问题描述：
【功能模块】
【操作步骤&问题现象】
前向过程中报错，然后一直输出
[WARNING] MD(121071,python):2021-03-21-22:06:10.264.793 [mindspore/ccsrc/minddata/dataset/util/task.cc:148] Join] GeneratorOp(ID:2) Thread ID 281472283959776 is not responding. Interrupt again
[WARNING] MD(121071,python):2021-03-21-22:06:11.265.062 [mindspore/ccsrc/minddata/dataset/util/task.cc:148] Join] GeneratorOp(ID:2) Thread ID 281472283959776 is not responding. Interrupt again
[WARNING] MD(121071,python):2021-03-21-22:06:12.265.344 [mindspore/ccsrc/minddata/dataset/util/task.cc:148] Join] GeneratorOp(ID:2) Thread ID 281472283959776 is not responding. Interrupt again
[WARNING] MD(121071,python):2021-03-21-22:06:13.265.507 [mindspore/ccsrc/minddata/dataset/util/task.cc:148] Join] GeneratorOp(ID:2) Thread ID 281472283959776 is not responding. Interrupt again
【截图信息】
【日志信息】（可选，上传日志内容或者附件）
[ERROR] PIPELINE(121071,python):2021-03-21-22:06:06.336.655 [mindspore/ccsrc/pipeline/jit/pipeline.cc:565] Compile]
The function call stack (See file 'analyze_fail.dat' for details):
# 0 In file /home/tuyanlun/archiconda3/envs/ms1.0/lib/python3.7/site-packages/mindspore/train/dataset_helper.py(87)
return self.network(*outputs)
^
# 1 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/network_define_pretrain.py(71)
if self.reduce_flag:
# 2 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/network_define_pretrain.py(70)
grads = self.grad(self.net_with_loss, weights)(data1, data2, data3, label)
^
# 3 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/network_define_pretrain.py(24)
def construct(self, data1, data2, data3, label):
# 4 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/network_define_pretrain.py(26)
feature1, feature2, feature3 = self._backbone(data)
^
# 5 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/resnet.py(317)
if self.pretrain:
^
# 6 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/resnet.py(318)
if self.use_MLP:
# 7 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/resnet.py(322)
out = self.end_point(out)
^
# 8 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/resnet.py(315)
out = self.flatten(out)
^
# 9 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/resnet.py(314)
out = self.mean(c5, (2, 3))
^
# 10 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/resnet.py(312)
c5 = self.layer4(c4)
^
# 11 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/resnet.py(311)
c4 = self.layer3(c3)
^
# 12 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/resnet.py(310)
c3 = self.layer2(c2)
^
# 13 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/resnet.py(309)
c2 = self.layer1(c1)
^
# 14 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/resnet.py(308)
c1 = self.maxpool(x)
^
# 15 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/resnet.py(307)
x = self.relu(x)
^
# 16 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/resnet.py(306)
x = self.bn1(x)
^
# 17 In file /home/tuyanlun/code/mindspore_r1.0/hpa/src/resnet.py(305)
x = self.conv1(x)
^
# 18 In file /home/tuyanlun/archiconda3/envs/ms1.0/lib/python3.7/site-packages/mindspore/nn/layer/conv.py(254)
if self.has_bias:
# 19 In file /home/tuyanlun/archiconda3/envs/ms1.0/lib/python3.7/site-packages/mindspore/nn/layer/conv.py(253)
output = self.conv2d(x, self.weight)
^
Traceback (most recent call last):
File "/home/tuyanlun/code/mindspore_r1.0/hpa/scripts/../pretrain.py", line 147, in
model.train(config.epochs, dataset, callbacks=cb, dataset_sink_mode=dataset_sink_mode)
File "/home/tuyanlun/archiconda3/envs/ms1.0/lib/python3.7/site-packages/mindspore/train/model.py", line 592, in train
sink_size=sink_size)
File "/home/tuyanlun/archiconda3/envs/ms1.0/lib/python3.7/site-packages/mindspore/train/model.py", line 391, in _train
self._train_dataset_sink_process(epoch, train_dataset, list_callback, cb_params, sink_size)
File "/home/tuyanlun/archiconda3/envs/ms1.0/lib/python3.7/site-packages/mindspore/train/model.py", line 452, in _train_dataset_sink_process
outputs = self._train_network(*inputs)
File "/home/tuyanlun/archiconda3/envs/ms1.0/lib/python3.7/site-packages/mindspore/nn/cell.py", line 322, in __call__
out = self.compile_and_run(*inputs)
File "/home/tuyanlun/archiconda3/envs/ms1.0/lib/python3.7/site-packages/mindspore/nn/cell.py", line 578, in compile_and_run
self.compile(*inputs)
File "/home/tuyanlun/archiconda3/envs/ms1.0/lib/python3.7/site-packages/mindspore/nn/cell.py", line 565, in compile
_executor.compile(self, *inputs, phase=self.phase, auto_parallel_mode=self._auto_parallel_mode)
File "/home/tuyanlun/archiconda3/envs/ms1.0/lib/python3.7/site-packages/mindspore/common/api.py", line 505, in compile
result = self._executor.compile(obj, args_list, phase, use_vm)
File "/home/tuyanlun/archiconda3/envs/ms1.0/lib/python3.7/site-packages/mindspore/ops/primitive.py", line 401, in __infer__
out[track] = fn(*(x[track] for x in args))
File "/home/tuyanlun/archiconda3/envs/ms1.0/lib/python3.7/site-packages/mindspore/ops/operations/nn_ops.py", line 1211, in infer_shape
validator.check_equal_int(len(x_shape_norm), 4, "x rank", self.name)
File "/home/tuyanlun/archiconda3/envs/ms1.0/lib/python3.7/site-packages/mindspore/_checkparam.py", line 239, in check_equal_int
return check_number(arg_value, value, Rel.EQ, int, arg_name, prim_name)
File "/home/tuyanlun/archiconda3/envs/ms1.0/lib/python3.7/site-packages/mindspore/_checkparam.py", line 147, in check_number
raise type_except(f'{arg_name} {prim_name} should be an {arg_type.__name__} and must {rel_str}, '
ValueError: `x rank` in `Conv2D` should be an int and must == 4, but got `5` with type `int`.
解决方案：
"ValueError: `x rank` in `Conv2D` should be an int and must == 4, but got `5` with type `int`."
卷积不支持5维输入，这个报错是合理的。
改变x的输入为4维