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feat(Inference): pipeline wired up (#171)

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* feat: Basic pipeline extended.

* feat: Added conversion of model list to existing structure (model_name, model_in_time). Fixed loading of previous models and dicts.

* fix: Had an unfinished function.

* fix: Inference wasn't getting model_over_time. Now transformations are not getting it either yet.

Co-authored-by: Daniel Szemerey <szemereydaniel@gmail.com>
This commit is contained in:
Mark Aron Szulyovszky
2022-01-14 10:34:28 +01:00
committed by GitHub
co-authored by Daniel Szemerey
parent 4aefba33ea
commit 797d45d036
9 changed files with 89 additions and 77 deletions
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models/saving.py
+9 -6
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@@ -7,10 +7,11 @@ from reporting.types import Reporting
def save_models(all_models_for_all_assets: list[Reporting.Asset], data_config:dict, training_config:dict) -> None:
def save_models(all_models_for_all_assets: list[Reporting.Asset], data_config:dict, training_config:dict, model_config:dict) -> None:
dict_for_pickle = dict()
dict_for_pickle['training_config'] = training_config
dict_for_pickle['data_config'] = data_config
dict_for_pickle['model_config'] = model_config
dict_for_pickle['all_models_for_all_assets'] = all_models_for_all_assets
date_string = datetime.datetime.now().strftime("%Y-%m-%d-%H-%M")
@@ -22,7 +23,7 @@ def save_models(all_models_for_all_assets: list[Reporting.Asset], data_config:di
pickle.dump( dict_for_pickle, open( "output/models/{}.p".format(date_string), "wb" ) )
def load_models(file_name:Union[str, None]) -> tuple[dict, dict, dict]:
def load_models(file_name:Union[str, None]) -> tuple[list[Reporting.Asset], dict, dict, dict]:
if file_name is None:
warnings.warn("No file name provided, will load latest models and configurations.")
@@ -31,10 +32,12 @@ def load_models(file_name:Union[str, None]) -> tuple[dict, dict, dict]:
assert len(files_in_directory) > 0, "No models found in output/models."
file_name = sorted(files_in_directory)[-1]
all_models_for_all_assets = pickle.load( open( "output/models/{}".format(file_name), "rb" ) )
packacked_dict = pickle.load( open( "output/models/{}".format(file_name), "rb" ) )
data_config = all_models_for_all_assets['data_config']
training_config = all_models_for_all_assets['training_config']
data_config = packacked_dict.pop("data_config", None)
training_config = packacked_dict.pop("training_config", None)
model_config = packacked_dict.pop("model_config", None)
all_models_for_all_assets = packacked_dict.pop("all_models_for_all_assets", None)
return all_models_for_all_assets, data_config, training_config
return all_models_for_all_assets, data_config, training_config, model_config