Extensions:                    cl_khr_fp64 cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_khr_3d_image_writes cl_khr_byte_addressable_store cl_khr_fp16 cl_khr_gl_sharing cl_amd_device_attribute_query cl_amd_media_ops cl_amd_media_ops2 cl_khr_image2d_from_buffer cl_khr_subgroups cl_khr_depth_images cl_amd_copy_buffer_p2p cl_amd_assembly_program

rocminfo
ROCk module is loaded
Able to open /dev/kfd read-write
=====================
HSA System Attributes
=====================
Runtime Version:         1.1
System Timestamp Freq.:  1000.000000MHz
Sig. Max Wait Duration:<PHONE_NUMBER>3709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count)
Machine Model:           LARGE
System Endianness:       LITTLE

==========
HSA Agents
==========
*******
Agent 1
*******
  Name:                    AMD Ryzen 7 3700X 8-Core Processor
  Uuid:                    CPU-XX
  Marketing Name:          AMD Ryzen 7 3700X 8-Core Processor
  Vendor Name:             CPU
  Feature:                 None specified
  Profile:                 FULL_PROFILE
  Float Round Mode:        NEAR
  Max Queue Number:        0(0x0)
  Queue Min Size:          0(0x0)
  Queue Max Size:          0(0x0)
  Queue Type:              MULTI
  Node:                    0
  Device Type:             CPU
  Cache Info:
    L1:                      32768(0x8000) KB
  Chip ID:                 0(0x0)
  Cacheline Size:          64(0x40)
  Max Clock Freq. (MHz):   0
  BDFID:                   0
  Internal Node ID:        0
  Compute Unit:            16
  SIMDs per CU:            0
  Shader Engines:          0
  Shader Arrs. per Eng.:   0
  WatchPts on Addr. Ranges:1
  Features:                None
  Pool Info:
    Pool 1
      Segment:                 GLOBAL; FLAGS: KERNARG, FINE GRAINED
      Size:                    16436616(0xfacd88) KB
      Allocatable:             TRUE
      Alloc Granule:           4KB
      Alloc Alignment:         4KB
      Accessible by all:       TRUE
    Pool 2
      Segment:                 GLOBAL; FLAGS: COARSE GRAINED
      Size:                    16436616(0xfacd88) KB
      Allocatable:             TRUE
      Alloc Granule:           4KB
      Alloc Alignment:         4KB
      Accessible by all:       TRUE
  ISA Info:
    N/A
*******
Agent 2
*******
  Name:                    gfx900
  Uuid:                    GPU-02151e1bb9ee2144
  Marketing Name:          Vega 10 XT [Radeon RX Vega 64]
  Vendor Name:             AMD
  Feature:                 KERNEL_DISPATCH
  Profile:                 BASE_PROFILE
  Float Round Mode:        NEAR
  Max Queue Number:        128(0x80)
  Queue Min Size:          4096(0x1000)
  Queue Max Size:          131072(0x20000)
  Queue Type:              MULTI
  Node:                    1
  Device Type:             GPU
  Cache Info:
    L1:                      16(0x10) KB
  Chip ID:                 26751(0x687f)
  Cacheline Size:          64(0x40)
  Max Clock Freq. (MHz):   1590
  BDFID:                   12032
  Internal Node ID:        1
  Compute Unit:            56
  SIMDs per CU:            4
  Shader Engines:          4
  Shader Arrs. per Eng.:   1
  WatchPts on Addr. Ranges:4
  Features:                KERNEL_DISPATCH
  Fast F16 Operation:      FALSE
  Wavefront Size:          64(0x40)
  Workgroup Max Size:      1024(0x400)
  Workgroup Max Size per Dimension:
    x                        1024(0x400)
    y                        1024(0x400)
    z                        1024(0x400)
  Max Waves Per CU:        40(0x28)
  Max Work-item Per CU:    2560(0xa00)
  Grid Max Size:<PHONE_NUMBER>(0xffffffff)
  Grid Max Size per Dimension:
    x<PHONE_NUMBER>(0xffffffff)
    y<PHONE_NUMBER>(0xffffffff)
    z<PHONE_NUMBER>(0xffffffff)
  Max fbarriers/Workgrp:   32
  Pool Info:
    Pool 1
      Segment:                 GLOBAL; FLAGS: COARSE GRAINED
      Size:                    8372224(0x7fc000) KB
      Allocatable:             TRUE
      Alloc Granule:           4KB
      Alloc Alignment:         4KB
      Accessible by all:       FALSE
    Pool 2
      Segment:                 GROUP
      Size:                    64(0x40) KB
      Allocatable:             FALSE
      Alloc Granule:           0KB
      Alloc Alignment:         0KB
      Accessible by all:       FALSE
  ISA Info:
    ISA 1
      Name:                    amdgcn-amd-amdhsa--gfx900
      Machine Models:          HSA_MACHINE_MODEL_LARGE
      Profiles:                HSA_PROFILE_BASE
      Default Rounding Mode:   NEAR
      Default Rounding Mode:   NEAR
      Fast f16:                TRUE
      Workgroup Max Size:      1024(0x400)
      Workgroup Max Size per Dimension:
        x                        1024(0x400)
        y                        1024(0x400)
        z                        1024(0x400)
      Grid Max Size:<PHONE_NUMBER>(0xffffffff)
      Grid Max Size per Dimension:
        x<PHONE_NUMBER>(0xffffffff)
        y<PHONE_NUMBER>(0xffffffff)
        z<PHONE_NUMBER>(0xffffffff)
      FBarrier Max Size:       32
*** Done ***

rocm-bandwidth-test
          RocmBandwidthTest Version: 2.3.11

          Launch Command is: rocm-bandwidth-test (rocm_bandwidth -a + rocm_bandwidth -A)

          Device: 0,  AMD Ryzen 7 3700X 8-Core Processor
          Device: 1,  Vega 10 XT [Radeon RX Vega 64],  2f:0.0

