"""simple docstring"""




import argparse
import logging
import os
import sys

import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers

import transformers
from transformers import BartForConditionalGeneration, BartTokenizer


logging.basicConfig(
    format="%(asctime)s | %(levelname)s | %(name)s |  [%(filename)s:%(lineno)d] %(message)s",
    datefmt="%Y-%m-%d %H:%M:%S",
    level=os.environ.get("LOGLEVEL", "INFO").upper(),
    stream=sys.stdout,
)

__lowerCamelCase											=  logging.getLogger(__name__)

__lowerCamelCase											=  {"facebook/bart-base": BartForConditionalGeneration}
__lowerCamelCase											=  {"facebook/bart-base": BartTokenizer}






def   UpperCAmelCase					(	):






							"""simple docstring"""





							A__	     =							argparse.ArgumentParser(description='Export Bart model + Beam Search to ONNX graph.'				)
							parser.add_argument(
							    '--validation_file'       ,    type=UpperCamelCase__       ,    default=UpperCamelCase__       ,    help='A csv or a json file containing the validation data.'				)
							parser.add_argument(
							    '--max_length'       ,    type=UpperCamelCase__       ,    default=5       ,    help='The maximum total input sequence length after tokenization.'       ,    )
							parser.add_argument(
							    '--num_beams'       ,    type=UpperCamelCase__       ,    default=UpperCamelCase__       ,    help=(
							        'Number of beams to use for evaluation. This argument will be '
							        'passed to ``model.generate``, which is used during ``evaluate`` and ``predict``.'
							    )       ,    )
							parser.add_argument(
							    '--model_name_or_path'       ,    type=UpperCamelCase__       ,    help='Path to pretrained model or model identifier from huggingface.co/models.'       ,    required=UpperCamelCase__       ,    )
							parser.add_argument(
							    '--config_name'       ,    type=UpperCamelCase__       ,    default=UpperCamelCase__       ,    help='Pretrained config name or path if not the same as model_name'       ,    )
							parser.add_argument(
							    '--device'       ,    type=UpperCamelCase__       ,    default='cpu'       ,    help='Device where the model will be run'       ,    )
							parser.add_argument('--output_file_path'       ,    type=UpperCamelCase__       ,    default=UpperCamelCase__       ,    help='Where to store the final ONNX file.'				)

							A__	     =							parser.parse_args()

							return args






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__="cpu"				):






							"""simple docstring"""





							A__	     =							model_dict[model_name].from_pretrained(UpperCamelCase__				).to(UpperCamelCase__				)
							A__	     =							tokenizer_dict[model_name].from_pretrained(UpperCamelCase__				)

							if model_name in ["facebook/bart-base"]:
														A__	     =							0
														A__	     =							None
														A__	     =							0

							return huggingface_model, tokenizer






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__       ,    UpperCamelCase__       ,    UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							model.eval()

							A__	     =							None
							A__	     =							torch.jit.script(BARTBeamSearchGenerator(UpperCamelCase__				)				)

							with torch.no_grad():
														A__	     =							'My friends are cool but they eat too many carbs.'
														A__	     =							tokenizer([ARTICLE_TO_SUMMARIZE]       ,    max_length=1_024       ,    return_tensors='pt'				).to(model.device				)

														A__	     =							model.generate(
														    inputs['input_ids']       ,    attention_mask=inputs['attention_mask']       ,    num_beams=UpperCamelCase__       ,    max_length=UpperCamelCase__       ,    early_stopping=UpperCamelCase__       ,    decoder_start_token_id=model.config.decoder_start_token_id       ,    )

														torch.onnx.export(
														    UpperCamelCase__       ,    (
														        inputs['input_ids'],
														        inputs['attention_mask'],
														        num_beams,
														        max_length,
														        model.config.decoder_start_token_id,
														    )       ,    UpperCamelCase__       ,    opset_version=14       ,    input_names=['input_ids', 'attention_mask', 'num_beams', 'max_length', 'decoder_start_token_id']       ,    output_names=['output_ids']       ,    dynamic_axes={
														        'input_ids': {0: 'batch', 1: 'seq'},
														        'output_ids': {0: 'batch', 1: 'seq_out'},
														    }       ,    example_outputs=UpperCamelCase__       ,    )

														logger.info('Model exported to {}'.format(UpperCamelCase__				)				)

