AttributeError: 'tuple' object has no attribute 'shape' when trying to run

[elapt1c]

it wont work no matter how many times i try i still get the same error: AttributeError: 'tuple' object has no attribute 'shape'

[elapt1c]

full output:

File ~\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\keras\utils\traceback_utils.py:67, in filter_traceback..error_handler(*args, **kwargs)
65 except Exception as e: # pylint: disable=broad-except
66 filtered_tb = _process_traceback_frames(e.traceback)
---> 67 raise e.with_traceback(filtered_tb) from None
68 finally:
69 del filtered_tb

File ~\AppData\Local\Temp_autograph_generated_file3lnwlhct.py:15, in outer_factory..inner_factory..tf__train_function(iterator)
13 try:
14 do_return = True
---> 15 retval = ag__.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope)
16 except:
17 do_return = False

AttributeError: in user code:

File "C:\Users\Owner\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\keras\engine\training.py", line 1051, in train_function  *
    return step_function(self, iterator)
File "C:\Users\Owner\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\keras\engine\training.py", line 1040, in step_function  **
    outputs = model.distribute_strategy.run(run_step, args=(data,))
File "C:\Users\Owner\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\keras\engine\training.py", line 1030, in run_step  **
    outputs = model.train_step(data)
File "C:\Users\Owner\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\keras\engine\training.py", line 894, in train_step
    return self.compute_metrics(x, y, y_pred, sample_weight)
File "C:\Users\Owner\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\keras\engine\training.py", line 987, in compute_metrics
    self.compiled_metrics.update_state(y, y_pred, sample_weight)
File "C:\Users\Owner\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\keras\engine\compile_utils.py", line 480, in update_state
    self.build(y_pred, y_true)
File "C:\Users\Owner\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\keras\engine\compile_utils.py", line 393, in build
    self._metrics = tf.__internal__.nest.map_structure_up_to(
File "C:\Users\Owner\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\keras\engine\compile_utils.py", line 526, in _get_metric_objects
    return [self._get_metric_object(m, y_t, y_p) for m in metrics]
File "C:\Users\Owner\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\keras\engine\compile_utils.py", line 526, in <listcomp>
    return [self._get_metric_object(m, y_t, y_p) for m in metrics]
File "C:\Users\Owner\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\keras\engine\compile_utils.py", line 547, in _get_metric_object
    y_t_rank = len(y_t.shape.as_list())

AttributeError: 'tuple' object has no attribute 'shape'

[mithunparab]

I resolve this issue by modifying the lstm_model.fit()
From: 👎🏻 ❌

lstm_model.fit(x=[training_encoder_input, training_decoder_input], y=[training_decoder_output],
    validation_data=([validation_encoder_input, validation_decoder_input], [validation_decoder_output]),
          batch_size=64, epochs=100)

To: 👍🏻 ✅

lstm_model.fit(x=[training_encoder_input, training_decoder_input], y=training_decoder_output,
    validation_data=([validation_encoder_input, validation_decoder_input], validation_decoder_output),
          batch_size=64, epochs=100)