remove unused imports

autoemulate/compare.py

@@ -1,16 +1,9 @@
-import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
 from sklearn.base import BaseEstimator
 from sklearn.decomposition import PCA
-from sklearn.metrics import make_scorer
-from sklearn.model_selection import cross_validate
 from sklearn.model_selection import KFold
-from sklearn.model_selection import PredefinedSplit
-from sklearn.model_selection import train_test_split
-from sklearn.pipeline import Pipeline
 from sklearn.preprocessing import StandardScaler
-from sklearn.utils.validation import check_is_fitted
 from sklearn.utils.validation import check_X_y
 from tqdm.autonotebook import tqdm
 
@@ -27,7 +20,6 @@
 from autoemulate.plotting import _plot_model
 from autoemulate.printing import _print_setup
 from autoemulate.save import ModelSerialiser
-from autoemulate.utils import _ensure_2d
 from autoemulate.utils import _get_full_model_name
 from autoemulate.utils import _redirect_warnings
 from autoemulate.utils import get_model_name

autoemulate/cross_validate.py

@@ -5,8 +5,6 @@
 import pandas as pd
 from sklearn.metrics import make_scorer
 from sklearn.model_selection import cross_validate
-from sklearn.model_selection import PredefinedSplit
-from sklearn.model_selection import train_test_split
 
 from autoemulate.utils import get_model_name
 from autoemulate.utils import get_model_params

autoemulate/emulators/conditional_neural_process.py

@@ -9,7 +9,6 @@
 from sklearn.utils.validation import check_array
 from sklearn.utils.validation import check_is_fitted
 from sklearn.utils.validation import check_X_y
-from skopt.space import Real
 from skorch import NeuralNetRegressor
 from skorch.callbacks import EarlyStopping
 from skorch.callbacks import GradientNormClipping

autoemulate/emulators/gaussian_process_sklearn.py

@@ -10,7 +10,6 @@
 from sklearn.utils.validation import check_is_fitted
 from sklearn.utils.validation import check_X_y
 from skopt.space import Categorical
-from skopt.space import Integer
 from skopt.space import Real
 
 from autoemulate.utils import _suppress_convergence_warnings

autoemulate/emulators/gaussian_process_torch.py

@@ -1,30 +1,13 @@
-from copy import deepcopy
-
 import gpytorch
 import numpy as np
 import torch
-from scipy.stats import loguniform
-from scipy.stats import randint
 from sklearn.base import BaseEstimator
 from sklearn.base import RegressorMixin
-from sklearn.exceptions import DataConversionWarning
-from sklearn.metrics import r2_score
-from sklearn.model_selection import train_test_split
 from sklearn.preprocessing._data import _handle_zeros_in_scale
 from sklearn.utils import check_array
 from sklearn.utils import check_X_y
 from sklearn.utils.validation import check_is_fitted
-from skopt.space import Categorical
-from skopt.space import Integer
-from skopt.space import Real
-from skorch.callbacks import Checkpoint
-from skorch.callbacks import EarlyStopping
-from skorch.callbacks import EpochScoring
 from skorch.callbacks import LRScheduler
-from skorch.callbacks import ProgressBar
-from skorch.dataset import Dataset
-from skorch.dataset import ValidSplit
-from skorch.helper import predefined_split
 from skorch.probabilistic import ExactGPRegressor
 
 from autoemulate.emulators.gaussian_process_utils import EarlyStoppingCustom

autoemulate/emulators/polynomials.py

@@ -8,7 +8,6 @@
 from sklearn.utils.validation import check_is_fitted
 from sklearn.utils.validation import check_X_y
 from skopt.space import Categorical
-from skopt.space import Integer
 
 
 class SecondOrderPolynomial(BaseEstimator, RegressorMixin):

autoemulate/emulators/random_forest.py

@@ -7,7 +7,6 @@
 from sklearn.utils.validation import check_X_y
 from skopt.space import Categorical
 from skopt.space import Integer
-from skopt.space import Real
 
 
 class RandomForest(BaseEstimator, RegressorMixin):

autoemulate/logging_config.py

@@ -1,7 +1,6 @@
 import logging
 import os
 import sys
-import warnings
 from pathlib import Path
 
 

autoemulate/model_processing.py

@@ -2,9 +2,6 @@
 from sklearn.multioutput import MultiOutputRegressor
 from sklearn.pipeline import Pipeline
 
-from autoemulate.utils import get_model_name
-from autoemulate.utils import get_short_model_name
-
 
 def _turn_models_into_multioutput(models, y):
     """Turn single output models into multioutput models if y is 2D.

autoemulate/plotting.py

@@ -1,13 +1,11 @@
 import inspect
-import time
 
 import matplotlib.pyplot as plt
 import numpy as np
 from sklearn.metrics import PredictionErrorDisplay
 from sklearn.pipeline import Pipeline
 
 from autoemulate.utils import _ensure_2d
-from autoemulate.utils import get_model_name
 
 
 def _validate_inputs(cv_results, model_name):

autoemulate/save.py

@@ -1,10 +1,6 @@
-import json
-import os
 from pathlib import Path
 
 import joblib
-import numpy as np
-import sklearn
 
 from autoemulate.utils import get_model_name
 

tests/models/test_cnp.py

@@ -150,7 +150,8 @@ def cnp_module():
         output_dim=1,
         hidden_dim=32,
         latent_dim=64,
-        hidden_layers=2,
+        hidden_layers_enc=2,
+        hidden_layers_dec=2,
         activation=nn.ReLU,
     )