Comments (4)
panzheyi
commented on July 17, 2024
Hi, it seems that the beta version of mxnet is removed on pip.
Instead, you can find a related version on https://repo.mxnet.io/dist/index.html (as the API of beta version is not stable, please download the version with the nearest built date to 20190108).
from st-metanet.
LiFXe
commented on July 17, 2024
谢谢，请问cuda与cudnn版本是？现在会报错
Successfully loading the model st-metanet [epoch: 131]
seq2seq_ (
Parameter seq2seq_encoder_c0_gru0_i2h_weight (shape=(192, 3), dtype=<class 'numpy.float32'>)
Parameter seq2seq_encoder_c0_gru0_h2h_weight (shape=(192, 64), dtype=<class 'numpy.float32'>)
Parameter seq2seq_encoder_c0_gru0_i2h_bias (shape=(192,), dtype=<class 'numpy.float32'>)
Parameter seq2seq_encoder_c0_gru0_h2h_bias (shape=(192,), dtype=<class 'numpy.float32'>)
Parameter seq2seq_encoder_c1_dense_z_w_dense0_weight (shape=(16, 32), dtype=float32)
Parameter seq2seq_encoder_c1_dense_z_w_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_z_w_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_encoder_c1_dense_z_w_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_z_w_dense2_weight (shape=(8192, 2), dtype=float32)
Parameter seq2seq_encoder_c1_dense_z_w_dense2_bias (shape=(8192,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_z_b_dense0_weight (shape=(16, 32), dtype=float32)
Parameter seq2seq_encoder_c1_dense_z_b_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_z_b_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_encoder_c1_dense_z_b_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_z_b_dense2_weight (shape=(1, 2), dtype=float32)
Parameter seq2seq_encoder_c1_dense_z_b_dense2_bias (shape=(1,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_r_w_dense0_weight (shape=(16, 32), dtype=float32)
Parameter seq2seq_encoder_c1_dense_r_w_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_r_w_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_encoder_c1_dense_r_w_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_r_w_dense2_weight (shape=(8192, 2), dtype=float32)
Parameter seq2seq_encoder_c1_dense_r_w_dense2_bias (shape=(8192,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_r_b_dense0_weight (shape=(16, 32), dtype=float32)
Parameter seq2seq_encoder_c1_dense_r_b_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_r_b_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_encoder_c1_dense_r_b_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_r_b_dense2_weight (shape=(1, 2), dtype=float32)
Parameter seq2seq_encoder_c1_dense_r_b_dense2_bias (shape=(1,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_i2h_w_dense0_weight (shape=(16, 32), dtype=float32)
Parameter seq2seq_encoder_c1_dense_i2h_w_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_i2h_w_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_encoder_c1_dense_i2h_w_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_i2h_w_dense2_weight (shape=(4096, 2), dtype=float32)
Parameter seq2seq_encoder_c1_dense_i2h_w_dense2_bias (shape=(4096,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_i2h_b_dense0_weight (shape=(16, 32), dtype=float32)
Parameter seq2seq_encoder_c1_dense_i2h_b_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_i2h_b_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_encoder_c1_dense_i2h_b_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_i2h_b_dense2_weight (shape=(1, 2), dtype=float32)
Parameter seq2seq_encoder_c1_dense_i2h_b_dense2_bias (shape=(1,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_h2h_w_dense0_weight (shape=(16, 32), dtype=float32)
Parameter seq2seq_encoder_c1_dense_h2h_w_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_h2h_w_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_encoder_c1_dense_h2h_w_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_h2h_w_dense2_weight (shape=(4096, 2), dtype=float32)
