PointNeXt
PointNeXt copied to clipboard
I'm having trouble running pointmlp
I entered the following command under the ModelNet40 classification dataset: CUDA_VISIBLE_DEVICES=0,1 python examples/classification/main.py --cfg cfgs/modelnet40ply2048/pointmlp.yaml
I get the following error:
Traceback (most recent call last):
File "examples/classification/main.py", line 67, in
May I ask where is the problem?
Hi, there😊, Thank you for your question, I will try PointMLP from my side, and if it is a bug I will fix it later, Thank you!
Hi, there, we are attending neurips and emnlp, I will fix it after the conference, thanks for your patience.
嗨,我们在那里参加 neurips 和 emnlp,我会在会议结束后修复它,感谢您的耐心等待。
thank you very much
Hi, there, we are attending neurips and emnlp, I will fix it after the conference, thanks for your patience. Excuse me again, have you fixed this error?
maybe try this,it can run !!
# GFLOPs GMACs Params.(M)
# 31.36 15.61 13.239
model:
NAME: BaseCls
encoder_args:
NAME: PointMLP
in_channels: 3
points: 1024
num_classes: 40
embed_dim: 64
groups: 1
res_expansion: 1.0
activation: "relu"
bias: False
use_xyz: False
normalize: "anchor"
dim_expansion: [ 2, 2, 2, 2 ]
pre_blocks: [ 2, 2, 2, 2 ]
pos_blocks: [ 2, 2, 2, 2 ]
k_neighbors: [ 24, 24, 24, 24 ]
reducers: [ 2, 2, 2, 2 ]
lr:
0.1
optimizer:
NAME: 'momentum'
momentum: 0.9
weight_decay: 2.0e-4
sched: cosine
epochs: 300
t_max: 300
min_lr: 0.005
warmup_epochs: 0 # Later change to 10?
criterion_args:
NAME: SmoothCrossEntropy
label_smoothing: 0.2
datatransforms:
train: [PointsToTensor, PointCloudScaleAndTranslate]
vote: [PointCloudScaleAndTranslate]
val: [PointsToTensor]
kwargs:
shift: [0.2, 0.2, 0.2]
batch_size: 32
val_batch_size: 64
maybe try this,it can run !!
# GFLOPs GMACs Params.(M) # 31.36 15.61 13.239 model: NAME: BaseCls encoder_args: NAME: PointMLP in_channels: 3 points: 1024 num_classes: 40 embed_dim: 64 groups: 1 res_expansion: 1.0 activation: "relu" bias: False use_xyz: False normalize: "anchor" dim_expansion: [ 2, 2, 2, 2 ] pre_blocks: [ 2, 2, 2, 2 ] pos_blocks: [ 2, 2, 2, 2 ] k_neighbors: [ 24, 24, 24, 24 ] reducers: [ 2, 2, 2, 2 ] lr: 0.1 optimizer: NAME: 'momentum' momentum: 0.9 weight_decay: 2.0e-4 sched: cosine epochs: 300 t_max: 300 min_lr: 0.005 warmup_epochs: 0 # Later change to 10? criterion_args: NAME: SmoothCrossEntropy label_smoothing: 0.2 datatransforms: train: [PointsToTensor, PointCloudScaleAndTranslate] vote: [PointCloudScaleAndTranslate] val: [PointsToTensor] kwargs: shift: [0.2, 0.2, 0.2] batch_size: 32 val_batch_size: 64
thank you very much!!! i will try