Created by: smartcai

   1）PaddlePaddle版本：paddlepaddle 1.7.0+paddlehub1.5.0 2）OS：Linux jupyter-262348-365692 4.4.0-166-generic #195-Ubuntu SMP Tue Oct 1 09:35:25 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux    3）CPU：Intel(R) Xeon(R) Gold 6148 CPU @ 2.40GHz    4）GPU：NA    5）系统环境：Python3.7.4

Code: #定义网络结构 class MyDNN(fluid.dygraph.Layer): def init(self, name_scope, num_classes=10): super(MyDNN, self).init(name_scope) name_scope = self.full_name() self.conv1 = Conv2D(num_channels=3, num_filters=96, filter_size=11, stride=4, padding=5, act='relu') self.pool1 = Pool2D(pool_size=2, pool_stride=2, pool_type='max') self.conv2 = Conv2D(num_channels=96, num_filters=256, filter_size=5, stride=1, padding=2, act='relu') self.pool2 = Pool2D(pool_size=2, pool_stride=2, pool_type='max') self.conv3 = Conv2D(num_channels=256, num_filters=384, filter_size=3, stride=1, padding=1, act='relu') self.conv4 = Conv2D(num_channels=384, num_filters=384, filter_size=3, stride=1, padding=1, act='relu') self.conv5 = Conv2D(num_channels=384, num_filters=256, filter_size=3, stride=1, padding=1, act='relu') self.pool5 = Pool2D(pool_size=2, pool_stride=2, pool_type='max') self.fc1 = Linear(input_dim=9216, output_dim=4096, act='relu') self.drop_ratio1 = 0.5 self.fc2 = Linear(input_dim=4096, output_dim=4096, act='relu') self.drop_ratio2 = 0.5 self.fc3 = Linear(input_dim=4096, output_dim=num_classes)

def forward(self, x):
    x = self.conv1(x)
    x = self.pool1(x)
    x = self.conv2(x)
    x = self.pool2(x)
    x = self.conv3(x)
    x = self.conv4(x)
    x = self.conv5(x)
    x = self.pool5(x)
    x = fluid.layers.reshape(x, [x.shape[0], -1])
    x = self.fc1(x)
    x= fluid.layers.dropout(x, self.drop_ratio1)
    x = self.fc2(x)
    x = fluid.layers.dropout(x, self.drop_ratio2)
    x = self.fc3(x)
    return x

#用动态图进行训练 with fluid.dygraph.guard(): model=MyDNN('Alexnet11') #模型实例化 model.train() #训练模式 opt= fluid.optimizer.Momentum(learning_rate=0.001,momentum=0.9,parameter_list=model.parameters())

epochs_num=100 #迭代次数

for pass_num in range(epochs_num):
    
    for batch_id,data in enumerate(train_reader()):
        
        images=np.array([x[0].reshape(3,100,100) for x in data],np.float32)
        
        labels = np.array([x[1] for x in data]).astype('int64')
        labels = labels[:, np.newaxis]
        # print(images.shape)
        image=fluid.dygraph.to_variable(images)
        label=fluid.dygraph.to_variable(labels)
        predict=model(image)#预测
        # print(predict)
        loss=fluid.layers.cross_entropy(predict,label)
        avg_loss=fluid.layers.mean(loss)#获取loss值
        
        acc=fluid.layers.accuracy(predict,label)#计算精度
        
        if batch_id!=0 and batch_id%50==0:
            print("train_pass:{},batch_id:{},train_loss:{},train_acc:{}".format(pass_num,batch_id,avg_loss.numpy(),acc.numpy()))
        
        avg_loss.backward()
        opt.minimize(avg_loss)
        model.clear_gradients()
        
fluid.save_dygraph(model.state_dict(),'MyDNN')#保存模型

Error: ---------------------------------------------------------------------------EnforceNotMet Traceback (most recent call last) in 18 image=fluid.dygraph.to_variable(images) 19 label=fluid.dygraph.to_variable(labels) ---> 20 predict=model(image)#预测 21 # print(predict) 22 loss=fluid.layers.cross_entropy(predict,label) /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py in call(self, *inputs, **kwargs) 302 self._built = True 303 --> 304 outputs = self.forward(*inputs, **kwargs) 305 return outputs 306 in forward(self, x) 29 x = self.pool5(x) 30 x = fluid.layers.reshape(x, [x.shape[0], -1]) ---> 31 x = self.fc1(x) 32 x= fluid.layers.dropout(x, self.drop_ratio1) 33 x = self.fc2(x) /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py in call(self, *inputs, **kwargs) 302 self._built = True 303 --> 304 outputs = self.forward(*inputs, **kwargs) 305 return outputs 306 /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/nn.py in forward(self, input) 930 931 if in_dygraph_mode(): --> 932 outs = core.ops.matmul(inputs, attrs) 933 pre_bias = outs['Out'][0] 934 EnforceNotMet:

C++ Call Stacks (More useful to developers):