Parameter seq2seq_encoder_c1_dense_h2h_w_dense2_bias (shape=(4096,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_h2h_b_dense0_weight (shape=(16, 32), dtype=float32)
Parameter seq2seq_encoder_c1_dense_h2h_b_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_h2h_b_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_encoder_c1_dense_h2h_b_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_encoder_c1_dense_h2h_b_dense2_weight (shape=(1, 2), dtype=float32)
Parameter seq2seq_encoder_c1_dense_h2h_b_dense2_bias (shape=(1,), dtype=float32)
Parameter seq2seq_encoder_g0_graph_weight (shape=(1, 1), dtype=<class 'numpy.float32'>)
Parameter seq2seq_encoder_g0_graph_mlp0_dense0_weight (shape=(16, 96), dtype=float32)
Parameter seq2seq_encoder_g0_graph_mlp0_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_encoder_g0_graph_mlp0_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_encoder_g0_graph_mlp0_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_encoder_g0_graph_mlp0_dense2_weight (shape=(8192, 2), dtype=float32)
Parameter seq2seq_encoder_g0_graph_mlp0_dense2_bias (shape=(8192,), dtype=float32)
Parameter seq2seq_decoder_c0_gru0_i2h_weight (shape=(192, 3), dtype=<class 'numpy.float32'>)
Parameter seq2seq_decoder_c0_gru0_h2h_weight (shape=(192, 64), dtype=<class 'numpy.float32'>)
Parameter seq2seq_decoder_c0_gru0_i2h_bias (shape=(192,), dtype=<class 'numpy.float32'>)
Parameter seq2seq_decoder_c0_gru0_h2h_bias (shape=(192,), dtype=<class 'numpy.float32'>)
Parameter seq2seq_decoder_c1_dense_z_w_dense0_weight (shape=(16, 32), dtype=float32)
Parameter seq2seq_decoder_c1_dense_z_w_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_z_w_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_decoder_c1_dense_z_w_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_z_w_dense2_weight (shape=(8192, 2), dtype=float32)
Parameter seq2seq_decoder_c1_dense_z_w_dense2_bias (shape=(8192,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_z_b_dense0_weight (shape=(16, 32), dtype=float32)
Parameter seq2seq_decoder_c1_dense_z_b_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_z_b_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_decoder_c1_dense_z_b_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_z_b_dense2_weight (shape=(1, 2), dtype=float32)
Parameter seq2seq_decoder_c1_dense_z_b_dense2_bias (shape=(1,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_r_w_dense0_weight (shape=(16, 32), dtype=float32)
Parameter seq2seq_decoder_c1_dense_r_w_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_r_w_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_decoder_c1_dense_r_w_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_r_w_dense2_weight (shape=(8192, 2), dtype=float32)
Parameter seq2seq_decoder_c1_dense_r_w_dense2_bias (shape=(8192,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_r_b_dense0_weight (shape=(16, 32), dtype=float32)
Parameter seq2seq_decoder_c1_dense_r_b_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_r_b_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_decoder_c1_dense_r_b_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_r_b_dense2_weight (shape=(1, 2), dtype=float32)
Parameter seq2seq_decoder_c1_dense_r_b_dense2_bias (shape=(1,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_i2h_w_dense0_weight (shape=(16, 32), dtype=float32)
Parameter seq2seq_decoder_c1_dense_i2h_w_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_i2h_w_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_decoder_c1_dense_i2h_w_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_i2h_w_dense2_weight (shape=(4096, 2), dtype=float32)
Parameter seq2seq_decoder_c1_dense_i2h_w_dense2_bias (shape=(4096,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_i2h_b_dense0_weight (shape=(16, 32), dtype=float32)
Parameter seq2seq_decoder_c1_dense_i2h_b_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_i2h_b_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_decoder_c1_dense_i2h_b_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_i2h_b_dense2_weight (shape=(1, 2), dtype=float32)
