



# 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

__snake_case						:List[str]      		=     '''tiny-wmt19-en-ru'''

# Build

# borrowed from a test
__snake_case						:List[Any]      		=     [
    '''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>''',
]
__snake_case						:Dict      		=     dict(zip(vocab, range(len(vocab))))
__snake_case						:Optional[int]      		=     ['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

with tempfile.TemporaryDirectory() as tmpdirname:
 __snake_case						:Tuple      		=     Path(tmpdirname)
 __snake_case						:Tuple      		=     build_dir / VOCAB_FILES_NAMES['''src_vocab_file''']
 __snake_case						:List[str]      		=     build_dir / VOCAB_FILES_NAMES['''tgt_vocab_file''']
 __snake_case						:Tuple      		=     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))

 __snake_case						:Tuple      		=     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,
 )

__snake_case						:int      		=     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,
)

__snake_case						:Optional[Any]      		=     FSMTForConditionalGeneration(config)
print(f'num of params {tiny_model.num_parameters()}')

# Test
__snake_case						:List[Any]      		=     tokenizer(['''Making tiny model'''], return_tensors='''pt''')
__snake_case						:Any      		=     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










import os

try:
 from .build_directory_md import good_file_paths
except ImportError:
 from build_directory_md import good_file_paths  # type: ignore

__snake_case						:Optional[Any]      		=     list(good_file_paths())
assert filepaths, "good_file_paths() failed!"

__snake_case						:Any      		=     [file for file in filepaths if file != file.lower()]
if upper_files:
 print(f'{len(upper_files)} files contain uppercase characters:')
 print('''\n'''.join(upper_files) + '''\n''')

__snake_case						:Tuple      		=     [file for file in filepaths if ''' ''' in file]
if space_files:
 print(f'{len(space_files)} files contain space characters:')
 print('''\n'''.join(space_files) + '''\n''')

__snake_case						:Optional[int]      		=     [file for file in filepaths if '''-''' in file]
if hyphen_files:
 print(f'{len(hyphen_files)} files contain hyphen characters:')
 print('''\n'''.join(hyphen_files) + '''\n''')

__snake_case						:Optional[int]      		=     [file for file in filepaths if os.sep not in file]
if nodir_files:
 print(f'{len(nodir_files)} files are not in a directory:')
 print('''\n'''.join(nodir_files) + '''\n''')

__snake_case						:int      		=     len(upper_files + space_files + hyphen_files + nodir_files)
if bad_files:
 import sys

 sys.exit(bad_files)