          Inter-Device Access

          D/D       0         1

          0         1         0

          1         1         1

          Inter-Device Numa Distance

          D/D       0         1

          0         0         N/A

          1         20        0

          Unidirectional copy peak bandwidth GB/s

          D/D       0           1

          0         N/A         9.295924

          1         8.892247    72.654038

          Bdirectional copy peak bandwidth GB/s

          D/D       0           1

          0         N/A         17.103560

          1         17.103560   N/A

Hi @nickdon2007 @webber26232 , thanks for reporting your observations.
We've been looking into the performance drop reported for the TF2.2 release branch. The issue has been identified and we'll try to provide the fixes in the next a few weeks with the next ROCm release.
cc @ekuznetsov139 @deven-amd

Ubuntu 20.04
Radeon VII
VBIOS version: 113-D3600200-106
rocm==3.7
tensorflow==2.3
benchmarks==cnn_tf_v2.1_compatible
python3 ./tf_cnn_benchmarks.py --num_gpus=1 --batch_size=64 --model=resnet50

Step	Img/sec	total_loss
1	images/sec: 284.8 +/- 0.0 (jitter = 0.0)	7.608
10	images/sec: 284.0 +/- 0.3 (jitter = 0.7)	7.849
20	images/sec: 284.0 +/- 0.2 (jitter = 0.6)	8.013
30	images/sec: 284.0 +/- 0.1 (jitter = 0.7)	7.939
40	images/sec: 283.9 +/- 0.1 (jitter = 0.8)	8.137
50	images/sec: 283.8 +/- 0.2 (jitter = 0.8)	8.051
60	images/sec: 283.7 +/- 0.1 (jitter = 0.8)	7.781
70	images/sec: 283.7 +/- 0.1 (jitter = 0.8)	7.856
80	images/sec: 283.7 +/- 0.1 (jitter = 0.9)	8.012
90	images/sec: 283.7 +/- 0.1 (jitter = 0.8)	7.842
100	images/sec: 283.7 +/- 0.1 (jitter = 0.7)	8.090
----------------------------------------------------------------
total images/sec: 283.60
----------------------------------------------------------------

python3 ./tf_cnn_benchmarks.py --num_gpus=1 --batch_size=64 --model=resnet50 --use_fp16

Done warm up
Step	Img/sec	total_loss
1	images/sec: 391.8 +/- 0.0 (jitter = 0.0)	7.573
10	images/sec: 394.2 +/- 0.5 (jitter = 1.9)	7.848
20	images/sec: 394.6 +/- 0.3 (jitter = 1.4)	7.966
30	images/sec: 394.7 +/- 0.3 (jitter = 1.1)	7.907
40	images/sec: 394.1 +/- 0.3 (jitter = 1.7)	8.070
50	images/sec: 394.2 +/- 0.2 (jitter = 1.6)	8.047
60	images/sec: 394.3 +/- 0.2 (jitter = 1.6)	7.769
70	images/sec: 394.4 +/- 0.2 (jitter = 1.5)	7.859
80	images/sec: 394.2 +/- 0.2 (jitter = 1.6)	7.965
90	images/sec: 394.1 +/- 0.2 (jitter = 1.7)	7.822
100	images/sec: 394.1 +/- 0.2 (jitter = 1.7)	8.058
----------------------------------------------------------------
total images/sec: 393.89
----------------------------------------------------------------

python3 ./tf_cnn_benchmarks.py --num_gpus=1 --batch_size=128 --model=resnet50

Done warm up
Step	Img/sec	total_loss
1	images/sec: 292.8 +/- 0.0 (jitter = 0.0)	7.781
10	images/sec: 292.6 +/- 0.2 (jitter = 0.7)	7.740
20	images/sec: 292.3 +/- 0.1 (jitter = 0.6)	7.827
30	images/sec: 292.2 +/- 0.1 (jitter = 0.3)	7.963
40	images/sec: 292.0 +/- 0.1 (jitter = 0.4)	7.884
50	images/sec: 291.9 +/- 0.1 (jitter = 0.5)	7.792
60	images/sec: 291.8 +/- 0.1 (jitter = 0.5)	8.015
70	images/sec: 291.7 +/- 0.1 (jitter = 0.6)	7.868
80	images/sec: 291.6 +/- 0.1 (jitter = 0.6)	7.933
90	images/sec: 291.5 +/- 0.1 (jitter = 0.6)	7.746
100	images/sec: 291.4 +/- 0.1 (jitter = 0.7)	7.997
----------------------------------------------------------------
total images/sec: 291.38
----------------------------------------------------------------

python3 ./tf_cnn_benchmarks.py --num_gpus=1 --batch_size=128 --model=resnet50 --use_fp16

Done warm up
Step	Img/sec	total_loss
1	images/sec: 292.8 +/- 0.0 (jitter = 0.0)	7.781
10	images/sec: 292.6 +/- 0.2 (jitter = 0.7)	7.740
20	images/sec: 292.3 +/- 0.1 (jitter = 0.6)	7.827
30	images/sec: 292.2 +/- 0.1 (jitter = 0.3)	7.963
40	images/sec: 292.0 +/- 0.1 (jitter = 0.4)	7.884
50	images/sec: 291.9 +/- 0.1 (jitter = 0.5)	7.792
60	images/sec: 291.8 +/- 0.1 (jitter = 0.5)	8.015
70	images/sec: 291.7 +/- 0.1 (jitter = 0.6)	7.868
80	images/sec: 291.6 +/- 0.1 (jitter = 0.6)	7.933
90	images/sec: 291.5 +/- 0.1 (jitter = 0.6)	7.746
100	images/sec: 291.4 +/- 0.1 (jitter = 0.7)	7.997
----------------------------------------------------------------
total images/sec: 291.38
----------------------------------------------------------------

Here are some RTX 3080 10GB results.
(Obs.: When you see some low scores at higher batch sizes with (UM), it's because CUDA Unified Memory and shared memory was used due to lack of VRAM.)
Pop_OS! 20.04.1
NVIDIA 460 driver
tensorflow-gpu 2.4.0
NVIDIA 20.12-tf2-py3 Docker image
sudo docker run --gpus all --name tf-20.12 --shm-size=10g --ulimit memlock=-1 --ulimit stack=67108864 -it --rm -v $HOME/Projects/nvidia/tensorflow-gpu/benchmarks-master/scripts/tf_cnn_benchmarks:/projects nvcr.io/nvidia/tensorflow:20.12-tf2-py3

