InternalError: Dst tensor is not initialized. [[{{node IteratorGetNext/_2}}]] [Op:__inference_distributed_function_24557]

[Adesoji1]

WARNING:tensorflow:sample_weight modes were coerced from
...
to
['...']
WARNING:tensorflow:sample_weight modes were coerced from
...
to
['...']
WARNING:tensorflow:sample_weight modes were coerced from
...
to
['...']
WARNING:tensorflow:sample_weight modes were coerced from
...
to
['...']
Train for 11523 steps, validate for 4153 steps
Epoch 1/5
1/11523 [..............................] - ETA: 33:47:16

InternalError Traceback (most recent call last)
in
6 epochs=EPOCHS,
7 validation_data=validation_generator,
----> 8 validation_steps=validation_generator.samples//validation_generator.batch_size)

~\anaconda3\envs\ev_2\lib\site-packages\tensorflow_core\python\util\deprecation.py in new_func(*args, **kwargs)
322 'in a future version' if date is None else ('after %s' % date),
323 instructions)
--> 324 return func(*args, **kwargs)
325 return tf_decorator.make_decorator(
326 func, new_func, 'deprecated',

~\anaconda3\envs\ev_2\lib\site-packages\tensorflow_core\python\keras\engine\training.py in fit_generator(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, validation_freq, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)
1304 use_multiprocessing=use_multiprocessing,
1305 shuffle=shuffle,
-> 1306 initial_epoch=initial_epoch)
1307
1308 @deprecation.deprecated(

~\anaconda3\envs\ev_2\lib\site-packages\tensorflow_core\python\keras\engine\training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs)
817 max_queue_size=max_queue_size,
818 workers=workers,
--> 819 use_multiprocessing=use_multiprocessing)
820
821 def evaluate(self,

~\anaconda3\envs\ev_2\lib\site-packages\tensorflow_core\python\keras\engine\training_v2.py in fit(self, model, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs)
340 mode=ModeKeys.TRAIN,
341 training_context=training_context,
--> 342 total_epochs=epochs)
343 cbks.make_logs(model, epoch_logs, training_result, ModeKeys.TRAIN)
344

~\anaconda3\envs\ev_2\lib\site-packages\tensorflow_core\python\keras\engine\training_v2.py in run_one_epoch(model, iterator, execution_function, dataset_size, batch_size, strategy, steps_per_epoch, num_samples, mode, training_context, total_epochs)
126 step=step, mode=mode, size=current_batch_size) as batch_logs:
127 try:
--> 128 batch_outs = execution_function(iterator)
129 except (StopIteration, errors.OutOfRangeError):
130 # TODO(kaftan): File bug about tf function and errors.OutOfRangeError?

~\anaconda3\envs\ev_2\lib\site-packages\tensorflow_core\python\keras\engine\training_v2_utils.py in execution_function(input_fn)
96 # numpy translates Tensors to values in Eager mode.
97 return nest.map_structure(_non_none_constant_value,
---> 98 distributed_function(input_fn))
99
100 return execution_function

~\anaconda3\envs\ev_2\lib\site-packages\tensorflow_core\python\eager\def_function.py in call(self, *args, **kwds)
566 xla_context.Exit()
567 else:
--> 568 result = self._call(*args, **kwds)
569
570 if tracing_count == self._get_tracing_count():

~\anaconda3\envs\ev_2\lib\site-packages\tensorflow_core\python\eager\def_function.py in _call(self, *args, **kwds)
597 # In this case we have created variables on the first call, so we run the
598 # defunned version which is guaranteed to never create variables.
--> 599 return self._stateless_fn(*args, **kwds) # pylint: disable=not-callable
600 elif self._stateful_fn is not None:
601 # Release the lock early so that multiple threads can perform the call

~\anaconda3\envs\ev_2\lib\site-packages\tensorflow_core\python\eager\function.py in call(self, *args, **kwargs)
2361 with self._lock:
2362 graph_function, args, kwargs = self._maybe_define_function(args, kwargs)
-> 2363 return graph_function._filtered_call(args, kwargs) # pylint: disable=protected-access
2364
2365 @Property

~\anaconda3\envs\ev_2\lib\site-packages\tensorflow_core\python\eager\function.py in _filtered_call(self, args, kwargs)
1609 if isinstance(t, (ops.Tensor,
1610 resource_variable_ops.BaseResourceVariable))),
-> 1611 self.captured_inputs)
1612
1613 def _call_flat(self, args, captured_inputs, cancellation_manager=None):

~\anaconda3\envs\ev_2\lib\site-packages\tensorflow_core\python\eager\function.py in _call_flat(self, args, captured_inputs, cancellation_manager)
1690 # No tape is watching; skip to running the function.
1691 return self._build_call_outputs(self._inference_function.call(
-> 1692 ctx, args, cancellation_manager=cancellation_manager))
1693 forward_backward = self._select_forward_and_backward_functions(
1694 args,

~\anaconda3\envs\ev_2\lib\site-packages\tensorflow_core\python\eager\function.py in call(self, ctx, args, cancellation_manager)
543 inputs=args,
544 attrs=("executor_type", executor_type, "config_proto", config),
--> 545 ctx=ctx)
546 else:
547 outputs = execute.execute_with_cancellation(

~\anaconda3\envs\ev_2\lib\site-packages\tensorflow_core\python\eager\execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
65 else:
66 message = e.message
---> 67 six.raise_from(core._status_to_exception(e.code, message), None)
68 except TypeError as e:
69 keras_symbolic_tensors = [

~\anaconda3\envs\ev_2\lib\site-packages\six.py in raise_from(value, from_value)

InternalError: Dst tensor is not initialized.
[[{{node IteratorGetNext/_2}}]] [Op:__inference_distributed_function_24557]

Function call stack:
distributed_function

on windows ebvironment, please how do i resolve this issue?