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我試圖運行使用Mxnet library在python中的this image classification example以及預先訓練的深度學習模型Inception-BN。執行罰球和錯誤在這條線：prob = model.predict(batch)[0]出現錯誤消息：在Python上運行使用Mxnet庫的深度學習圖像分類示例的錯誤
MXNetError: InferShape Error in ch_concat_3c_chconcat: [14:35:56] src/operator/./concat-inl.h:152: Check failed: (dshape[j]) == (tmp[j]) Incorrect shape[2]: (1,320,15,15). (first input shape: (1,576,14,14))
我試圖重新下載盜夢空間-BN模型，以確保它是最新的，但它並沒有發揮作用。我懷疑問題可能在線：model = mx.model.FeedForward.load(prefix, num_round, ctx=mx.gpu(), numpy_batch_size=1)我必須更改gpu對於cpu因爲我的服務器沒有配備gpu。儘管如此，這個錯誤似乎並沒有指向這個方向。
任何想法如何解決它？使用cpu而不是gpu是性能較低的問題嗎？
最後這裏是完整的錯誤信息：
---------------------------------------------------------------------------
MXNetError Traceback (most recent call last)
<ipython-input-7-98e51e4226e1> in <module>()
1 # Get prediction probability of 1000 classes from model
----> 2 prob = model.predict(batch)[0]
3 # Argsort, get prediction index from largest prob to lowest
4 pred = np.argsort(prob)[::-1]
5 # Get top1 label
/users/CREATE/olb/mxnet/python/mxnet/model.pyc in predict(self, X, num_batch, return_data, reset)
589 data_shapes = X.provide_data
590 data_names = [x[0] for x in data_shapes]
--> 591 self._init_predictor(data_shapes)
592 batch_size = X.batch_size
593 data_arrays = [self._pred_exec.arg_dict[name] for name in data_names]
/users/CREATE/olb/mxnet/python/mxnet/model.pyc in _init_predictor(self, input_shapes)
520 # for now only use the first device
521 pred_exec = self.symbol.simple_bind(
--> 522 self.ctx[0], grad_req='null', **dict(input_shapes))
523 pred_exec.copy_params_from(self.arg_params, self.aux_params)
524
/users/CREATE/olb/mxnet/python/mxnet/symbol.pyc in simple_bind(self, ctx, grad_req, type_dict, **kwargs)
623 if type_dict is None:
624 type_dict = {k: mx_real_t for k in self.list_arguments()}
--> 625 arg_shapes, _, aux_shapes = self.infer_shape(**kwargs)
626 arg_types, _, aux_types = self.infer_type(**type_dict)
627 if arg_shapes == None or arg_types == None:
/users/CREATE/olb/mxnet/python/mxnet/symbol.pyc in infer_shape(self, *args, **kwargs)
410 The order is in the same order as list_auxiliary()
411 """
--> 412 return self._infer_shape_impl(False, *args, **kwargs)
413
414 def infer_shape_partial(self, *args, **kwargs):
/users/CREATE/olb/mxnet/python/mxnet/symbol.pyc in _infer_shape_impl(self, partial, *args, **kwargs)
470 ctypes.byref(aux_shape_ndim),
471 ctypes.byref(aux_shape_data),
--> 472 ctypes.byref(complete)))
473 if complete.value != 0:
474 arg_shapes = [
/users/CREATE/olb/mxnet/python/mxnet/base.pyc in check_call(ret)
75 """
76 if ret != 0:
---> 77 raise MXNetError(py_str(_LIB.MXGetLastError()))
78
79 def c_str(string):
MXNetError: InferShape Error in ch_concat_3c_chconcat: [14:35:56] src/operator/./concat-inl.h:152: Check failed: (dshape[j]) == (tmp[j]) Incorrect shape[2]: (1,320,15,15). (first input shape: (1,576,14,14))