ext_portrait_segmentation
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clovaai
Converting .pth model to onnx
I am trying to convert the pth model to onnx and I get the following error:
Traceback (most recent call last):
File "
RuntimeError: Failed to export an ONNX attribute 'onnx::Gather', since it's not constant, please try to make things (e.g., kernel size) static if possible
I think the error is caused by the AveragePool2D
(6) (d2): S2block( (down_res): AvgPool2d(kernel_size=4, stride=4, padding=0) (7) (d2): S2block( (down_res): AvgPool2d(kernel_size=2, stride=2, padding=0)
Please let me know if you have converted the model to onnx format before or if this error seems familiar.
add this code： size_array = [int(s) for s in x.size()[2:]] out = torch.nn.functional.avg_pool2d(x, size_array).view(batch, -1)
add this code： size_array = [int(s) for s in x.size()[2:]] out = torch.nn.functional.avg_pool2d(x, size_array).view(batch, -1) @richard-salaschavez I ran into the same problem. @xidiancpy Where to add this code?
add upon the avg_pool2d
发自我的iPhone
在 2020年11月7日，下午8:40，AlexanderGuthrie [email protected] 写道：
add this code： size_array = [int(s) for s in x.size()[2:]] out = torch.nn.functional.avg_pool2d(x, size_array).view(batch, -1) @richard-salaschavez I ran into the same problem. @xidiancpy Where to add this code?
— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub, or unsubscribe.
add upon the avg_pool2d 发自我的iPhone … 在 2020年11月7日，下午8:40，AlexanderGuthrie @.***> 写道： add this code： size_array = [int(s) for s in x.size()[2:]] out = torch.nn.functional.avg_pool2d(x, size_array).view(batch, -1) @richard-salaschavez I ran into the same problem. @xidiancpy Where to add this code? — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub, or unsubscribe.
谢谢 thank you but I think I need a different solution. I added print(desc,value,value.node(),value.node().kind()) to symbolic_helper.py so that I can debug. I am getting this error:
v 426 defined in (%426 : Float(1:37632, 12:3136, 56:56, 56:1, requires_grad=1, device=cpu) = onnx::Conv[dilations=[1, 1], group=12, kernel_shape=[3, 3], pads=[1, 1, 1, 1], strides=[2, 2]](%413, %414) # /usr/local/lib/python3.8/dist-packages/torch/nn/modules/conv.py:419:0 )
%426 : Float(1:37632, 12:3136, 56:56, 56:1, requires_grad=1, device=cpu) = onnx::Conv[dilations=[1, 1], group=12, kernel_shape=[3, 3], pads=[1, 1, 1, 1], strides=[2, 2]](%413, %414) # /usr/local/lib/python3.8/dist-packages/torch/nn/modules/conv.py:419:0
onnx::Conv
is 447 defined in (%447 : int[] = prim::ListConstruct(%441, %446) )
%447 : int[] = prim::ListConstruct(%441, %446)
prim::ListConstruct
Traceback (most recent call last):
...
File "/usr/local/lib/python3.8/dist-packages/torch/onnx/symbolic_helper.py", line 81, in _parse_arg
raise RuntimeError("Failed to export an ONNX attribute '" + v.node().kind() +
RuntimeError: Failed to export an ONNX attribute 'onnx::Gather', since it's not constant, please try to make things (e.g., kernel size) static if possible
Also I am new to exporting .pth to .onnx and this is my exporting code:
import torch
import torch.onnx
from models.SINet import SINet
config = [[[3, 1], [5, 1]], [[3, 1], [3, 1]],[[3, 1], [5, 1]], [[3, 1], [3, 1]], [[5, 1], [3, 2]], [[5, 2], [3, 4]],[[3, 1], [3, 1]], [[5, 1], [5, 1]], [[3, 2], [3, 4]], [[3, 1], [5, 2]]]
model = SINet(classes=2, p=2, q=8, config=config,chnn=1)
state_dict = torch.load('result/SINet/SINet.pth', map_location=torch.device('cpu'))
model.load_state_dict(state_dict)
dummy_input = torch.FloatTensor(1, 3, 224, 224)
torch.onnx.export(model,dummy_input,"SINet.onnx",export_params=True,input_names=['input'],output_names=['output'],dynamic_axes={'input' : {0: 'batch_size'},'output' : {0 : 'batch_size'}})
Is this a similar problem but with nn.Conv2d()? If so, how do I resolve? Any advice to complete this onnx export appreciated.
sorry
发自我的iPhone
在 2020年11月7日，下午10:38，AlexanderGuthrie [email protected] 写道：
add upon the avg_pool2d 发自我的iPhone … 在 2020年11月7日，下午8:40，AlexanderGuthrie @.***> 写道： add this code： size_array = [int(s) for s in x.size()[2:]] out = torch.nn.functional.avg_pool2d(x, size_array).view(batch, -1) @richard-salaschavez I ran into the same problem. @xidiancpy Where to add this code? — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub, or unsubscribe.
谢谢 thank you but I think I need a different solution. I added print(desc,value,value.node(),value.node().kind()) to symbolic_helper.py so that I can debug. I am getting this error:
v 426 defined in (%426 : Float(1:37632, 12:3136, 56:56, 56:1, requires_grad=1, device=cpu) = onnx::Conv[dilations=[1, 1], group=12, kernel_shape=[3, 3], pads=[1, 1, 1, 1], strides=[2, 2]](%413, %414) # /usr/local/lib/python3.8/dist-packages/torch/nn/modules/conv.py:419:0 ) %426 : Float(1:37632, 12:3136, 56:56, 56:1, requires_grad=1, device=cpu) = onnx::Conv[dilations=[1, 1], group=12, kernel_shape=[3, 3], pads=[1, 1, 1, 1], strides=[2, 2]](%413, %414) # /usr/local/lib/python3.8/dist-packages/torch/nn/modules/conv.py:419:0 onnx::Conv
is 447 defined in (%447 : int[] = prim::ListConstruct(%441, %446) ) %447 : int[] = prim::ListConstruct(%441, %446) prim::ListConstruct Traceback (most recent call last): ... File "/usr/local/lib/python3.8/dist-packages/torch/onnx/symbolic_helper.py", line 81, in _parse_arg raise RuntimeError("Failed to export an ONNX attribute '" + v.node().kind() + RuntimeError: Failed to export an ONNX attribute 'onnx::Gather', since it's not constant, please try to make things (e.g., kernel size) static if possible Also I am new to exporting .pth to .onnx and this is my exporting code:
import torch import torch.onnx from models.SINet import SINet
config = [[[3, 1], [5, 1]], [[3, 1], [3, 1]],[[3, 1], [5, 1]], [[3, 1], [3, 1]], [[5, 1], [3, 2]], [[5, 2], [3, 4]],[[3, 1], [3, 1]], [[5, 1], [5, 1]], [[3, 2], [3, 4]], [[3, 1], [5, 2]]] model = SINet(classes=2, p=2, q=8, config=config,chnn=1) state_dict = torch.load('result/SINet/SINet.pth', map_location=torch.device('cpu')) model.load_state_dict(state_dict) dummy_input = torch.FloatTensor(1, 3, 224, 224) torch.onnx.export(model,dummy_input,"SINet.onnx",export_params=True,input_names=['input'],output_names=['output'],dynamic_axes={'input' : {0: 'batch_size'},'output' : {0 : 'batch_size'}}) Any advice to resolve this error and complete this onnx export?
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@richard-salaschavez @xidiancpy I successfully converted the SINet pytorch model to a .onnx model using the SINet_ONNX.ipynb notebook by @anilsathyan7