def __init__(self,
model_id: str = '',
model_name: str = '',
vector_length: int = '',
description: str = '',
paper: str = '',
repo: str = '',
architecture: str = 'Not stated.',
tasks: str = 'Not stated.',
release_date: date = '',
limitations: str = 'Not stated.',
installation: str = 'Not stated.',
example: str = 'Not stated.',
markdown_filepath: str = '',
**kwargs):
"""
Model definition.
Args:
model_id: the identity of the model. Required for AutoEncoder.
model_name: The name of the model
vector_length: The length of the vector
description: The description of the encoder
paper: The paper which dictates the encoder
repo: The repository fo the model
architecture: The architecture of the model.
task: The downstream task that the model was trained on
limitations: The limitations of the encoder
installation: How to isntall the encoder.
example: The example of the encoder
"""
self.model_id = model_id
self.model_name = model_name
self.vector_length = vector_length
self.description = description
self.paper = paper
self.repo = repo
self.architecture = architecture
self.tasks = tasks
self.release_date = release_date.__str__(
) if release_date is not None else None
self.limitations = limitations
self.installation = installation
self.example = example
self.markdown_filepath = markdown_filepath
for k, v in kwargs.items():
# assert( k in self.__class__.__allowed )
setattr(self, k, v)
if markdown_filepath != '':
self.from_markdown(markdown_filepath)
def get_logfile_name(self, log_date: date, log_number: int) -> str:
return self.logDir + '/' + log_date.__str__() + "_" + str(
log_number) + ".txt"
def get_boundaries(self, from_date: date, to_date: date) -> (int, int):
from_id = self._git.search_repositories(
query=from_date.__str__())[0].id
to_id = self._git.search_repositories(query=to_date.__str__())[0].id
return from_id, to_id