FP32
ResNet50
AlexNet
Inception v3
VGG16
GoogLeNet
ResNet152

batch_size=512
/
4715.95
/
/
/
/

batch_size=256
54.2 (UM)
4578.22
/
/
/
/

batch_size=128
62.8 (UM)
4237.48
52.8 (UM)
/
1016.12
/

batch_size=64
396.26
3373.96
278.23
245.71
906.01
/

batch_size=32
362.88
2467.48
260.47
238.11
802.6
150.18

FP16
ResNet50
AlexNet
Inception v3
VGG16
GoogLeNet
ResNet152

batch_size=512
/
6504.74
/
/
/
/

batch_size=256
/
5819.6
/
/
1790.52
/

batch_size=128
947.3
4919.44
635.26
355.78
1645.71
/

batch_size=64
900.25
3797.61
578.34
326.88
1498.69
384.89

batch_size=32
736.35
2512.88
517.68
295.81
1307.13
321.85

Here are some RTX 3080 10GB results.
(Obs.: When you see some low scores at higher batch sizes with (UM), it's because CUDA Unified Memory and shared memory was used due to lack of VRAM.)
Pop_OS! 20.04.1
NVIDIA 460 driver
tensorflow-gpu 2.4.0
NVIDIA 20.12-tf2-py3 Docker image
sudo docker run --gpus all --name tf-20.12 --shm-size=10g --ulimit memlock=-1 --ulimit stack=67108864 -it --rm -v $HOME/Projects/nvidia/tensorflow-gpu/benchmarks-master/scripts/tf_cnn_benchmarks:/projects nvcr.io/nvidia/tensorflow:20.12-tf2-py3

FP32
ResNet50
AlexNet
Inception v3
VGG16
GoogLeNet
ResNet152

batch_size=512
/
4715.95
/
/
/
/

batch_size=256
54.2 (UM)
4578.22
/
/
/
/

batch_size=128
62.8 (UM)
4237.48
52.8 (UM)
/
1016.12
/

batch_size=64
396.26
3373.96
278.23
245.71
906.01
/

batch_size=32
362.88
2467.48
260.47
238.11
802.6
150.18

FP16
ResNet50
AlexNet
Inception v3
VGG16
GoogLeNet
ResNet152

batch_size=512
/
6504.74
/
/
/
/

batch_size=256
/
5819.6
/
/
1790.52
/

batch_size=128
947.3
4919.44
635.26
355.78
1645.71
/

batch_size=64
900.25
3797.61
578.34
326.88
1498.69
384.89

batch_size=32
736.35
2512.88
517.68
295.81
1307.13
321.85

Any 6900 XT benchmarks?

@EmilPi  6900 XT would be very interesting indeed

@Daniel451 @EmilPi @qixiang109 Unfortunately, without ROCm support for RDNA*, we can't test ROCm performance yet. However, I've managed to test a 6800 XT with tensorflow-directml (1.15.4, the latest version as of now) on W10! That's at least a little light for RDNA owners who are interested in ML. Here are the numbers:
Ryzen 9 5950X
32GB 3200MHz RAM
6800 XT
Windows 10 20H2 19042.867
AMD Adrenalin 21.3.1
Python 3.7.10
tensorflow-directml 1.15.4

FP32
ResNet50
AlexNet
Inception v3
VGG16
GoogLeNet
ResNet152

batch_size=128
63.2
590.1
52.6
29.6
244.0
/

batch_size=64
/
/
/
/
/
27.9

FP16
ResNet50
AlexNet
Inception v3
VGG16
GoogLeNet
ResNet152

batch_size=128
52
528.2
41.0
23.9
174.0
23.1

I have MI50 and V100 available which I can use for benchmarking. What would be the best benchmarks to run? I see the original benchmarks seem outdated

Dose anyone try the benchmark on Rocm 4.5? Seemly Rocm now support gfx1030(6800xt/6900xt)?
There is someone testing 6700xt:
Link：https://www.zhihu.com/question/469674526/answer/2189926640
From:ZHIHU
Linux-5.10, nvidia driver 460.91.03, cuda 11.2, pytorch-1.9.1,Tesla A100running benchmark for framework pytorch
cuda version= 11.2
cudnn version= 8100
pytorch's vgg16 eval at fp32: 11.3ms avg
pytorch's vgg16 train at fp32: 46.5ms avg
pytorch's resnet152 eval at fp32: 44.4ms avg
pytorch's resnet152 train at fp32: 157.3ms avg
pytorch's densenet161 eval at fp32: 45.8ms avg
pytorch's densenet161 train at fp32: 154.8ms avg
pytorch's vgg16 eval at fp16: 7.8ms avg
pytorch's vgg16 train at fp16: 41.9ms avg
pytorch's resnet152 eval at fp16: 48.2ms avg
pytorch's resnet152 train at fp16: 163.0ms avg
pytorch's densenet161 eval at fp16: 48.1ms avg
pytorch's densenet161 train at fp16: 174.4ms avg
Linux-5.14.5, ROCm-4.3.0, pytorch-1.9.1, Radeon 6700XT ：running benchmark for framework pytorch
cuda version= None
cudnn version= 2012000
pytorch's vgg16 eval at fp32: 67.7ms avg
pytorch's vgg16 train at fp32: 194.5ms avg
pytorch's resnet152 eval at fp32: 57.8ms avg
pytorch's resnet152 train at fp32: 226.2ms avg
pytorch's densenet161 eval at fp32: 63.9ms avg
pytorch's densenet161 train at fp32: 228.0ms avg
pytorch's vgg16 eval at fp16: 25.8ms avg
pytorch's vgg16 train at fp16: 118.2ms avg
pytorch's resnet152 eval at fp16: 52.4ms avg
pytorch's resnet152 train at fp16: 183.4ms avg
pytorch's densenet161 eval at fp16: 54.5ms avg
pytorch's densenet161 train at fp16: 195.7ms avg

Any 6900 XT benchmarks?

