You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I'm using the official example scripts/configs for the officially supported tasks/models/datasets.
Environment
The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_70.
If you want to use the GeForce RTX 3090 GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/
warnings.warn(incompatible_device_warn.format(device_name, capability, " ".join(arch_list), device_name))
sys.platform: linux
Python: 3.8.0 (default, Nov 6 2019, 21:49:08) [GCC 7.3.0]
CUDA available: True
CUDA_HOME: /usr/local/cuda
NVCC: Build cuda_11.0_bu.TC445_37.28540450_0
GPU 0: GeForce RTX 3090
GPU 1: GeForce GTX 1080 Ti
GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
PyTorch: 1.8.0
PyTorch compiling details: PyTorch built with:
GCC 7.3
C++ Version: 201402
Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications
Results for bohemina. Also there is few artifact, and result for SPE have changed color
junseokoh1
changed the title
[Bug] Error with p"Positional Encoding as Spatial Inductive Bias in GANs" inference result have artifact
[Bug] Error with "Positional Encoding as Spatial Inductive Bias in GANs" inference result have artifact
Feb 10, 2023
Prerequisite
Task
I'm using the official example scripts/configs for the officially supported tasks/models/datasets.
Environment
The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_70.
If you want to use the GeForce RTX 3090 GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/
warnings.warn(incompatible_device_warn.format(device_name, capability, " ".join(arch_list), device_name))
sys.platform: linux
Python: 3.8.0 (default, Nov 6 2019, 21:49:08) [GCC 7.3.0]
CUDA available: True
CUDA_HOME: /usr/local/cuda
NVCC: Build cuda_11.0_bu.TC445_37.28540450_0
GPU 0: GeForce RTX 3090
GPU 1: GeForce GTX 1080 Ti
GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
PyTorch: 1.8.0
PyTorch compiling details: PyTorch built with:
-Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.8.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON,
TorchVision: 0.9.0
OpenCV: 4.7.0
MMCV: 1.7.0
MMGen: 0.7.2+f9f00fd
MMCV Compiler: GCC 7.3
MMCV CUDA Compiler: 10.2
Reproduces the problem - code sample
I used official code from your github.
Nothing chaged.
Reproduces the problem - command or script
Comment that i used
For fish
CUDA_VISIBLE_DEVICES=1 python3 tools/utils/singan_inference.py configs/positional_encoding_in_gans/singan_csg_fish.py
/home/uhrgan/Neurocomputing/mmgeneration/infer_param/singan_csg_fis_20210406_175532-f0ec7b61.pth --samples-path output/fish --save-prev-res --seed 22
For bohemina - CSG
CUDA_VISIBLE_DEVICES=1 python3 tools/utils/singan_inference.py configs/positional_encoding_in_gans/singan_csg_bohemian.py
/home/uhrgan/Neurocomputing/mmgeneration/infer_param/singan_csg_bohemian_20210407_195455-5ed56db2.pth --samples-path output/bohemina_csg --save-prev-res --seed 22
For bohemina - SPE
CUDA_VISIBLE_DEVICES=1 python3 tools/utils/singan_inference.py configs/positional_encoding_in_gans/singan_spe-dim4_bohemian.py
/home/uhrgan/Neurocomputing/mmgeneration/infer_param/singan_spe-dim4_bohemian_20210406_175820-6e484a35.pth --samples-path output/bohemina_spe --save-prev-res --seed 22
Following guide line I also add test_cfg to sigan_bohemian.py & singan_fish.py file.
config file that i used.
base = [
'../base/models/singan/singan.py', '../base/datasets/singan.py',
'../base/default_runtime.py'
]
num_scales = 10 # start from zero
model = dict(
generator=dict(num_scales=num_scales),
discriminator=dict(num_scales=num_scales))
train_cfg = dict(
noise_weight_init=0.1,
iters_per_scale=2000,
)
test_cfg = dict(
delete = True,
pkl_data = '/home/uhrgan/Neurocomputing/mmgeneration/infer_param/singan_csg_fis_20210406_175532-f0ec7b61.pkl'
)
data = dict(
train=dict(
img_path='./data/singan/fish-crop.jpg', min_size=25, max_size=300))
optimizer = None
lr_config = None
checkpoint_config = dict(by_epoch=False, interval=2000, max_keep_ckpts=3)
custom_hooks = [
dict(
type='MMGenVisualizationHook',
output_dir='visual',
interval=500,
bgr2rgb=True,
res_name_list=['fake_imgs', 'recon_imgs', 'real_imgs']),
dict(
type='PickleDataHook',
output_dir='pickle',
interval=-1,
after_run=True,
data_name_list=['noise_weights', 'fixed_noises', 'curr_stage'])
]
total_iters = 22000
But result have artifact
Reproduces the problem - error message
There is no error message, but result have artifacts
Additional information
No response
The text was updated successfully, but these errors were encountered: