






"""simple docstring"""
class     UpperCamelCase_ :





	def __init__(   self      :				str		)		->    Optional[Any]:
				UpperCAmelCase_  :				str      =      0
				UpperCAmelCase_  :				Tuple      =      0
				UpperCAmelCase_  :				Optional[Any]      =      {}





	def   _SCREAMING_SNAKE_CASE   (   self      :				Tuple			,			lowerCAmelCase_      :				Union[str, Any]		)		->    Union[str, Any]:
				if vertex not in self.adjacency:
							UpperCAmelCase_  :				str      =      {}
							self.num_vertices += 1





	def   _SCREAMING_SNAKE_CASE   (   self      :				Any			,			lowerCAmelCase_      :				Any			,			lowerCAmelCase_      :				List[str]			,			lowerCAmelCase_      :				List[str]		)		->    Tuple:
				self.add_vertex(lowerCAmelCase_		)
				self.add_vertex(lowerCAmelCase_		)

				if head == tail:
							return

				UpperCAmelCase_  :				str      =      weight
				UpperCAmelCase_  :				Union[str, Any]      =      weight





	def   _SCREAMING_SNAKE_CASE   (   self      :				Dict		)		->    Union[str, Any]:
				UpperCAmelCase_  :				List[str]      =      self.get_edges()
				for edge in edges:
							UpperCAmelCase_  ,			UpperCAmelCase_  ,			UpperCAmelCase_  :				Dict      =      edge
							edges.remove((tail, head, weight)		)
				for i in range(len(lowerCAmelCase_		)		):
							UpperCAmelCase_  :				List[Any]      =      list(edges[i]		)

				edges.sort(key=lambda lowerCAmelCase_		: e[2]		)
				for i in range(len(lowerCAmelCase_		) - 1		):
							if edges[i][2] >= edges[i + 1][2]:
										UpperCAmelCase_  :				List[Any]      =      edges[i][2] + 1
				for edge in edges:
							UpperCAmelCase_  ,			UpperCAmelCase_  ,			UpperCAmelCase_  :				Union[str, Any]      =      edge
							UpperCAmelCase_  :				Optional[int]      =      weight
							UpperCAmelCase_  :				List[str]      =      weight





	def __str__(   self      :				List[str]		)		->    Dict:
				UpperCAmelCase_  :				Optional[int]      =      ""
				for tail in self.adjacency:
							for head in self.adjacency[tail]:
										UpperCAmelCase_  :				Optional[Any]      =      self.adjacency[head][tail]
										string += f"""{head} -> {tail} == {weight}\n"""
				return string.rstrip("\n"		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				int		)		->    Optional[Any]:
				UpperCAmelCase_  :				str      =      []
				for tail in self.adjacency:
							for head in self.adjacency[tail]:
										output.append((tail, head, self.adjacency[head][tail])		)
				return output





	def   _SCREAMING_SNAKE_CASE   (   self      :				Union[str, Any]		)		->    Union[str, Any]:
				return self.adjacency.keys()





	@staticmethod
	def   _SCREAMING_SNAKE_CASE   (   lowerCAmelCase_      :				Any=None			,			lowerCAmelCase_      :				Tuple=None		)		->    Union[str, Any]:
				UpperCAmelCase_  :				List[str]      =      Graph()
				if vertices is None:
							UpperCAmelCase_  :				Optional[Any]      =      []
				if edges is None:
							UpperCAmelCase_  :				List[Any]      =      []
				for vertex in vertices:
							g.add_vertex(lowerCAmelCase_		)
				for edge in edges:
							g.add_edge(*lowerCAmelCase_		)
				return g







	class     UpperCamelCase_ :





		def __init__(   self      :				int		)		->    List[Any]:
					UpperCAmelCase_  :				Tuple      =      {}
					UpperCAmelCase_  :				List[str]      =      {}





		def __len__(   self      :				Optional[int]		)		->    List[str]:
					return len(self.parent		)





		def   _SCREAMING_SNAKE_CASE   (   self      :				str			,			lowerCAmelCase_      :				Any		)		->    str:
					if item in self.parent:
								return self.find(lowerCAmelCase_		)

					UpperCAmelCase_  :				List[str]      =      item
					UpperCAmelCase_  :				Dict      =      0
					return item





		def   _SCREAMING_SNAKE_CASE   (   self      :				int			,			lowerCAmelCase_      :				int		)		->    Dict:
					if item not in self.parent:
								return self.make_set(lowerCAmelCase_		)
					if item != self.parent[item]:
								UpperCAmelCase_  :				Optional[int]      =      self.find(self.parent[item]		)
					return self.parent[item]





		def   _SCREAMING_SNAKE_CASE   (   self      :				Tuple			,			lowerCAmelCase_      :				Tuple			,			lowerCAmelCase_      :				Optional[int]		)		->    List[Any]:
					UpperCAmelCase_  :				Union[str, Any]      =      self.find(lowerCAmelCase_		)
					UpperCAmelCase_  :				Any      =      self.find(lowerCAmelCase_		)

					if roota == roota:
								return roota

					if self.rank[roota] > self.rank[roota]:
								UpperCAmelCase_  :				Tuple      =      roota
								return roota

					if self.rank[roota] < self.rank[roota]:
								UpperCAmelCase_  :				List[Any]      =      roota
								return roota

					if self.rank[roota] == self.rank[roota]:
								self.rank[roota] += 1
								UpperCAmelCase_  :				Optional[Any]      =      roota
								return roota
					return None





	@staticmethod
	def   _SCREAMING_SNAKE_CASE   (   lowerCAmelCase_      :				Union[str, Any]		)		->    int:
				UpperCAmelCase_  :				Union[str, Any]      =      graph.num_vertices

				UpperCAmelCase_  :				Any      =      Graph.UnionFind()
				UpperCAmelCase_  :				int      =      []
				while num_components > 1:
							UpperCAmelCase_  :				Dict      =      {}
							for vertex in graph.get_vertices():
										UpperCAmelCase_  :				Dict      =      -1

							UpperCAmelCase_  :				Dict      =      graph.get_edges()
							for edge in edges:
										UpperCAmelCase_  ,			UpperCAmelCase_  ,			UpperCAmelCase_  :				List[Any]      =      edge
										edges.remove((tail, head, weight)		)
							for edge in edges:
										UpperCAmelCase_  ,			UpperCAmelCase_  ,			UpperCAmelCase_  :				Union[str, Any]      =      edge
										UpperCAmelCase_  :				Optional[Any]      =      union_find.find(lowerCAmelCase_		)
										UpperCAmelCase_  :				Dict      =      union_find.find(lowerCAmelCase_		)
										if seta != seta:
													if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
																UpperCAmelCase_  :				str      =      [head, tail, weight]

													if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
																UpperCAmelCase_  :				Optional[Any]      =      [head, tail, weight]
							for vertex in cheap_edge:
										if cheap_edge[vertex] != -1:
													UpperCAmelCase_  ,			UpperCAmelCase_  ,			UpperCAmelCase_  :				Tuple      =      cheap_edge[vertex]
													if union_find.find(lowerCAmelCase_		) != union_find.find(lowerCAmelCase_		):
																union_find.union(lowerCAmelCase_			,			lowerCAmelCase_		)
																mst_edges.append(cheap_edge[vertex]		)
																UpperCAmelCase_  :				List[Any]      =      num_components - 1
				UpperCAmelCase_  :				List[str]      =      Graph.build(edges=lowerCAmelCase_		)
				return mst











"""simple docstring"""
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny vocab first, and then a tiny model - so the outcome is truly tiny -
# all files ~60KB. As compared to taking a full-size model, reducing to the minimum its layers and
# emb dimensions, but keeping the full vocab + merges files, leading to ~3MB in total for all files.
# The latter is done by `fsmt-make-super-tiny-model.py`.
#
# It will be used then as "stas/tiny-wmt19-en-ru"

from pathlib import Path
import json
import tempfile

from transformers import FSMTTokenizer, FSMTConfig, FSMTForConditionalGeneration
from transformers.models.fsmt.tokenization_fsmt import VOCAB_FILES_NAMES

lowerCamelCase_       			=   '''tiny-wmt19-en-ru'''

# Build

# borrowed from a test
lowerCamelCase_       			=   [
    '''l''',
    '''o''',
    '''w''',
    '''e''',
    '''r''',
    '''s''',
    '''t''',
    '''i''',
    '''d''',
    '''n''',
    '''w</w>''',
    '''r</w>''',
    '''t</w>''',
    '''lo''',
    '''low''',
    '''er</w>''',
    '''low</w>''',
    '''lowest</w>''',
    '''newer</w>''',
    '''wider</w>''',
    '''<unk>''',
]
lowerCamelCase_       			=   dict(zip(vocab, range(len(vocab))))
lowerCamelCase_       			=   ['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

with tempfile.TemporaryDirectory() as tmpdirname:
			lowerCamelCase_       			=   Path(tmpdirname)
			lowerCamelCase_       			=   build_dir / VOCAB_FILES_NAMES['''src_vocab_file''']
			lowerCamelCase_       			=   build_dir / VOCAB_FILES_NAMES['''tgt_vocab_file''']
			lowerCamelCase_       			=   build_dir / VOCAB_FILES_NAMES['''merges_file''']
			with open(src_vocab_file, '''w''') as fp:
						fp.write(json.dumps(vocab_tokens))
			with open(tgt_vocab_file, '''w''') as fp:
						fp.write(json.dumps(vocab_tokens))
			with open(merges_file, '''w''') as fp:
						fp.write('''\n'''.join(merges))

			lowerCamelCase_       			=   FSMTTokenizer(
			    langs=['''en''', '''ru'''],
			    src_vocab_size=len(vocab),
			    tgt_vocab_size=len(vocab),
			    src_vocab_file=src_vocab_file,
			    tgt_vocab_file=tgt_vocab_file,
			    merges_file=merges_file,
			)

lowerCamelCase_       			=   FSMTConfig(
    langs=['''ru''', '''en'''],
    src_vocab_size=1000,
    tgt_vocab_size=1000,
    d_model=4,
    encoder_layers=1,
    decoder_layers=1,
    encoder_ffn_dim=4,
    decoder_ffn_dim=4,
    encoder_attention_heads=1,
    decoder_attention_heads=1,
)

lowerCamelCase_       			=   FSMTForConditionalGeneration(config)
print(f'num of params {tiny_model.num_parameters()}')

# Test
lowerCamelCase_       			=   tokenizer(['''Making tiny model'''], return_tensors='''pt''')
lowerCamelCase_       			=   tiny_model(**batch)

print('''test output:''', len(outputs.logits[0]))

# Save
tiny_model.half()  # makes it smaller
tiny_model.save_pretrained(mname_tiny)
tokenizer.save_pretrained(mname_tiny)

print(f'Generated {mname_tiny}')

# Upload
# transformers-cli upload tiny-wmt19-en-ru



