Created by: xiangyubo

   1）PaddlePaddle版本：paddle.fluid.1.2.0    4）系统环境：Linux，Python2.7 训练时候使用 fluid.io.save_inference_model保存模型，预测的时候使用fluid.io.load_inference_model加载模型文件。保存的是我自己训练的 vgg 模型。保存没问题，加载的时候报错

Traceback (most recent call last):
  File "classify-infer.py", line 43, in <module>
    executor=exe)
  File "/home/work/xiangyubo/paddle_release_home/python/lib/python2.7/site-packages/paddle/fluid/io.py", line 784, in load_inference_model
    load_persistables(executor, dirname, program, params_filename)
  File "/home/work/xiangyubo/paddle_release_home/python/lib/python2.7/site-packages/paddle/fluid/io.py", line 529, in load_persistables
    filename=filename)
  File "/home/work/xiangyubo/paddle_release_home/python/lib/python2.7/site-packages/paddle/fluid/io.py", line 395, in load_vars
    filename=filename)
  File "/home/work/xiangyubo/paddle_release_home/python/lib/python2.7/site-packages/paddle/fluid/io.py", line 436, in load_vars
    executor.run(load_prog)
  File "/home/work/xiangyubo/paddle_release_home/python/lib/python2.7/site-packages/paddle/fluid/executor.py", line 472, in run
    self.executor.run(program.desc, scope, 0, True, True)
paddle.fluid.core.EnforceNotMet: Cannot read more from file ./classify-model/vgg-classify-params at [/paddle/paddle/fluid/operators/load_combine_op.cc:58]
PaddlePaddle Call Stacks: 
0       0x7f4bdb4b2226p paddle::platform::EnforceNotMet::EnforceNotMet(std::__exception_ptr::exception_ptr, char const*, int) + 486
1       0x7f4bdbb97ab4p paddle::operators::LoadCombineOp::RunImpl(paddle::framework::Scope const&, boost::variant<paddle::platform::CUDAPlace, paddle::platform::CPUPlace, paddle::platform::CUDAPinnedPlace, 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_, 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_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_> const&) const + 2004
2       0x7f4bdcda56afp paddle::framework::OperatorBase::Run(paddle::framework::Scope const&, boost::variant<paddle::platform::CUDAPlace, paddle::platform::CPUPlace, paddle::platform::CUDAPinnedPlace, 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_, 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_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_> const&) + 463
3       0x7f4bdb588ef3p paddle::framework::Executor::RunPreparedContext(paddle::framework::ExecutorPrepareContext*, paddle::framework::Scope*, bool, bool, bool) + 227
4       0x7f4bdb589920p paddle::framework::Executor::Run(paddle::framework::ProgramDesc const&, paddle::framework::Scope*, int, bool, bool) + 128
5       0x7f4bdb49e0dbp
6       0x7f4bdb4da18ep
7       0x7f4c3efcabb8p PyEval_EvalFrameEx + 25016
8       0x7f4c3efce0bdp PyEval_EvalCodeEx + 2061
9       0x7f4c3efcb345p PyEval_EvalFrameEx + 26949
10      0x7f4c3efce0bdp PyEval_EvalCodeEx + 2061
11      0x7f4c3efcb345p PyEval_EvalFrameEx + 26949
12      0x7f4c3efce0bdp PyEval_EvalCodeEx + 2061
13      0x7f4c3efcb345p PyEval_EvalFrameEx + 26949
14      0x7f4c3efce0bdp PyEval_EvalCodeEx + 2061
15      0x7f4c3efcb345p PyEval_EvalFrameEx + 26949
16      0x7f4c3efce0bdp PyEval_EvalCodeEx + 2061
17      0x7f4c3efcb345p PyEval_EvalFrameEx + 26949
18      0x7f4c3efce0bdp PyEval_EvalCodeEx + 2061
19      0x7f4c3efce1f2p PyEval_EvalCode + 50
20      0x7f4c3eff6f42p PyRun_FileExFlags + 146
21      0x7f4c3eff82d9p PyRun_SimpleFileExFlags + 217
22      0x7f4c3f00e00dp Py_Main + 3149
23      0x7f4c3e20bbd5p __libc_start_main + 245
24            0x4007a1p

我的 vgg 模型基本和paddle在github上的一样，只是我自己加了一层 bn

class VGGNet():
    def __init__(self, layers=16):
        self.layers = layers

    def net(self, input, class_dim=1000):
        layers = self.layers
        vgg_spec = {
            11: ([1, 1, 2, 2, 2]),
            13: ([2, 2, 2, 2, 2]),
            16: ([2, 2, 3, 3, 3]),
            19: ([2, 2, 4, 4, 4])
        }
        assert layers in vgg_spec.keys(), \
            "supported layers are {} but input layer is {}".format(vgg_spec.keys(), layers)

        nums = vgg_spec[layers]
        conv1 = self.conv_block(input, 64, nums[0])
        conv2 = self.conv_block(conv1, 128, nums[1])
        conv3 = self.conv_block(conv2, 256, nums[2])
        conv4 = self.conv_block(conv3, 512, nums[3])
        conv5 = self.conv_block(conv4, 512, nums[4])

        fc_dim = 4096
        fc1 = fluid.layers.fc(
            input=conv5,
            size=fc_dim,
            act='relu',
            param_attr=fluid.param_attr.ParamAttr(
                initializer=fluid.initializer.Normal(scale=0.005)),
            bias_attr=fluid.param_attr.ParamAttr(
                initializer=fluid.initializer.Constant(value=0.1)))
        fc1 = fluid.layers.dropout(x=fc1, dropout_prob=0.5)
        fc2 = fluid.layers.fc(
            input=fc1,
            size=fc_dim,
            act='relu',
            param_attr=fluid.param_attr.ParamAttr(
                initializer=fluid.initializer.Normal(scale=0.005)),
            bias_attr=fluid.param_attr.ParamAttr(
                initializer=fluid.initializer.Constant(value=0.1)))
        fc2 = fluid.layers.dropout(x=fc2, dropout_prob=0.5)
        out = fluid.layers.fc(
            input=fc2,
            size=class_dim,
            act='softmax',
            param_attr=fluid.param_attr.ParamAttr(
                initializer=fluid.initializer.Normal(scale=0.005)),
            bias_attr=fluid.param_attr.ParamAttr(
                initializer=fluid.initializer.Constant(value=0.1)))

        return out

    def conv_block(self, input, num_filter, groups):
        conv = input
        for i in range(groups):
            if i == groups - 1:
                act = None
            else:
                act = 'relu'
            conv = fluid.layers.conv2d(
                input=conv,
                num_filters=num_filter,
                filter_size=3,
                stride=1,
                padding=1,
                act=act,
                param_attr=fluid.param_attr.ParamAttr(
                    initializer=fluid.initializer.Normal(scale=0.01)),
                bias_attr=fluid.param_attr.ParamAttr(
                    initializer=fluid.initializer.Constant(value=0.0)))
        conv = fluid.layers.batch_norm(input=conv, act=act)
        return fluid.layers.pool2d(
            input=conv, pool_size=2, pool_type='max', pool_stride=2)