salmanmashayekh opened a new issue #16230: Loading Sagemaker NTM Artifacts URL: https://github.com/apache/incubator-mxnet/issues/16230 I have trained a Neural Topic Model with Sagemaker and now I am trying to load/deploy the model locally. The artifacts include a `symbol` and an a `parameters` file. I am using the following to load the model: ``` sym, arg_params, aux_params = mx.model.load_checkpoint(prefix, iteration) module_model = mx.mod.Module(symbol=sym, label_names=None, context=mx.cpu()) ``` But when I try to `bind` the model: ``` module_model.bind( for_training = False, data_shapes = [('data', (1, VOCAB_SIZE))] ) ``` It fails with the following error: ``` --------------------------------------------------------------------------- MXNetError Traceback (most recent call last) ~/anaconda3/envs/python3/lib/python3.6/site-packages/mxnet/symbol/symbol.py in simple_bind(self, ctx, grad_req, type_dict, stype_dict, group2ctx, shared_arg_names, shared_exec, shared_buffer, **kwargs) 1622 shared_exec_handle, -> 1623 ctypes.byref(exe_handle))) 1624 except MXNetError as e: ~/anaconda3/envs/python3/lib/python3.6/site-packages/mxnet/base.py in check_call(ret) 252 if ret != 0: --> 253 raise MXNetError(py_str(_LIB.MXGetLastError())) 254 MXNetError: Error in operator sample_normal0: vector::_M_range_insert During handling of the above exception, another exception occurred: RuntimeError Traceback (most recent call last) <ipython-input-349-822926d8cf09> in <module>() 8 for_training = True, 9 data_shapes = [('data', (1,VOCAB_SIZE))], ---> 10 force_rebind = True, 11 ) 12 ~/anaconda3/envs/python3/lib/python3.6/site-packages/mxnet/module/module.py in bind(self, data_shapes, label_shapes, for_training, inputs_need_grad, force_rebind, shared_module, grad_req) 427 fixed_param_names=self._fixed_param_names, 428 grad_req=grad_req, group2ctxs=self._group2ctxs, --> 429 state_names=self._state_names) 430 self._total_exec_bytes = self._exec_group._total_exec_bytes 431 if shared_module is not None: ~/anaconda3/envs/python3/lib/python3.6/site-packages/mxnet/module/executor_group.py in __init__(self, symbol, contexts, workload, data_shapes, label_shapes, param_names, for_training, inputs_need_grad, shared_group, logger, fixed_param_names, grad_req, state_names, group2ctxs) 277 self.num_outputs = len(self.symbol.list_outputs()) 278 --> 279 self.bind_exec(data_shapes, label_shapes, shared_group) 280 281 def decide_slices(self, data_shapes): ~/anaconda3/envs/python3/lib/python3.6/site-packages/mxnet/module/executor_group.py in bind_exec(self, data_shapes, label_shapes, shared_group, reshape) 373 else: 374 self.execs.append(self._bind_ith_exec(i, data_shapes_i, label_shapes_i, --> 375 shared_group)) 376 377 self.data_shapes = data_shapes ~/anaconda3/envs/python3/lib/python3.6/site-packages/mxnet/module/executor_group.py in _bind_ith_exec(self, i, data_shapes, label_shapes, shared_group) 660 type_dict=input_types, shared_arg_names=self.param_names, 661 shared_exec=shared_exec, group2ctx=group2ctx, --> 662 shared_buffer=shared_data_arrays, **input_shapes) 663 self._total_exec_bytes += int(executor.debug_str().split('\n')[-3].split()[1]) 664 return executor ~/anaconda3/envs/python3/lib/python3.6/site-packages/mxnet/symbol/symbol.py in simple_bind(self, ctx, grad_req, type_dict, stype_dict, group2ctx, shared_arg_names, shared_exec, shared_buffer, **kwargs) 1627 error_msg += "%s: %s\n" % (k, v) 1628 error_msg += "%s" % e -> 1629 raise RuntimeError(error_msg) 1630 1631 # update shared_buffer RuntimeError: simple_bind error. Arguments: data: (1, 52908) Error in operator sample_normal0: vector::_M_range_insert ``` From the model architecture (https://arxiv.org/pdf/1809.02687.pdf), I know that the input data shape is a vector with `VOCAB_SIZE` length. Any ideas what I am doing wrong?
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