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]

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