Forever running while loop in Reinforcement Learning agent evaluation

Question

#Evaluating agents performance
total_epochs, total_penalties = 0, 0
episodes = 1

for _ in range(episodes):
  state = env.reset()
  epochs, penalties, reward = 0 ,0 ,0

  done = False

  while not done:
    state, reward, done, info = env.step(np.argmax(q_table[state]))

    if reward == -10:
      penalties += 1

    epochs += 1

  total_penalties += penalties
  total_epochs += epochs

print(f"Results after {episodes} episodes")
print(f"Averge Timestep: {total_epochs / episodes}")
print(f"Average penalties: {total_penalties / episodes}")

The execution is forever struck on line {state, reward, done, info = env.step(np.argmax(q_table[state])}

#specifically on np.argmax part

i tried breaking down the code and its working fine individually,

the np.argmax(q_table[state]) line if wroking as a standalone but as soon as i put it in while loop the exection is struck forever there.