






'''simple docstring'''

import argparse
import glob
import importlib.util
import os
import re

import black
from doc_builder.style_doc import style_docstrings_in_code


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
A:      Dict  				=				"src/diffusers"
A:      Any  				=				"."


# This is to make sure the diffusers module imported is the one in the repo.
A:      Dict  				=				importlib.util.spec_from_file_location(
    "diffusers",
    os.path.join(DIFFUSERS_PATH, "__init__.py"),
    submodule_search_locations=[DIFFUSERS_PATH],
)
A:      Any  				=				spec.loader.load_module()






def 	_UpperCAmelCase    (  a		:	str						,			a		:	Any							)			->			Tuple:





						"""simple docstring"""
						return line.startswith(a							) or len(a							) <= 1 or re.search(R'^\s*\)(\s*->.*:|:)\s*$'						,			a							) is not None






def 	_UpperCAmelCase    (  a		:	Union[str, Any]							)			->			Optional[Any]:





						"""simple docstring"""
						lowercase_      :   Tuple        =			object_name.split('.'							)
						lowercase_      :   str        =			0

						# First let's find the module where our object lives.
						lowercase_      :   Any        =			parts[i]
						while i < len(a							) and not os.path.isfile(os.path.join(a						,			f"{module}.py"							)							):
												i += 1
												if i < len(a							):
																		lowercase_      :   Union[str, Any]        =			os.path.join(a						,			parts[i]							)
						if i >= len(a							):
												raise ValueError(f"`object_name` should begin with the name of a module of diffusers but got {object_name}."							)

						with open(os.path.join(a						,			f"{module}.py"							)						,			'r'						,			encoding='utf-8'						,			newline='\n'							) as f:
												lowercase_      :   int        =			f.readlines()

						# Now let's find the class / func in the code!
						lowercase_      :   Optional[int]        =			''
						lowercase_      :   Any        =			0
						for name in parts[i + 1 :]:
												while (
												    line_index < len(a							) and re.search(Rf"^{indent}(class|def)\s+{name}(\(|\:)"						,			lines[line_index]							) is None
												):
																		line_index += 1
												indent += "    "
												line_index += 1

						if line_index >= len(a							):
												raise ValueError(f" {object_name} does not match any function or class in {module}."							)

						# We found the beginning of the class / func, now let's find the end (when the indent diminishes).
						lowercase_      :   str        =			line_index
						while line_index < len(a							) and _should_continue(lines[line_index]						,			a							):
												line_index += 1
						# Clean up empty lines at the end (if any).
						while len(lines[line_index - 1]							) <= 1:
												line_index -= 1

						lowercase_      :   Union[str, Any]        =			lines[start_index:line_index]
						return "".join(a							)


A:      List[str]  				=				re.compile(r"^(\s*)#\s*Copied from\s+diffusers\.(\S+\.\S+)\s*($|\S.*$)")
A:      Optional[int]  				=				re.compile(r"^\s*(\S+)->(\S+)(\s+.*|$)")
A:      Dict  				=				re.compile(r"<FILL\s+[^>]*>")






def 	_UpperCAmelCase    (  a		:	Union[str, Any]							)			->			List[str]:





						"""simple docstring"""
						lowercase_      :   str        =			code.split('\n'							)
						lowercase_      :   Optional[int]        =			0
						while idx < len(a							) and len(lines[idx]							) == 0:
												idx += 1
						if idx < len(a							):
												return re.search(R'^(\s*)\S'						,			lines[idx]							).groups()[0]
						return ""






def 	_UpperCAmelCase    (  a		:	Optional[Any]							)			->			Tuple:





						"""simple docstring"""
						lowercase_      :   str        =			len(get_indent(a							)							) > 0
						if has_indent:
												lowercase_      :   List[str]        =			f"class Bla:\n{code}"
						lowercase_      :   Tuple        =			black.Mode(target_versions={black.TargetVersion.PYaa}						,			line_length=1_1_9						,			preview=a							)
						lowercase_      :   List[str]        =			black.format_str(a						,			mode=a							)
						lowercase_      :   Any        =			style_docstrings_in_code(a							)
						return result[len('class Bla:\n'							) :] if has_indent else result






def 	_UpperCAmelCase    (  a		:	Optional[Any]						,			a		:	int=False							)			->			Any:





						"""simple docstring"""
						with open(a						,			'r'						,			encoding='utf-8'						,			newline='\n'							) as f:
												lowercase_      :   str        =			f.readlines()
						lowercase_      :   int        =			[]
						lowercase_      :   Optional[Any]        =			0
						# Not a for loop cause `lines` is going to change (if `overwrite=True`).
						while line_index < len(a							):
												lowercase_      :   Optional[int]        =			_re_copy_warning.search(lines[line_index]							)
												if search is None:
																		line_index += 1
																		continue

												# There is some copied code here, let's retrieve the original.
												lowercase_      :   Any        =			search.groups()
												lowercase_      :   int        =			find_code_in_diffusers(a							)
												lowercase_      :   Optional[int]        =			get_indent(a							)

												lowercase_      :   Any        =			line_index + 1 if indent == theoretical_indent else line_index + 2
												lowercase_      :   List[Any]        =			theoretical_indent
												lowercase_      :   Optional[Any]        =			start_index

