






'''simple docstring'''





import argparse
import datetime
import io
import itertools
import json
import math
import os
import platform
import re
import shlex
import subprocess
import sys
from pathlib import Path
from statistics import fmean

import pandas as pd
import torch
from tqdm import tqdm

import transformers


lowercase  :							str			  =    float('''nan''')




class 		UpperCAmelCase_						:


						'''simple docstring'''




						def __init__(	self		,				_SCREAMING_SNAKE_CASE				) ->				Union[str, Any]:
								snake_case_				:							List[str]						 =       sys.stdout
								snake_case_				:							Any						 =       open(UpperCAmelCase__		,				"a"				)






						def __getattr__(	self		,				_SCREAMING_SNAKE_CASE				) ->				Tuple:
								return getattr(self.stdout		,				UpperCAmelCase__				)






						def       _lowerCAmelCase       (	self		,				_SCREAMING_SNAKE_CASE				) ->				Union[str, Any]:
								self.stdout.write(UpperCAmelCase__				)
								# strip tqdm codes
								self.file.write(re.sub(r"^.*\r"		,				""		,				UpperCAmelCase__		,				0		,				re.M				)				)




def      lowerCAmelCase__	(    _a       :			List[str]=80  ,      _a       :			Dict=False    ):
		snake_case_				:							List[str]						 =       []

		# deal with critical env vars
		snake_case_				:							Optional[Any]						 =       ["CUDA_VISIBLE_DEVICES"]
		for key in env_keys:
				snake_case_				:							int						 =       os.environ.get(_UpperCamelCase  ,      _UpperCamelCase    )
				if val is not None:
						cmd.append(F'''{key}={val}'''    )

    # python executable (not always needed if the script is executable)
		snake_case_				:							Union[str, Any]						 =       sys.executable if full_python_path else sys.executable.split("/"    )[-1]
		cmd.append(_UpperCamelCase    )

		# now the normal args
		cmd += list(map(shlex.quote  ,      sys.argv    )    )

		# split up into up to MAX_WIDTH lines with shell multi-line escapes
		snake_case_				:							Optional[int]						 =       []
		snake_case_				:							List[str]						 =       ""
		while len(_UpperCamelCase    ) > 0:
				current_line += F'''{cmd.pop(0    )} '''
				if len(_UpperCamelCase    ) == 0 or len(_UpperCamelCase    ) + len(cmd[0]    ) + 1 > max_width - 1:
						lines.append(_UpperCamelCase    )
						snake_case_				:							Optional[int]						 =       ""
		return "\\\n".join(_UpperCamelCase    )

def      lowerCAmelCase__	(    _a       :			Dict  ,      _a       :			int    ):
		snake_case_				:							str						 =       re.sub(R"[\\\n]+"  ,      " "  ,      args.base_cmd    )

		# remove --output_dir if any and set our own
		snake_case_				:							Any						 =       re.sub("--output_dir\s+[^\s]+"  ,      ""  ,      args.base_cmd    )
		args.base_cmd += F''' --output_dir {output_dir}'''

		# ensure we have --overwrite_output_dir
		snake_case_				:							Union[str, Any]						 =       re.sub("--overwrite_output_dir\s+"  ,      ""  ,      args.base_cmd    )
		args.base_cmd += " --overwrite_output_dir"

		return [sys.executable] + shlex.split(args.base_cmd    )

def      lowerCAmelCase__	(    _a       :			Dict  ,      _a       :			Optional[int]  ,      _a       :			Optional[int]  ,      _a       :			List[str]  ,      _a       :			Tuple  ,      _a       :			List[str]  ,      _a       :			int    ):


		if 0:
				import random
				from time import sleep

				sleep(0    )
				return dict(
				    {k: random.uniform(0  ,      1_00    ) for k in metric_keys}  ,      **{target_metric_key: random.choice([nan, 10.31, 100.2, 55.6_666, 222.22_222_222]    )}  ,      )

		snake_case_				:							str						 =       subprocess.run(_UpperCamelCase  ,      capture_output=_UpperCamelCase  ,      text=_UpperCamelCase    )

		if verbose:
				print("STDOUT"  ,      result.stdout    )
				print("STDERR"  ,      result.stderr    )

