Created by: NHZlX

There must be reader instead of datareader.

train_reader = paddle.batch(datareader.train(), batch_size=batch_size)

2. I use the flowers102 dataset from paddle.dataset.flowers.train() and set the batch size to 1, but something wrong happened. Here is the log:

Traceback (most recent call last):
  File "se_resnext.py", line 157, in <module>
    train(learning_rate=0.1, batch_size=1, num_passes=100)
  File "se_resnext.py", line 127, in train
    exe.run(fluid.default_startup_program())
  File "/home/xingzhaolong/.jumbo/lib/python2.7/site-packages/paddle/v2/fluid/executor.py", line 177, in run
    self.executor.run(program.desc, scope, 0, True, True)
paddle.v2.fluid.core.EnforceNotMet: enforce allocating <= available failed, 10484135494 > 10440015616
 at [/home/xingzhaolong/pr/temp/do_something/paddle/platform/gpu_info.cc:89]
PaddlePaddle Call Stacks: 
0       0x7fab14ccdae6p paddle::platform::EnforceNotMet::EnforceNotMet(std::__exception_ptr::exception_ptr, char const*, int) + 486
1       0x7fab16b8c2eep paddle::platform::GpuMaxChunkSize() + 766
2       0x7fab14d622ebp paddle::memory::GetGPUBuddyAllocator(int) + 139
3       0x7fab14d624fcp void* paddle::memory::Alloc<paddle::platform::CUDAPlace>(paddle::platform::CUDAPlace, unsigned long) + 28
4       0x7fab14cd4f8ap paddle::framework::Tensor::PlaceholderImpl<paddle::platform::CUDAPlace>::PlaceholderImpl(paddle::platform::CUDAPlace, unsigned long, std::type_index) + 58

Seems something wrong with the memory allocating. I use the Graphics with about 10Gb memory. 2 Tesla K40m On | 0000:83:00.0 Off | 0 | | N/A 37C P0 61W / 235W | 1567MiB / 11439MiB | 0% Default | I meet the same problem when running fluid_mnist.py. Help welcome .