


'''simple docstring'''



import json
import sys






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Optional[int]						,      _SCREAMING_SNAKE_CASE      :   int   ):
					with open(_SCREAMING_SNAKE_CASE						,      encoding='utf-8'   ) as f:
										__a			:       Optional[Any]					    =  json.load(_SCREAMING_SNAKE_CASE   )

					__a			:       str					    =  ['<details>', '<summary>Show updated benchmarks!</summary>', ' ']

					for benchmark_name in sorted(_SCREAMING_SNAKE_CASE   ):
										__a			:       Optional[Any]					    =  results[benchmark_name]

										__a			:       List[str]					    =  benchmark_name.split('/'   )[-1]
										output_md.append(F"""### Benchmark: {benchmark_file_name}"""   )

										__a			:       List[Any]					    =  '| metric |'
										__a			:       List[Any]					    =  '|--------|'
										__a			:       Union[str, Any]					    =  '| new / old (diff) |'
										for metric_name in sorted(_SCREAMING_SNAKE_CASE   ):
															__a			:       str					    =  benchmark_res[metric_name]
															__a			:       str					    =  metric_vals['new']
															__a			:       Dict					    =  metric_vals.get('old'						,      _SCREAMING_SNAKE_CASE   )
															__a			:       Dict					    =  metric_vals.get('diff'						,      _SCREAMING_SNAKE_CASE   )

															__a			:       Union[str, Any]					    =  F""" {new_val:f}""" if isinstance(_SCREAMING_SNAKE_CASE						,      (int, float)   ) else 'None'

															if old_val is not None:
																				val_str += F""" / {old_val:f}""" if isinstance(_SCREAMING_SNAKE_CASE						,      (int, float)   ) else "None"
															if dif_val is not None:
																				val_str += F""" ({dif_val:f})""" if isinstance(_SCREAMING_SNAKE_CASE						,      (int, float)   ) else "None"

															title += " " + metric_name + " |"
															lines += "---|"
															value += val_str + " |"

										output_md += [title, lines, value, " "]

					output_md.append('</details>'   )

					with open(_SCREAMING_SNAKE_CASE						,      'w'						,      encoding='utf-8'   ) as f:
										f.writelines('\n'.join(_SCREAMING_SNAKE_CASE   )   )


if __name__ == "__main__":
	__lowercase	:						List[str]       =	sys.argv[1]
	__lowercase	:						str       =	sys.argv[2]

	format_json_to_md(input_json_file, output_md_file)







'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__lowercase	:						Union[str, Any]       =	{
    'configuration_blenderbot': [
        'BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BlenderbotConfig',
        'BlenderbotOnnxConfig',
    ],
    'tokenization_blenderbot': ['BlenderbotTokenizer'],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__lowercase	:						List[Any]       =	['BlenderbotTokenizerFast']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__lowercase	:						List[Any]       =	[
	    'BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'BlenderbotForCausalLM',
	    'BlenderbotForConditionalGeneration',
	    'BlenderbotModel',
	    'BlenderbotPreTrainedModel',
	]


try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__lowercase	:						Union[str, Any]       =	[
	    'TFBlenderbotForConditionalGeneration',
	    'TFBlenderbotModel',
	    'TFBlenderbotPreTrainedModel',
	]


try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__lowercase	:						Dict       =	[
	    'FlaxBlenderbotForConditionalGeneration',
	    'FlaxBlenderbotModel',
	    'FlaxBlenderbotPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_blenderbot import (
	    BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    BlenderbotConfig,
	    BlenderbotOnnxConfig,
	)
	from .tokenization_blenderbot import BlenderbotTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_blenderbot import (
		    BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    BlenderbotForCausalLM,
		    BlenderbotForConditionalGeneration,
		    BlenderbotModel,
		    BlenderbotPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_blenderbot import (
		    TFBlenderbotForConditionalGeneration,
		    TFBlenderbotModel,
		    TFBlenderbotPreTrainedModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_blenderbot import (
		    FlaxBlenderbotForConditionalGeneration,
		    FlaxBlenderbotModel,
		    FlaxBlenderbotPreTrainedModel,
		)

else:
	import sys

	__lowercase	:						str       =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