		# save the streams
		snake_case_				:							int						 =       variation.replace(" "  ,      "-"    )
		with open(Path(_UpperCamelCase    ) / F'''log.{prefix}.stdout.txt'''  ,      "w"    ) as f:
				f.write(result.stdout    )
		with open(Path(_UpperCamelCase    ) / F'''log.{prefix}.stderr.txt'''  ,      "w"    ) as f:
				f.write(result.stderr    )

		if result.returncode != 0:
				if verbose:
						print("failed"    )
				return {target_metric_key: nan}

		with io.open(F'''{output_dir}/all_results.json'''  ,      "r"  ,      encoding="utf-8"    ) as f:
				snake_case_				:							List[str]						 =       json.load(_UpperCamelCase    )

		# filter out just the keys we want
		return {k: v for k, v in metrics.items() if k in metric_keys}

def      lowerCAmelCase__	(    _a       :			str  ,      _a       :			Optional[Any]  ,      _a       :			Optional[int]  ,      _a       :			Optional[Any]  ,      _a       :			Optional[int]  ,      _a       :			Any  ,      _a       :			Dict  ,      _a       :			Optional[int]  ,      _a       :			List[str]  ,      _a       :			Dict  ,      ):
		snake_case_				:							Optional[Any]						 =       []
		snake_case_				:							Optional[Any]						 =       []
		snake_case_				:							Dict						 =       F'''{id}: {variation:<{longest_variation_len}}'''
		snake_case_				:							List[str]						 =       F'''{preamble}: '''
		snake_case_				:							Optional[Any]						 =       set(report_metric_keys + [target_metric_key]    )
		for i in tqdm(range(_UpperCamelCase    )  ,      desc=_UpperCamelCase  ,      leave=_UpperCamelCase    ):
				snake_case_				:							List[Any]						 =       process_run_single(
				    _UpperCamelCase  ,      _UpperCamelCase  ,      _UpperCamelCase  ,      _UpperCamelCase  ,      _UpperCamelCase  ,      _UpperCamelCase  ,      _UpperCamelCase    )
				snake_case_				:							Union[str, Any]						 =       single_run_metrics[target_metric_key]
				if not math.isnan(_UpperCamelCase    ):
						metrics.append(_UpperCamelCase    )
						results.append(_UpperCamelCase    )
						outcome += "✓"
				else:
						outcome += "✘"
		snake_case_				:							Optional[Any]						 =       F'''\33[2K\r{outcome}'''
		if len(_UpperCamelCase    ) > 0:
				snake_case_				:							Union[str, Any]						 =       {k: fmean([x[k] for x in metrics]    ) for k in metrics[0].keys()}
				snake_case_				:							Union[str, Any]						 =       round(mean_metrics[target_metric_key]  ,      2    )
				snake_case_				:							str						 =       F'''{outcome} {mean_target}'''
				if len(_UpperCamelCase    ) > 1:
						results_str += F''' {tuple(round(_UpperCamelCase  ,      2    ) for x in results    )}'''
				print(_UpperCamelCase    )
				snake_case_				:							List[str]						 =       variation
				return mean_metrics
		else:
				print(_UpperCamelCase    )
				return {variation_key: variation, target_metric_key: nan}

def      lowerCAmelCase__	(    ):
		snake_case_				:							Optional[int]						 =       torch.cuda.get_device_properties(torch.device("cuda"    )    )
		return F'''
Datetime    : {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'    )}

Software:
transformers: {transformers.__version__}
torch       : {torch.__version__}
cuda        : {torch.version.cuda}
python      : {platform.python_version()}

Hardware:
{torch.cuda.device_count()} GPUs      : {properties.name}, {properties.total_memory/2**30:0.2f}GB
'''

def      lowerCAmelCase__	(    _a       :			Tuple  ,      _a       :			Tuple  ,      _a       :			Dict  ,      _a       :			Optional[Any]  ,      _a       :			Dict    ):
		snake_case_				:							Optional[int]						 =       pd.DataFrame(_UpperCamelCase    )
		snake_case_				:							Tuple						 =       "variation"
		snake_case_				:							int						 =       "diff_%"

		snake_case_				:							Optional[Any]						 =       nan
		if base_variation is not None and len(df[df[variation_key] == base_variation]    ):
				# this may still return nan
				snake_case_				:							Optional[Any]						 =       df.loc[df[variation_key] == base_variation][target_metric_key].item()
		if math.isnan(_UpperCamelCase    ):
				# as a fallback, use the minimal value as the sentinel
				snake_case_				:							Optional[int]						 =       df.loc[df[target_metric_key] != nan][target_metric_key].min()

