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E:\work\ncnn\build\tools\onnx\pnnx>pnnx bestyb2.onnx inputshape=[1,3,640,640] fp16=1 pnnxparam = bestyb2.pnnx.param pnnxbin = bestyb2.pnnx.bin pnnxpy = bestyb2_pnnx.py pnnxonnx = bestyb2.pnnx.onnx ncnnparam = bestyb2.ncnn.param ncnnbin = bestyb2.ncnn.bin ncnnpy = bestyb2_ncnn.py fp16 = 1 optlevel = 2 device = cpu inputshape = [1,3,640,640]f32 inputshape2 = customop = moduleop = ############# pass_level0 onnx inline_containers ... 0.01ms eliminate_noop ... 0.39ms fold_constants ... 0.44ms canonicalize ... 0.51ms shape_inference ... 159.82ms fold_constants_dynamic_shape ... 0.22ms inline_if_graph ... 0.05ms fuse_constant_as_attribute ... 0.60ms eliminate_noop_with_shape ... 0.26ms ┌──────────────────┬──────────┬──────────┐ │ │ orig │ opt │ ├──────────────────┼──────────┼──────────┤ │ node │ 234 │ 234 │ │ initializer │ 139 │ 130 │ │ functions │ 0 │ 0 │ ├──────────────────┼──────────┼──────────┤ │ nn module op │ 0 │ 0 │ │ custom module op │ 0 │ 0 │ │ aten op │ 0 │ 0 │ │ prims op │ 0 │ 0 │ │ onnx native op │ 234 │ 234 │ ├──────────────────┼──────────┼──────────┤ │ Add │ 8 │ 8 │ │ Concat │ 19 │ 19 │ │ Conv │ 64 │ 64 │ │ Div │ 1 │ 1 │ │ MaxPool │ 3 │ 3 │ │ Mul │ 58 │ 58 │ │ Reshape │ 5 │ 5 │ │ Resize │ 2 │ 2 │ │ Sigmoid │ 58 │ 58 │ │ Slice │ 2 │ 2 │ │ Softmax │ 1 │ 1 │ │ Split │ 9 │ 9 │ │ Sub │ 2 │ 2 │ │ Transpose │ 2 │ 2 │ └──────────────────┴──────────┴──────────┘ ############# pass_level1 onnx ############# pass_level2 ############# pass_level3 open failed ############# pass_level4 ############# pass_level5 ############# pass_ncnn
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同じ状況です。解決策等あれば教えてください。
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convertmodel.com网站目前无法访问,推荐使用pnnx转换模型 https://github.com/pnnx/pnnx
快速安装 pip3 install pnnx 转换方法 pnnx resnet18.onnx inputshape=[1,3,224,224]
我成功了,欢迎参考:https://mp.weixin.qq.com/s/wtBa9aD2gdzwJmxSg9VUXA
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E:\work\ncnn\build\tools\onnx\pnnx>pnnx bestyb2.onnx inputshape=[1,3,640,640] fp16=1
pnnxparam = bestyb2.pnnx.param
pnnxbin = bestyb2.pnnx.bin
pnnxpy = bestyb2_pnnx.py
pnnxonnx = bestyb2.pnnx.onnx
ncnnparam = bestyb2.ncnn.param
ncnnbin = bestyb2.ncnn.bin
ncnnpy = bestyb2_ncnn.py
fp16 = 1
optlevel = 2
device = cpu
inputshape = [1,3,640,640]f32
inputshape2 =
customop =
moduleop =
############# pass_level0 onnx
inline_containers ... 0.01ms
eliminate_noop ... 0.39ms
fold_constants ... 0.44ms
canonicalize ... 0.51ms
shape_inference ... 159.82ms
fold_constants_dynamic_shape ... 0.22ms
inline_if_graph ... 0.05ms
fuse_constant_as_attribute ... 0.60ms
eliminate_noop_with_shape ... 0.26ms
┌──────────────────┬──────────┬──────────┐
│ │ orig │ opt │
├──────────────────┼──────────┼──────────┤
│ node │ 234 │ 234 │
│ initializer │ 139 │ 130 │
│ functions │ 0 │ 0 │
├──────────────────┼──────────┼──────────┤
│ nn module op │ 0 │ 0 │
│ custom module op │ 0 │ 0 │
│ aten op │ 0 │ 0 │
│ prims op │ 0 │ 0 │
│ onnx native op │ 234 │ 234 │
├──────────────────┼──────────┼──────────┤
│ Add │ 8 │ 8 │
│ Concat │ 19 │ 19 │
│ Conv │ 64 │ 64 │
│ Div │ 1 │ 1 │
│ MaxPool │ 3 │ 3 │
│ Mul │ 58 │ 58 │
│ Reshape │ 5 │ 5 │
│ Resize │ 2 │ 2 │
│ Sigmoid │ 58 │ 58 │
│ Slice │ 2 │ 2 │
│ Softmax │ 1 │ 1 │
│ Split │ 9 │ 9 │
│ Sub │ 2 │ 2 │
│ Transpose │ 2 │ 2 │
└──────────────────┴──────────┴──────────┘
############# pass_level1 onnx
############# pass_level2
############# pass_level3
open failed
############# pass_level4
############# pass_level5
############# pass_ncnn
The text was updated successfully, but these errors were encountered: