
'''simple docstring'''



import enum
import inspect
import warnings
from functools import wraps
from typing import Callable, Optional

from .logging import get_logger


__A          =    set()
__A          =    get_logger(__name__)





def  _A		(							lowercase__ = None	):

						'''simple docstring'''





						def decorator(lowercase__	):
												global _emitted_deprecation_warnings

												if inspect.isclass(lowercase__	):
																		lowercase__							 =       deprecated_class_or_function.__init__
																		lowercase__							 =       deprecated_class_or_function.__name__
												else:
																		lowercase__							 =       deprecated_class_or_function
																		lowercase__							 =       deprecated_function.__name__
																		# Support deprecating __init__ class method: class name instead
																		lowercase__							 =       name if name != '''__init__''' else deprecated_function.__qualname__.split("""."""	)[-2]

												lowercase__							 =       (
												    f'''{name} is deprecated and will be removed in the next major version of datasets.''' + f''' {help_message}'''
												    if help_message
												    else ''''''
												)

												@wraps(lowercase__	)
												def wrapper(*lowercase__		,		**lowercase__	):
																		lowercase__							 =       hash(lowercase__	)
																		if func_hash not in _emitted_deprecation_warnings:
																								warnings.warn(lowercase__		,		category=lowercase__		,		stacklevel=2	)
																								_emitted_deprecation_warnings.add(lowercase__	)
																		return deprecated_function(*lowercase__		,		**lowercase__	)

												lowercase__							 =       '''deprecated'''

												if inspect.isclass(lowercase__	):
																		lowercase__							 =       wrapper
																		return deprecated_class_or_function
												else:
																		return wrapper

						return decorator





class 			A							(       enum.EnumMeta				):



			def __getattribute__(					cls       ,     lowerCamelCase__       )			->		Tuple:




									'''simple docstring'''



									lowercase__							 =       super().__getattribute__(_snake_case       )
									if isinstance(_snake_case       ,     enum.Enum       ) and obj._on_access:
															obj._on_access()
									return obj



			def __getitem__(					cls       ,     lowerCamelCase__       )			->		Optional[Any]:




									'''simple docstring'''



									lowercase__							 =       super().__getitem__(_snake_case       )
									if member._on_access:
															member._on_access()
									return member



			def __call__(					cls       ,     lowerCamelCase__       ,     lowerCamelCase__=None       ,     *, lowerCamelCase__=None       ,     lowerCamelCase__=None       ,     lowerCamelCase__=None       ,     lowerCamelCase__=1       )			->		str:




									'''simple docstring'''



									lowercase__							 =       super().__call__(_snake_case       ,     _snake_case       ,     module=_snake_case       ,     qualname=_snake_case       ,     type=_snake_case       ,     start=_snake_case       )
									if isinstance(_snake_case       ,     enum.Enum       ) and obj._on_access:
															obj._on_access()
									return obj





class 			A							(       enum.Enum		,						metaclass=a_				):



			def __new__(					cls       ,     lowerCamelCase__       )			->		List[Any]:




									'''simple docstring'''



									lowercase__							 =       object.__new__(cls       )
									lowercase__							 =       value
									lowercase__							 =       member.deprecate
									return member



			@property
			def A__ (					self       )			->		Optional[Any]:




									'''simple docstring'''



									return ""



			def A__ (					self       )			->		List[Any]:




									'''simple docstring'''



									lowercase__							 =       F''' {self.help_message}''' if self.help_message else ''''''
									warnings.warn(
									    F'''\'{self.__objclass__.__name__}\' is deprecated and will be removed in the next major version of datasets.'''
									    + help_message       ,     _snake_case       ,     stacklevel=3       ,     )








'''simple docstring'''



import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter

from transformers import HfArgumentParser





def  _A		(							lowercase__=None		,		lowercase__=None	):
						return field(default_factory=lambda: default		,		metadata=lowercase__	)





@dataclass
class 			A							:
			lowerCamelCase							:							str       		=  field(
			    metadata={"""help""": """The csv file to plot."""}		,						)
			lowerCamelCase							:							bool       		=  field(
			    default=__UpperCAmelCase		,						metadata={"""help""": """Whether to plot along batch size or sequence length. Defaults to sequence length."""}		,						)
			lowerCamelCase							:							bool       		=  field(
			    default=__UpperCAmelCase		,						metadata={"""help""": """Whether the csv file has time results or memory results. Defaults to memory results."""}		,						)
			lowerCamelCase							:							bool       		=  field(
			    default=__UpperCAmelCase		,						metadata={"""help""": """Disable logarithmic scale when plotting"""}		,						)
			lowerCamelCase							:							bool       		=  field(
			    default=__UpperCAmelCase		,						metadata={
			        """help""": """Whether the csv file has training results or inference results. Defaults to inference results."""
			    }		,						)
			lowerCamelCase							:							Optional[str]       		=  field(
			    default=__UpperCAmelCase		,						metadata={"""help""": """Filename under which the plot will be saved. If unused no plot is saved."""}		,						)
			lowerCamelCase							:							Optional[List[str]]       		=  list_field(
			    default=__UpperCAmelCase		,						metadata={"""help""": """List of model names that are used instead of the ones in the csv file."""}				)





