





from __future__ import annotations

from typing import Any
class 							snake_case_		:







		def __init__(		self      ,  __lowercase      ,  __lowercase )					-> int:  # noqa: A002
				lowerCamelCase :			List[str]    		=item
				lowerCamelCase :			Tuple    		=next

class 							snake_case_		:







		def __init__(		self )					-> Union[str, Any]:
				lowerCamelCase :			Optional[Any]    		=None
				lowerCamelCase :			Dict    		=0







		def       __lowercase (		self      ,  __lowercase )					-> Dict:
				lowerCamelCase :			List[Any]    		=Node(_lowerCAmelCase      ,  self.head )
				self.size += 1







		def       __lowercase (		self )					-> Optional[Any]:
				# Switched 'self.is_empty()' to 'self.head is None'
				# because mypy was considering the possibility that 'self.head'
				# can be None in below else part and giving error
				if self.head is None:
						return None
				else:
						lowerCamelCase :			List[Any]    		=self.head.item
						lowerCamelCase :			str    		=self.head.next
						self.size -= 1
						return item







		def       __lowercase (		self )					-> Optional[Any]:
				return self.head is None







		def __str__(		self )					-> int:
				if self.is_empty():
						return ""
				else:
						lowerCamelCase :			str    		=self.head
						lowerCamelCase :			List[str]    		=''''''
						lowerCamelCase :			Any    		=[]
						while iterate:
								item_list.append(str(iterate.item ) )
								lowerCamelCase :			Union[str, Any]    		=iterate.next

						lowerCamelCase :			Optional[int]    		=''' --> '''.join(_lowerCAmelCase )

						return item_str







		def __len__(		self )					-> Optional[int]:
				return self.size







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 							lowerCamelCase    (							UpperCAmelCase_	:      Union[str, Any]=None   ,       UpperCAmelCase_	:      Union[str, Any]=None      )->			Tuple:

       """simple docstring"""




       return field(default_factory=lambda: default   ,       metadata=UpperCAmelCase_      )


@dataclass
class        UpperCAmelCase__				:



     '''simple docstring'''
     _SCREAMING_SNAKE_CASE      :					str     					=    field(
         metadata={"help": "The csv file to plot."}      ,		)
     _SCREAMING_SNAKE_CASE      :					bool     					=    field(
         default=UpperCAmelCase__      ,		metadata={"help": "Whether to plot along batch size or sequence length. Defaults to sequence length."}      ,		)
     _SCREAMING_SNAKE_CASE      :					bool     					=    field(
         default=UpperCAmelCase__      ,		metadata={"help": "Whether the csv file has time results or memory results. Defaults to memory results."}      ,		)
     _SCREAMING_SNAKE_CASE      :					bool     					=    field(
         default=UpperCAmelCase__      ,		metadata={"help": "Disable logarithmic scale when plotting"}      ,		)
     _SCREAMING_SNAKE_CASE      :					bool     					=    field(
         default=UpperCAmelCase__      ,		metadata={
             "help": "Whether the csv file has training results or inference results. Defaults to inference results."
         }      ,		)
     _SCREAMING_SNAKE_CASE      :					Optional[str]     					=    field(
         default=UpperCAmelCase__      ,		metadata={"help": "Filename under which the plot will be saved. If unused no plot is saved."}      ,		)
     _SCREAMING_SNAKE_CASE      :					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 							lowerCamelCase    (							UpperCAmelCase_	:      Dict      )->			int:

       """simple docstring"""




       try:
              int(UpperCAmelCase_      )
              return True
       except ValueError:
              return False





def 							lowerCamelCase    (							UpperCAmelCase_	:      List[str]      )->			str:

       """simple docstring"""




       try:
              float(UpperCAmelCase_      )
              return True
       except ValueError:
              return False


class        UpperCAmelCase__				:



     '''simple docstring'''
     def __init__(				self ,    _lowerCAmelCase	):
            a			   =args
            a			   =defaultdict(lambda: {"bsz": [], "seq_len": [], "result": {}}	)

            with open(self.args.csv_file ,    newline=""""""	) as csv_file:
                   a			   =csv.DictReader(_lowerCAmelCase	)
                   for row in reader:
                          a			   =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
                                 a			   =int(row["""result"""]	)
                          elif can_convert_to_float(row["""result"""]	):
                                 # value is not None
                                 a			   =float(row["""result"""]	)






     def        lowerCAmelCase__  (				self	):
            a   ,      a			   =plt.subplots()
            a			   ="""Time usage""" if self.args.is_time else """Memory usage"""
            a			   =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()	):
                   a			   =sorted(set(self.result_dict[model_name]["""bsz"""]	)	)
                   a			   =sorted(set(self.result_dict[model_name]["""seq_len"""]	)	)
                   a			   =self.result_dict[model_name]["""result"""]

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

                   a			   =(
                       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:
                                 a			   =np.asarray(
                                     [results[(x, inner_loop_value)] for x in x_axis_array if (x, inner_loop_value) in results] ,    dtype=_lowerCAmelCase ,    )
                          else:
                                 a			   =np.asarray(
                                     [results[(inner_loop_value, x)] for x in x_axis_array if (inner_loop_value, x) in results] ,    dtype=np.floataa ,    )

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

                          a			   =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.'''

            a			   =title_str[:-4]
            a			   ="""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 							lowerCamelCase    (							)->			Optional[Any]:

       """simple docstring"""




       a			   =HfArgumentParser(UpperCAmelCase_      )
       a			   =parser.parse_args_into_dataclasses()[0]
       a			   =Plot(args=UpperCAmelCase_      )
       plot.plot()


if __name__ == "__main__":
    main()
