input: Write a python function to perform k-means clustering on a given dataset and return the cluster labels.
  ```python
  assert kmeans_clustering('data.txt', 3, 0) == [expected labels array here]
  assert kmeans_clustering('data.txt', 4, 42) == [expected labels array here]
  assert kmeans_clustering('data.txt', 2, 7) == [expected labels array here]
output: def kmeans_clustering(file_path, k, random_state):
      import numpy as np
      from sklearn.cluster import KMeans
  
      # Load data from the file
      data = np.loadtxt(file_path, delimiter=',')
  
      # Perform K-means clustering
      kmeans = KMeans(n_clusters=k, random_state=random_state)
      kmeans.fit(data)
  
      # Return the cluster labels
      return kmeans.labels_.tolist()