Parameter seq2seq_decoder_c1_dense_i2h_b_dense2_bias (shape=(1,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_h2h_w_dense0_weight (shape=(16, 32), dtype=float32)
Parameter seq2seq_decoder_c1_dense_h2h_w_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_h2h_w_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_decoder_c1_dense_h2h_w_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_h2h_w_dense2_weight (shape=(4096, 2), dtype=float32)
Parameter seq2seq_decoder_c1_dense_h2h_w_dense2_bias (shape=(4096,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_h2h_b_dense0_weight (shape=(16, 32), dtype=float32)
Parameter seq2seq_decoder_c1_dense_h2h_b_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_h2h_b_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_decoder_c1_dense_h2h_b_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_decoder_c1_dense_h2h_b_dense2_weight (shape=(1, 2), dtype=float32)
Parameter seq2seq_decoder_c1_dense_h2h_b_dense2_bias (shape=(1,), dtype=float32)
Parameter seq2seq_decoder_g0_graph_weight (shape=(1, 1), dtype=<class 'numpy.float32'>)
Parameter seq2seq_decoder_g0_graph_mlp0_dense0_weight (shape=(16, 96), dtype=float32)
Parameter seq2seq_decoder_g0_graph_mlp0_dense0_bias (shape=(16,), dtype=float32)
Parameter seq2seq_decoder_g0_graph_mlp0_dense1_weight (shape=(2, 16), dtype=float32)
Parameter seq2seq_decoder_g0_graph_mlp0_dense1_bias (shape=(2,), dtype=float32)
Parameter seq2seq_decoder_g0_graph_mlp0_dense2_weight (shape=(8192, 2), dtype=float32)
Parameter seq2seq_decoder_g0_graph_mlp0_dense2_bias (shape=(8192,), dtype=float32)
Parameter decoder0_proj_weight (shape=(2, 96), dtype=float32)
Parameter decoder0_proj_bias (shape=(2,), dtype=float32)
Parameter geo_encoder_dense0_weight (shape=(32, 989), dtype=float32)
Parameter geo_encoder_dense0_bias (shape=(32,), dtype=float32)
Parameter geo_encoder_dense1_weight (shape=(32, 32), dtype=float32)
Parameter geo_encoder_dense1_bias (shape=(32,), dtype=float32)
)
NUMBER OF PARAMS: 268224
INFO:root:Processing 1000 timestamps
INFO:root:Processing 2000 timestamps
INFO:root:shape of feature: (2266, 1024, 989)
INFO:root:shape of data: (2266, 12, 1024, 3)
INFO:root:shape of label: (2266, 3, 1024, 3)
INFO:root:Processing 0 timestamps
INFO:root:shape of feature: (346, 1024, 989)
INFO:root:shape of data: (346, 12, 1024, 3)
INFO:root:shape of label: (346, 3, 1024, 3)
INFO:root:Processing 0 timestamps
INFO:root:shape of feature: (306, 1024, 989)
INFO:root:shape of data: (306, 12, 1024, 3)
INFO:root:shape of label: (306, 3, 1024, 3)
Traceback (most recent call last):
File "train.py", line 172, in
main(args)
File "train.py", line 150, in main
metrics = [MAE(scaler), RMSE(scaler), IndexMAE(scaler, [0,1,2]), IndexRMSE(scaler, [0,1,2])],
File "train.py", line 72, in fit
self.process_data(epoch, train, metrics)
File "train.py", line 58, in process_data
self.step(batch_data[0].shape[0])
File "train.py", line 37, in step
gluon.utils.clip_global_norm(grads, self.clip_gradient * math.sqrt(len(self.ctx)))
File "/home/lfx19/anaconda3/envs/stmetanet_lfx/lib/python3.5/site-packages/mxnet/gluon/utils.py", line 148, in clip_global_norm
if not np.isfinite(total_norm.asscalar()):
File "/home/lfx19/anaconda3/envs/stmetanet_lfx/lib/python3.5/site-packages/mxnet/ndarray/ndarray.py", line 2005, in asscalar
return self.asnumpy()[0]
File "/home/lfx19/anaconda3/envs/stmetanet_lfx/lib/python3.5/site-packages/mxnet/ndarray/ndarray.py", line 1987, in asnumpy
ctypes.c_size_t(data.size)))
File "/home/lfx19/anaconda3/envs/stmetanet_lfx/lib/python3.5/site-packages/mxnet/base.py", line 252, in check_call
raise MXNetError(py_str(_LIB.MXGetLastError()))
mxnet.base.MXNetError: [19:31:14] src/operator/contrib/./../linalg_impl.h:212: Check failed: e == CUBLAS_STATUS_SUCCESS (13 vs. 0) cuBLAS: CUBLAS_STATUS_EXECUTION_FAILED
