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HI There,
I tried to run your old training code given in tools dir. When I tried to run your training code with single gpu and with coco data set I get this error: CUDA error: an illegal memory access was encountered CUDA kernel . In your requirements file you didn't mention the pytorch version you used. Is it because of the the pytorch version. By the way I am using T4 gpu and cudnn version is 11.3 python=3.20.4 pytorch=1.12.1.
for trainning is used config this configfile:
MODEL:
META_ARCHITECTURE: "panoptic_deeplab"
BN_MOMENTUM: 0.01
BACKBONE:
NAME: "resnet50"
DILATION: (False, False, False)
PRETRAINED: True
DECODER:
IN_CHANNELS: 2048
FEATURE_KEY: "res5"
DECODER_CHANNELS: 256
ATROUS_RATES: (3, 6, 9)
PANOPTIC_DEEPLAB:
LOW_LEVEL_CHANNELS: (1024, 512, 256)
LOW_LEVEL_KEY: ["res4", "res3", "res2"]
LOW_LEVEL_CHANNELS_PROJECT: (128, 64, 32)
INSTANCE:
ENABLE: True
LOW_LEVEL_CHANNELS_PROJECT: (64, 32, 16)
DECODER_CHANNELS: 128
HEAD_CHANNELS: 32
ASPP_CHANNELS: 256
NUM_CLASSES: (1, 2)
CLASS_KEY: ["center", "offset"]
DATASET:
ROOT: "/home/nazib/Data/coco/"
DATASET: "coco_panoptic"
NUM_CLASSES: 133
TRAIN_SPLIT: 'train2017'
TEST_SPLIT: 'val2017'
CROP_SIZE: (1025, 2049)
MIRROR: True
MIN_SCALE: 0.5
MAX_SCALE: 2.0
SCALE_STEP_SIZE: 0.1
MEAN: (0.485, 0.456, 0.406)
STD: (0.229, 0.224, 0.225)
SEMANTIC_ONLY: False
IGNORE_STUFF_IN_OFFSET: True
SMALL_INSTANCE_AREA: 4096
SMALL_INSTANCE_WEIGHT: 3
SOLVER:
BASE_LR: 0.00005
WEIGHT_DECAY: 0.0
WEIGHT_DECAY_NORM: 0.0
BIAS_LR_FACTOR: 1.0
WEIGHT_DECAY_BIAS: 0.0
OPTIMIZER: "adam"
LR_SCHEDULER_NAME: "WarmupPolyLR"
WARMUP_ITERS: 0
LOSS:
SEMANTIC:
NAME: "hard_pixel_mining"
IGNORE: 255
TOP_K_PERCENT: 0.2
WEIGHT: 1.0
CENTER:
NAME: "mse"
WEIGHT: 200.0
OFFSET:
NAME: "l1"
WEIGHT: 0.01
TRAIN:
IMS_PER_BATCH: 8
MAX_ITER: 90000
DEBUG:
DEBUG: True
DEBUG_FREQ: 100
TEST:
EVAL_INSTANCE: True
EVAL_PANOPTIC: True
POST_PROCESSING:
CENTER_THRESHOLD: 0.1
NMS_KERNEL: 7
TOP_K_INSTANCE: 200
STUFF_AREA: 2048
OUTPUT_DIR: "./output/panoptic_deeplab_R50_os32_cityscapes"
GPUS: (0, 1, 2, 3, 4, 5, 6, 7)
WORKERS: 1
The text was updated successfully, but these errors were encountered:
HI There,
I tried to run your old training code given in tools dir. When I tried to run your training code with single gpu and with coco data set I get this error: CUDA error: an illegal memory access was encountered CUDA kernel . In your requirements file you didn't mention the pytorch version you used. Is it because of the the pytorch version. By the way I am using T4 gpu and cudnn version is 11.3 python=3.20.4 pytorch=1.12.1.
for trainning is used config this configfile:
MODEL:
META_ARCHITECTURE: "panoptic_deeplab"
BN_MOMENTUM: 0.01
BACKBONE:
NAME: "resnet50"
DILATION: (False, False, False)
PRETRAINED: True
DECODER:
IN_CHANNELS: 2048
FEATURE_KEY: "res5"
DECODER_CHANNELS: 256
ATROUS_RATES: (3, 6, 9)
PANOPTIC_DEEPLAB:
LOW_LEVEL_CHANNELS: (1024, 512, 256)
LOW_LEVEL_KEY: ["res4", "res3", "res2"]
LOW_LEVEL_CHANNELS_PROJECT: (128, 64, 32)
INSTANCE:
ENABLE: True
LOW_LEVEL_CHANNELS_PROJECT: (64, 32, 16)
DECODER_CHANNELS: 128
HEAD_CHANNELS: 32
ASPP_CHANNELS: 256
NUM_CLASSES: (1, 2)
CLASS_KEY: ["center", "offset"]
DATASET:
ROOT: "/home/nazib/Data/coco/"
DATASET: "coco_panoptic"
NUM_CLASSES: 133
TRAIN_SPLIT: 'train2017'
TEST_SPLIT: 'val2017'
CROP_SIZE: (1025, 2049)
MIRROR: True
MIN_SCALE: 0.5
MAX_SCALE: 2.0
SCALE_STEP_SIZE: 0.1
MEAN: (0.485, 0.456, 0.406)
STD: (0.229, 0.224, 0.225)
SEMANTIC_ONLY: False
IGNORE_STUFF_IN_OFFSET: True
SMALL_INSTANCE_AREA: 4096
SMALL_INSTANCE_WEIGHT: 3
SOLVER:
BASE_LR: 0.00005
WEIGHT_DECAY: 0.0
WEIGHT_DECAY_NORM: 0.0
BIAS_LR_FACTOR: 1.0
WEIGHT_DECAY_BIAS: 0.0
OPTIMIZER: "adam"
LR_SCHEDULER_NAME: "WarmupPolyLR"
WARMUP_ITERS: 0
LOSS:
SEMANTIC:
NAME: "hard_pixel_mining"
IGNORE: 255
TOP_K_PERCENT: 0.2
WEIGHT: 1.0
CENTER:
NAME: "mse"
WEIGHT: 200.0
OFFSET:
NAME: "l1"
WEIGHT: 0.01
TRAIN:
IMS_PER_BATCH: 8
MAX_ITER: 90000
DEBUG:
DEBUG: True
DEBUG_FREQ: 100
TEST:
EVAL_INSTANCE: True
EVAL_PANOPTIC: True
POST_PROCESSING:
CENTER_THRESHOLD: 0.1
NMS_KERNEL: 7
TOP_K_INSTANCE: 200
STUFF_AREA: 2048
OUTPUT_DIR: "./output/panoptic_deeplab_R50_os32_cityscapes"
GPUS: (0, 1, 2, 3, 4, 5, 6, 7)
WORKERS: 1
The text was updated successfully, but these errors were encountered: