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AttributeError: 'bytes' object has no attribute 'encode' #43

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MEIXuYan opened this issue Jul 19, 2018 · 9 comments
Closed

AttributeError: 'bytes' object has no attribute 'encode' #43

MEIXuYan opened this issue Jul 19, 2018 · 9 comments

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@MEIXuYan
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MEIXuYan commented Jul 19, 2018 •
edited

Got error when running learning/main.py, my running environment :
ubuntu 16.04
pytorch 0.3.0 CUDA 9.0
Notice that I'm running with Semantic 3D datasets.

AttributeError: 'bytes' object has no attribute 'encode'
AttributeError: 'Program' object has no attribute '_program'

  Will save to results/sema3d/trainval_best
Total number of parameters: 213772
Module(
  (ecc): GraphNetwork(
    (0): RNNGraphConvModule(
      (_cell): GRUCellEx(32, 32)(ingate layernorm)
      (_fnet): Sequential(
        (0): Linear(in_features=13, out_features=32, bias=True)
        (1): ReLU(inplace)
        (2): Linear(in_features=32, out_features=128, bias=True)
        (3): ReLU(inplace)
        (4): Linear(in_features=128, out_features=64, bias=True)
        (5): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True)
        (6): ReLU(inplace)
        (7): Linear(in_features=64, out_features=32, bias=False)
      )
    )
    (1): Linear(in_features=352, out_features=8, bias=True)
  )
  (ptn): PointNet(
    (stn): STNkD(
      (convs): Sequential(
        (0): Conv1d(11, 64, kernel_size=(1,), stride=(1,))
        (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True)
        (2): ReLU(inplace)
        (3): Conv1d(64, 64, kernel_size=(1,), stride=(1,))
        (4): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True)
        (5): ReLU(inplace)
        (6): Conv1d(64, 128, kernel_size=(1,), stride=(1,))
        (7): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True)
        (8): ReLU(inplace)
      )
      (fcs): Sequential(
        (0): Linear(in_features=128, out_features=128, bias=True)
        (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True)
        (2): ReLU(inplace)
        (3): Linear(in_features=128, out_features=64, bias=True)
        (4): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True)
        (5): ReLU(inplace)
      )
      (proj): Linear(in_features=64, out_features=4, bias=True)
    )
    (convs): Sequential(
      (0): Conv1d(11, 64, kernel_size=(1,), stride=(1,))
      (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True)
      (2): ReLU(inplace)
      (3): Conv1d(64, 64, kernel_size=(1,), stride=(1,))
      (4): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True)
      (5): ReLU(inplace)
      (6): Conv1d(64, 128, kernel_size=(1,), stride=(1,))
      (7): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True)
      (8): ReLU(inplace)
      (9): Conv1d(128, 128, kernel_size=(1,), stride=(1,))
      (10): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True)
      (11): ReLU(inplace)
      (12): Conv1d(128, 256, kernel_size=(1,), stride=(1,))
      (13): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True)
      (14): ReLU(inplace)
    )
    (fcs): Sequential(
      (0): Linear(in_features=257, out_features=256, bias=True)
      (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True)
      (2): ReLU(inplace)
      (3): Linear(in_features=256, out_features=64, bias=True)
      (4): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True)
      (5): ReLU(inplace)
      (6): Linear(in_features=64, out_features=32, bias=True)
    )
  )
)
Epoch 0/500 (results/sema3d/trainval_best):
  0%|                                                                         | 0/7 [00:00<?, ?it/s]Traceback (most recent call last):
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/main.py", line 388, in <module>
    main()
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/main.py", line 287, in main
    acc, loss, oacc, avg_iou = train()
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/main.py", line 185, in train
    outputs = model.ecc(embeddings)
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/torch/nn/modules/module.py", line 357, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/graphnet.py", line 97, in forward
    input = module(input)
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/torch/nn/modules/module.py", line 357, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/modules.py", line 54, in forward
    input = ecc.GraphConvFunction(nc, nc, idxn, idxe, degs, degs_gpu, self._edge_mem_limit)(hx, weights)
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/ecc/GraphConvModule.py", line 67, in forward
    cuda_kernels.conv_aggregate_fw(output.narrow(0,startd,numd), products.view(-1,self._out_channels), self._degs_gpu.narrow(0,startd,numd))
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/ecc/cuda_kernels.py", line 120, in conv_aggregate_fw
    function, stream = get_kernel_func('conv_aggregate_fw_kernel_v2', conv_aggregate_fw_kernel_v2(), get_dtype(src))
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/ecc/cuda_kernels.py", line 33, in get_kernel_func
    prog = Program(ksrc.encode('utf-8'), (kname+dtype+'.cu').encode('utf-8'))
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/pynvrtc/compiler.py", line 52, in __init__
    include_names)
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/pynvrtc/interface.py", line 200, in nvrtcCreateProgram
    c_char_p(encode_str(src)), c_char_p(encode_str(name)),
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/pynvrtc/interface.py", line 54, in encode_str
    return s.encode("utf-8")
AttributeError: 'bytes' object has no attribute 'encode'
Exception ignored in: <bound method Program.__del__ of <pynvrtc.compiler.Program object at 0x7ff0da9abfd0>>
Traceback (most recent call last):
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/pynvrtc/compiler.py", line 56, in __del__
    self._interface.nvrtcDestroyProgram(self._program)
AttributeError: 'Program' object has no attribute '_program'
@loicland
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Hi,

