Why in R "predict" function of Keras doesn't recognize correct input dimensions?

Question

I'have implemented a keras lstm network in R and I can train it and use correctly the fit function. But when I use "predict" function, I meet following errors:

pred <- base_model %>% predict(matchsetarray)

WARNING:tensorflow:Model was constructed with shape (96, 2, 26) for input KerasTensor(type_spec=TensorSpec(shape=(96, 2, 26), dtype=tf.float32, name='lstm_3_input'), name='lstm_3_input', description="created by layer 'lstm_3_input'"), but it was called on an input with incompatible shape (32, 2, 26). Error in py_call_impl(callable, dots$args, dots$keywords) : ValueError: in user code:

File "C:\Users\Utente\AppData\Local\R-MINI~1\envs\R-RETI~1\lib\site-packages\keras\engine\training.py", line 1801, in predict_function  *
    return step_function(self, iterator)
File "C:\Users\Utente\AppData\Local\R-MINI~1\envs\R-RETI~1\lib\site-packages\keras\engine\training.py", line 1790, in step_function  **
    outputs = model.distribute_strategy.run(run_step, args=(data,))
File "C:\Users\Utente\AppData\Local\R-MINI~1\envs\R-RETI~1\lib\site-packages\keras\engine\training.py", line 1783, in run_step  **
    outputs = model.predict_step(data)
File "C:\Users\Utente\AppData\Local\R-MINI~1\envs\R-RETI~1\lib\site-packages\keras\engine\training.py", line 1751, in predict_step
    return self(x, training=False)
File "C:\Users\Utente\AppData\Local\R-MINI~1\envs\R-RETI~1\lib\site-packages\keras\utils\traceback_utils.py", line 67, in error_handler
    raise e.with_traceback(filtered_tb) from None
File "C:\Users\

However the dimension of predict input is (96,2,26), but "predict" consider the input "matchsetarray" of dimension (32, 2, 26). Could I force predict to read teh correct format?

I tryed to verify the dimension of input "matchsetarray":

dim(matchsetarray) [1] 96 2 26

It's the correct dimension expected by "predict" function.