'''simple docstring'''

import importlib
import inspect
from functools import wraps
from typing import TYPE_CHECKING, Optional, Union

from .download.streaming_download_manager import (
    xbasename,
    xdirname,
    xet_parse,
    xexists,
    xgetsize,
    xglob,
    xgzip_open,
    xisdir,
    xisfile,
    xjoin,
    xlistdir,
    xnumpy_load,
    xopen,
    xpandas_read_csv,
    xpandas_read_excel,
    xPath,
    xrelpath,
    xsio_loadmat,
    xsplit,
    xsplitext,
    xwalk,
    xxml_dom_minidom_parse,
)
from .utils.logging import get_logger
from .utils.patching import patch_submodule
from .utils.py_utils import get_imports


lowerCAmelCase_			:			int    	=   get_logger(__name__)


if TYPE_CHECKING:
       from .builder import DatasetBuilder


def __a			(						__lowerCamelCase      :    Tuple			,		__lowerCamelCase      :    Optional[Union[str, bool]] = None					)						->				List[Any]:
      '''simple docstring'''


      lowercase_     			=   importlib.import_module(__lowerCamelCase					)

      # TODO(QL): always update the module to add subsequent new authentication
      if hasattr(__lowerCamelCase			,		"_patched_for_streaming"					) and module._patched_for_streaming:
            return

      def wrap_auth(__lowerCamelCase      :    Tuple					):
            @wraps(__lowerCamelCase					)
            def wrapper(*__lowerCamelCase      :    List[Any]			,		**__lowerCamelCase      :    Dict					):
                  return function(*__lowerCamelCase			,		use_auth_token=__lowerCamelCase			,		**__lowerCamelCase					)

            lowercase_     			=   "wrap_auth"
            return wrapper

      # open files in a streaming fashion
      patch_submodule(__lowerCamelCase			,		"open"			,		wrap_auth(__lowerCamelCase					)					).start()
      patch_submodule(__lowerCamelCase			,		"os.listdir"			,		wrap_auth(__lowerCamelCase					)					).start()
      patch_submodule(__lowerCamelCase			,		"os.walk"			,		wrap_auth(__lowerCamelCase					)					).start()
      patch_submodule(__lowerCamelCase			,		"glob.glob"			,		wrap_auth(__lowerCamelCase					)					).start()
      # allow to navigate in remote zip files
      patch_submodule(__lowerCamelCase			,		"os.path.join"			,		__lowerCamelCase					).start()
      patch_submodule(__lowerCamelCase			,		"os.path.dirname"			,		__lowerCamelCase					).start()
      patch_submodule(__lowerCamelCase			,		"os.path.basename"			,		__lowerCamelCase					).start()
      patch_submodule(__lowerCamelCase			,		"os.path.relpath"			,		__lowerCamelCase					).start()
      patch_submodule(__lowerCamelCase			,		"os.path.split"			,		__lowerCamelCase					).start()
      patch_submodule(__lowerCamelCase			,		"os.path.splitext"			,		__lowerCamelCase					).start()
      # allow checks on paths
      patch_submodule(__lowerCamelCase			,		"os.path.exists"			,		wrap_auth(__lowerCamelCase					)					).start()
      patch_submodule(__lowerCamelCase			,		"os.path.isdir"			,		wrap_auth(__lowerCamelCase					)					).start()
      patch_submodule(__lowerCamelCase			,		"os.path.isfile"			,		wrap_auth(__lowerCamelCase					)					).start()
      patch_submodule(__lowerCamelCase			,		"os.path.getsize"			,		wrap_auth(__lowerCamelCase					)					).start()
      patch_submodule(__lowerCamelCase			,		"pathlib.Path"			,		__lowerCamelCase					).start()
      # file readers
      patch_submodule(__lowerCamelCase			,		"gzip.open"			,		wrap_auth(__lowerCamelCase					)					).start()
      patch_submodule(__lowerCamelCase			,		"numpy.load"			,		wrap_auth(__lowerCamelCase					)					).start()
      patch_submodule(__lowerCamelCase			,		"pandas.read_csv"			,		wrap_auth(__lowerCamelCase					)			,		attrs=["__version__"]					).start()
      patch_submodule(__lowerCamelCase			,		"pandas.read_excel"			,		wrap_auth(__lowerCamelCase					)			,		attrs=["__version__"]					).start()
      patch_submodule(__lowerCamelCase			,		"scipy.io.loadmat"			,		wrap_auth(__lowerCamelCase					)			,		attrs=["__version__"]					).start()
      patch_submodule(__lowerCamelCase			,		"xml.etree.ElementTree.parse"			,		wrap_auth(__lowerCamelCase					)					).start()
      patch_submodule(__lowerCamelCase			,		"xml.dom.minidom.parse"			,		wrap_auth(__lowerCamelCase					)					).start()
      lowercase_     			=   True






def __a			(						__lowerCamelCase      :    "DatasetBuilder"					)						->				Any:
      '''simple docstring'''


      extend_module_for_streaming(builder.__module__			,		use_auth_token=builder.use_auth_token					)
      # if needed, we also have to extend additional internal imports (like wmt14 -> wmt_utils)
      if not builder.__module__.startswith("datasets."					):  # check that it's not a packaged builder like csv
            for imports in get_imports(inspect.getfile(builder.__class__					)					):
                  if imports[0] == "internal":
                        lowercase_     			=   imports[1]
                        lowercase_     			=   ".".join(builder.__module__.split("."					)[:-1] + [internal_import_name]					)
                        extend_module_for_streaming(__lowerCamelCase			,		use_auth_token=builder.use_auth_token					)

    # builders can inherit from other builders that might use streaming functionality
    # (for example, ImageFolder and AudioFolder inherit from FolderBuilder which implements examples generation)
    # but these parents builders are not patched automatically as they are not instantiated, so we patch them here
      from .builder import DatasetBuilder

      lowercase_     			=   [
          cls.__module__
          for cls in type(__lowerCamelCase					).__mro__[1:]  # make sure it's not the same module we've already patched
          if issubclass(cls			,		__lowerCamelCase					) and cls.__module__ != DatasetBuilder.__module__
      ]  # check it's not a standard builder from datasets.builder
      for module in parent_builder_modules:
            extend_module_for_streaming(__lowerCamelCase			,		use_auth_token=builder.use_auth_token					)







'''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			(						__lowerCamelCase      :    Optional[Any]=None			,		__lowerCamelCase      :    List[str]=None					)						->				Any:
      '''simple docstring'''


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





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




def __a			(						__lowerCamelCase      :    int					)						->				Tuple:
      '''simple docstring'''


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


def __a			(						__lowerCamelCase      :    Union[str, Any]					)						->				str:
      '''simple docstring'''


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





class 				lowercase    :


   def __init__( self					:						Dict ,		__lowerCAmelCase					:						Tuple)   ->       Dict:
         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 __UpperCAmelCase							( self					:						Optional[int])   ->       Tuple:
         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			(						)						->				Tuple:
      '''simple docstring'''


      lowercase_     			=   HfArgumentParser(__lowerCamelCase					)
      lowercase_     			=   parser.parse_args_into_dataclasses()[0]
      lowercase_     			=   Plot(args=__lowerCamelCase					)
      plot.plot()


if __name__ == "__main__":
       main()






