

import unittest

from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate






def 					lowerCamelCase_     (							UpperCAmelCase_							:     Any	)						->				Union[str, Any]:




	'''simple docstring'''




	return x + 2







class 	lowercase    (				unittest.TestCase							):


		"""simple docstring"""




		def 		A__					(				self):
			_UpperCamelCase   :		int			=						'x = 3'
			_UpperCamelCase   :		Union[str, Any]			=						{}
			_UpperCamelCase   :		List[Any]			=						evaluate(__snake_case	,       {}	,       state=__snake_case)
			assert result == 3
			self.assertDictEqual(__snake_case	,       {'x': 3})

			_UpperCamelCase   :		List[Any]			=						'x = y'
			_UpperCamelCase   :		int			=						{'y': 5}
			_UpperCamelCase   :		Any			=						evaluate(__snake_case	,       {}	,       state=__snake_case)
			# evaluate returns the value of the last assignment.
			assert result == 5
			self.assertDictEqual(__snake_case	,       {'x': 5, 'y': 5})


		def 		A__					(				self):
			_UpperCamelCase   :		str			=						'y = add_two(x)'
			_UpperCamelCase   :		str			=						{'x': 3}
			_UpperCamelCase   :		str			=						evaluate(__snake_case	,       {'add_two': add_two}	,       state=__snake_case)
			assert result == 5
			self.assertDictEqual(__snake_case	,       {'x': 3, 'y': 5})

			# Won't work without the tool
			with CaptureStdout() as out:
				_UpperCamelCase   :		List[str]			=						evaluate(__snake_case	,       {}	,       state=__snake_case)
			assert result is None
			assert "tried to execute add_two" in out.out


		def 		A__					(				self):
			_UpperCamelCase   :		Any			=						'x = 3'
			_UpperCamelCase   :		List[Any]			=						{}
			_UpperCamelCase   :		Union[str, Any]			=						evaluate(__snake_case	,       {}	,       state=__snake_case)
			assert result == 3
			self.assertDictEqual(__snake_case	,       {'x': 3})


		def 		A__					(				self):
			_UpperCamelCase   :		List[str]			=						'test_dict = {\'x\': x, \'y\': add_two(x)}'
			_UpperCamelCase   :		Tuple			=						{'x': 3}
			_UpperCamelCase   :		Optional[Any]			=						evaluate(__snake_case	,       {'add_two': add_two}	,       state=__snake_case)
			self.assertDictEqual(__snake_case	,       {'x': 3, 'y': 5})
			self.assertDictEqual(__snake_case	,       {'x': 3, 'test_dict': {'x': 3, 'y': 5}})


		def 		A__					(				self):
			_UpperCamelCase   :		Optional[int]			=						'x = 3\ny = 5'
			_UpperCamelCase   :		Union[str, Any]			=						{}
			_UpperCamelCase   :		List[Any]			=						evaluate(__snake_case	,       {}	,       state=__snake_case)
			# evaluate returns the value of the last assignment.
			assert result == 5
			self.assertDictEqual(__snake_case	,       {'x': 3, 'y': 5})


		def 		A__					(				self):
			_UpperCamelCase   :		List[str]			=						'text = f\'This is x: {x}.\''
			_UpperCamelCase   :		Optional[int]			=						{'x': 3}
			_UpperCamelCase   :		List[str]			=						evaluate(__snake_case	,       {}	,       state=__snake_case)
			# evaluate returns the value of the last assignment.
			assert result == "This is x: 3."
			self.assertDictEqual(__snake_case	,       {'x': 3, 'text': 'This is x: 3.'})


		def 		A__					(				self):
			_UpperCamelCase   :		Dict			=						'if x <= 3:\n    y = 2\nelse:\n    y = 5'
			_UpperCamelCase   :		str			=						{'x': 3}
			_UpperCamelCase   :		Tuple			=						evaluate(__snake_case	,       {}	,       state=__snake_case)
			# evaluate returns the value of the last assignment.
			assert result == 2
			self.assertDictEqual(__snake_case	,       {'x': 3, 'y': 2})

			_UpperCamelCase   :		Optional[int]			=						{'x': 8}
			_UpperCamelCase   :		Dict			=						evaluate(__snake_case	,       {}	,       state=__snake_case)
			# evaluate returns the value of the last assignment.
			assert result == 5
			self.assertDictEqual(__snake_case	,       {'x': 8, 'y': 5})


		def 		A__					(				self):
			_UpperCamelCase   :		List[Any]			=						'test_list = [x, add_two(x)]'
			_UpperCamelCase   :		List[str]			=						{'x': 3}
			_UpperCamelCase   :		List[Any]			=						evaluate(__snake_case	,       {'add_two': add_two}	,       state=__snake_case)
			self.assertListEqual(__snake_case	,       [3, 5])
			self.assertDictEqual(__snake_case	,       {'x': 3, 'test_list': [3, 5]})


		def 		A__					(				self):
			_UpperCamelCase   :		str			=						'y = x'
			_UpperCamelCase   :		List[str]			=						{'x': 3}
			_UpperCamelCase   :		Dict			=						evaluate(__snake_case	,       {}	,       state=__snake_case)
			assert result == 3
			self.assertDictEqual(__snake_case	,       {'x': 3, 'y': 3})


		def 		A__					(				self):
			_UpperCamelCase   :		str			=						'test_list = [x, add_two(x)]\ntest_list[1]'
			_UpperCamelCase   :		Optional[int]			=						{'x': 3}
			_UpperCamelCase   :		str			=						evaluate(__snake_case	,       {'add_two': add_two}	,       state=__snake_case)
			assert result == 5
			self.assertDictEqual(__snake_case	,       {'x': 3, 'test_list': [3, 5]})

