Errors in model.fit

[spatiallysaying]

I am encountering errors when running the Language model notbook /usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:1844: UserWarning: Model.fit_generator is deprecated and will be removed in a future version. Please use Model.fit, which supports generators. warnings.warn('Model.fit_generator is deprecated and '

---

ValueError Traceback (most recent call last)

in () 1 metrics = model.fit_generator(generator_step["valid"]["g"], generator_step["valid"]["s"], 2 validation_data=generator_step["test"]["g"], validation_steps=generator_step["test"]["s"], ----> 3 epochs=10, verbose=0, callbacks=[ReportCallback()])

10 frames

/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/func_graph.py in wrapper(*args, **kwargs) 975 except Exception as e: # pylint:disable=broad-except 976 if hasattr(e, "ag_error_metadata"): --> 977 raise e.ag_error_metadata.to_exception(e) 978 else: 979 raise

ValueError: in user code:

/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:805 train_function  *
    return step_function(self, iterator)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:795 step_function  **
    outputs = model.distribute_strategy.run(run_step, args=(data,))
/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/distribute_lib.py:1259 run
    return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/distribute_lib.py:2730 call_for_each_replica
    return self._call_for_each_replica(fn, args, kwargs)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/distribute_lib.py:3417 _call_for_each_replica
    return fn(*args, **kwargs)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:788 run_step  **
    outputs = model.train_step(data)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:757 train_step
    self.optimizer.minimize(loss, self.trainable_variables, tape=tape)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/optimizer_v2/optimizer_v2.py:498 minimize
    return self.apply_gradients(grads_and_vars, name=name)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/optimizer_v2/optimizer_v2.py:598 apply_gradients
    grads_and_vars = optimizer_utils.filter_empty_gradients(grads_and_vars)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/optimizer_v2/utils.py:79 filter_empty_gradients
    ([v.name for _, v in grads_and_vars],))

ValueError: No gradients provided for any variable: ['embedding/embeddings:0', 'lstm/lstm_cell/kernel:0', 'lstm/lstm_cell/recurrent_kernel:0', 'lstm/lstm_cell/bias:0', 'time_distributed/kernel:0', 'time_distributed/bias:0'].