InvalidArgumentError: Matrix size-incompatible: In[0]: [1408,1], In[1]: [5,5] [[{{node loss/crf_1_loss/MatMul_1}}]]

[paktiger]

history = model.fit(X_tr, np.array(y_tr), batch_size=32, epochs=5, validation_split=0.1, verbose=1)
I have tried the above command and I am getting the following errors:
Train on 3495 samples, validate on 389 samples
Epoch 1/5

InvalidArgumentError Traceback (most recent call last)
in
----> 1 history = model.fit(X_tr, np.array(y_tr), batch_size=32, epochs=5, validation_split=0.1, verbose=1)

~\Anaconda3\lib\site-packages\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, **kwargs)
1037 initial_epoch=initial_epoch,
1038 steps_per_epoch=steps_per_epoch,
-> 1039 validation_steps=validation_steps)
1040
1041 def evaluate(self, x=None, y=None,

~\Anaconda3\lib\site-packages\keras\engine\training_arrays.py in fit_loop(model, f, ins, out_labels, batch_size, epochs, verbose, callbacks, val_f, val_ins, shuffle, callback_metrics, initial_epoch, steps_per_epoch, validation_steps)
197 ins_batch[i] = ins_batch[i].toarray()
198
--> 199 outs = f(ins_batch)
200 outs = to_list(outs)
201 for l, o in zip(out_labels, outs):

~\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py in call(self, inputs)
2713 return self._legacy_call(inputs)
2714
-> 2715 return self._call(inputs)
2716 else:
2717 if py_any(is_tensor(x) for x in inputs):

~\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py in _call(self, inputs)
2673 fetched = self._callable_fn(*array_vals, run_metadata=self.run_metadata)
2674 else:
-> 2675 fetched = self._callable_fn(*array_vals)
2676 return fetched[:len(self.outputs)]
2677

~\Anaconda3\lib\site-packages\tensorflow\python\client\session.py in call(self, *args, **kwargs)
1437 ret = tf_session.TF_SessionRunCallable(
1438 self._session._session, self._handle, args, status,
-> 1439 run_metadata_ptr)
1440 if run_metadata:
1441 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

~\Anaconda3\lib\site-packages\tensorflow\python\framework\errors_impl.py in exit(self, type_arg, value_arg, traceback_arg)
526 None, None,
527 compat.as_text(c_api.TF_Message(self.status.status)),
--> 528 c_api.TF_GetCode(self.status.status))
529 # Delete the underlying status object from memory otherwise it stays alive
530 # as there is a reference to status from this from the traceback due to

InvalidArgumentError: Index out of range using input dim 2; input has only 2 dims
[[{{node loss/crf_1_loss/strided_slice_5}}]]

Please guide me how can I solve these errors. I am new to keras and python.

[helpmefindaname]

The error is in how you build your model and that part you're not showing

[cbk197]

can you show. how do you fix it ? i have same a problem.

[mathshangw]

excuse me did someone solve it ?