async def model_fingerprint(
file_importer: "TrainingDataImporter") -> Fingerprint:
"""Create a model fingerprint from its used configuration and training data.
Args:
file_importer: File importer which provides the training data and model config.
Returns:
The fingerprint.
"""
from rasa.core.domain import Domain
import rasa
import time
# bf mod
# config = await file_importer.get_config()
domain = await file_importer.get_domain()
# stories = await file_importer.get_stories()
stories_hash = await file_importer.get_stories_hash()
nlu_data = await file_importer.get_nlu_data()
nlu_config = await file_importer.get_nlu_config()
core_config = await file_importer.get_core_config()
domain_dict = domain.as_dict()
templates = domain_dict.pop("responses")
domain_without_nlg = Domain.from_dict(domain_dict)
return {
FINGERPRINT_CONFIG_KEY:
_get_hash_of_config(core_config, exclude_keys=CONFIG_MANDATORY_KEYS),
FINGERPRINT_CONFIG_CORE_KEY:
_get_hash_of_config(core_config,
include_keys=CONFIG_MANDATORY_KEYS_CORE),
FINGERPRINT_CONFIG_NLU_KEY: {
lang: _get_hash_of_config(config,
include_keys=CONFIG_MANDATORY_KEYS_NLU)
for (lang, config) in nlu_config.items()
},
FINGERPRINT_DOMAIN_WITHOUT_NLG_KEY:
hash(domain_without_nlg),
FINGERPRINT_NLG_KEY:
get_dict_hash(templates),
FINGERPRINT_NLU_DATA_KEY:
{lang: hash(nlu_data[lang])
for lang in nlu_data},
FINGERPRINT_STORIES_KEY:
stories_hash,
FINGERPRINT_TRAINED_AT_KEY:
time.time(),
FINGERPRINT_RASA_VERSION_KEY:
rasa.__version__,
}
async def model_fingerprint(
file_importer: "TrainingDataImporter") -> Fingerprint:
"""Create a model fingerprint from its used configuration and training data.
Args:
file_importer: File importer which provides the training data and model config.
Returns:
The fingerprint.
"""
import time
# bf mod
config = await file_importer.get_config()
domain = await file_importer.get_domain()
stories_hash = await file_importer.get_stories_hash()
nlu_data = await file_importer.get_nlu_data()
nlu_config = await file_importer.get_nlu_config()
responses = domain.templates
# Do a copy of the domain to not change the actual domain (shallow is enough)
domain = copy.copy(domain)
# don't include the response texts in the fingerprint.
# Their fingerprint is separate.
domain.templates = []
return {
FINGERPRINT_CONFIG_KEY:
_get_hash_of_config(config, exclude_keys=CONFIG_KEYS),
FINGERPRINT_CONFIG_CORE_KEY:
_get_hash_of_config(config, include_keys=CONFIG_KEYS_CORE),
FINGERPRINT_CONFIG_NLU_KEY: {
lang: _get_hash_of_config(config, include_keys=CONFIG_KEYS_NLU)
for (lang, config) in nlu_config.items()
} if len(nlu_config) else "",
FINGERPRINT_DOMAIN_WITHOUT_NLG_KEY:
hash(domain),
FINGERPRINT_NLG_KEY:
get_dict_hash(responses),
FINGERPRINT_PROJECT:
project_fingerprint(),
FINGERPRINT_NLU_DATA_KEY:
{lang: hash(nlu_data[lang])
for lang in nlu_data},
FINGERPRINT_STORIES_KEY:
stories_hash,
FINGERPRINT_TRAINED_AT_KEY:
time.time(),
FINGERPRINT_RASA_VERSION_KEY:
rasa.__version__, # pytype: disable=module-attr
}
def _get_hash_of_config(
config: Optional[Dict],
include_keys: Optional[List[Text]] = None,
exclude_keys: Optional[List[Text]] = None,
) -> Text:
if not config:
return ""
keys = include_keys or list(filter(lambda k: k not in exclude_keys, config.keys()))
sub_config = {k: config[k] for k in keys if k in config}
return get_dict_hash(sub_config)
async def model_fingerprint(
file_importer: "TrainingDataImporter") -> Fingerprint:
"""Create a model fingerprint from its used configuration and training data.
Args:
file_importer: File importer which provides the training data and model config.
Returns:
The fingerprint.
"""
import time
config = await file_importer.get_config()
domain = await file_importer.get_domain()
stories = await file_importer.get_stories()
nlu_data = await file_importer.get_nlu_data()
responses = domain.templates
# don't include the response texts in the fingerprint.
# Their fingerprint is separate.
domain.templates = []
return {
FINGERPRINT_CONFIG_KEY:
_get_hash_of_config(config, exclude_keys=CONFIG_KEYS),
FINGERPRINT_CONFIG_CORE_KEY:
_get_hash_of_config(config, include_keys=CONFIG_KEYS_CORE),
FINGERPRINT_CONFIG_NLU_KEY:
_get_hash_of_config(config, include_keys=CONFIG_KEYS_NLU),
FINGERPRINT_DOMAIN_WITHOUT_NLG_KEY:
hash(domain),
FINGERPRINT_NLG_KEY:
get_dict_hash(responses),
FINGERPRINT_PROJECT:
project_fingerprint(),
FINGERPRINT_NLU_DATA_KEY:
hash(nlu_data),
FINGERPRINT_STORIES_KEY:
hash(stories),
FINGERPRINT_TRAINED_AT_KEY:
time.time(),
FINGERPRINT_RASA_VERSION_KEY:
rasa.__version__, # pytype: disable=module-attr
}
def _get_hash_of_config(
config_path: Text,
include_keys: Optional[List[Text]] = None,
exclude_keys: Optional[List[Text]] = None,
) -> Text:
if not config_path or not os.path.exists(config_path):
return ""
try:
config_dict = rasa.utils.io.read_config_file(config_path)
keys = include_keys or list(
filter(lambda k: k not in exclude_keys, config_dict.keys()))
sub_config = dict(
(k, config_dict[k]) for k in keys if k in config_dict)
return get_dict_hash(sub_config)
except yaml.parser.ParserError as e:
logger.debug("Failed to read config file '{}'. Error: {}".format(
config_path, e))
return ""
async def test_create_fingerprint_from_invalid_paths(project, project_files):
from rasa.nlu.training_data import TrainingData
from rasa.core.training.structures import StoryGraph
project_files = _project_files(project, *project_files)
expected = _fingerprint(
config="",
config_nlu="",
config_core="",
domain=hash(Domain.empty()),
nlg=get_dict_hash(Domain.empty().templates),
stories=0,
nlu={}, # bf
rasa_version=rasa.__version__,
)
actual = await model_fingerprint(project_files)
assert actual[FINGERPRINT_TRAINED_AT_KEY] is not None
del actual[FINGERPRINT_TRAINED_AT_KEY]
del expected[FINGERPRINT_TRAINED_AT_KEY]
assert actual == expected
