()
								elif path.is_dir():
										shutil.rmtree(UpperCAmelCase)




class 						_UpperCAmelCase      (     unittest.TestCase							):






		def _snake_case		(						self				:     Optional[Any]):
				super().tearDown()
				# Reset the state of the AcceleratorState singleton.
				AcceleratorState._reset_state()
				PartialState._reset_state()




class 						_UpperCAmelCase      (     unittest.TestCase							):






		def _snake_case		(						self				:     Any   ,  UpperCAmelCase				:     Union[mock.Mock, List[mock.Mock]]):
				SCREAMING_SNAKE_CASE_				:List[str]				     =						mocks if isinstance(UpperCAmelCase   ,  (tuple, list)) else [mocks]
				for m in self.mocks:
						m.start()
						self.addCleanup(m.stop)




def     lowercase	(    a ):



		'''simple docstring'''




		SCREAMING_SNAKE_CASE_				:List[Any]				     =						AcceleratorState()
		SCREAMING_SNAKE_CASE_				:Any				     =						tensor[None].clone().to(state.device )
		SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						gather(a ).cpu()
		SCREAMING_SNAKE_CASE_				:Tuple				     =						tensor[0].cpu()
		for i in range(tensors.shape[0] ):
				if not torch.equal(tensors[i]     , a ):
						return False
		return True



class 						_UpperCAmelCase      :






		def __init__(						self				:     Optional[int]   ,  UpperCAmelCase				:     List[Any]   ,  UpperCAmelCase				:     Optional[Any]   ,  UpperCAmelCase				:     Union[str, Any]):
				SCREAMING_SNAKE_CASE_				:Any				     =						returncode
				SCREAMING_SNAKE_CASE_				:List[str]				     =						stdout
				SCREAMING_SNAKE_CASE_				:Dict				     =						stderr




async def     lowercase	(    a     , a ):



		'''simple docstring'''




		while True:
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						await stream.readline()
				if line:
						callback(a )
				else:
						break


async def     lowercase	(    a     , a=None     , a=None     , a=None     , a=False     , a=False ):



		'''simple docstring'''




		if echo:
				print("\nRunning: "     , " ".join(a ) )

		SCREAMING_SNAKE_CASE_				:str				     =						await asyncio.create_subprocess_exec(
		    cmd[0]     , *cmd[1:]     , stdin=a     , stdout=asyncio.subprocess.PIPE     , stderr=asyncio.subprocess.PIPE     , env=a     , )

		# note: there is a warning for a possible deadlock when using `wait` with huge amounts of data in the pipe
		# https://docs.python.org/3/library/asyncio-subprocess.html#asyncio.asyncio.subprocess.Process.wait
		#
		# If it starts hanging, will need to switch to the following code. The problem is that no data
		# will be seen until it's done and if it hangs for example there will be no debug info.
		# out, err = await p.communicate()
		# return _RunOutput(p.returncode, out, err)

		SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						[]
		SCREAMING_SNAKE_CASE_				:Dict				     =						[]

		def tee(a     , a     , a     , a="" ):
				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						line.decode("utf-8" ).rstrip()
				sink.append(a )
				if not quiet:
						print(a     , a     , file=a )

    # XXX: the timeout doesn't seem to make any difference here
		await asyncio.wait(
		    [
		        asyncio.create_task(_read_stream(p.stdout     , lambda a : tee(a     , a     , sys.stdout     , label="stdout:" ) ) ),
		        asyncio.create_task(_read_stream(p.stderr     , lambda a : tee(a     , a     , sys.stderr     , label="stderr:" ) ) ),
		    ]     , timeout=a     , )
		return _RunOutput(await p.wait()     , a     , a )


def     lowercase	(    a     , a=None     , a=None     , a=180     , a=False     , a=True ):



		'''simple docstring'''




		SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						asyncio.get_event_loop()
		SCREAMING_SNAKE_CASE_				:Dict				     =						loop.run_until_complete(
		    _stream_subprocess(a     , env=a     , stdin=a     , timeout=a     , quiet=a     , echo=a ) )

		SCREAMING_SNAKE_CASE_				:Optional[int]				     =						" ".join(a )
		if result.returncode > 0:
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						"\n".join(result.stderr )
				raise RuntimeError(
				    F"'{cmd_str}' failed with returncode {result.returncode}\n\n"
				    F"The combined stderr from workers follows:\n{stderr}" )

		return result



class 						_UpperCAmelCase      (     lowercase							):
		pass




def     lowercase	(    a     , a=False ):