Stack trace returned 10 entries:
[bt] (0) /home/lfx19/anaconda3/envs/stmetanet_lfx/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x40585a) [0x7f270f00f85a]
[bt] (1) /home/lfx19/anaconda3/envs/stmetanet_lfx/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x405e71) [0x7f270f00fe71]
[bt] (2) /home/lfx19/anaconda3/envs/stmetanet_lfx/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x3557f7b) [0x7f2712161f7b]
[bt] (3) /home/lfx19/anaconda3/envs/stmetanet_lfx/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x37a637f) [0x7f27123b037f]
[bt] (4) /home/lfx19/anaconda3/envs/stmetanet_lfx/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x37ab979) [0x7f27123b5979]
[bt] (5) /home/lfx19/anaconda3/envs/stmetanet_lfx/lib/python3.5/site-packages/mxnet/libmxnet.so(mxnet::imperative::PushFCompute(std::function<void (nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocatormxnet::TBlob > const&, std::vector<mxnet::OpReqType, std::allocatormxnet::OpReqType > const&, std::vector<mxnet::TBlob, std::allocatormxnet::TBlob > const&)> const&, nnvm::Op const*, nnvm::NodeAttrs const&, mxnet::Context const&, std::vector<mxnet::engine::Var*, std::allocatormxnet::engine::Var* > const&, std::vector<mxnet::engine::Var*, std::allocatormxnet::engine::Var* > const&, std::vector<mxnet::Resource, std::allocatormxnet::Resource > const&, std::vector<mxnet::NDArray*, std::allocatormxnet::NDArray* > const&, std::vector<mxnet::NDArray*, std::allocatormxnet::NDArray* > const&, std::vector<unsigned int, std::allocator > const&, std::vector<mxnet::OpReqType, std::allocatormxnet::OpReqType > const&)::{lambda(mxnet::RunContext)#1}::operator()(mxnet::RunContext) const+0x2e8) [0x7f2711926d78]
[bt] (6) /home/lfx19/anaconda3/envs/stmetanet_lfx/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x2c6e749) [0x7f2711878749]
[bt] (7) /home/lfx19/anaconda3/envs/stmetanet_lfx/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x2c77f74) [0x7f2711881f74]
[bt] (8) /home/lfx19/anaconda3/envs/stmetanet_lfx/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x2c7c253) [0x7f2711886253]
[bt] (9) /home/lfx19/anaconda3/envs/stmetanet_lfx/lib/python3.5/site-packages/mxnet/libmxnet.so(+0x2c7c4a6) [0x7f27118864a6]
from st-metanet.
LiFXe
commented on July 17, 2024
非常感谢！另现在又遇新的报错，希望能得到您的指点，谢谢🙏
您好。pip上现在看不到过去版本的mxnet了。https://dist.mxnet.io/python/cu90
—You are receiving this because you authored the thread.Reply to this email directly, view it on GitHub, or unsubscribe.
[
{
"@context": "http://schema.org",
"@type": "EmailMessage",
"potentialAction": {
"@type": "ViewAction",
"target": "#5 (comment)",
"url": "#5 (comment)",
"name": "View Issue"
},
"description": "View this Issue on GitHub",
"publisher": {
"@type": "Organization",
"name": "GitHub",
"url": "https://github.com"
}
}
]
from st-metanet.
panzheyi
commented on July 17, 2024
cuda与cudnn版本没有特别的要求，只要cuda版本和mxnet-cu的版本匹配，cudnn版本与cuda版本匹配即可。
from st-metanet.
Related Issues (16)
- Questions regarding the setup
- What is it 'model' in import model in train.py in flow-prediction/src/ and what is its role? thank you
- Which part of code loads BJ_POI.h5 and BJ_ROAD.h5 files? HOT 1
- Running error with sudden cancellation HOT 3
- Run errors with "DeferredInitializationError"
- About BJ_FEATURE.h5
- OSError: libcudart.so.9.0: cannot open shared object file: No such file or directory
- AttributeError: 'NDArray' object has no attribute 'device'
- Runing error. HOT 2
- Running error HOT 3
- Modeling and Training of EMK/NMK Learner HOT 2
- Question regarding Seq2Seq input data HOT 1
- Regarding update function in MetaGat HOT 2
- 您好，求教报错原因是什么，谢谢！mxnet.base.MXNetError: [22:13:41] src/operator/contrib/./../linalg_impl.h:212: Check failed: e == CUBLAS_STATUS_SUCCESS (13 vs. 0) cuBLAS: CUBLAS_STATUS_EXECUTION_FAILED
- date range HOT 1
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from st-metanet.