I am not able to reproduce it. Would you mind adding the following lines at line 33 of superpoint_graph-release/learning/ecc/cuda_kernels.py:

ksrc.encode('utf-8')
(kname+dtype+'.cu').encode('utf-8')

to see which call causes the crash?

@MEIXuYan
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MEIXuYan commented Jul 20, 2018 •
edited

@loicland I have added the codes you mentioned above like this:

def get_kernel_func(kname, ksrc, dtype):
    if kname+dtype not in modules:
        ksrc = ksrc.replace('DTYPE', dtype)
        prog = Program(ksrc.encode('utf-8'), (kname+dtype+'.cu').encode('utf-8'))
        ksrc.encode('utf-8')
        (kname + dtype + '.cu').encode('utf-8')
        ptx = prog.compile()
        log = prog._interface.nvrtcGetProgramLog(prog._program)
        if len(log.strip()) > 0: print(log)
        module = cupy.cuda.function.Module()
        module.load(bytes(ptx.encode()))
        modules[kname+dtype] = module
    else:
        module = modules[kname+dtype]

but after running it, problem occurred again, like the following:

Will save to results/sema3d/trainval_best
Total number of parameters: 213772
Module(
  (ecc): GraphNetwork(
    (0): RNNGraphConvModule(
      (_cell): GRUCellEx(32, 32)(ingate layernorm)
      (_fnet): Sequential(
        (0): Linear(in_features=13, out_features=32, bias=True)
        (1): ReLU(inplace)
        (2): Linear(in_features=32, out_features=128, bias=True)
        (3): ReLU(inplace)
        (4): Linear(in_features=128, out_features=64, bias=True)
        (5): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True)
        (6): ReLU(inplace)
        (7): Linear(in_features=64, out_features=32, bias=False)
      )
    )
    (1): Linear(in_features=352, out_features=8, bias=True)
  )
  (ptn): PointNet(
    (stn): STNkD(
      (convs): Sequential(
        (0): Conv1d(11, 64, kernel_size=(1,), stride=(1,))
        (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True)
        (2): ReLU(inplace)
        (3): Conv1d(64, 64, kernel_size=(1,), stride=(1,))
        (4): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True)
        (5): ReLU(inplace)
        (6): Conv1d(64, 128, kernel_size=(1,), stride=(1,))
        (7): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True)
        (8): ReLU(inplace)
      )
      (fcs): Sequential(
        (0): Linear(in_features=128, out_features=128, bias=True)
        (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True)
        (2): ReLU(inplace)
        (3): Linear(in_features=128, out_features=64, bias=True)
        (4): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True)
        (5): ReLU(inplace)
      )
      (proj): Linear(in_features=64, out_features=4, bias=True)
    )
    (convs): Sequential(
      (0): Conv1d(11, 64, kernel_size=(1,), stride=(1,))
      (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True)
      (2): ReLU(inplace)
      (3): Conv1d(64, 64, kernel_size=(1,), stride=(1,))
      (4): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True)
      (5): ReLU(inplace)
      (6): Conv1d(64, 128, kernel_size=(1,), stride=(1,))
      (7): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True)
      (8): ReLU(inplace)
      (9): Conv1d(128, 128, kernel_size=(1,), stride=(1,))
      (10): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True)
      (11): ReLU(inplace)
