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pyg-team / pytorch_geometric

Graph Neural Network Library for PyTorch
https://pyg.org
MIT License
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TypeError: 'list' object is not callable #9437

Closed nowyouseemejoe closed 6 days ago

nowyouseemejoe commented 1 week ago

🐛 Describe the bug

from torch.nn import Linear, ReLU, Dropout
from torch_geometric.nn import Sequential, GCNConv, JumpingKnowledge
from torch_geometric.nn import global_mean_pool

model = Sequential('x, edge_index, batch', [
    (Dropout(p=0.5), 'x -> x'),
    (GCNConv(2, 64), 'x, edge_index -> x1'),
    ReLU(inplace=True),
    (GCNConv(64, 64), 'x1, edge_index -> x2'),
    ReLU(inplace=True),
    (lambda x1, x2: [x1, x2], 'x1, x2 -> xs'),
    (JumpingKnowledge("cat", 64, num_layers=2), 'xs -> x'),
    (global_mean_pool, 'x, batch -> x'),
    Linear(2 * 64, 3),
]).to('cpu')

It throws TypeError: 'list' object is not callable

Versions

PyTorch version: 2.2.2+cu121 Is debug build: False CUDA used to build PyTorch: 12.1 ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.3 LTS (x86_64) GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 Clang version: Could not collect CMake version: version 3.27.2 Libc version: glibc-2.35

Python version: 3.9.19 | packaged by conda-forge | (main, Mar 20 2024, 12:50:21) [GCC 12.3.0] (64-bit runtime) Python platform: Linux-6.2.0-39-generic-x86_64-with-glibc2.35 Is CUDA available: True CUDA runtime version: 12.4.131 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3090 Ti GPU 1: NVIDIA GeForce RTX 3090 Ti

Nvidia driver version: 550.54.14 cuDNN version: Probably one of the following: /usr/lib/x86_64-linux-gnu/libcudnn.so.8.6.0 /usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.6.0 /usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.6.0 /usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.6.0 /usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.6.0 /usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.6.0 /usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.6.0 /usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn.so.8.5.0 /usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.5.0 /usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.5.0 /usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.5.0 /usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.5.0 /usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.5.0 /usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.5.0 HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True

CPU: Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 43 bits physical, 48 bits virtual Byte Order: Little Endian CPU(s): 48 On-line CPU(s) list: 0-47 Vendor ID: AuthenticAMD Model name: AMD Ryzen Threadripper 3960X 24-Core Processor CPU family: 23 Model: 49 Thread(s) per core: 2 Core(s) per socket: 24 Socket(s): 1 Stepping: 0 Frequency boost: enabled CPU max MHz: 3800.0000 CPU min MHz: 2200.0000 BogoMIPS: 7585.68 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sev sev_es Virtualization: AMD-V L1d cache: 768 KiB (24 instances) L1i cache: 768 KiB (24 instances) L2 cache: 12 MiB (24 instances) L3 cache: 128 MiB (8 instances) NUMA node(s): 1 NUMA node0 CPU(s): 0-47 Vulnerability Gather data sampling: Not affected Vulnerability Itlb multihit: Not affected Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Not affected Vulnerability Retbleed: Mitigation; untrained return thunk; SMT enabled with STIBP protection Vulnerability Spec rstack overflow: Mitigation; safe RET Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Retpolines, IBPB conditional, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected

Versions of relevant libraries: [pip3] fast-pytorch-kmeans==0.2.0.1 [pip3] flake8==7.0.0 [pip3] mypy==1.9.0 [pip3] mypy-extensions==1.0.0 [pip3] numpy==1.24.4 [pip3] numpydoc==1.6.0 [pip3] paddle2onnx==1.0.6 [pip3] pytorchts==0.6.0 [pip3] reformer-pytorch==1.4.4 [pip3] torch==2.2.2 [pip3] torch_cluster==1.6.3+pt22cu121 [pip3] torch-ema==0.3 [pip3] torch-geometric==2.6.0 [pip3] torch_scatter==2.1.2+pt22cu121 [pip3] torch_sparse==0.6.18+pt22cu121 [pip3] torch_spline_conv==1.2.2+pt22cu121 [pip3] torchaudio==2.2.2 [pip3] torchmetrics==0.10.1 [pip3] torchsummary==1.5.1 [pip3] torchvision==0.17.2 [pip3] triton==2.2.0 [conda] fast-pytorch-kmeans 0.2.0.1 pypi_0 pypi [conda] nomkl 1.0 h5ca1d4c_0 conda-forge [conda] numpy 1.24.4 pypi_0 pypi [conda] numpydoc 1.6.0 pyhd8ed1ab_0 conda-forge [conda] pytorchts 0.6.0 pypi_0 pypi [conda] reformer-pytorch 1.4.4 pypi_0 pypi [conda] torch 2.2.2 pypi_0 pypi [conda] torch-cluster 1.6.3+pt22cu121 pypi_0 pypi [conda] torch-ema 0.3 pypi_0 pypi [conda] torch-geometric 2.6.0 pypi_0 pypi [conda] torch-scatter 2.1.2+pt22cu121 pypi_0 pypi [conda] torch-sparse 0.6.18+pt22cu121 pypi_0 pypi [conda] torch-spline-conv 1.2.2+pt22cu121 pypi_0 pypi [conda] torchaudio 2.2.2 pypi_0 pypi [conda] torchmetrics 0.10.1 pypi_0 pypi [conda] torchsummary 1.5.1 pypi_0 pypi [conda] torchvision 0.17.2 pypi_0 pypi [conda] triton 2.2.0 pypi_0 pypi

rusty1s commented 6 days ago

Ups, will be fixed in https://github.com/pyg-team/pytorch_geometric/pull/9449.