0 std::string paddle::platform::GetTraceBackString<std::string const&>(std::string const&, char const*, int) 1 paddle::platform::EnforceNotMet::EnforceNotMet(std::string const&, char const*, int) 2 void paddle::operators::math::Blaspaddle::platform::CPUDeviceContext::MatMul(paddle::framework::Tensor const&, paddle::operators::math::MatDescriptor const&, paddle::framework::Tensor const&, paddle::operators::math::MatDescriptor const&, float, paddle::framework::Tensor*, float) const 3 paddle::operators::MatMulKernel<paddle::platform::CPUDeviceContext, float>::Compute(paddle::framework::ExecutionContext const&) const 4 std::Function_handler<void (paddle::framework::ExecutionContext const&), paddle::framework::OpKernelRegistrarFunctor<paddle::platform::CPUPlace, false, 0ul, paddle::operators::MatMulKernel<paddle::platform::CPUDeviceContext, float>, paddle::operators::MatMulKernel<paddle::platform::CPUDeviceContext, double> >::operator()(char const*, char const*, int) const::{lambda(paddle::framework::ExecutionContext const&)#1 (closed)}>::M_invoke(std::Any_data const&, paddle::framework::ExecutionContext const&) 5 paddle::imperative::PreparedOp::Run(std::map<std::string, std::vector<std::shared_ptrpaddle::imperative::VarBase, std::allocator<std::shared_ptrpaddle::imperative::VarBase > >, std::lessstd::string, std::allocator<std::pair<std::string const, std::vector<std::shared_ptrpaddle::imperative::VarBase, std::allocator<std::shared_ptrpaddle::imperative::VarBase > > > > > const*, std::map<std::string, std::vector<std::shared_ptrpaddle::imperative::VarBase, std::allocator<std::shared_ptrpaddle::imperative::VarBase > >, std::lessstd::string, std::allocator<std::pair<std::string const, std::vector<std::shared_ptrpaddle::imperative::VarBase, std::allocator<std::shared_ptrpaddle::imperative::VarBase > > > > > const*, std::unordered_map<std::string, boost::variant<boost::blank, int, float, std::string, std::vector<int, std::allocator >, std::vector<float, std::allocator >, std::vector<std::string, std::allocatorstd::string >, bool, std::vector<bool, std::allocator >, paddle::framework::BlockDesc*, long, std::vector<paddle::framework::BlockDesc*, std::allocatorpaddle::framework::BlockDesc* >, std::vector<long, std::allocator >, boost::detail::variant::void, boost::detail::variant::void, boost::detail::variant::void, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_>, std::hashstd::string, std::equal_tostd::string, std::allocator<std::pair<std::string const, boost::variant<boost::blank, int, float, std::string, std::vector<int, std::allocator >, std::vector<float, std::allocator >, std::vector<std::string, std::allocatorstd::string >, bool, std::vector<bool, std::allocator >, paddle::framework::BlockDesc*, long, std::vector<paddle::framework::BlockDesc*, std::allocatorpaddle::framework::BlockDesc* >, std::vector<long, std::allocator >, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_> > > > const*) 6 paddle::imperative::OpBase::Run(std::map<std::string, std::vector<std::shared_ptrpaddle::imperative::VarBase, std::allocator<std::shared_ptrpaddle::imperative::VarBase > >, std::lessstd::string, std::allocator<std::pair<std::string const, std::vector<std::shared_ptrpaddle::imperative::VarBase, std::allocator<std::shared_ptrpaddle::imperative::VarBase > > > > > const&, std::map<std::string, std::vector<std::shared_ptrpaddle::imperative::VarBase, std::allocator<std::shared_ptrpaddle::imperative::VarBase > >, std::lessstd::string, std::allocator<std::pair<std::string const, std::vector<std::shared_ptrpaddle::imperative::VarBase, std::allocator<std::shared_ptrpaddle::imperative::VarBase > > > > > const&) 7 paddle::imperative::Tracer::TraceOp(std::string const&, std::map<std::string, std::vector<std::shared_ptrpaddle::imperative::VarBase, std::allocator<std::shared_ptrpaddle::imperative::VarBase > >, std::lessstd::string, std::allocator<std::pair<std::string const, std::vector<std::shared_ptrpaddle::imperative::VarBase, std::allocator<std::shared_ptrpaddle::imperative::VarBase > > > > > const&, std::map<std::string, std::vector<std::shared_ptrpaddle::imperative::VarBase, std::allocator<std::shared_ptrpaddle::imperative::VarBase > >, std::lessstd::string, std::allocator<std::pair<std::string const, std::vector<std::shared_ptrpaddle::imperative::VarBase, std::allocator<std::shared_ptrpaddle::imperative::VarBase > > > > > const&, std::unordered_map<std::string, boost::variant<boost::blank, int, float, std::string, std::vector<int, std::allocator >, std::vector<float, std::allocator >, std::vector<std::string, std::allocatorstd::string >, bool, std::vector<bool, std::allocator >, paddle::framework::BlockDesc*, long, std::vector<paddle::framework::BlockDesc*, std::allocatorpaddle::framework::BlockDesc* >, std::vector<long, std::allocator >, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_>, std::hashstd::string, std::equal_tostd::string, std::allocator<std::pair<std::string const, boost::variant<boost::blank, int, float, std::string, std::vector<int, std::allocator >, std::vector<float, std::allocator >, std::vector<std::string, std::allocatorstd::string >, bool, std::vector<bool, std::allocator >, paddle::framework::BlockDesc*, long, std::vector<paddle::framework::BlockDesc*, std::allocatorpaddle::framework::BlockDesc* >, std::vector<long, std::allocator >, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_> > > >)

Error Message Summary:

Error: An error occurred here. There is no accurate error hint for this error yet. We are continuously in the process of increasing hint for this kind of error check. It would be helpful if you could inform us of how this conversion went by opening a github issue. And we will resolve it with high priority.

• New issue link: https://github.com/PaddlePaddle/Paddle/issues/new
• Recommended issue content: all error stack information [Hint: Expected dim_a.width_ == dim_b.height_, but received dim_a.width_:2304 != dim_b.height_:9216.] at (/paddle/paddle/fluid/operators/math/blas_impl.h:747)