panzheyi / ST-MetaNet

The codes and data of paper "Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning"
MIT License
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mxnet-cu90 == 1.5.0b20190108 如何安装? #5

Closed LiFXe closed 3 years ago

LiFXe commented 3 years ago

作者您好,请问如何装此版本?pip命令报错找不到此版本。期待您的回复,提前感谢!

panzheyi commented 3 years ago

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).

LiFXe commented 3 years ago

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::allocator > const&, std::vector<mxnet::OpReqType, std::allocator > const&, std::vector<mxnet::TBlob, std::allocator > const&)> const&, nnvm::Op const, nnvm::NodeAttrs const&, mxnet::Context const&, std::vector<mxnet::engine::Var, std::allocator<mxnet::engine::Var> > const&, std::vector<mxnet::engine::Var, std::allocator<mxnet::engine::Var> > const&, std::vector<mxnet::Resource, std::allocator > const&, std::vector<mxnet::NDArray, std::allocator<mxnet::NDArray> > const&, std::vector<mxnet::NDArray, std::allocator<mxnet::NDArray*> > const&, std::vector<unsigned int, std::allocator > const&, std::vector<mxnet::OpReqType, std::allocator > 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]

LiFXe commented 3 years ago
        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

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panzheyi commented 3 years ago

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。