with not official support on rocm-4.5: ;)
>TF_ROCM_FUSION_ENABLE=1 python3 tf_cnn_benchmarks.py --num_gpus=1 --batch_size=128 --model=resnet50

Step	Img/sec	total_loss
1	images/sec: 305.5 +/- 0.0 (jitter = 0.0)	7.781
10	images/sec: 304.3 +/- 0.3 (jitter = 1.1)	7.740
20	images/sec: 304.0 +/- 0.2 (jitter = 1.0)	7.827
30	images/sec: 304.0 +/- 0.2 (jitter = 0.9)	7.967
40	images/sec: 304.1 +/- 0.1 (jitter = 0.8)	7.885
50	images/sec: 304.1 +/- 0.1 (jitter = 0.7)	7.792
60	images/sec: 304.0 +/- 0.1 (jitter = 0.8)	8.011
70	images/sec: 303.9 +/- 0.1 (jitter = 0.8)	7.870
80	images/sec: 303.8 +/- 0.1 (jitter = 0.9)	7.923
90	images/sec: 303.8 +/- 0.1 (jitter = 0.9)	7.745
100	images/sec: 303.8 +/- 0.1 (jitter = 0.8)	7.990
----------------------------------------------------------------
total images/sec: 303.76
----------------------------------------------------------------

>TF_ROCM_FUSION_ENABLE=1 python3 tf_cnn_benchmarks.py --num_gpus=1 --batch_size=128 --model=resnet50 --use_fp16
Step	Img/sec	total_loss
1	images/sec: 457.7 +/- 0.0 (jitter = 0.0)	7.788
10	images/sec: 453.4 +/- 0.8 (jitter = 3.0)	7.738
20	images/sec: 452.8 +/- 0.6 (jitter = 2.0)	7.821
30	images/sec: 452.7 +/- 0.4 (jitter = 2.3)	7.962
40	images/sec: 452.6 +/- 0.4 (jitter = 2.3)	7.888
50	images/sec: 452.5 +/- 0.3 (jitter = 2.3)	7.795
60	images/sec: 452.5 +/- 0.3 (jitter = 2.5)	8.018
70	images/sec: 452.5 +/- 0.3 (jitter = 2.7)	7.868
80	images/sec: 452.7 +/- 0.3 (jitter = 2.9)	7.916
90	images/sec: 452.5 +/- 0.3 (jitter = 2.8)	7.739
100	images/sec: 452.4 +/- 0.3 (jitter = 2.9)	8.006
----------------------------------------------------------------
total images/sec: 452.35
----------------------------------------------------------------

My previous Radeon VII results are here: https://github.com/ROCmSoftwarePlatform/tensorflow-upstream/issues/173#issuecomment-485216090
Hopefully AMD's next generation consumer GPUs include Matrix cores if they are actually bringing support to RDNA.
Titan RTX:
python3 tf_cnn_benchmarks.py --num_gpus=1 --batch_size=128 --model=resnet50

Step	Img/sec	total_loss
1	images/sec: 352.6 +/- 0.0 (jitter = 0.0)	7.781
10	images/sec: 355.6 +/- 0.7 (jitter = 1.8)	7.740
20	images/sec: 355.5 +/- 0.4 (jitter = 1.1)	7.827
30	images/sec: 355.4 +/- 0.3 (jitter = 0.9)	7.966
40	images/sec: 355.6 +/- 0.2 (jitter = 1.0)	7.880
50	images/sec: 355.5 +/- 0.2 (jitter = 1.0)	7.790
60	images/sec: 355.4 +/- 0.2 (jitter = 0.9)	8.013
70	images/sec: 355.4 +/- 0.2 (jitter = 0.9)	7.866
80	images/sec: 355.3 +/- 0.1 (jitter = 0.9)	7.920
90	images/sec: 355.3 +/- 0.1 (jitter = 0.9)	7.743
100	images/sec: 355.3 +/- 0.1 (jitter = 0.9)	7.991
----------------------------------------------------------------
total images/sec: 355.08
----------------------------------------------------------------

python3 tf_cnn_benchmarks.py --num_gpus=1 --batch_size=128 --model=resnet50 --use_fp16

Step	Img/sec	total_loss
1	images/sec: 1127.1 +/- 0.0 (jitter = 0.0)	7.788
10	images/sec: 1119.9 +/- 3.7 (jitter = 7.1)	7.741
20	images/sec: 1122.1 +/- 2.6 (jitter = 9.3)	7.826
30	images/sec: 1121.3 +/- 2.1 (jitter = 5.0)	7.962
40	images/sec: 1121.6 +/- 1.9 (jitter = 5.6)	7.885
50	images/sec: 1119.3 +/- 1.7 (jitter = 8.4)	7.795
60	images/sec: 1117.8 +/- 1.6 (jitter = 9.5)	8.012
70	images/sec: 1116.1 +/- 1.6 (jitter = 12.6)	7.874
80	images/sec: 1115.2 +/- 1.4 (jitter = 13.9)	7.929
90	images/sec: 1114.7 +/- 1.5 (jitter = 13.8)	7.739
100	images/sec: 1114.1 +/- 1.4 (jitter = 14.1)	8.000
----------------------------------------------------------------
total images/sec: 1112.65
----------------------------------------------------------------

CDNA and up compute carte (MI100 ...) have already Matrix core
This benchmark is not optimised and no more update for tensorflow2... May be we can find some more update benchmark...
finally (?) the support is not official... hop it may have some optimisations after official support..

