
# 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 model through reduction of a normal pre-trained model, but keeping the
# full vocab, merges file, and thus also resulting in a larger model due to a large vocab size.
# This gives ~3MB in total for all files.
#
# If you want a 50 times smaller than this see `fsmt-make-super-tiny-model.py`, which is slightly more complicated
#
#
# It will be used then as "stas/tiny-wmt19-en-de"

# Build
from transformers import FSMTTokenizer, FSMTConfig, FSMTForConditionalGeneration

__a  			=					'''facebook/wmt19-en-de'''
__a  			=					FSMTTokenizer.from_pretrained(mname)
# get the correct vocab sizes, etc. from the master model
__a  			=					FSMTConfig.from_pretrained(mname)
config.update(
    dict(
        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,
    )
)

__a  			=					FSMTForConditionalGeneration(config)
print(f"num of params {tiny_model.num_parameters()}")

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

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

# Save
__a  			=					'''tiny-wmt19-en-de'''
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-de








from maths.prime_factors import prime_factors
def 				__lowerCamelCase						( UpperCAmelCase_						:		int						):




      """simple docstring"""





      if not isinstance(UpperCAmelCase_ ,  UpperCAmelCase_						):
            a						:Dict 							=       F'''Input value of [number={number}] must be an integer'''
            raise TypeError(UpperCAmelCase_						)
      if number < 1:
            raise ValueError('''Input must be a positive integer'''						)
      return -1 if len(prime_factors(UpperCAmelCase_						)						) % 2 else 1


if __name__ == "__main__":
     import doctest

     doctest.testmod()





