Update __init__.py

Author: Programmer-RD-AI

DimRed/__init__.py

@@ -1,13 +1,51 @@
+from sklearn.pipeline import make_pipeline
 import pandas as pd
 import matplotlib.pyplot as plt
+from sklearn.metrics import classification_report
+from sklearn.preprocessing import LabelEncoder
 import numpy as np
+from pprint import pprint
+import json
+import wandb
 from sklearn.model_selection import ParameterGrid
 # TODO make_pipeline is excessive
+from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import StandardScaler
+import xgboost as xgb
+import lightgbm as lgb
+from sklearn.linear_model import LogisticRegression
+from sklearn.svm import SVC
+from sklearn.tree import DecisionTreeClassifier
+from sklearn.ensemble import RandomForestClassifier
+from sklearn.neighbors import KNeighborsClassifier
+import threading
+import cupy as cp
+import warnings
+from dotenv import load_dotenv
+from tqdm import tqdm
 from sklearn.pipeline import Pipeline, make_pipeline
 from typing import *
-from sklearn.pipeline import make_pipeline
+import seaborn as sns
+from sklearn.model_selection import GridSearchCV
+import math
+import os
+import random
+from sklearn.decomposition import PCA, IncrementalPCA
+from sklearn import datasets
+from wandb.lightgbm import wandb_callback, log_summary
+import logging
+from wandb.xgboost import WandbCallback
+load_dotenv()
+PROJECT_NAME = os.getenv("PROJECT_NAME")
+logging.getLogger('lightgbm').setLevel(logging.WARNING)
+logging.getLogger("wandb").setLevel(logging.ERROR)
+os.environ["WANDB_SILENT"] = "true"
+warnings.filterwarnings("ignore")
+RANDOM_STATE = 42
+random.seed(RANDOM_STATE)
+np.random.seed(RANDOM_STATE)
+from DimRed.config import *
 from DimRed.helper_functions import *
+from DimRed.analysis import *
 from DimRed.variation import *
 from DimRed.evaluation import *
-from DimRed.analysis import *