getting rid of some more problematic type hints

cluster/clusterer.py

@@ -1,8 +1,6 @@
 from dataclasses import dataclass
 from typing import Callable
 
-import numpy as np
-
 
 @dataclass
 class Clusterer:
@@ -11,8 +9,8 @@ class Clusterer:
 
     def eval(
         self,
-        pred_labels: np.array,
-        true_labels: np.array,
+        pred_labels,
+        true_labels,
     ) -> None:
         ...
 

cluster/distance.py

@@ -7,7 +7,7 @@ import numpy as np
 def euclidean(
     point: np.array,
     data: np.array,
-) -> np.array:
+):
     """
     Computed the euclidean distance
     between a point and the rest 

cluster/opts.py

@@ -3,7 +3,7 @@ from cluster.kmedoids import Kmedoids
 from cluster.kmeans import Kmeans
 
 
-clustering_methods: dict[str, Clusterer] = {
+clustering_methods = {
     "kmeans-clustering": Kmeans,
     "kmedoids-clustering": Kmedoids,
 }

cluster/plot.py

@@ -4,13 +4,12 @@ import numpy as np
 import matplotlib
 import matplotlib.pyplot as plt 
 import seaborn as sns
-from cluster.clusterer import Clusterer
 
 
 matplotlib.use("Agg")
 sns.set()
 
-def plot(clusterer: Clusterer, X: np.array) -> None:
+def plot(clusterer, X) -> None:
     cluster_data = clusterer.to_dict(X)["clusters"]
     # plot the clusters and data points
     fig, ax = plt.subplots(figsize=(8, 6))
@@ -36,7 +35,7 @@ def plot(clusterer: Clusterer, X: np.array) -> None:
     clusterer.plot = plt_bytes(fig)
 
 
-def plt_bytes(fig) -> str:
+def plt_bytes(fig):
     buf = io.BytesIO()
     fig.savefig(buf, format="png")
     plt.close(fig)

neural_network/main.py

@@ -6,7 +6,7 @@ from neural_network.backprop import bp
 from neural_network.plot import plot
 
 
-def init(X: np.array, hidden_size: int) -> dict:
+def init(X: np.array, hidden_size: int):
     """
     returns a dictionary containing randomly initialized
     weights and biases to start off the neural_network

neural_network/plot.py

@@ -4,11 +4,10 @@ import io
 import seaborn as sns
 import matplotlib
 import matplotlib.pyplot as plt
-from neural_network.neural_network import NeuralNetwork
 
 matplotlib.use("Agg")
 
-def plot(model: NeuralNetwork) -> None:
+def plot(model) -> None:
     sns.set()
     fig, ax = plt.subplots()
     sns.lineplot(