      (12): Conv1d(128, 256, kernel_size=(1,), stride=(1,))
      (13): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True)
      (14): ReLU(inplace)
    )
    (fcs): Sequential(
      (0): Linear(in_features=257, out_features=256, bias=True)
      (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True)
      (2): ReLU(inplace)
      (3): Linear(in_features=256, out_features=64, bias=True)
      (4): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True)
      (5): ReLU(inplace)
      (6): Linear(in_features=64, out_features=32, bias=True)
    )
  )
)
Epoch 0/500 (results/sema3d/trainval_best):
  0%|                                                                         | 0/7 [00:00<?, ?it/s]Traceback (most recent call last):
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/main.py", line 388, in <module>
    main()
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/main.py", line 287, in main
    acc, loss, oacc, avg_iou = train()
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/main.py", line 185, in train
    outputs = model.ecc(embeddings)
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/torch/nn/modules/module.py", line 357, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/graphnet.py", line 97, in forward
    input = module(input)
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/torch/nn/modules/module.py", line 357, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/modules.py", line 54, in forward
    input = ecc.GraphConvFunction(nc, nc, idxn, idxe, degs, degs_gpu, self._edge_mem_limit)(hx, weights)
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/ecc/GraphConvModule.py", line 67, in forward
    cuda_kernels.conv_aggregate_fw(output.narrow(0,startd,numd), products.view(-1,self._out_channels), self._degs_gpu.narrow(0,startd,numd))
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/ecc/cuda_kernels.py", line 122, in conv_aggregate_fw
    function, stream = get_kernel_func('conv_aggregate_fw_kernel_v2', conv_aggregate_fw_kernel_v2(), get_dtype(src))
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/ecc/cuda_kernels.py", line 33, in get_kernel_func
    prog = Program(ksrc.encode('utf-8'), (kname+dtype+'.cu').encode('utf-8'))
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/pynvrtc/compiler.py", line 52, in __init__
    include_names)
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/pynvrtc/interface.py", line 200, in nvrtcCreateProgram
    c_char_p(encode_str(src)), c_char_p(encode_str(name)),
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/pynvrtc/interface.py", line 54, in encode_str
    return s.encode("utf-8")
AttributeError: 'bytes' object has no attribute 'encode'
Exception ignored in: <bound method Program.__del__ of <pynvrtc.compiler.Program object at 0x7f53a0e84978>>
Traceback (most recent call last):
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/pynvrtc/compiler.py", line 56, in __del__
    self._interface.nvrtcDestroyProgram(self._program)
AttributeError: 'Program' object has no attribute '_program'

Notice that I ran this code in Python 3.5 and Pytorch 0.3.1

@loicland
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Owner

Hi,

I meant to put the lines

ksrc.encode('utf-8')
(kname+dtype+'.cu').encode('utf-8')

above

prog = Program(ksrc.encode('utf-8'), (kname+dtype+'.cu').encode('utf-8'))

to see which one cause the error.

