feature extraction(using V2 and V3)

[inverai]

---> 2 face_feature_extractor = MobileFaceFeatureExtractor(model_file, epoch, batch_size, context, gpu_id)

in init(self, model_file, epoch, batch_size, context, gpu_id)
10 self.model.bind(for_training = False, data_shapes=[('data', (self.batch_size, 1, 100, 100))])
11 sym, arg_params, aux_params = mxnet.model.load_checkpoint(self.model_file, self.epoch)
---> 12 self.model.set_params(arg_params, aux_params)
13
14

D:\UserInfo\DownDir\Conda\envs\tensor\lib\site-packages\mxnet\module\module.py in set_params(self, arg_params, aux_params, allow_missing, force_init, allow_extra)
348 self.init_params(initializer=None, arg_params=arg_params, aux_params=aux_params,
349 allow_missing=allow_missing, force_init=force_init,
--> 350 allow_extra=allow_extra)
351 return
352

D:\UserInfo\DownDir\Conda\envs\tensor\lib\site-packages\mxnet\module\module.py in init_params(self, initializer, arg_params, aux_params, allow_missing, force_init, allow_extra)
307 for name, arr in sorted(self._arg_params.items()):
308 desc = InitDesc(name, attrs.get(name, None))
--> 309 _impl(desc, arr, arg_params)
310
311 for name, arr in sorted(self._aux_params.items()):

D:\UserInfo\DownDir\Conda\envs\tensor\lib\site-packages\mxnet\module\module.py in _impl(name, arr, cache)
295 # just in case the cached array is just the target itself
296 if cache_arr is not arr:
--> 297 cache_arr.copyto(arr)
298 else:
299 if not allow_missing:

D:\UserInfo\DownDir\Conda\envs\tensor\lib\site-packages\mxnet\ndarray\ndarray.py in copyto(self, other)
2072 warnings.warn('You are attempting to copy an array to itself', RuntimeWarning)
2073 return False
-> 2074 return _internal._copyto(self, out=other)
2075 elif isinstance(other, Context):
2076 hret = NDArray(_new_alloc_handle(self.shape, other, True, self.dtype))

D:\UserInfo\DownDir\Conda\envs\tensor\lib\site-packages\mxnet\ndarray\register.py in _copyto(data, out, name, **kwargs)

D:\UserInfo\DownDir\Conda\envs\tensor\lib\site-packages\mxnet_ctypes\ndarray.py 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:

D:\UserInfo\DownDir\Conda\envs\tensor\lib\site-packages\mxnet\base.py in check_call(ret)
250 """
251 if ret != 0:
--> 252 raise MXNetError(py_str(_LIB.MXGetLastError()))
253
254

MXNetError: [21:47:41] c:\jenkins\workspace\mxnet-tag\mxnet\src\operator\tensor../elemwise_op_common.h:135: Check failed: assign(&dattr, vec.at(i)) Incompatible attr in node at 0-th output: expected [32,3,3,3], got [32,1,3,3]

[inverai]

self.model.bind(for_training = False, data_shapes=[('data', (self.batch_size, 3, 100, 100))])

change 1 to 3, then :
---> 22 self.model.forward(Batch([mxnet.nd.array(batch_data)]))
MXNetError: [21:53:02] C:\Jenkins\workspace\mxnet-tag\mxnet\src\executor\graph_executor.cc:858: Shape of unspecifie arg: conv1_weight changed. This can cause the new executor to not share parameters with the old one. Please check for error in network.If this is intended, set partial_shaping=True to suppress this warning.

[becauseofAI]

@inverai
Can you run the command python3 get_face_feature_v2_mxnet.py or python3 get_face_feature_v3_mxnet.py directly and can you get the right result?

[inverai]

...