		'''simple docstring'''




		try:
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						subprocess.check_output(a     , stderr=subprocess.STDOUT )
				if return_stdout:
						if hasattr(a     , "decode" ):
								SCREAMING_SNAKE_CASE_				:List[str]				     =						output.decode("utf-8" )
						return output
		except subprocess.CalledProcessError as e:
				raise SubprocessCallException(
				    F"Command `{' '.join(a )}` failed with the following error:\n\n{e.output.decode()}" ) from e










import glob
import os
import random
from string import ascii_lowercase, digits

import cva
import numpy as np

# Parrameters
SCREAMING_SNAKE_CASE__     					=			(720, 1_280)  # Height, Width
SCREAMING_SNAKE_CASE__     					=			(0.4, 0.6)  # if height or width lower than this scale, drop it.
SCREAMING_SNAKE_CASE__     					=			1 / 100
SCREAMING_SNAKE_CASE__     					=			""
SCREAMING_SNAKE_CASE__     					=			""
SCREAMING_SNAKE_CASE__     					=			""
SCREAMING_SNAKE_CASE__     					=			250


def     lowercase	(    ):



		'''simple docstring'''




		SCREAMING_SNAKE_CASE_     ,				SCREAMING_SNAKE_CASE_				:str				     =						get_dataset(a     , a )
		for index in range(a ):
				SCREAMING_SNAKE_CASE_				:Any				     =						random.sample(range(len(a ) )     , 4 )
				SCREAMING_SNAKE_CASE_     ,				SCREAMING_SNAKE_CASE_     ,				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						update_image_and_anno(
				    a     , a     , a     , a     , a     , filter_scale=a     , )

				# Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
				SCREAMING_SNAKE_CASE_				:int				     =						random_chars(32 )
				SCREAMING_SNAKE_CASE_				:Dict				     =						path.split(os.sep )[-1].rsplit("."     , 1 )[0]
				SCREAMING_SNAKE_CASE_				:Dict				     =						F"{OUTPUT_DIR}/{file_name}_MOSAIC_{letter_code}"
				cva.imwrite(F"{file_root}.jpg"     , a     , [cva.IMWRITE_JPEG_QUALITY, 85] )
				print(F"Succeeded {index+1}/{NUMBER_IMAGES} with {file_name}" )
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						[]
				for anno in new_annos:
						SCREAMING_SNAKE_CASE_				:Any				     =						anno[3] - anno[1]
						SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						anno[4] - anno[2]
						SCREAMING_SNAKE_CASE_				:Any				     =						anno[1] + width / 2
						SCREAMING_SNAKE_CASE_				:Optional[int]				     =						anno[2] + height / 2
						SCREAMING_SNAKE_CASE_				:Optional[int]				     =						F"{anno[0]} {x_center} {y_center} {width} {height}"
						annos_list.append(a )
				with open(F"{file_root}.txt"     , "w" ) as outfile:
						outfile.write("\n".join(line for line in annos_list ) )


def     lowercase	(    a     , a ):



		'''simple docstring'''




		SCREAMING_SNAKE_CASE_				:int				     =						[]
		SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						[]
		for label_file in glob.glob(os.path.join(a     , "*.txt" ) ):
				SCREAMING_SNAKE_CASE_				:List[str]				     =						label_file.split(os.sep )[-1].rsplit("."     , 1 )[0]
				with open(a ) as in_file:
						SCREAMING_SNAKE_CASE_				:List[Any]				     =						in_file.readlines()
				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						os.path.join(a     , F"{label_name}.jpg" )

				SCREAMING_SNAKE_CASE_				:Dict				     =						[]
				for obj_list in obj_lists:
						SCREAMING_SNAKE_CASE_				:Dict				     =						obj_list.rstrip("\n" ).split(" " )
						SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						float(obj[1] ) - float(obj[3] ) / 2
						SCREAMING_SNAKE_CASE_				:Dict				     =						float(obj[2] ) - float(obj[4] ) / 2
						SCREAMING_SNAKE_CASE_				:List[Any]				     =						float(obj[1] ) + float(obj[3] ) / 2
						SCREAMING_SNAKE_CASE_				:List[str]				     =						float(obj[2] ) + float(obj[4] ) / 2

						boxes.append([int(obj[0] ), xmin, ymin, xmax, ymax] )
				if not boxes:
						continue
				img_paths.append(a )
				labels.append(a )
		return img_paths, labels


def     lowercase	(    a     , a     , a     , a     , a     , a = 0.0     , ):