The Titan RTX is slightly faster than a RTX 3080 since its FP32 accumulation runs at full throughput like Nvidia's professional/data center cards when using Tensor cores. Geforce RTX cards are limited to 0.5x throughput when using Tensor cores, it's a way to segment their lineup similar to how AMD/Nvidia limit FP64 throughput.
https://lambdalabs.com/gpu-benchmarks
I used this benchmark to test my MacBook M1 Pro and my Titan RTX: https://github.com/tlkh/tf-metal-experiments
python train_benchmark.py --type cnn --model resnet50 --xla --fp16 --steps 100
python train_benchmark.py --type cnn --model mobilenetv2 --xla --fp16 --steps 100
python train_benchmark.py --type transformer --model distilbert-base-uncased --xla --fp16 --steps 100
python train_benchmark.py --type transformer --model bert-large-uncased --bs 16 --xla --fp16 --steps 30

Model | GPU | BatchSize | Throughput
ResNet50 | Titan RTX |128 |901.0 img/sec
MobileNetV2 | Titan RTX |128 |1467.2 img/sec
DistilBERT | Titan RTX | 64 | 1216.9 seq/sec
BERTLarge | Titan RTX | 16 | 126.7 seq/sec

If it's alright I'd like to post here the benchmark results I got with my rx 6800 using ROCm 4.5.2 and amdgpu-dkms version 1:<IP_ADDRESS>502-1350682 (from the latest amdgpu-pro driver stack):
> TF_ROCM_FUSION_ENABLE=1 python3 tf_cnn_benchmarks.py --num_gpus=1 --batch_size=128 --model=resnet50

Step    Img/sec total_loss
1       images/sec: 226.9 +/- 0.0 (jitter = 0.0)        7.781
10      images/sec: 226.4 +/- 0.3 (jitter = 0.1)        7.740
20      images/sec: 226.5 +/- 0.2 (jitter = 0.2)        7.827
30      images/sec: 226.4 +/- 0.1 (jitter = 0.2)        7.966
40      images/sec: 226.4 +/- 0.1 (jitter = 0.2)        7.883
50      images/sec: 226.5 +/- 0.1 (jitter = 0.2)        7.800
60      images/sec: 226.5 +/- 0.1 (jitter = 0.3)        8.008
70      images/sec: 226.5 +/- 0.1 (jitter = 0.2)        7.872
80      images/sec: 226.5 +/- 0.1 (jitter = 0.2)        7.930
90      images/sec: 226.5 +/- 0.1 (jitter = 0.2)        7.743
100     images/sec: 226.6 +/- 0.1 (jitter = 0.2)        7.996
----------------------------------------------------------------
total images/sec: 226.54
----------------------------------------------------------------

> TF_ROCM_FUSION_ENABLE=1 python3 tf_cnn_benchmarks.py --num_gpus=1 --batch_size=128 --model=resnet50 --use_fp16

Step    Img/sec total_loss
1       images/sec: 316.8 +/- 0.0 (jitter = 0.0)        7.786
10      images/sec: 316.4 +/- 0.3 (jitter = 0.5)        7.742
20      images/sec: 316.7 +/- 0.2 (jitter = 0.6)        7.826
30      images/sec: 316.8 +/- 0.1 (jitter = 0.7)        7.964
40      images/sec: 316.8 +/- 0.1 (jitter = 0.7)        7.884
50      images/sec: 316.9 +/- 0.1 (jitter = 0.6)        7.799
60      images/sec: 316.8 +/- 0.1 (jitter = 0.6)        8.015
70      images/sec: 316.7 +/- 0.1 (jitter = 0.7)        7.867
80      images/sec: 316.7 +/- 0.1 (jitter = 0.6)        7.922
90      images/sec: 316.7 +/- 0.1 (jitter = 0.6)        7.753
100     images/sec: 316.7 +/- 0.1 (jitter = 0.6)        7.999
----------------------------------------------------------------
total images/sec: 316.61
----------------------------------------------------------------

I guess these results are somewhat in line with @Djip007's results, as at least according to userbenchmark.com the 6900 XT is around 40% faster than the 6800.
However, what I don't understand is how is the Radeon VII able to basically match the 6900 XT and beat the rx 6800 with the above set of benchmarks which I ran, when both the 6900 XT and 6800 are clearly the faster GPUs at least according to Geekbench's OpenCL benchmarks (note how the 6900 XT scores 167460, the 6800 scores 129251, and the Vega 20 i.e. Radeon VII only scores 96073).  Could this performance discrepancy be explained by the Radeon VII's massive memory bandwidth, or the fact that the RDNA series of GPUs are not as optimized for compute (microarch-wise) as Radeon VII, or is it just that ROCm and the amdgpu-pro drivers haven't been optimized for performing compute tasks on RDNA cards?

Ran some benchmarks on my RX6800XT (Quiet Mode Switch) in the Docker ROCm5.2.0-TF2.8-dev container:
>TF_ROCM_FUSION_ENABLE=1 python3 tf_cnn_benchmarks.py --num_gpus=1 --batch_size=128 --model=resnet50

Step    Img/sec total_loss
1       images/sec: 258.0 +/- 0.0 (jitter = 0.0)        7.781
10      images/sec: 168.1 +/- 20.7 (jitter = 0.5)       7.740
20      images/sec: 203.7 +/- 10.6 (jitter = 0.3)       7.826
30      images/sec: 219.1 +/- 7.1 (jitter = 0.4)        7.965
40      images/sec: 227.7 +/- 5.4 (jitter = 0.4)        7.878
50      images/sec: 233.1 +/- 4.3 (jitter = 0.3)        7.790
60      images/sec: 236.9 +/- 3.6 (jitter = 0.3)        8.006
70      images/sec: 239.7 +/- 3.1 (jitter = 0.4)        7.866
80      images/sec: 241.8 +/- 2.7 (jitter = 0.4)        7.929
90      images/sec: 243.4 +/- 2.4 (jitter = 0.5)        7.745
100     images/sec: 244.8 +/- 2.2 (jitter = 0.5)        7.997
----------------------------------------------------------------
total images/sec: 244.74
----------------------------------------------------------------

> TF_ROCM_FUSION_ENABLE=1 python3 tf_cnn_benchmarks.py --num_gpus=1 --batch_size=128 --model=resnet50 --use_fp16

Step    Img/sec total_loss
1       images/sec: 360.7 +/- 0.0 (jitter = 0.0)        7.784
10      images/sec: 368.3 +/- 0.9 (jitter = 1.5)        7.745
20      images/sec: 368.8 +/- 0.5 (jitter = 0.9)        7.827
30      images/sec: 368.9 +/- 0.3 (jitter = 0.6)        7.964
40      images/sec: 368.9 +/- 0.3 (jitter = 0.6)        7.881
50      images/sec: 368.9 +/- 0.2 (jitter = 0.6)        7.792
60      images/sec: 368.7 +/- 0.2 (jitter = 0.8)        8.013
70      images/sec: 368.6 +/- 0.2 (jitter = 1.0)        7.873
80      images/sec: 368.6 +/- 0.2 (jitter = 1.0)        7.926
90      images/sec: 368.5 +/- 0.1 (jitter = 1.0)        7.739
100     images/sec: 368.2 +/- 0.2 (jitter = 1.2)        7.999
----------------------------------------------------------------
total images/sec: 368.10
----------------------------------------------------------------

I would try it in Power Mode, but that would involve opening my case and flipping the BIOS switch on the card, which is too much work at this time.


high load on CPU from Ruby interpreter after installation (probably infinite loop) on Windows

This package cause an infinite loop in RUBY somehow. It stays even when i try to close VScode.
I have only last stable Ruby and Shopify CLI installed as gem in my system, if it can helps.
I am not familiar with Ruby so I can't debug this loop by myself unfortunately.