		# create diff column if possible
		if not math.isnan(_UpperCamelCase    ):
				snake_case_				:							Dict						 =       df.apply(
				    lambda _a    : round(1_00 * (r[target_metric_key] - sentinel_value) / sentinel_value    )
				    if not math.isnan(r[target_metric_key]    )
				    else 0  ,      axis="columns"  ,      )

		# re-order columns
		snake_case_				:							List[Any]						 =       [variation_key, target_metric_key, diff_key, *report_metric_keys]
		snake_case_				:							str						 =       df.reindex(_UpperCamelCase  ,      axis="columns"    )  # reorder cols

		# capitalize
		snake_case_				:							List[Any]						 =       df.rename(str.capitalize  ,      axis="columns"    )

		# make the cols as narrow as possible
		snake_case_				:							List[str]						 =       df.rename(lambda _a    : c.replace("_"  ,      "<br>"    )  ,      axis="columns"    )
		snake_case_				:							List[str]						 =       df.rename(lambda _a    : c.replace("_"  ,      "\n"    )  ,      axis="columns"    )

		snake_case_				:							Union[str, Any]						 =       ["", "Copy between the cut-here-lines and paste as is to github or a forum"]
		report += ["----------8<-----------------8<--------"]
		report += ["*** Results:", df_github.to_markdown(index=_UpperCamelCase  ,      floatfmt=".2f"    )]
		report += ["```"]
		report += ["*** Setup:", get_versions()]
		report += ["*** The benchmark command line was:", get_original_command()]
		report += ["```"]
		report += ["----------8<-----------------8<--------"]
		report += ["*** Results (console):", df_console.to_markdown(index=_UpperCamelCase  ,      floatfmt=".2f"    )]

		print("\n\n".join(_UpperCamelCase    )    )

def      lowerCAmelCase__	(    ):
		snake_case_				:							Optional[int]						 =       argparse.ArgumentParser()
		parser.add_argument(
		    "--base-cmd"  ,      default=_UpperCamelCase  ,      type=_UpperCamelCase  ,      required=_UpperCamelCase  ,      help="Base cmd"  ,      )
		parser.add_argument(
		    "--variations"  ,      default=_UpperCamelCase  ,      type=_UpperCamelCase  ,      nargs="+"  ,      required=_UpperCamelCase  ,      help="Multi-dimensional variations, example: \'|--fp16|--bf16\' \'|--tf32\'"  ,      )
		parser.add_argument(
		    "--base-variation"  ,      default=_UpperCamelCase  ,      type=_UpperCamelCase  ,      help="Baseline variation to compare to. if None the minimal target value will be used to compare against"  ,      )
		parser.add_argument(
		    "--target-metric-key"  ,      default=_UpperCamelCase  ,      type=_UpperCamelCase  ,      required=_UpperCamelCase  ,      help="Target metric key in output_dir/all_results.json, e.g., train_samples_per_second"  ,      )
		parser.add_argument(
		    "--report-metric-keys"  ,      default=""  ,      type=_UpperCamelCase  ,      help="Report metric keys - other metric keys from output_dir/all_results.json to report, e.g., train_loss. Use a single argument e.g., \'train_loss train_samples"  ,      )
		parser.add_argument(
		    "--repeat-times"  ,      default=1  ,      type=_UpperCamelCase  ,      help="How many times to re-run each variation - an average will be reported"  ,      )
		parser.add_argument(
		    "--output_dir"  ,      default="output_benchmark"  ,      type=_UpperCamelCase  ,      help="The output directory where all the benchmark reports will go to and additionally this directory will be used to override --output_dir in the script that is being benchmarked"  ,      )
		parser.add_argument(
		    "--verbose"  ,      default=_UpperCamelCase  ,      action="store_true"  ,      help="Whether to show the outputs of each run or just the benchmark progress"  ,      )
		snake_case_				:							Union[str, Any]						 =       parser.parse_args()

		snake_case_				:							List[Any]						 =       args.output_dir
		Path(_UpperCamelCase    ).mkdir(exist_ok=_UpperCamelCase    )
		snake_case_				:							List[Any]						 =       get_base_command(_UpperCamelCase  ,      _UpperCamelCase    )

