问题描述：
问题算子
ops.ReduceMean算子
实验环境
- 操作系统： Ubuntu20.04
- Python版本： Python3.7.5
- Mindspore版本: mindspore-gpu 1.5.0
- CUDA版本： 11.1
安装命令
conda install mindspore-gpu=1.5.0 cudatoolkit=11.1 -c mindspore -c conda-forge
具体代码
1. 使用 ops.ReduceMean()算子替代GlobalAvgPool算子
import mindspore.nn as nnfrom mindspore import ops
class GlobalAvgPool(nn.Cell):
def __init__(self):
super(GlobalAvgPool, self).__init__()
self.global_avg_pool = ops.ReduceMean(keep_dims=False)
def construct(self, x):
return self.global_avg_pool(x=x, axis=(0, 1))
2. 将上面实现的算子放在CNN中
class CNN(nn.Cell):
def __init__(self, num_class, img_channel, img_size, actions):
super(CNN, self).__init__()
self.layers = list()
last_out_channel = img_channel
for i in range(len(actions)):
conv = nn.Conv2d(in_channels=last_out_channel,
out_channels=actions[i]['filter_num'],
kernel_size=actions[i]['kernel_size'],
pad_mode='same')
last_out_channel = actions[i]['filter_num']
self.layers.append(conv)
self.layers.append(nn.ReLU())
self.sequential_cell = nn.SequentialCell(self.layers)
self.global_avg_pool = GlobalAvgPool()
self.flatten = nn.Flatten()
self.dense = nn.Dense(in_channels=last_out_channel,out_channels=num_class)
def construct(self, x):
x = self.sequential_cell(x)
x = self.global_avg_pool(x)
x = self.flatten(x)
x = self.dense(x)
return x
运行训练报错：
{0: {'layer_id': 0, 'filter_num': 9, 'kernel_size': 7}, 1: {'layer_id': 1, 'filter_num': 18, 'kernel_size': 5}, 2: {'layer_id': 2, 'filter_num': 18, 'kernel_size': 7}, 3: {'layer_id': 3, 'filter_num': 36, 'kernel_size': 14}, 4: {'layer_id': 4, 'filter_num': 36, 'kernel_size': 14}, 5: {'layer_id': 5, 'filter_num': 36, 'kernel_size': 5}, 6: {'layer_id': 6, 'filter_num': 36, 'kernel_size': 14}, 7: {'layer_id': 7, 'filter_num': 36, 'kernel_size': 5}, 8: {'layer_id': 8, 'filter_num': 36, 'kernel_size': 14}, 9: {'layer_id': 9, 'filter_num': 18, 'kernel_size': 7}}
CNN<
(sequential_cell): SequentialCell<
(0): Conv2d
(1): ReLU<>
(2): Conv2d
(3): ReLU<>
(4): Conv2d
(5): ReLU<>
(6): Conv2d
(7): ReLU<>
(8): Conv2d
(9): ReLU<>
(10): Conv2d
(11): ReLU<>
(12): Conv2d
(13): ReLU<>
(14): Conv2d
(15): ReLU<>
(16): Conv2d
(17): ReLU<>
(18): Conv2d
(19): ReLU<>
>
(global_avg_pool): GlobalAvgPool<>
(flatten): Flatten<>
(dense): Dense
>[EXCEPTION] ANALYZER(117475,7f5958cab740,python):2021-12-19-15:21:05.166.863 [mindspore/ccsrc/pipeline/jit/static_analysis/prim.cc:504] ConvertAbstractToPython] Unsupported parameter type for python primitive.AbstractKeywordArg(key : xvalue : AbstractTensor(shape: (64, 18, 28, 28), element: AbstractScalar(Type: Float32, Value: AnyValue, Shape: NoShape), value_ptr: 0x556598062db0, value: AnyValue))
Traceback (most recent call last):
File "/home/yons/Desktop/fnas/QHW-NAS/NAS/train.py", line 49, in
train()
File "/home/yons/Desktop/fnas/QHW-NAS/NAS/train.py", line 34, in train
callbacks=[summary_collector], dataset_sink_mode=False)
File "/home/yons/anaconda3/envs/mindspore/lib/python3.7/site-packages/mindspore/train/model.py", line 726, in train
sink_size=sink_size)
File "/home/yons/anaconda3/envs/mindspore/lib/python3.7/site-packages/mindspore/train/model.py", line 498, in _train
self._train_process(epoch, train_dataset, list_callback, cb_params)
File "/home/yons/anaconda3/envs/mindspore/lib/python3.7/site-packages/mindspore/train/model.py", line 626, in _train_process
outputs = self._train_network(*next_element)
File "/home/yons/anaconda3/envs/mindspore/lib/python3.7/site-packages/mindspore/nn/cell.py", line 404, in __call__
out = self.compile_and_run(*inputs)
File "/home/yons/anaconda3/envs/mindspore/lib/python3.7/site-packages/mindspore/nn/cell.py", line 682, in compile_and_run
self.compile(*inputs)
File "/home/yons/anaconda3/envs/mindspore/lib/python3.7/site-packages/mindspore/nn/cell.py", line 669, in compile
_cell_graph_executor.compile(self, *inputs, phase=self.phase, auto_parallel_mode=self._auto_parallel_mode)
File "/home/yons/anaconda3/envs/mindspore/lib/python3.7/site-packages/mindspore/common/api.py", line 548, in compile
result = self._graph_executor.compile(obj, args_list, phase, use_vm, self.queue_name)
TypeError: mindspore/ccsrc/pipeline/jit/static_analysis/prim.cc:504 ConvertAbstractToPython] Unsupported parameter type for python primitive.AbstractKeywordArg(key : xvalue : AbstractTensor(shape: (64, 18, 28, 28), element: AbstractScalar(Type: Float32, Value: AnyValue, Shape: NoShape), value_ptr: 0x556598062db0, value: AnyValue))
The function call stack (See file '/home/yons/Desktop/fnas/QHW-NAS/NAS/rank_0/om/analyze_fail.dat' for more details):# 0 In file /home/yons/anaconda3/envs/mindspore/lib/python3.7/site-packages/mindspore/nn/wrap/cell_wrapper.py(353)
loss = self.network(*inputs)
^# 1 In file /home/yons/anaconda3/envs/mindspore/lib/python3.7/site-packages/mindspore/nn/wrap/cell_wrapper.py(110)
out = self._backbone(data)
^# 2 In file /home/yons/Desktop/fnas/QHW-NAS/NAS/neural_network/model.py(34)
x = self.global_avg_pool(x)
^# 3 In file /home/yons/Desktop/fnas/QHW-NAS/NAS/neural_network/model.py(11)
return self.global_avg_pool(x=x, axis=(0, 1))
^
Process finished with exit code 1
解答：
ops.ReduceMean使用错误，
self.global_avg_pool(x, axis=(0, 1))
改成：
self.global_avg_pool(x, (0, 1))