Hmmm. The Windows support hasn't made it to Shopify CLI yet. There are more details about this in this issue. So somehow the fact that this is happening is weird. It doesn't seem related to what we're offering at all.
What is the second command?

It's "Console host window"
On Shopify you can clearly find "windows installation" for shopify-cli and it definitely works (mostly). But with official VSCode extension i have this issue.
Strange part is - I reinstalled everything on my laptop in just the same way and it works fine! Soo maybe some bug with Ruby related to specific hardware I have in my PC?
Maybe you can help me in debugging? Any tips how to find what causes Ruby to go crazy?

This shouldn't be necessary once Shopify CLI gets updated. We're in an awkward period that is longer than I anticipated. As such, I'll add a note that Windows support is experimental on the README.

@blindbeat, it got merged yesterday but is still unreleased. It will show up in the next one.
Can you try with the .bat.bat file in the meantime? Seems like that's a different bug that only happens on Windows. 😔
// I swear this Windows stuff is biting me in so many unexpected ways.


missing input device variable

Hyprland Version

System/Version info
Hyprland, built from branch HEAD at commit c5e28ebcfe00a510922779b2c568cfa52a317445  (props: bump ver 0.37.1).
Date: Sat Mar 16 14:51:49 2024
Tag: v0.37.1

flags: (if any)

System Information:
System name: Linux
Node name: thewallet
Release: 6.8.2-arch2-1
Version: #1 SMP PREEMPT_DYNAMIC Thu, 28 Mar 2024 17:06:35 +0000

GPU information:
c1:00.0 VGA compatible controller [0300]: Advanced Micro Devices, Inc. [AMD/ATI] Phoenix1 [1002:15bf] (rev c4) (prog-if 00 [VGA controller])

os-release: NAME="Arch Linux"
PRETTY_NAME="Arch Linux"
ID=arch
BUILD_ID=rolling
ANSI_COLOR="38;2;23;147;209"
HOME_URL="https://archlinux.org/"
DOCUMENTATION_URL="https://wiki.archlinux.org/"
SUPPORT_URL="https://bbs.archlinux.org/"
BUG_REPORT_URL="https://gitlab.archlinux.org/groups/archlinux/-/issues"
PRIVACY_POLICY_URL="https://terms.archlinux.org/docs/privacy-policy/"
LOGO=archlinux-logo

plugins:

Bug or Regression?
Bug
Description
Since upgrading to 0.37.1-1 one of my scripts broke. It was supposed to toggle my touchpad (and deactivate it if a mouse was detected via another script) and now it can't find the variable anymore.
mice:
    Mouse at 6288bb5532f0:
        frmw0004:00-32ac:0006-consumer-control-1
            default speed: 0.00000
    Mouse at 6288bb678330:
        pixa3854:00-093a:0274-mouse
            default speed: 0.00000
    Mouse at 6288bb4f9770:
        pixa3854:00-093a:0274-touchpad
            default speed: 0.00000

Keyboards:
    Keyboard at 6288bb553030:
        video-bus
            rules: r "", m "", l "de", v "", o ""
            active keymap: German
            main: no
    Keyboard at 6288bb5197c0:
        power-button
            rules: r "", m "", l "de", v "", o ""
            active keymap: German
            main: no
    Keyboard at 6288bb628e10:
        frmw0004:00-32ac:0006-consumer-control
            rules: r "", m "", l "de", v "", o ""
            active keymap: German
            main: no
    Keyboard at 6288bb67ba40:
        frmw0004:00-32ac:0006-wireless-radio-control
            rules: r "", m "", l "de", v "", o ""
            active keymap: German
            main: no
    Keyboard at 6288bb6e11f0:
        at-translated-set-2-keyboard
            rules: r "", m "", l "de", v "", o ""
            active keymap: German
            main: yes

Tablets:

Touch:

Switches:
    Switch Device at 6288bb4078d0:
        Lid Switch

my script
#!/bin/sh

# When executed toggle touchpad state

# Set device to be toggled
HYPRLAND_DEVICE="pixa3854:00-093a:0274-touchpad"
HYPRLAND_VARIABLE="device:$HYPRLAND_DEVICE:enabled"

if [ -z "$XDG_RUNTIME_DIR" ]; then
  export XDG_RUNTIME_DIR=/run/user/$(id -u)
fi

# Check if device is currently enabled (1 = enabled, 0 = disabled)
DEVICE="$(hyprctl getoption $HYPRLAND_VARIABLE | grep 'int: 1')"

if [ -z "$DEVICE" ]; then
    # if the device is disabled, then enable
      # notify-send -u normal "Enabling Touchpad"
    hyprctl keyword $HYPRLAND_VARIABLE true
else
    # if the device is enabled, then disable
    # notify-send -u normal "Disabling Touchpad"
    hyprctl keyword $HYPRLAND_VARIABLE false
fi

My script just results in:
config option <device:pixa3854:00-093a:0274-touchpad:enabled> does not exist. which just plain confuses me
How to reproduce
Use the script above on a touchpad device, I don't have another machine to try this on sadly.
Crash reports, logs, images, videos
No response

Currently you have to do this. https://github.com/hyprwm/Hyprland/discussions/4283

@sungyoonc Why do i need to add this now and not in earlier versions ?

