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 ?