zheng-da opened a new issue #10609: Gluon code fails in the normal mode but succeeds in the hybrid mode. URL: https://github.com/apache/incubator-mxnet/issues/10609 ## Description ```python from mxnet import gluon import mxnet as mx gru = gluon.rnn.GRUCell(5) gru.initialize(ctx=mx.cpu(0)) data = mx.nd.random.uniform(shape=(2, 3)) state = mx.nd.random.uniform(shape=(2, 5)) out = gru(data, state) ``` the code above fails with the following error: ``` MXNetError Traceback (most recent call last) <ipython-input-1-47be0261e99b> in <module>() 5 data = mx.nd.random.uniform(shape=(2, 3)) 6 state = mx.nd.random.uniform(shape=(2, 5)) ----> 7 out = gru(data, state) /home/ubuntu/incubator-mxnet/python/mxnet/gluon/block.pyc in __call__(self, *args) 411 def __call__(self, *args): 412 """Calls forward. Only accepts positional arguments.""" --> 413 return self.forward(*args) 414 415 def forward(self, *args): /home/ubuntu/incubator-mxnet/python/mxnet/gluon/rnn/rnn_cell.pyc in forward(self, inputs, states) 287 # pylint: disable= arguments-differ 288 self._counter += 1 --> 289 return super(RecurrentCell, self).forward(inputs, states) 290 291 /home/ubuntu/incubator-mxnet/python/mxnet/gluon/block.pyc in forward(self, x, *args) 627 return self._call_cached_op(x, *args) 628 params = {i: j.data(ctx) for i, j in self._reg_params.items()} --> 629 return self.hybrid_forward(ndarray, x, *args, **params) 630 631 assert isinstance(x, Symbol), \ /home/ubuntu/incubator-mxnet/python/mxnet/gluon/rnn/rnn_cell.pyc in hybrid_forward(self, F, inputs, states, i2h_weight, h2h_weight, i2h_bias, h2h_bias) 610 bias=h2h_bias, 611 num_hidden=self._hidden_size * 3, --> 612 name=prefix+'h2h') 613 614 i2h_r, i2h_z, i2h = F.SliceChannel(i2h, num_outputs=3, /home/ubuntu/incubator-mxnet/python/mxnet/ndarray/register.pyc in FullyConnected(data, weight, bias, num_hidden, no_bias, flatten, out, name, **kwargs) /home/ubuntu/incubator-mxnet/python/mxnet/_ctypes/ndarray.pyc in _imperative_invoke(handle, ndargs, keys, vals, out) 90 c_str_array(keys), 91 c_str_array([str(s) for s in vals]), ---> 92 ctypes.byref(out_stypes))) 93 94 if original_output is not None: /home/ubuntu/incubator-mxnet/python/mxnet/base.pyc in check_call(ret) 147 """ 148 if ret != 0: --> 149 raise MXNetError(py_str(_LIB.MXGetLastError())) 150 151 MXNetError: Shape inconsistent, Provided = [15,5], inferred shape=(15,1) ``` If I call hybridize the block and pass the data again to the block. It works. ```python gru.hybridize() out = gru(data, state) ``` Is this a bug?
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