





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        _lowercase   (  _UpperCAmelCase=None     , _UpperCAmelCase=None			)  ->					Any:
    return field(default_factory=lambda: default     , metadata=SCREAMING_SNAKE_CASE__			)

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





def        _lowercase   (  _UpperCAmelCase			)  ->					Any:


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





def        _lowercase   (  _UpperCAmelCase			)  ->					Any:


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

class  __A       :


    def __init__(						self				,	UpperCAmelCase_							):
        lowerCamelCase			=args
        lowerCamelCase			=defaultdict(lambda: {"bsz": [], "seq_len": [], "result": {}}							)

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


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

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

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

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

                lowerCamelCase			=np.asarray(UpperCamelCase__				,	UpperCamelCase__							)[: len(UpperCamelCase__							)]
                plt.scatter(
                    UpperCamelCase__				,	UpperCamelCase__				,	label=f"""{label_model_name} - {inner_loop_label}: {inner_loop_value}"""							)
                plt.plot(UpperCamelCase__				,	UpperCamelCase__				,	"""--"""							)

            title_str += f""" {label_model_name} vs."""

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

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

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





def        _lowercase   (  )  ->					List[str]:
    lowerCamelCase			=HfArgumentParser(SCREAMING_SNAKE_CASE__			)
    lowerCamelCase			=parser.parse_args_into_dataclasses()[0]
    lowerCamelCase			=Plot(args=SCREAMING_SNAKE_CASE__			)
    plot.plot()


if __name__ == "__main__":
       main()












import pytest
import requests

from datasets.utils.file_utils import http_head

from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline





@pytest.mark.integration
def        _lowercase   (  )  ->					str:
				with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT			):
								with pytest.raises(_UpperCAmelCase			):
												requests.request("""GET"""     , """https://huggingface.co"""			)
								with pytest.raises(requests.exceptions.ConnectTimeout			):
												requests.request("""GET"""     , """https://huggingface.co"""     , timeout=1.0			)





@pytest.mark.integration
def        _lowercase   (  )  ->					Union[str, Any]:
				with offline(OfflineSimulationMode.CONNECTION_FAILS			):
								with pytest.raises(requests.exceptions.ConnectionError			):
												requests.request("""GET"""     , """https://huggingface.co"""			)





def        _lowercase   (  )  ->					int:
				with offline(OfflineSimulationMode.HF_DATASETS_OFFLINE_SET_TO_1			):
								with pytest.raises(_UpperCAmelCase			):
												http_head("""https://huggingface.co"""			)