		'''simple docstring'''




		SCREAMING_SNAKE_CASE_				:int				     =						np.zeros([output_size[0], output_size[1], 3]     , dtype=np.uinta )
		SCREAMING_SNAKE_CASE_				:Tuple				     =						scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
		SCREAMING_SNAKE_CASE_				:List[str]				     =						scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
		SCREAMING_SNAKE_CASE_				:Any				     =						int(scale_x * output_size[1] )
		SCREAMING_SNAKE_CASE_				:List[Any]				     =						int(scale_y * output_size[0] )

		SCREAMING_SNAKE_CASE_				:Any				     =						[]
		SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						[]
		for i, index in enumerate(a ):
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						all_img_list[index]
				path_list.append(a )
				SCREAMING_SNAKE_CASE_				:Tuple				     =						all_annos[index]
				SCREAMING_SNAKE_CASE_				:Any				     =						cva.imread(a )
				if i == 0:  # top-left
						SCREAMING_SNAKE_CASE_				:int				     =						cva.resize(a     , (divid_point_x, divid_point_y) )
						SCREAMING_SNAKE_CASE_				:Any				     =						img
						for bbox in img_annos:
								SCREAMING_SNAKE_CASE_				:Tuple				     =						bbox[1] * scale_x
								SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						bbox[2] * scale_y
								SCREAMING_SNAKE_CASE_				:List[Any]				     =						bbox[3] * scale_x
								SCREAMING_SNAKE_CASE_				:Tuple				     =						bbox[4] * scale_y
								new_anno.append([bbox[0], xmin, ymin, xmax, ymax] )
				elif i == 1:  # top-right
						SCREAMING_SNAKE_CASE_				:Dict				     =						cva.resize(a     , (output_size[1] - divid_point_x, divid_point_y) )
						SCREAMING_SNAKE_CASE_				:Optional[int]				     =						img
						for bbox in img_annos:
								SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						scale_x + bbox[1] * (1 - scale_x)
								SCREAMING_SNAKE_CASE_				:Dict				     =						bbox[2] * scale_y
								SCREAMING_SNAKE_CASE_				:Optional[int]				     =						scale_x + bbox[3] * (1 - scale_x)
								SCREAMING_SNAKE_CASE_				:Tuple				     =						bbox[4] * scale_y
								new_anno.append([bbox[0], xmin, ymin, xmax, ymax] )
				elif i == 2:  # bottom-left
						SCREAMING_SNAKE_CASE_				:List[str]				     =						cva.resize(a     , (divid_point_x, output_size[0] - divid_point_y) )
						SCREAMING_SNAKE_CASE_				:int				     =						img
						for bbox in img_annos:
								SCREAMING_SNAKE_CASE_				:Tuple				     =						bbox[1] * scale_x
								SCREAMING_SNAKE_CASE_				:Dict				     =						scale_y + bbox[2] * (1 - scale_y)
								SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						bbox[3] * scale_x
								SCREAMING_SNAKE_CASE_				:List[str]				     =						scale_y + bbox[4] * (1 - scale_y)
								new_anno.append([bbox[0], xmin, ymin, xmax, ymax] )
				else:  # bottom-right
						SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						cva.resize(
						    a     , (output_size[1] - divid_point_x, output_size[0] - divid_point_y) )
						SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						img
						for bbox in img_annos:
								SCREAMING_SNAKE_CASE_				:Optional[int]				     =						scale_x + bbox[1] * (1 - scale_x)
								SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						scale_y + bbox[2] * (1 - scale_y)
								SCREAMING_SNAKE_CASE_				:Dict				     =						scale_x + bbox[3] * (1 - scale_x)
								SCREAMING_SNAKE_CASE_				:List[Any]				     =						scale_y + bbox[4] * (1 - scale_y)
								new_anno.append([bbox[0], xmin, ymin, xmax, ymax] )

    # Remove bounding box small than scale of filter
		if filter_scale > 0:
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						[
				    anno
				    for anno in new_anno
				    if filter_scale < (anno[3] - anno[1]) and filter_scale < (anno[4] - anno[2])
				]

		return output_img, new_anno, path_list[0]


def     lowercase	(    a ):



		'''simple docstring'''




		assert number_char > 1, "The number of character should greater than 1"
		SCREAMING_SNAKE_CASE_				:Dict				     =						ascii_lowercase + digits
		return "".join(random.choice(a ) for _ in range(a ) )


if __name__ == "__main__":
		main()
		print("DONE ✅")






