Closed youjin-c closed 5 years ago
Hello, I was running the example and got this error.
python src/main.py +---------------------+----------------------------+ | Parameter | Value | +=====================+============================+ | Approximation order | 20 | +---------------------+----------------------------+ | Dropout | 0.500 | +---------------------+----------------------------+ | Edge path | ./input/cora_edges.csv | +---------------------+----------------------------+ | Epochs | 300 | +---------------------+----------------------------+ | Features path | ./input/cora_features.json | +---------------------+----------------------------+ | Filters | 16 | +---------------------+----------------------------+ | Learning rate | 0.001 | +---------------------+----------------------------+ | Log path | ./logs/cora_logs.json | +---------------------+----------------------------+ | Scale | 1 | +---------------------+----------------------------+ | Seed | 42 | +---------------------+----------------------------+ | Target path | ./input/cora_target.csv | +---------------------+----------------------------+ | Test size | 0.200 | +---------------------+----------------------------+ | Tolerance | 0.000 | +---------------------+----------------------------+ | Weight decay | 0.001 | +---------------------+----------------------------+ Wavelet calculation and sparsification started. 100%|███████████████████████████████████████████████████████████████████████████████████| 2708/2708 [00:11<00:00, 237.23it/s] 100%|███████████████████████████████████████████████████████████████████████████████████| 2708/2708 [00:11<00:00, 228.91it/s] Normalizing the sparsified wavelets. Density of wavelets: 0.2%. Density of inverse wavelets: 0.04%. Training. Loss: 0%| | 0/300 [00:00<?, ?it/s]Traceback (most recent call last): File "src/main.py", line 24, in <module> main() File "src/main.py", line 18, in main trainer.fit() File "/home/paperspace/Thesis/GraphWaveletNeuralNetwork/src/gwnn.py", line 131, in fit prediction = self.model(self.phi_indices, self.phi_values , self.phi_inverse_indices, self.phi_inverse_values, self.feature_indices, self.feature_values) File "/home/paperspace/miniconda2/envs/thesis/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__ result = self.forward(*input, **kwargs) File "/home/paperspace/Thesis/GraphWaveletNeuralNetwork/src/gwnn.py", line 44, in forward deep_features_1 = self.convolution_1(phi_indices, phi_values, phi_inverse_indices, phi_inverse_values, feature_indices, feature_values, self.args.dropout) File "/home/paperspace/miniconda2/envs/thesis/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__ result = self.forward(*input, **kwargs) File "/home/paperspace/Thesis/GraphWaveletNeuralNetwork/src/gwnn_layer.py", line 55, in forward localized_features = spmm(phi_product_indices, phi_product_values, self.ncount, filtered_features) File "/home/paperspace/miniconda2/envs/thesis/lib/python3.6/site-packages/torch_sparse/spmm.py", line 21, in spmm out = scatter_add(out, row, dim=0, dim_size=m) File "/home/paperspace/miniconda2/envs/thesis/lib/python3.6/site-packages/torch_scatter/add.py", line 73, in scatter_add return out.scatter_add_(dim, index, src) RuntimeError: the derivative for 'index' is not implemented
Your PyTorch Geometric version might be different.
Hello, I was running the example and got this error.