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JNeRF-master is download from here
fengxiang@LAPTOP-4ARTIG9C:/mnt/d/JNeRF/JNeRF-master$ python3 tools/run_net.py --config-file ./projects/ngp/configs/ngp_base.py [i 0922 22:32:25.090768 68 compiler.py:955] Jittor(1.3.5.16) src: /home/fengxiang/.local/lib/python3.8/site-packages/jittor [i 0922 22:32:25.092662 68 compiler.py:956] g++ at /usr/bin/g++(9.4.0) [i 0922 22:32:25.092723 68 compiler.py:957] cache_path: /home/fengxiang/.cache/jittor/jt1.3.5/g++9.4.0/py3.8.10/Linux-5.10.16.xca/11thGenIntelRCxaa/default [i 0922 22:32:26.438366 68 install_cuda.py:88] cuda_driver_version: [11, 6] [i 0922 22:32:26.447372 68 init.py:411] Found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/bin/nvcc(11.2.152) at /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/bin/nvcc. [i 0922 22:32:26.475327 68 init.py:411] Found addr2line(2.34) at /usr/bin/addr2line. [i 0922 22:32:26.662258 68 compiler.py:1010] cuda key:cu11.2.152 [i 0922 22:32:26.872002 68 init.py:227] Total mem: 12.28GB, using 4 procs for compiling. [i 0922 22:32:26.949771 68 jit_compiler.cc:28] Load cc_path: /usr/bin/g++ [i 0922 22:32:27.730311 68 init.cc:62] Found cuda archs: [86,] [i 0922 22:32:27.814026 68 compile_extern.py:517] mpicc not found, distribution disabled. [i 0922 22:32:27.846909 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/include/cublas.h [i 0922 22:32:27.856165 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcublas.so [i 0922 22:32:27.856235 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcublasLt.so.11 [i 0922 22:32:28.354437 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/include/cudnn.h [i 0922 22:32:28.369732 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcudnn.so.8 [i 0922 22:32:28.369803 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcudnn_ops_infer.so.8 [i 0922 22:32:28.372593 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcudnn_ops_train.so.8 [i 0922 22:32:28.372934 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcudnn_cnn_infer.so.8 [i 0922 22:32:28.385145 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcudnn_cnn_train.so.8 [i 0922 22:32:28.863379 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/include/curand.h [i 0922 22:32:28.883515 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcurand.so [i 0922 22:32:28.896946 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/include/cufft.h [i 0922 22:32:28.913695 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcufft.so [i 0922 22:32:29.007277 68 cuda_flags.cc:32] CUDA enabled. [i 0922 22:32:29.015585 68 cuda_flags.cc:32] CUDA enabled. [i 0922 22:32:29.016354 68 cuda_flags.cc:32] CUDA enabled. [i 0922 22:32:29.016460 68 cuda_flags.cc:32] CUDA enabled. [i 0922 22:32:29.016566 68 cuda_flags.cc:32] CUDA enabled. [i 0922 22:32:29.016684 68 cuda_flags.cc:32] CUDA enabled. [i 0922 22:32:29.016779 68 cuda_flags.cc:32] CUDA enabled. [i 0922 22:32:29.016874 68 cuda_flags.cc:32] CUDA enabled. [i 0922 22:32:29.016973 68 cuda_flags.cc:32] CUDA enabled. [i 0922 22:32:29.017173 68 cuda_flags.cc:32] CUDA enabled. [i 0922 22:32:29.018092 68 cuda_flags.cc:32] CUDA enabled. Loading config from: ./projects/ngp/configs/ngp_base.py load train data 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:06<00:00, 30.67it/s]Traceback (most recent call last): File "tools/run_net.py", line 54, in main() File "tools/run_net.py", line 44, in main runner = Runner() File "/home/fengxiang/JNeRF/python/jnerf/runner/runner.py", line 24, in init self.dataset["train"] = build_from_cfg(self.cfg.dataset.train, DATASETS) File "/home/fengxiang/JNeRF/python/jnerf/utils/registry.py", line 33, in build_from_cfg module = obj_cls(**args) File "/home/fengxiang/JNeRF/python/jnerf/dataset/dataset.py", line 48, in init self.load_data() File "/home/fengxiang/JNeRF/python/jnerf/dataset/dataset.py", line 157, in load_data self.image_data=jt.array(self.image_data) File "/home/fengxiang/.local/lib/python3.8/site-packages/jittor/init.py", line 323, in array ret = ops.array(data) RuntimeError: Wrong inputs arguments, Please refer to examples(help(jt.ops.array)).
