code: def train_step(model, optimizer, x_train, y_train):
      with tf.GradientTape() as tape:
          predictions = model(x_train, training=True)
          loss = loss_object(y_train, predictions)
      grads = tape.gradient(loss, model.trainable_variables)
      optimizer.apply_gradients(zip(grads, model.trainable_variables))
  
      train_loss(loss)
      train_accuracy(y_train, predictions)
  
file_path: wandb/tests/functional_tests/t0_main/mp/13-synctb-gradienttape.py
imports: import argparse
  import datetime
  import numpy
  import tensorflow
  import wandb
label_desc: Use image node_id 1 for calling a global function with example usage: train_step(model, optimizer, x_train, y_train) without return types