			_UpperCamelCase   :		Dict			=						'test_dict = {\'x\': x, \'y\': add_two(x)}\ntest_dict[\'y\']'
			_UpperCamelCase   :		Union[str, Any]			=						{'x': 3}
			_UpperCamelCase   :		Dict			=						evaluate(__snake_case	,       {'add_two': add_two}	,       state=__snake_case)
			assert result == 5
			self.assertDictEqual(__snake_case	,       {'x': 3, 'test_dict': {'x': 3, 'y': 5}})






		def 		A__					(				self):
			_UpperCamelCase   :		Union[str, Any]			=						'x = 0\nfor i in range(3):\n    x = i'
			_UpperCamelCase   :		str			=						{}
			_UpperCamelCase   :		List[str]			=						evaluate(__snake_case	,       {'range': range}	,       state=__snake_case)
			assert result == 2
			self.assertDictEqual(__snake_case	,       {'x': 2, 'i': 2})







import argparse

import torch

from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging


logging.set_verbosity_info()
lowerCAmelCase__								=		logging.get_logger(__name__)

lowerCAmelCase__								=		[
    ["""attention""", """attn"""],
    ["""encoder_attention""", """encoder_attn"""],
    ["""q_lin""", """q_proj"""],
    ["""k_lin""", """k_proj"""],
    ["""v_lin""", """v_proj"""],
    ["""out_lin""", """out_proj"""],
    ["""norm_embeddings""", """layernorm_embedding"""],
    ["""position_embeddings""", """embed_positions"""],
    ["""embeddings""", """embed_tokens"""],
    ["""ffn.lin""", """fc"""],
]






def 					lowerCamelCase_     (							UpperCAmelCase_							:     List[Any]	)						->				Optional[int]:




	'''simple docstring'''




	if k == "embeddings.weight":
		return "shared.weight"

	for parlai_name, hf_name in PATTERNS:
		_UpperCamelCase   :		List[Any]			=						k.replace(UpperCAmelCase_							,       UpperCAmelCase_	)

	if k.startswith('encoder'	):
		_UpperCamelCase   :		Optional[Any]			=						k.replace('.attn'							,       '.self_attn'	)
		_UpperCamelCase   :		Optional[int]			=						k.replace('norm1'							,       'self_attn_layer_norm'	)
		_UpperCamelCase   :		Tuple			=						k.replace('norm2'							,       'final_layer_norm'	)
	elif k.startswith('decoder'	):
		_UpperCamelCase   :		Any			=						k.replace('norm1'							,       'self_attn_layer_norm'	)
		_UpperCamelCase   :		Tuple			=						k.replace('norm2'							,       'encoder_attn_layer_norm'	)
		_UpperCamelCase   :		Tuple			=						k.replace('norm3'							,       'final_layer_norm'	)
	return k






def 					lowerCamelCase_     (							UpperCAmelCase_							:     Dict	)						->				Optional[Any]:




	'''simple docstring'''




	_UpperCamelCase   :		Union[str, Any]			=						[
	    'model.encoder.layernorm_embedding.weight',
	    'model.encoder.layernorm_embedding.bias',
	    'model.decoder.layernorm_embedding.weight',
	    'model.decoder.layernorm_embedding.bias',
	]
	for k in keys:
		_UpperCamelCase   :		Optional[int]			=						sd.pop(UpperCAmelCase_	)
		_UpperCamelCase   :		str			=						k.replace('layernorm_embedding'							,       'layer_norm'	)
		assert new_k not in sd
		_UpperCamelCase   :		Tuple			=						v


lowerCAmelCase__								=		["""START"""]






@torch.no_grad()
def 					lowerCamelCase_     (							UpperCAmelCase_							:     Tuple							,       UpperCAmelCase_							:     Optional[Any]							,       UpperCAmelCase_							:     Any	)						->				List[str]:




	'''simple docstring'''




	_UpperCamelCase   :		Optional[Any]			=						torch.load(UpperCAmelCase_							,       map_location='cpu'	)
	_UpperCamelCase   :		int			=						model['model']
	_UpperCamelCase   :		List[Any]			=						BlenderbotConfig.from_json_file(UpperCAmelCase_	)
	_UpperCamelCase   :		Any			=						BlenderbotForConditionalGeneration(UpperCAmelCase_	)
	_UpperCamelCase   :		int			=						m.model.state_dict().keys()
	_UpperCamelCase   :		Union[str, Any]			=						[]
	_UpperCamelCase   :		int			=						{}
	for k, v in sd.items():
		if k in IGNORE_KEYS:
			continue

		_UpperCamelCase   :		Optional[int]			=						rename_state_dict_key(UpperCAmelCase_	)
		if new_k not in valid_keys:
			failures.append([k, new_k]	)
		else:
			_UpperCamelCase   :		int			=						v
	if cfg.normalize_before:  # Blenderbot-3B checkpoints. Rename layernorm_embedding -> layer_norm
		rename_layernorm_keys(UpperCAmelCase_	)
	m.model.load_state_dict(UpperCAmelCase_							,       strict=UpperCAmelCase_	)
	m.half()
	m.save_pretrained(UpperCAmelCase_	)


if __name__ == "__main__":
							lowerCAmelCase__								=		argparse.ArgumentParser()
							# Required parameters
							parser.add_argument("""--src_path""", type=str, help="""like blenderbot-model.bin""")
							parser.add_argument("""--save_dir""", default="""hf_blenderbot""", type=str, help="""Where to save converted model.""")
							parser.add_argument(
							    """--hf_config_json""", default="""blenderbot-3b-config.json""", type=str, help="""Path to config to use"""
							)
							lowerCAmelCase__								=		parser.parse_args()
							convert_parlai_checkpoint(args.src_path, args.save_dir, args.hf_config_json)