														A__	     =							remove_dup_initializers(os.path.abspath(UpperCamelCase__				)				)

														logger.info('Deduplicated and optimized model written to {}'.format(UpperCamelCase__				)				)

														A__	     =							onnxruntime.InferenceSession(UpperCamelCase__				)
														A__	     =							ort_sess.run(
														    UpperCamelCase__       ,    {
														        'input_ids': inputs['input_ids'].cpu().numpy(),
														        'attention_mask': inputs['attention_mask'].cpu().numpy(),
														        'num_beams': np.array(UpperCamelCase__				),
														        'max_length': np.array(UpperCamelCase__				),
														        'decoder_start_token_id': np.array(model.config.decoder_start_token_id				),
														    }       ,    )

														np.testing.assert_allclose(summary_ids.cpu().numpy()       ,    ort_out[0]       ,    rtol=1E-3       ,    atol=1E-3				)

														logger.info('Model outputs from torch and ONNX Runtime are similar.'				)
														logger.info('Success.'				)






def   UpperCAmelCase					(	):






							"""simple docstring"""





							A__	     =							parse_args()
							A__	     =							5
							A__	     =							4

							# Make one log on every process with the configuration for debugging.
							logging.basicConfig(
							    format='%(asctime)s - %(levelname)s - %(name)s - %(message)s'       ,    datefmt='%m/%d/%Y %H:%M:%S'       ,    level=logging.INFO       ,    )

							logger.setLevel(logging.INFO				)
							transformers.utils.logging.set_verbosity_error()

							A__	     =							torch.device(args.device				)

							A__     ,  A__	     =							load_model_tokenizer(args.model_name_or_path       ,    UpperCamelCase__				)

							if model.config.decoder_start_token_id is None:
														raise ValueError('Make sure that `config.decoder_start_token_id` is correctly defined'				)

							model.to(UpperCamelCase__				)

							if args.max_length:
														A__	     =							args.max_length

							if args.num_beams:
														A__	     =							args.num_beams

							if args.output_file_path:
														A__	     =							args.output_file_path
							else:
														A__	     =							'BART.onnx'

							logger.info('Exporting model to ONNX'				)
							export_and_validate_model(UpperCamelCase__       ,    UpperCamelCase__       ,    UpperCamelCase__       ,    UpperCamelCase__       ,    UpperCamelCase__				)


if __name__ == "__main__":
				main()






"""simple docstring"""




import re
import tempfile
from pathlib import Path

import pytest
import yaml

from datasets.utils.readme import ReadMe


# @pytest.fixture
# def example_yaml_structure():

__lowerCamelCase											=  yaml.safe_load(
    "\\nname: \"\"\nallow_empty: false\nallow_empty_text: true\nsubsections:\n  - name: \"Dataset Card for X\" # First-level markdown heading\n    allow_empty: false\n    allow_empty_text: true\n    subsections:\n      - name: \"Table of Contents\"\n        allow_empty: false\n        allow_empty_text: false\n        subsections: null\n      - name: \"Dataset Description\"\n        allow_empty: false\n        allow_empty_text: false\n        subsections:\n          - name: \"Dataset Summary\"\n            allow_empty: false\n            allow_empty_text: false\n            subsections: null\n          - name: \"Supported Tasks and Leaderboards\"\n            allow_empty: true\n            allow_empty_text: true\n            subsections: null\n          - name: Languages\n            allow_empty: false\n            allow_empty_text: true\n            subsections: null\n"
)