Because of hyprlang changes on #4656 .

okay so i need to use some temporary file somewhere and i can't cleanly query the status of the input device anymore from hyprland directly?

As far as I know, yes.

on hyprlang-git you can device[nameofdevice]:prop


Use the document ID as a prefix to make the footnote anchor unique

What if we keep track what ids have been used and we only use it when needed?

What if we keep track what ids have been used and we only use it when needed?

Sure, we can do that. Let me fix it


lut should be provided in array (vs texture) to the shaders

one array for color
one array for opacity

The texture has a limited resolution (currently 256 values) which ends up degrading the data visualization.

lut helpers should only be use for visualization, not for actual data processing in the shaders.

actually we should pass info through 2 textures but do interpolation in shader:
rgba texture for colors:
[R value1, G value1, B value1, Index1, R value2, G value2, B value2, Index2, ...]
ga texture for opacity:
[A alpha1, Index1, A alpha2, Index2, ...]


Setting up a Fresh project to work with Deno KV is obscure

If I create a project using ‘deno init’ then the Language Server (and therefore VS Code) can type-check code that uses Deno KV by default. (Though it won’t run unless you enable Deno KV, since it’s an unstable API.)
If I create a new Fresh project then it doesn’t work.
The reason for this is the reference declarations at the top of main.ts. To enable type checking for unstable API’s, turning on unstable API’s in either VS Code’s settings or in deno.json doesn’t work. You need to edit main.ts and add a reference declaration.
(Actually the reference declaration can be anywhere, but main.ts is the logical place to put it.)
This seems needlessly obscure. My suggestion: enable type-checking for unstable API’s by default. There is still another step to actually use them, but this is more consistent with non-Fresh projects and with the ‘deno check’ command.

More context: Deno changed in early January to always type-check unstable API's.
See: https://github.com/denoland/deno/pull/21825


Add GitHub workflow to protect certain files from modifications

:warning: Note on feature completeness :warning:
We are narrowing the scope of acceptable enhancements to DefectDojo in preparation for v3. Learn more here:
https://github.com/DefectDojo/django-DefectDojo/blob/master/readme-docs/CONTRIBUTING.md
Description
As part of preparation for v3, there is a need for code stability in certain areas. This PR includes a script and workflow that will report back to the PR if files marked as protected. For now, modifications to protected files will comment only and not fail the PR. At some point in the near future, it will switch to being a gating check.

We're going to have to follow this was a much smaller initial list of files to protect - that's a rather broad list.

We're going to have to follow this was a much smaller initial list of files to protect - that's a rather broad list.

I agree. Unfortunately, this was the ask. We still have a little time to talk about paring down the list. I would rather start with too little than start with too much. On the flip side, this job won't be blocking commits, so I can see why some would want to move ahead. I'm very open to suggestions.


Consider using a proper license

E.g. Zero-Clause BSD or MIT No Attribution if you want the license to be as free as possible.
WTFPL is not usable in countries that don't have a concept of public domain dedication, like all of continental Europe.
Even in for the US the license seems questionable. "[C]hanging it is allowed as long as the name is changed" – So, if Alice modifies your code and releases it under a new name; and Bob modifies and distributes Alice's code under your name, did Bob infringe your rights? What if Alice modifies and distributes your code twice? Can she use the original name again?

Hi @Kijewski!
Thanks for reaching out! I'm sorry to hear Europe doesn't recognize the Public Domain. That must make things difficult.
MIT-0 is a good approximation for the WTFPL, but it is written in legalese, which makes me uncomfortable because such language is exclusionary and carries an implicit threat of judicial violence (especially here in the US). The WTFPL is more of a protest against the very concept of software licensing (rather than an actual, enforceable license), which makes me feel better.
But just in case it wasn't clear, I have no rights in regards to this software that you could possibly infringe upon. Go wild! If you aren't able to use this library directly, just steal it and slap an MIT-0 license on the fork. :wink:
It is, however, worth noting that the optional crate features do have third-party dependencies that are subject to the licensing restrictions set by their authors. The serde feature brings in serde, while the local feature brings in tz-rs and const_fn. All three of those dependencies are dual-licensed MIT/Apache 2.0, which should make reconciling them within a Rust app pretty easy.
I do really appreciate you reaching out, though, and don't want you to feel discouraged by my philosophical hardline. If you have any other ideas for making this library better, please feel free to open another issue.
Thanks again!


tests: Add Dockerfile for docker integration swarm tests

Add Nginx Dockerfile that enables the ip command that will be
used in swarm integration tests
Fixes #387
Signed-off-by: Gabriela Cervantes<EMAIL_ADDRESS>

lgtm

@mcastelino could you review this PR?

@iphutch changes applied

@mcastelino the main issue is that you can not run an "ip a" this is not supported anymore using the Nginx docker hub image however this was actually seen previously in CC 2.1x

