Merge pull request #101 from Project-Resilience/sdk

Import abstract classes from SDK

use_cases/eluc/README.md

@@ -141,6 +141,8 @@ the percentage of land that was changed. In other words decision makers have to:
 
 *Note: Before running anything make sure to set your python path environment variable with: `export PYTHONPATH=$PWD` while in the eluc directory.*
 
+Additionaly, the Project Resilience SDK is required to use the MVP. Currently it is not hosted on PyPi so it must be installed manually. To do so, clone the [Project Resilience SDK](https://github.com/Project-Resilience/sdk) and run pip install . in its root directory.
+
 ### Predictions
 
 Given **context** and **actions** -> predict **outcomes**  

use_cases/eluc/app/components/prediction.py

@@ -8,12 +8,13 @@
 from dash import html
 import pandas as pd
 
+from prsdk.predictors.predictor import Predictor
+
 from app import constants as app_constants
 from data import constants
 from persistence.persistors.hf_persistor import HuggingFacePersistor
 from persistence.serializers.neural_network_serializer import NeuralNetSerializer
 from persistence.serializers.sklearn_serializer import SKLearnSerializer
-from predictors.predictor import Predictor
 from predictors.percent_change.percent_change_predictor import PercentChangePredictor
 
 

use_cases/eluc/experiments/predictor_experiments.ipynb

@@ -26,11 +26,12 @@
     "from scipy.stats import ttest_1samp, ttest_ind\n",
     "from sklearn.metrics import mean_absolute_error\n",
     "\n",
+    "from prsdk.predictors.predictor import Predictor\n",
+    "\n",
     "from data.eluc_data import ELUCData\n",
     "from data import constants\n",
     "from persistence.serializers.neural_network_serializer import NeuralNetSerializer\n",
     "from persistence.serializers.sklearn_serializer import SKLearnSerializer\n",
-    "from predictors.predictor import Predictor\n",
     "from predictors.neural_network.neural_net_predictor import NeuralNetPredictor\n",
     "from predictors.sklearn_predictor.sklearn_predictor import LinearRegressionPredictor, RandomForestPredictor"
    ]

use_cases/eluc/persistence/persistors/hf_persistor.py

@@ -5,7 +5,7 @@
 
 from huggingface_hub import HfApi, snapshot_download
 
-from persistence.persistors.persistor import Persistor
+from prsdk.persistence.persistors.persistor import Persistor
 
 
 class HuggingFacePersistor(Persistor):
@@ -27,7 +27,7 @@ def persist(self, model, model_path: Path, repo_id: str, **persistence_args):
         then uploads the model to a HuggingFace repo.
         """
         # Save model and write readme
-        self.file_serializer.save(model, model_path)
+        self.serializer.save(model, model_path)
         self.write_readme(model_path)
 
         # Get token if it exists
@@ -58,7 +58,7 @@ def from_pretrained(self, path_or_url: str, **hf_args):
         """
         path = Path(path_or_url)
         if path.exists() and path.is_dir():
-            return self.file_serializer.load(path)
+            return self.serializer.load(path)
         # TODO: Need a try except block to catch download errors
         url_path = path_or_url.replace("/", "--")
         local_dir = hf_args.get("local_dir", f"huggingface_models/{url_path}")
@@ -67,4 +67,4 @@ def from_pretrained(self, path_or_url: str, **hf_args):
             hf_args["local_dir"] = local_dir
             snapshot_download(repo_id=path_or_url, **hf_args)
 
-        return self.file_serializer.load(Path(local_dir))
+        return self.serializer.load(Path(local_dir))

use_cases/eluc/persistence/serializers/neural_network_serializer.py

@@ -7,7 +7,8 @@
 import joblib
 import torch
 
-from persistence.serializers.serializer import Serializer
+from prsdk.persistence.serializers.serializer import Serializer
+
 from predictors.neural_network.eluc_neural_net import ELUCNeuralNet
 from predictors.neural_network.neural_net_predictor import NeuralNetPredictor
 

use_cases/eluc/persistence/serializers/prescriptor_serializer.py

@@ -6,8 +6,9 @@
 
 import torch
 
+from prsdk.persistence.serializers.serializer import Serializer
+
 from data.eluc_encoder import ELUCEncoder
-from persistence.serializers.serializer import Serializer
 from prescriptors.nsga2.candidate import Candidate
 from prescriptors.nsga2.land_use_prescriptor import LandUsePrescriptor
 

use_cases/eluc/persistence/serializers/sklearn_serializer.py

@@ -6,7 +6,8 @@
 
 import joblib
 
-from persistence.serializers.serializer import Serializer
+from prsdk.persistence.serializers.serializer import Serializer
+
 from predictors.sklearn_predictor.sklearn_predictor import SKLearnPredictor
 