def  _A		(							lowercase__	):
						try:
												int(lowercase__	)
												return True
						except ValueError:
												return False





def  _A		(							lowercase__	):
						try:
												float(lowercase__	)
												return True
						except ValueError:
												return False





class 			A							:



			def __init__(					self       ,     lowerCamelCase__       )			->		int:




									'''simple docstring'''



									lowercase__							 =       args
									lowercase__							 =       defaultdict(lambda: {"bsz": [], "seq_len": [], "result": {}}       )

									with open(self.args.csv_file       ,     newline=""""""       ) as csv_file:
															lowercase__							 =       csv.DictReader(lowerCamelCase__       )
															for row in reader:
																					lowercase__							 =       row["""model"""]
																					self.result_dict[model_name]["bsz"].append(int(row["""batch_size"""]       )       )
																					self.result_dict[model_name]["seq_len"].append(int(row["""sequence_length"""]       )       )
																					if can_convert_to_int(row["""result"""]       ):
																											# value is not None
																											lowercase__							 =       int(row["""result"""]       )
																					elif can_convert_to_float(row["""result"""]       ):
																											# value is not None
																											lowercase__							 =       float(row["""result"""]       )



			def A__ (					self       )			->		Tuple:




									'''simple docstring'''



									lowercase__ ,						lowercase__							 =       plt.subplots()
									lowercase__							 =       """Time usage""" if self.args.is_time else """Memory usage"""
									lowercase__							 =       title_str + """ for training""" if self.args.is_train else title_str + """ for inference"""

									if not self.args.no_log_scale:
															# set logarithm scales
															ax.set_xscale("""log"""       )
															ax.set_yscale("""log"""       )

									for axis in [ax.xaxis, ax.yaxis]:
															axis.set_major_formatter(ScalarFormatter()       )

									for model_name_idx, model_name in enumerate(self.result_dict.keys()       ):
															lowercase__							 =       sorted(set(self.result_dict[model_name]["""bsz"""]       )       )
															lowercase__							 =       sorted(set(self.result_dict[model_name]["""seq_len"""]       )       )
															lowercase__							 =       self.result_dict[model_name]["""result"""]

															((lowercase__) ,						(lowercase__))							 =       (
															    (batch_sizes, sequence_lengths) if self.args.plot_along_batch else (sequence_lengths, batch_sizes)
															)

															lowercase__							 =       (
															    model_name if self.args.short_model_names is None else self.args.short_model_names[model_name_idx]
															)

															for inner_loop_value in inner_loop_array:
																					if self.args.plot_along_batch:
																											lowercase__							 =       np.asarray(
																											    [results[(x, inner_loop_value)] for x in x_axis_array if (x, inner_loop_value) in results]       ,     dtype=lowerCamelCase__       ,     )
																					else:
																											lowercase__							 =       np.asarray(
																											    [results[(inner_loop_value, x)] for x in x_axis_array if (inner_loop_value, x) in results]       ,     dtype=np.floataa       ,     )

																					((lowercase__) ,						(lowercase__))							 =       (
																					    ("""batch_size""", """len""") if self.args.plot_along_batch else ("""in #tokens""", """bsz""")
																					)

																					lowercase__							 =       np.asarray(lowerCamelCase__       ,     lowerCamelCase__       )[: len(lowerCamelCase__       )]
																					plt.scatter(
																					    lowerCamelCase__       ,     lowerCamelCase__       ,     label=F'''{label_model_name} - {inner_loop_label}: {inner_loop_value}'''       )
																					plt.plot(lowerCamelCase__       ,     lowerCamelCase__       ,     """--"""       )

															title_str += F''' {label_model_name} vs.'''

									lowercase__							 =       title_str[:-4]
									lowercase__							 =       """Time in s""" if self.args.is_time else """Memory in MB"""

									# plot
									plt.title(lowerCamelCase__       )
									plt.xlabel(lowerCamelCase__       )
									plt.ylabel(lowerCamelCase__       )
									plt.legend()

									if self.args.figure_png_file is not None:
															plt.savefig(self.args.figure_png_file       )
									else:
															plt.show()





def  _A		(							):
						lowercase__							 =       HfArgumentParser(lowercase__	)
						lowercase__							 =       parser.parse_args_into_dataclasses()[0]
						lowercase__							 =       Plot(args=lowercase__	)
						plot.plot()


if __name__ == "__main__":
				main()