__lowerCamelCase											=  {
    "name": "root",
    "text": "",
    "is_empty_text": True,
    "subsections": [
        {
            "name": "Dataset Card for My Dataset",
            "text": "",
            "is_empty_text": True,
            "subsections": [
                {"name": "Table of Contents", "text": "Some text here.", "is_empty_text": False, "subsections": []},
                {
                    "name": "Dataset Description",
                    "text": "Some text here.",
                    "is_empty_text": False,
                    "subsections": [
                        {
                            "name": "Dataset Summary",
                            "text": "Some text here.",
                            "is_empty_text": False,
                            "subsections": [],
                        },
                        {
                            "name": "Supported Tasks and Leaderboards",
                            "text": "",
                            "is_empty_text": True,
                            "subsections": [],
                        },
                        {"name": "Languages", "text": "Language Text", "is_empty_text": False, "subsections": []},
                    ],
                },
            ],
        }
    ],
}


__lowerCamelCase											=  "\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n"


__lowerCamelCase											=  "\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n#### Extra Ignored Subsection\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n"

__lowerCamelCase											=  {
    "name": "root",
    "text": "",
    "is_empty_text": True,
    "subsections": [
        {
            "name": "Dataset Card for My Dataset",
            "text": "",
            "is_empty_text": True,
            "subsections": [
                {"name": "Table of Contents", "text": "Some text here.", "is_empty_text": False, "subsections": []},
                {
                    "name": "Dataset Description",
                    "text": "Some text here.",
                    "is_empty_text": False,
                    "subsections": [
                        {
                            "name": "Dataset Summary",
                            "text": "Some text here.",
                            "is_empty_text": False,
                            "subsections": [
                                {
                                    "name": "Extra Ignored Subsection",
                                    "text": "",
                                    "is_empty_text": True,
                                    "subsections": [],
                                }
                            ],
                        },
                        {
                            "name": "Supported Tasks and Leaderboards",
                            "text": "",
                            "is_empty_text": True,
                            "subsections": [],
                        },
                        {"name": "Languages", "text": "Language Text", "is_empty_text": False, "subsections": []},
                    ],
                },
            ],
        }
    ],
}

__lowerCamelCase											=  "\\n---\n---\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n"

__lowerCamelCase											=  (
    "The following issues were found for the README at `{path}`:\n-\tEmpty YAML markers are present in the README."
)

__lowerCamelCase											=  "\\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n"

__lowerCamelCase											=  (
    "The following issues were found for the README at `{path}`:\n-\tNo YAML markers are present in the README."
)

__lowerCamelCase											=  "\\n---\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n"

__lowerCamelCase											=  "The following issues were found for the README at `{path}`:\n-\tOnly the start of YAML tags present in the README."

__lowerCamelCase											=  "\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n"
__lowerCamelCase											=  "The following issues were found for the README at `{path}`:\n-\tExpected some content in section `Dataset Summary` but it is empty.\n-\tExpected some text in section `Dataset Summary` but it is empty (text in subsections are ignored)."


__lowerCamelCase											=  "\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n"
__lowerCamelCase											=  "The following issues were found for the README at `{path}`:\n-\tExpected some content in section `Dataset Card for My Dataset` but it is empty.\n-\tSection `Dataset Card for My Dataset` expected the following subsections: `Table of Contents`, `Dataset Description`. Found 'None'."

__lowerCamelCase											=  "\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Languages\nLanguage Text\n"

__lowerCamelCase											=  "The following issues were found for the README at `{path}`:\n-\tSection `Dataset Description` is missing subsection: `Supported Tasks and Leaderboards`."


__lowerCamelCase											=  "\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\n"

__lowerCamelCase											=  "The following issues were found for the README at `{path}`:\n-\tExpected some content in section `Languages` but it is empty."

__lowerCamelCase											=  "\\n---\nlanguage:\n- zh\n- en\n---\n\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n"
__lowerCamelCase											=  "The following issues were found for the README at `{path}`:\n-\tThe README has no first-level headings. One heading is expected. Skipping further validation for this README."

__lowerCamelCase											=  "\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n# Dataset Card My Dataset\n"

__lowerCamelCase											=  "The following issues were found for the README at `{path}`:\n-\tThe README has several first-level headings: `Dataset Card for My Dataset`, `Dataset Card My Dataset`. Only one heading is expected. Skipping further validation for this README."

__lowerCamelCase											=  "\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n"

__lowerCamelCase											=  "The following issues were found for the README at `{path}`:\n-\tNo first-level heading starting with `Dataset Card for` found in README. Skipping further validation for this README."

__lowerCamelCase											=  ""

__lowerCamelCase											=  "The following issues were found for the README at `{path}`:\n-\tThe README has no first-level headings. One heading is expected. Skipping further validation for this README.\n-\tNo YAML markers are present in the README."

__lowerCamelCase											=  "\\n---\nlanguage:\n- zh\n- en\n---\n\n# Dataset Card for My Dataset\n# Dataset Card for My Dataset\n## Table of Contents\nSome text here.\n## Dataset Description\nSome text here.\n### Dataset Summary\nSome text here.\n### Supported Tasks and Leaderboards\n### Languages\nLanguage Text\n"

__lowerCamelCase											=  "The following issues were found while parsing the README at `{path}`:\n-\tMultiple sections with the same heading `Dataset Card for My Dataset` have been found. Please keep only one of these sections."






@pytest.mark.parametrize(
    'readme_md, expected_dict'       ,    [
        (README_CORRECT, CORRECT_DICT),
        (README_CORRECT_FOUR_LEVEL, CORRECT_DICT_FOUR_LEVEL),
    ]       ,    )
def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							assert ReadMe.from_string(UpperCamelCase__       ,    UpperCamelCase__				).to_dict() == expected_dict






@pytest.mark.parametrize(
    'readme_md, expected_error'       ,    [
        (README_NO_YAML, EXPECTED_ERROR_README_NO_YAML),
        (README_EMPTY_YAML, EXPECTED_ERROR_README_EMPTY_YAML),
        (README_INCORRECT_YAML, EXPECTED_ERROR_README_INCORRECT_YAML),
        (README_EMPTY, EXPECTED_ERROR_README_EMPTY),
        (README_NONE_SUBSECTION, EXPECTED_ERROR_README_NONE_SUBSECTION),
        (README_MISSING_FIRST_LEVEL, EXPECTED_ERROR_README_MISSING_FIRST_LEVEL),
        (README_MISSING_SUBSECTION, EXPECTED_ERROR_README_MISSING_SUBSECTION),
        (README_MISSING_TEXT, EXPECTED_ERROR_README_MISSING_TEXT),
        (README_WRONG_FIRST_LEVEL, EXPECTED_ERROR_README_WRONG_FIRST_LEVEL),
        (README_MULTIPLE_WRONG_FIRST_LEVEL, EXPECTED_ERROR_README_MULTIPLE_WRONG_FIRST_LEVEL),
        (README_MISSING_CONTENT, EXPECTED_ERROR_README_MISSING_CONTENT),
    ]       ,    )
def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							with pytest.raises(UpperCamelCase__       ,    match=re.escape(expected_error.format(path='root'				)				)				):
														A__	     =							ReadMe.from_string(UpperCamelCase__       ,    UpperCamelCase__				)
														readme.validate()






@pytest.mark.parametrize(
    'readme_md, expected_error'       ,    [
        (README_MULTIPLE_SAME_HEADING_1, EXPECTED_ERROR_README_MULTIPLE_SAME_HEADING_1),
    ]       ,    )
def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							with pytest.raises(UpperCamelCase__       ,    match=re.escape(expected_error.format(path='root'				)				)				):
														ReadMe.from_string(UpperCamelCase__       ,    UpperCamelCase__				)






@pytest.mark.parametrize(
    'readme_md,'       ,    [
        (README_MULTIPLE_SAME_HEADING_1),
    ]       ,    )
def   UpperCAmelCase					(	UpperCamelCase__				):






							"""simple docstring"""





							ReadMe.from_string(UpperCamelCase__       ,    UpperCamelCase__       ,    suppress_parsing_errors=UpperCamelCase__				)






@pytest.mark.parametrize(
    'readme_md, expected_dict'       ,    [
        (README_CORRECT, CORRECT_DICT),
        (README_CORRECT_FOUR_LEVEL, CORRECT_DICT_FOUR_LEVEL),
    ]       ,    )
def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							with tempfile.TemporaryDirectory() as tmp_dir:
														A__	     =							Path(UpperCamelCase__				) / 'README.md'
														with open(UpperCamelCase__       ,    'w+'				) as readme_file:
																					readme_file.write(UpperCamelCase__				)
														A__	     =							ReadMe.from_readme(UpperCamelCase__       ,    UpperCamelCase__				).to_dict()
														assert out["name"] == path
														assert out["text"] == ""
														assert out["is_empty_text"]
														assert out["subsections"] == expected_dict["subsections"]






@pytest.mark.parametrize(
    'readme_md, expected_error'       ,    [
        (README_NO_YAML, EXPECTED_ERROR_README_NO_YAML),
        (README_EMPTY_YAML, EXPECTED_ERROR_README_EMPTY_YAML),
        (README_INCORRECT_YAML, EXPECTED_ERROR_README_INCORRECT_YAML),
        (README_EMPTY, EXPECTED_ERROR_README_EMPTY),
        (README_NONE_SUBSECTION, EXPECTED_ERROR_README_NONE_SUBSECTION),
        (README_MISSING_FIRST_LEVEL, EXPECTED_ERROR_README_MISSING_FIRST_LEVEL),
        (README_MISSING_SUBSECTION, EXPECTED_ERROR_README_MISSING_SUBSECTION),
        (README_MISSING_TEXT, EXPECTED_ERROR_README_MISSING_TEXT),
        (README_WRONG_FIRST_LEVEL, EXPECTED_ERROR_README_WRONG_FIRST_LEVEL),
        (README_MULTIPLE_WRONG_FIRST_LEVEL, EXPECTED_ERROR_README_MULTIPLE_WRONG_FIRST_LEVEL),
        (README_MISSING_CONTENT, EXPECTED_ERROR_README_MISSING_CONTENT),
    ]       ,    )
def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							with tempfile.TemporaryDirectory() as tmp_dir:
														A__	     =							Path(UpperCamelCase__				) / 'README.md'
														with open(UpperCamelCase__       ,    'w+'				) as readme_file:
																					readme_file.write(UpperCamelCase__				)
														A__	     =							expected_error.format(path=UpperCamelCase__				)
														with pytest.raises(UpperCamelCase__       ,    match=re.escape(UpperCamelCase__				)				):
																					A__	     =							ReadMe.from_readme(UpperCamelCase__       ,    UpperCamelCase__				)
																					readme.validate()






@pytest.mark.parametrize(
    'readme_md, expected_error'       ,    [
        (README_MULTIPLE_SAME_HEADING_1, EXPECTED_ERROR_README_MULTIPLE_SAME_HEADING_1),
    ]       ,    )
def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							with tempfile.TemporaryDirectory() as tmp_dir:
														A__	     =							Path(UpperCamelCase__				) / 'README.md'
														with open(UpperCamelCase__       ,    'w+'				) as readme_file:
																					readme_file.write(UpperCamelCase__				)
														A__	     =							expected_error.format(path=UpperCamelCase__				)
														with pytest.raises(UpperCamelCase__       ,    match=re.escape(UpperCamelCase__				)				):
																					ReadMe.from_readme(UpperCamelCase__       ,    UpperCamelCase__				)






@pytest.mark.parametrize(
    'readme_md,'       ,    [
        (README_MULTIPLE_SAME_HEADING_1),
    ]       ,    )
def   UpperCAmelCase					(	UpperCamelCase__				):






							"""simple docstring"""





							with tempfile.TemporaryDirectory() as tmp_dir:
														A__	     =							Path(UpperCamelCase__				) / 'README.md'
														with open(UpperCamelCase__       ,    'w+'				) as readme_file:
																					readme_file.write(UpperCamelCase__				)
														ReadMe.from_readme(UpperCamelCase__       ,    UpperCamelCase__       ,    suppress_parsing_errors=UpperCamelCase__				)