Types of your inputs are: self = module, args = (list, ),
The function declarations are: VarHolder* array__(PyObject* obj)
Failed reason:[f 0922 22:32:37.806230 68 helper_cuda.h:128] CUDA error at /home/fengxiang/.local/lib/python3.8/site-packages/jittor/src/mem/allocator/cuda_host_allocator.cc:22 code=2( cudaErrorMemoryAllocation ) cudaMallocHost(&ptr, size)
The text was updated successfully, but these errors were encountered:
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JNeRF-master is download from here
fengxiang@LAPTOP-4ARTIG9C:/mnt/d/JNeRF/JNeRF-master$ python3 tools/run_net.py --config-file ./projects/ngp/configs/ngp_base.py
[i 0922 22:32:25.090768 68 compiler.py:955] Jittor(1.3.5.16) src: /home/fengxiang/.local/lib/python3.8/site-packages/jittor
[i 0922 22:32:25.092662 68 compiler.py:956] g++ at /usr/bin/g++(9.4.0)
[i 0922 22:32:25.092723 68 compiler.py:957] cache_path: /home/fengxiang/.cache/jittor/jt1.3.5/g++9.4.0/py3.8.10/Linux-5.10.16.xca/11thGenIntelRCxaa/default
[i 0922 22:32:26.438366 68 install_cuda.py:88] cuda_driver_version: [11, 6]
[i 0922 22:32:26.447372 68 init.py:411] Found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/bin/nvcc(11.2.152) at /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/bin/nvcc.
[i 0922 22:32:26.475327 68 init.py:411] Found addr2line(2.34) at /usr/bin/addr2line.
[i 0922 22:32:26.662258 68 compiler.py:1010] cuda key:cu11.2.152
[i 0922 22:32:26.872002 68 init.py:227] Total mem: 12.28GB, using 4 procs for compiling.
[i 0922 22:32:26.949771 68 jit_compiler.cc:28] Load cc_path: /usr/bin/g++
[i 0922 22:32:27.730311 68 init.cc:62] Found cuda archs: [86,]
[i 0922 22:32:27.814026 68 compile_extern.py:517] mpicc not found, distribution disabled.
[i 0922 22:32:27.846909 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/include/cublas.h
[i 0922 22:32:27.856165 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcublas.so
[i 0922 22:32:27.856235 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcublasLt.so.11
[i 0922 22:32:28.354437 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/include/cudnn.h
[i 0922 22:32:28.369732 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcudnn.so.8
[i 0922 22:32:28.369803 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcudnn_ops_infer.so.8
[i 0922 22:32:28.372593 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcudnn_ops_train.so.8
[i 0922 22:32:28.372934 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcudnn_cnn_infer.so.8
[i 0922 22:32:28.385145 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcudnn_cnn_train.so.8
[i 0922 22:32:28.863379 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/include/curand.h
[i 0922 22:32:28.883515 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcurand.so
[i 0922 22:32:28.896946 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/include/cufft.h
[i 0922 22:32:28.913695 68 compile_extern.py:30] found /home/fengxiang/.cache/jittor/jtcuda/cuda11.2_cudnn8_linux/lib64/libcufft.so
[i 0922 22:32:29.007277 68 cuda_flags.cc:32] CUDA enabled.
[i 0922 22:32:29.015585 68 cuda_flags.cc:32] CUDA enabled.
[i 0922 22:32:29.016354 68 cuda_flags.cc:32] CUDA enabled.
[i 0922 22:32:29.016460 68 cuda_flags.cc:32] CUDA enabled.
[i 0922 22:32:29.016566 68 cuda_flags.cc:32] CUDA enabled.
[i 0922 22:32:29.016684 68 cuda_flags.cc:32] CUDA enabled.
[i 0922 22:32:29.016779 68 cuda_flags.cc:32] CUDA enabled.
[i 0922 22:32:29.016874 68 cuda_flags.cc:32] CUDA enabled.
[i 0922 22:32:29.016973 68 cuda_flags.cc:32] CUDA enabled.
[i 0922 22:32:29.017173 68 cuda_flags.cc:32] CUDA enabled.
[i 0922 22:32:29.018092 68 cuda_flags.cc:32] CUDA enabled.
Loading config from: ./projects/ngp/configs/ngp_base.py
load train data
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:06<00:00, 30.67it/s]Traceback (most recent call last):
File "tools/run_net.py", line 54, in
main()
File "tools/run_net.py", line 44, in main
runner = Runner()
File "/home/fengxiang/JNeRF/python/jnerf/runner/runner.py", line 24, in init
self.dataset["train"] = build_from_cfg(self.cfg.dataset.train, DATASETS)
File "/home/fengxiang/JNeRF/python/jnerf/utils/registry.py", line 33, in build_from_cfg
module = obj_cls(**args)
File "/home/fengxiang/JNeRF/python/jnerf/dataset/dataset.py", line 48, in init
self.load_data()
File "/home/fengxiang/JNeRF/python/jnerf/dataset/dataset.py", line 157, in load_data
self.image_data=jt.array(self.image_data)
File "/home/fengxiang/.local/lib/python3.8/site-packages/jittor/init.py", line 323, in array
ret = ops.array(data)
RuntimeError: Wrong inputs arguments, Please refer to examples(help(jt.ops.array)).
Types of your inputs are:
self = module,
args = (list, ),
The function declarations are:
VarHolder* array__(PyObject* obj)
Failed reason:[f 0922 22:32:37.806230 68 helper_cuda.h:128] CUDA error at /home/fengxiang/.local/lib/python3.8/site-packages/jittor/src/mem/allocator/cuda_host_allocator.cc:22 code=2( cudaErrorMemoryAllocation ) cudaMallocHost(&ptr, size)
The text was updated successfully, but these errors were encountered: