NotImplementedError: Wrong number or type of arguments for overloaded function 'IVector_create'

[huayong]

出现的问题如title， 主要目的是实现分割任务，所以自己写了个reader生成器来读取自己的训练数据，代码如下：

def load_image(file, image_size=224, mean_file=None): im = cv2.imread(file) im = cv2.resize(im, (image_size, image_size)) im = np.array(im).astype(np.float32) mean = np.array([103.94, 116.78, 123.68]) im = im / 255.0 - mean / 255.0 im = im / 255.0 im = im.transpose((2, 0, 1)) im = im.astype(np.float32) return im

def load_label(file, label_size=224): label_data = cv2.imread(file, cv2.IMREAD_GRAYSCALE) label_data = cv2.resize(label_data, (label_size, label_size)) label_data = np.array(label_data) label_data = label_data.astype(int) return label_data

def reader_creator(sub_name):

def reader():
    set_file = SET_FILE.format(sub_name)
    sets = [line.strip() for line in open(set_file, 'r')]
    for line in sets:
        line = line.strip()
        data_file = DATA_FILE.format(line)
        label_file = LABEL_FILE.format(line)
        data = load_image(data_file)
        label = load_label(label_file)
        data = np.array(data)
        label = np.array(label)
        yield data, label
return reader

但是在train过程中出现错误如下： Traceback (most recent call last): File "/Applications/PyCharm CE.app/Contents/helpers/pydev/pydevd.py", line 1599, in globals = debugger.run(setup['file'], None, None, is_module) File "/Applications/PyCharm CE.app/Contents/helpers/pydev/pydevd.py", line 1026, in run pydev_imports.execfile(file, globals, locals) # execute the script File "/Volumes/Huayong/baidu/paddlepaddle/Seg/seg_train.py", line 96, in train(net, class_num) File "/Volumes/Huayong/baidu/paddlepaddle/Seg/seg_train.py", line 79, in train 'label': 1}) File "/Library/Python/2.7/site-packages/paddle/v2/trainer.py", line 169, in train in_args = feeder(data_batch) File "/Library/Python/2.7/site-packages/py_paddle/dataprovider_converter.py", line 282, in call return self.convert(dat, argument) File "/Library/Python/2.7/site-packages/paddle/v2/data_feeder.py", line 133, in convert return DataProviderConverter.convert(self, reorder_data(dat), argument) File "/Library/Python/2.7/site-packages/py_paddle/dataprovider_converter.py", line 277, in convert scanner.finish_scan(argument) File "/Library/Python/2.7/site-packages/py_paddle/dataprovider_converter.py", line 211, in finish_scan ids = swig_paddle.IVector.create(self.ids, self.data_in_gpu) File "/Library/Python/2.7/site-packages/py_paddle/swig_paddle.py", line 1344, in create return _swig_paddle.IVector_create(args) NotImplementedError: Wrong number or type of arguments for overloaded function 'IVector_create'. Possible C/C++ prototypes are: IVector::create(std::vector< int,std::allocator< int > > const &,bool) IVector::create(std::vector< int,std::allocator< int > > const &) train代码如下： def train(net, class_num): lbl = paddle.layer.data( name="label", type=paddle.data_type.integer_value(224224))

cost = paddle.layer.cross_entropy_cost(input=net,
                                       label=lbl)

# Create parameters
parameters = paddle.parameters.create(cost)

# Create optimizer
# momentum_optimizer = paddle.optimizer.Momentum(
#     momentum=0.9,
#     regularization=paddle.optimizer.L2Regularization(rate=0.0002 * 128),
#     learning_rate=0.1 / 128.0,
#     learning_rate_decay_a=0.1,
#     learning_rate_decay_b=50000 * 100,
#     learning_rate_schedule='discexp')

# create optimizer
adam_optimizer = paddle.optimizer.Adam(
    learning_rate=2e-3,
    regularization=paddle.optimizer.L2Regularization(rate=8e-4),
    model_average=paddle.optimizer.ModelAverage(average_window=0.5))

# Create trainer
trainer = paddle.trainer.SGD(
    cost=cost, parameters=parameters, update_equation=adam_optimizer)

# End batch and end pass event handler
def event_handler(event):
    if isinstance(event, paddle.event.EndIteration):
        if event.batch_id % 2 == 0:
            print "\nPass %d, Batch %d, Cost %f, %s" % (
                event.pass_id, event.batch_id, event.cost, event.metrics)
        else:
            sys.stdout.write('.')
            sys.stdout.flush()
    if isinstance(event, paddle.event.EndPass):
        # save parameters
        with open('params_pass_%d.tar' % event.pass_id, 'w') as f:
            trainer.save_parameter_to_tar(f)

        result = trainer.test(
            reader=paddle.batch(
                seg_reader.train(), batch_size=1),
            feeding={'image': 0,
                     'label': 1})
        print "\nTest with Pass %d, %s" % (event.pass_id, result.metrics)

trainer.train(
    reader=paddle.batch(
        paddle.reader.shuffle(
            seg_reader.train(), buf_size=50000),
        batch_size=1),
    num_passes=1,
    event_handler=event_handler,
    feeding={'image': 0,
             'label': 1})
return

pycharm debug模式下查看读取的数据应该没有问题

[huayong]

看过以前提的issue，测试改变image和label类型转成int，label改成224x224一维矩阵还是一样的错误。实在是找不到是什么原因，希望帮忙看一下

[wanghaoshuang]

你的datalayer用的什么data type? 请参考以下类型：

data = paddle.layer.data(
         name="data", height=500, width=500, type=paddle.data_type.dense_array(DIM_SIZE))
label = paddle.layer.data(
         name="label", type=paddle.data_type.integer_value_sequence(500*500))

[huayong]

@wanghaoshuang 试了一下，还是一样的错误

[shanyi15]

您好，此issue在近一个月内暂无更新，我们将于今天内关闭。若在关闭后您仍需跟进提问，可重新开启此问题，我们将在24小时内回复您。因关闭带来的不便我们深表歉意，请您谅解~感谢您对PaddlePaddle的支持! Hello, this issue has not been updated in the past month. We will close it today for the sake of other user‘s experience. If you still need to follow up on this question after closing, please feel free to reopen it. In that case, we will get back to you within 24 hours. We apologize for the inconvenience caused by the closure and thank you so much for your support of PaddlePaddle Group!