 

use_cases/eluc/predictors/custom/template/template_predictor.py

@@ -3,8 +3,9 @@
 """
 import pandas as pd
 
+from prsdk.predictors.predictor import Predictor
+
 from data import constants
-from predictors.predictor import Predictor
 
 
 class TemplatePredictor(Predictor):

use_cases/eluc/predictors/neural_network/neural_net_predictor.py

@@ -14,9 +14,10 @@
 from torch.utils.data import DataLoader
 from torch.utils.tensorboard import SummaryWriter
 
+from prsdk.predictors.predictor import Predictor
+
 from data import constants
 from data.torch_data import TorchDataset
-from predictors.predictor import Predictor
 from predictors.neural_network.eluc_neural_net import ELUCNeuralNet
 
 

use_cases/eluc/predictors/percent_change/percent_change_predictor.py

@@ -3,8 +3,9 @@
 """
 import pandas as pd
 
+from prsdk.predictors.predictor import Predictor
+
 from data import constants
-from predictors.predictor import Predictor
 
 
 class PercentChangePredictor(Predictor):

use_cases/eluc/predictors/scoring/scorer.py

@@ -8,10 +8,11 @@
 
 import pandas as pd
 
+from prsdk.predictors.predictor import Predictor
+
 import data.constants as constants
 from data.eluc_data import ELUCData
 from persistence.persistors.hf_persistor import HuggingFacePersistor
-from predictors.predictor import Predictor
 from predictors.scoring.validator import Validator
 
 

use_cases/eluc/predictors/sklearn_predictor/sklearn_predictor.py

@@ -8,8 +8,9 @@
 from sklearn.linear_model import LinearRegression
 from sklearn.ensemble import RandomForestRegressor
 
+from prsdk.predictors.predictor import Predictor
+
 from data import constants
-from predictors.predictor import Predictor
 
 
 class SKLearnPredictor(Predictor, ABC):

use_cases/eluc/prescriptors/heuristics/heuristics.py

@@ -5,8 +5,9 @@
 
 import pandas as pd
 
+from prsdk.prescriptors.prescriptor import Prescriptor
+
 from data import constants
-from prescriptors.prescriptor import Prescriptor
 
 
 class HeuristicPrescriptor(Prescriptor, ABC):

use_cases/eluc/prescriptors/nsga2/land_use_prescriptor.py

@@ -6,11 +6,12 @@
 import torch
 from torch.utils.data import DataLoader
 
+from prsdk.prescriptors.prescriptor import Prescriptor
+
 from data import constants
 from data.eluc_data import ELUCEncoder
 from data.torch_data import TorchDataset
 from prescriptors.nsga2.candidate import Candidate
-from prescriptors.prescriptor import Prescriptor
 
 
 class LandUsePrescriptor(Prescriptor):

use_cases/eluc/prescriptors/nsga2/trainer.py

@@ -10,10 +10,11 @@
 import torch
 from torch.utils.data import DataLoader
 
+from prsdk.predictors.predictor import Predictor
+
 from data import constants
 from data.eluc_data import ELUCEncoder
 from data.torch_data import TorchDataset
-from predictors.predictor import Predictor
 from prescriptors.nsga2 import nsga2_utils
 from prescriptors.nsga2.candidate import Candidate
 from prescriptors.nsga2.land_use_prescriptor import LandUsePrescriptor

use_cases/eluc/prescriptors/prescriptor_manager.py

@@ -5,8 +5,8 @@
 """
 import pandas as pd
 
-from predictors.predictor import Predictor
-from prescriptors.prescriptor import Prescriptor
+from prsdk.predictors.predictor import Predictor
+from prsdk.prescriptors.prescriptor import Prescriptor
 
 
 class PrescriptorManager():

use_cases/eluc/requirements.txt

@@ -19,6 +19,7 @@ numpy==1.23.5
 pandas==1.5.3
 plotly==5.14.1
 protobuf==3.20.3
+-e git+https://github.com/Project-Resilience/sdk.git@368bcb03378d5456e98f5c839e264f8c117d5abb#egg=prsdk
 pylint==2.17.4
 regionmask==0.10.0
 scikit-learn==1.2.2