		# split each dimension into its --foo variations
		snake_case_				:							str						 =       [list(map(str.strip  ,      re.split(R"\|"  ,      _UpperCamelCase    )    )    ) for x in args.variations]
		# build a cartesian product of dimensions and convert those back into cmd-line arg strings,
		# while stripping white space for inputs that were empty
		snake_case_				:							List[str]						 =       list(map(str.strip  ,      map(" ".join  ,      itertools.product(*_UpperCamelCase    )    )    )    )
		snake_case_				:							Optional[int]						 =       max(len(_UpperCamelCase    ) for x in variations    )

		# split wanted keys
		snake_case_				:							Union[str, Any]						 =       args.report_metric_keys.split()

		# capture prints into a log file for convenience
		snake_case_				:							Tuple						 =       F'''benchmark-report-{datetime.datetime.now().strftime('%Y-%m-%d-%H-%M-%S'    )}.txt'''
		print(F'''\nNote: each run\'s output is also logged under {output_dir}/log.*.std*.txt'''    )
		print(F'''and this script\'s output is also piped into {report_fn}'''    )

		snake_case_				:							int						 =       Tee(_UpperCamelCase    )

		print(F'''\n*** Running {len(_UpperCamelCase    )} benchmarks:'''    )
		print(F'''Base command: {' '.join(_UpperCamelCase    )}'''    )

		snake_case_				:							Any						 =       "variation"
		snake_case_				:							str						 =       []
		for id, variation in enumerate(tqdm(_UpperCamelCase  ,      desc="Total completion: "  ,      leave=_UpperCamelCase    )    ):
				snake_case_				:							Tuple						 =       base_cmd + variation.split()
				results.append(
				    process_run(
				        id + 1  ,      _UpperCamelCase  ,      _UpperCamelCase  ,      _UpperCamelCase  ,      _UpperCamelCase  ,      args.target_metric_key  ,      _UpperCamelCase  ,      args.repeat_times  ,      _UpperCamelCase  ,      args.verbose  ,      )    )

		process_results(_UpperCamelCase  ,      args.target_metric_key  ,      _UpperCamelCase  ,      args.base_variation  ,      _UpperCamelCase    )


if __name__ == "__main__":
							main()








def      lowerCAmelCase__	(    _a       :			str  ,      _a       :			int    ):
		# "extended trapezoidal rule"
		# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
		snake_case_				:							Optional[Any]						 =       (boundary[1] - boundary[0]) / steps
		snake_case_				:							str						 =       boundary[0]
		snake_case_				:							Dict						 =       boundary[1]
		snake_case_				:							str						 =       make_points(_a  ,      _a  ,      _a    )
		snake_case_				:							str						 =       0.0
		y += (h / 2.0) * f(_a    )
		for i in x_i:
				# print(i)
				y += h * f(_a    )
		y += (h / 2.0) * f(_a    )
		return y

def      lowerCAmelCase__	(    _a       :			str  ,      _a       :			Optional[Any]  ,      _a       :			Tuple    ):
		snake_case_				:							Tuple						 =       a + h
		while x < (b - h):
				yield x
				snake_case_				:							List[str]						 =       x + h

def      lowerCAmelCase__	(    _a       :			Tuple    ):  # enter your function here
		snake_case_				:							Tuple						 =       (x - 0) * (x - 0)
		return y

def      lowerCAmelCase__	(    ):
		snake_case_				:							Union[str, Any]						 =       0.0  # Lower bound of integration
		snake_case_				:							List[Any]						 =       1.0  # Upper bound of integration
		snake_case_				:							Tuple						 =       10.0  # define number of steps or resolution
		snake_case_				:							List[Any]						 =       [a, b]  # define boundary of integration
		snake_case_				:							Any						 =       method_a(_a  ,      _a    )
		print(F'''y = {y}'''    )


if __name__ == "__main__":
							main()