@MEIXuYan
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Author

MEIXuYan commented Jul 21, 2018 •
edited

sorry, the output is :

Epoch 0/500 (results/sema3d/trainval_best):
  0%|                                                                         | 0/7 [00:00<?, ?it/s]Traceback (most recent call last):
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/main.py", line 388, in <module>
    main()
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/main.py", line 287, in main
    acc, loss, oacc, avg_iou = train()
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/main.py", line 185, in train
    outputs = model.ecc(embeddings)
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/torch/nn/modules/module.py", line 357, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/graphnet.py", line 97, in forward
    input = module(input)
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/torch/nn/modules/module.py", line 357, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/modules.py", line 54, in forward
    input = ecc.GraphConvFunction(nc, nc, idxn, idxe, degs, degs_gpu, self._edge_mem_limit)(hx, weights)
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/ecc/GraphConvModule.py", line 67, in forward
    cuda_kernels.conv_aggregate_fw(output.narrow(0,startd,numd), products.view(-1,self._out_channels), self._degs_gpu.narrow(0,startd,numd))
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/ecc/cuda_kernels.py", line 122, in conv_aggregate_fw
    function, stream = get_kernel_func('conv_aggregate_fw_kernel_v2', conv_aggregate_fw_kernel_v2(), get_dtype(src))
  File "/home/xuyan/pytorch_xuyan/superpoint_graph-release/learning/ecc/cuda_kernels.py", line 35, in get_kernel_func
    prog = Program(ksrc.encode('utf-8'), (kname+dtype+'.cu').encode('utf-8'))
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/pynvrtc/compiler.py", line 52, in __init__
    include_names)
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/pynvrtc/interface.py", line 200, in nvrtcCreateProgram
    c_char_p(encode_str(src)), c_char_p(encode_str(name)),
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/pynvrtc/interface.py", line 54, in encode_str
    return s.encode("utf-8")
AttributeError: 'bytes' object has no attribute 'encode'
Exception ignored in: <bound method Program.__del__ of <pynvrtc.compiler.Program object at 0x7fb27a822588>>
Traceback (most recent call last):
  File "/home/xuyan/tensorflow_xuyan/virtual_3.5/lib/python3.5/site-packages/pynvrtc/compiler.py", line 56, in __del__
    self._interface.nvrtcDestroyProgram(self._program)
AttributeError: 'Program' object has no attribute '_program'

@minhaoxu1995
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minhaoxu1995 commented Jul 23, 2018 •
edited

Hi

I have the same problem as @MEIXuYan .

My env: Ubuntu 16.04, Python 3.6, Pytorch 0.3.1, CUDA 9.0. When I run the learning script, the terminal shows the same error info as Xuyan's.

I tried to change the line 54 of interface.py in

~/anaconda3/envs/spgenv/lib/python3.6/site-packages/pynvrtc

from return s.encode("utf-8") to return s, and the learning script is running with no error now. I am not sure about the principle beneath but it is working...

@loicland
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Owner

loicland commented Jul 23, 2018 •
edited

Hi,

I would discourage changing directly the python package, as it could have adverse consequences with other project.

Program expects bytes or integer, and not string. For some reason, that I am not able to reproduce, it seems that in your case the names are already encoded. Hence, following your fix, I would suggest replacing line 3̶5̶ 33 of /learning/ecc/cuda_kernels.py by

prog = Program(ksrc, (kname+dtype+'.cu'))

Could you tell me if it fixes the issue?

@minhaoxu1995
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Hi Loic,

I think you meant line 33, then it works. Thanks!

@loicland
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Good. I did not write the kernel, mys007 did. I will refer it to him in case he has more insight what might be going on.

@loicland loicland mentioned this issue Aug 30, 2018
Closed
@mys007
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mys007 commented Aug 30, 2018

This was caused by recently merged NVIDIA/pynvrtc#2 and fixed here today - 44bcbe8

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@loicland @mys007 @MEIXuYan @minhaoxu1995