code: def eval_and_log_metrics(prefix, actual, pred, epoch):
      rmse = np.sqrt(mean_squared_error(actual, pred))
      mlflow.log_metric(f"{prefix}_rmse", rmse, step=epoch)
      return rmse
  
imports: import math
  import warnings
  import click
  import numpy
  import pandas
  from sklearn.metrics import mean_squared_error
  from sklearn.model_selection import train_test_split
  from tensorflow import keras
  from tensorflow.keras.callbacks import Callback
  from tensorflow.keras.layers import Dense, Lambda
  from tensorflow.keras.models import Sequential
  from tensorflow.keras.optimizers import SGD
  import mlflow
  from mlflow.models import infer_signature
label_desc: Use image node_id 1 for calling a global function with example usage: eval_and_log_metrics(prefix, actual, pred, epoch) and returns: rmse