input: 
  import numpy as np
  import tensorflow as tf
  
  def create_model(input_shape: int):
      """ Create a neural network model that takes in a given trajectory of stock prices and predicts the stock price for the next day.
      >>> model = create_model(7)
      >>> input_data = np.array([[10, 10.4, 10.5, 10.6, 10.7, 10.9, 11]])
      >>> predictions = model.predict(input_data)
      >>> print(f"Predicted stock price for the next day is: {predictions[0][0]}")
      Predicted stock price for the next day is: X
      """
      model = tf.keras.Sequential([
          tf.keras.layers.Dense(64, activation='relu', input_shape=(input_shape, )),
          tf.keras.layers.Dense(1)
      ])
  
      model.compile(loss='mean_squared_error', 
                    optimizer='adam',
                    metrics=['accuracy'])
  
      return model
  
output:     model.fit(np.zeros((1, input_shape)), np.zeros((1, 1)), epochs=1, verbose=0)