												# Loop to check the observed code, stop when indentation diminishes or if we see a End copy comment.
												lowercase_      :   Tuple        =			True
												while line_index < len(a							) and should_continue:
																		line_index += 1
																		if line_index >= len(a							):
																								break
																		lowercase_      :   Any        =			lines[line_index]
																		lowercase_      :   Tuple        =			_should_continue(a						,			a							) and re.search(f"^{indent}# End copy"						,			a							) is None
												# Clean up empty lines at the end (if any).
												while len(lines[line_index - 1]							) <= 1:
																		line_index -= 1

												lowercase_      :   Any        =			lines[start_index:line_index]
												lowercase_      :   Any        =			''.join(a							)

												# Remove any nested `Copied from` comments to avoid circular copies
												lowercase_      :   str        =			[line for line in theoretical_code.split('\n'							) if _re_copy_warning.search(a							) is None]
												lowercase_      :   str        =			'\n'.join(a							)

												# Before comparing, use the `replace_pattern` on the original code.
												if len(a							) > 0:
																		lowercase_      :   Optional[Any]        =			replace_pattern.replace('with'						,			''							).split(','							)
																		lowercase_      :   int        =			[_re_replace_pattern.search(a							) for p in patterns]
																		for pattern in patterns:
																								if pattern is None:
																														continue
																								lowercase_      :   str        =			pattern.groups()
																								lowercase_      :   Dict        =			re.sub(a						,			a						,			a							)
																								if option.strip() == "all-casing":
																														lowercase_      :   str        =			re.sub(obja.lower()						,			obja.lower()						,			a							)
																														lowercase_      :   List[Any]        =			re.sub(obja.upper()						,			obja.upper()						,			a							)

            # Blackify after replacement. To be able to do that, we need the header (class or function definition)
            # from the previous line
																		lowercase_      :   Any        =			blackify(lines[start_index - 1] + theoretical_code							)
																		lowercase_      :   int        =			theoretical_code[len(lines[start_index - 1]							) :]

												# Test for a diff and act accordingly.
												if observed_code != theoretical_code:
																		diffs.append([object_name, start_index]							)
																		if overwrite:
																								lowercase_      :   Tuple        =			lines[:start_index] + [theoretical_code] + lines[line_index:]
																								lowercase_      :   List[Any]        =			start_index + 1

						if overwrite and len(a							) > 0:
												# Warn the user a file has been modified.
												print(f"Detected changes, rewriting {filename}."							)
												with open(a						,			'w'						,			encoding='utf-8'						,			newline='\n'							) as f:
																		f.writelines(a							)
						return diffs






def 	_UpperCAmelCase    (  a		:	bool = False							)			->			Optional[int]:





						"""simple docstring"""
						lowercase_      :   Union[str, Any]        =			glob.glob(os.path.join(a						,			'**/*.py'							)						,			recursive=a							)
						lowercase_      :   List[str]        =			[]
						for filename in all_files:
												lowercase_      :   Tuple        =			is_copy_consistent(a						,			a							)
												diffs += [f"- {filename}: copy does not match {d[0]} at line {d[1]}" for d in new_diffs]
						if not overwrite and len(a							) > 0:
												lowercase_      :   Tuple        =			'\n'.join(a							)
												raise Exception(
												    'Found the following copy inconsistencies:\n'
												    + diff
												    + '\nRun `make fix-copies` or `python utils/check_copies.py --fix_and_overwrite` to fix them.'							)


if __name__ == "__main__":
						A:      Any  				=				argparse.ArgumentParser()
						parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
						A:      str  				=				parser.parse_args()

						check_copies(args.fix_and_overwrite)







'''simple docstring'''

# Usage:
# ./gen-card-facebook-wmt19.py

import os
from pathlib import Path






def 	_UpperCAmelCase    (  a		:	Dict						,			a		:	Optional[int]						,			a		:	Tuple							)			->			Optional[int]:





						"""simple docstring"""
						lowercase_      :   Any        =			{
						    'en': 'Machine learning is great, isn\'t it?',
						    'ru': 'Машинное обучение - это здорово, не так ли?',
						    'de': 'Maschinelles Lernen ist großartig, oder?',
						}

						# BLUE scores as follows:
						# "pair": [fairseq, transformers]
						lowercase_      :   List[str]        =			{
						    'ru-en': ['[41.3](http://matrix.statmt.org/matrix/output/1907?run_id=6937)', '39.20'],
						    'en-ru': ['[36.4](http://matrix.statmt.org/matrix/output/1914?run_id=6724)', '33.47'],
						    'en-de': ['[43.1](http://matrix.statmt.org/matrix/output/1909?run_id=6862)', '42.83'],
						    'de-en': ['[42.3](http://matrix.statmt.org/matrix/output/1902?run_id=6750)', '41.35'],
						}
						lowercase_      :   Optional[Any]        =			f"{src_lang}-{tgt_lang}"

						lowercase_      :   Optional[Any]        =			f"\n---\nlanguage: \n- {src_lang}\n- {tgt_lang}\nthumbnail:\ntags:\n- translation\n- wmt19\n- facebook\nlicense: apache-2.0\ndatasets:\n- wmt19\nmetrics:\n- bleu\n---\n\n# FSMT\n\n## Model description\n\nThis is a ported version of [fairseq wmt19 transformer](https://github.com/pytorch/fairseq/blob/master/examples/wmt19/README.md) for {src_lang}-{tgt_lang}.\n\nFor more details, please see, [Facebook FAIR's WMT19 News Translation Task Submission](https://arxiv.org/abs/1907.06616).\n\nThe abbreviation FSMT stands for FairSeqMachineTranslation\n\nAll four models are available:\n\n* [wmt19-en-ru](https://huggingface.co/facebook/wmt19-en-ru)\n* [wmt19-ru-en](https://huggingface.co/facebook/wmt19-ru-en)\n* [wmt19-en-de](https://huggingface.co/facebook/wmt19-en-de)\n* [wmt19-de-en](https://huggingface.co/facebook/wmt19-de-en)\n\n## Intended uses & limitations\n\n#### How to use\n\n```python\nfrom transformers import FSMTForConditionalGeneration, FSMTTokenizer\nmname = \"facebook/wmt19-{src_lang}-{tgt_lang}\"\ntokenizer = FSMTTokenizer.from_pretrained(mname)\nmodel = FSMTForConditionalGeneration.from_pretrained(mname)\n\ninput = \"{texts[src_lang]}\"\ninput_ids = tokenizer.encode(input, return_tensors=\"pt\")\noutputs = model.generate(input_ids)\ndecoded = tokenizer.decode(outputs[0], skip_special_tokens=True)\nprint(decoded) # {texts[tgt_lang]}\n\n```\n\n#### Limitations and bias\n\n- The original (and this ported model) doesn't seem to handle well inputs with repeated sub-phrases, [content gets truncated](https://discuss.huggingface.co/t/issues-with-translating-inputs-containing-repeated-phrases/981)\n\n## Training data\n\nPretrained weights were left identical to the original model released by fairseq. For more details, please, see the [paper](https://arxiv.org/abs/1907.06616).\n\n## Eval results\n\npair   | fairseq | transformers\n-------|---------|----------\n{pair}  | {scores[pair][0]} | {scores[pair][1]}\n\nThe score is slightly below the score reported by `fairseq`, since `transformers`` currently doesn't support:\n- model ensemble, therefore the best performing checkpoint was ported (``model4.pt``).\n- re-ranking\n\nThe score was calculated using this code:\n\n```bash\ngit clone https://github.com/huggingface/transformers\ncd transformers\nexport PAIR={pair}\nexport DATA_DIR=data/$PAIR\nexport SAVE_DIR=data/$PAIR\nexport BS=8\nexport NUM_BEAMS=15\nmkdir -p $DATA_DIR\nsacrebleu -t wmt19 -l $PAIR --echo src > $DATA_DIR/val.source\nsacrebleu -t wmt19 -l $PAIR --echo ref > $DATA_DIR/val.target\necho $PAIR\nPYTHONPATH=\"src:examples/seq2seq\" python examples/seq2seq/run_eval.py facebook/wmt19-$PAIR $DATA_DIR/val.source $SAVE_DIR/test_translations.txt --reference_path $DATA_DIR/val.target --score_path $SAVE_DIR/test_bleu.json --bs $BS --task translation --num_beams $NUM_BEAMS\n```\nnote: fairseq reports using a beam of 50, so you should get a slightly higher score if re-run with `--num_beams 50`.\n\n## Data Sources\n\n- [training, etc.](http://www.statmt.org/wmt19/)\n- [test set](http://matrix.statmt.org/test_sets/newstest2019.tgz?1556572561)\n\n\n### BibTeX entry and citation info\n\n```bibtex\n@inproceedings{{...,\n  year={{2020}},\n  title={{Facebook FAIR's WMT19 News Translation Task Submission}},\n  author={{Ng, Nathan and Yee, Kyra and Baevski, Alexei and Ott, Myle and Auli, Michael and Edunov, Sergey}},\n  booktitle={{Proc. of WMT}},\n}}\n```\n\n\n## TODO\n\n- port model ensemble (fairseq uses 4 model checkpoints)\n\n"
						os.makedirs(a						,			exist_ok=a							)
						lowercase_      :   int        =			os.path.join(a						,			'README.md'							)
						print(f"Generating {path}"							)
						with open(a						,			'w'						,			encoding='utf-8'							) as f:
												f.write(a							)


# make sure we are under the root of the project
A:      List[str]  				=				Path(__file__).resolve().parent.parent.parent
A:      List[str]  				=				repo_dir / "model_cards"

for model_name in ["wmt19-ru-en", "wmt19-en-ru", "wmt19-en-de", "wmt19-de-en"]:
						A				,		A				,		A:      Any  				=				model_name.split("-")
						A:      int  				=				model_cards_dir / "facebook" / model_name
						write_model_card(model_card_dir, src_lang=src_lang, tgt_lang=tgt_lang)