@GabyCT LGTM

@mcastelino https://github.com/01org/cc-oci-runtime/issues/1013


An uncaught exception with full screen code

OS X El Capitan gives nice traces on uncaught exceptions. I don't know if this applicable with Yosemite, but may be a clue for fixing issues.
MacVim Snapshot 77
OSX El Capitan 10.11
With MacVim and full screen I've got following exception trace:
2015-07-22 13:35:14.476 MacVim[3732:2892587] *** Assertion failure in -[_NSWindowFullScreenTransition startExitFullScreenTransitionForCGWindow:targetFrame:duration:completionHandler:], /Library/Caches/com.apple.xbs/Sources/AppKit/AppKit-1386.12/AppKit.subproj/NSWindowFullScreenTransition.m:604
2015-07-22 13:35:14.479 MacVim[3732:2892587] An uncaught exception was raised
2015-07-22 13:35:14.479 MacVim[3732:2892587] Invalid parameter not satisfying: _fullScreenState == NSExitingFullScreen
2015-07-22 13:35:14.479 MacVim[3732:2892587] (
	0   CoreFoundation                      0x00007fff8c9c7b5c __exceptionPreprocess + 172
	1   libobjc.A.dylib                     0x00007fff8d19a8e8 objc_exception_throw + 48
	2   CoreFoundation                      0x00007fff8c9c793a +[NSException raise:format:arguments:] + 106
	3   Foundation                          0x00007fff85c32bcc -[NSAssertionHandler handleFailureInMethod:object:file:lineNumber:description:] + 198
	4   AppKit                              0x00007fff87d38a03 -[_NSFullScreenTransition startExitFullScreenTransitionForCGWindow:targetFrame:duration:completionHandler:] + 168
	5   AppKit                              0x00007fff87d3894e -[_NSWindowFullScreenTransition _exitFullScreenModeForWindow:duration:completionHandler:] + 185
	6   AppKit                              0x00007fff88222c87 NSPerformVisuallyAtomicChange + 147
	7   AppKit                              0x00007fff88335541 __106-[_NSWindowFullScreenTransition _performExitFullScreenModeForWindow:options:customWindows:doKitAnimation:]_block_invoke + 668
	8   AppKit                              0x00007fff8824e288 __177-[NSDockConnection(FullScreenMessages) sendFullScreenExitForTransition:synchronous:window:exitForClose:backgroundWindows:participatingWindows:customAnimation:completionHandler:]_block_invoke + 60
	9   libxpc.dylib                        0x00007fff8ba6fcfb _xpc_connection_reply_callout + 26
	10  libxpc.dylib                        0x00007fff8ba6fc9c _xpc_connection_call_reply + 36
	11  libdispatch.dylib                   0x00007fff91350c11 _dispatch_client_callout + 8
	12  libdispatch.dylib                   0x00007fff91361fdc _dispatch_main_queue_callback_4CF + 1677
	13  CoreFoundation                      0x00007fff8c90ec19 __CFRUNLOOP_IS_SERVICING_THE_MAIN_DISPATCH_QUEUE__ + 9
	14  CoreFoundation                      0x00007fff8c8c97cd __CFRunLoopRun + 1949
	15  CoreFoundation                      0x00007fff8c8c8dc8 CFRunLoopRunSpecific + 296
	16  HIToolbox                           0x00007fff8c45ba59 RunCurrentEventLoopInMode + 235
	17  HIToolbox                           0x00007fff8c45b6f7 ReceiveNextEventCommon + 184
	18  HIToolbox                           0x00007fff8c45b62f _BlockUntilNextEventMatchingListInModeWithFilter + 71
	19  AppKit                              0x00007fff87a8779c _DPSNextEvent + 945
	20  AppKit                              0x00007fff87e555c9 -[NSApplication _nextEventMatchingEventMask:untilDate:inMode:dequeue:] + 343
	21  AppKit                              0x00007fff87a7d6dc -[NSApplication run] + 682
	22  AppKit                              0x00007fff879ffb6d NSApplicationMain + 1176
	23  libdyld.dylib                       0x00007fff887b05ad start + 1
	24  ???                                 0x0000000000000003 0x0 + 3
)

I think this is related to Yosemite fullscreen bugs

+1, got this bug when trying to exit split-screen.

+1, encounter this when i quit Mac Vim

Thanks @wulh , i have same prolem.

Thanks @wulh ,I have same problem, and It is fixed after closing "Prefer native full-screen support".

Have you guys tried the issue on OS X 10.11.1? I can't reproduce it anymore.

It seems OS X 10.11 issue.

I never could reproduce this on 10.11.


Custom list of random colors

Is there a way of editing the list of random colors? Actually, in my case I am more interested in editing the list of random gradients. Alternatively, setting a fixed gradient would also be nice.

Thank you for your interest. 😄
As you said, it would be nice to have a function to set a fixed gradient.
I will add it soon.
If there is a query or method you want, please recommend it.
On the other hand,

"Is there a way of editing the list of random colors?"

Is it mean customization random list like your commit ?
If that's the case, full customization seems a bit difficult. But how about this way?
// gradient.json file
[
    {
        "number": 0,     // add unique number
        "color": {  },
        "text": "...",
        "textBg": " ..."
    },
    {
        "number": 1,
        "color": {  },
        "text": "...",
        "textBg": "..."
    },
    ...
]

And use like this.
https://.../api?color=gradient&colorList=0,1

Setting list of random colors to add unique numbers of the desired color scheme in the query.

Hey, thanks for your response!

But how about this way?

This is actually even better, because you could select the colors that fit each element. It would be perfect in my case, as I'm trying to use it to create some drawings.
Looking forward to the update. Keep up the great work! 😄


Carrot.move() strategy is not optimal for long splines.

Hello everyone,
I noticed an issue with the rosys driver, that aborts long splines, before the robot reaches the end of the spline.

On the image, you can see, that the robot started to move to Waypoint 2, before it reached Waypoint 1.
I figured out, that the reason is, that in the Carrot.move() method the carrot is moved forward by 1% of the spline length.
For very long splines this procedure leads to the behavior in the screenshot.
I would suggest to calculate a step_size for the move() Method based on the desired distance and the spline length.
Here is my code:
@dataclass(kw_only=True)
class Carrot:
    __slots__ = ['spline', 'offset', 't', 'estimated_length']
    spline: Spline
    offset: Point = field(default_factory=lambda: Point(x=0, y=0))
    t: float = 0

    def __post_init__(self):
        self.estimated_length = self.spline.estimated_length()

    def move(self, hook: Point, distance: float) -> bool:
        step_size = distance / self.estimated_length

        while hook.distance(self.offset_point) < distance:
            self.t += step_size
            if self.t >= 1.0:
                return False
        return True

Even in this example the distance between hook and carrot can be quite far away from the given distance.
Maybe it would be better to calculate the step_size like this:  step_size = distance / self.estimated_length / 10.
I could not create a pull request, because of missing permissions, therefore I created this issue.
Best regards
Andreas

Hi Andreas,
thanks for bringing this up! You're right, the carrot move strategy doesn't work well for long splines. Because of the rather complicated nature of splines it isn't trivial to move the carrot by an exact distance. Therefore I originally chose the rather arbitrary value of 0.01 (in terms of parameter t) and never improved upon this solution.
But as you demonstrated, we can use the spline's estimated_length to relate the carrot distance to the approximate spline length. You should, however, divide by something like 10 (as you suggested) to compensate for multiple aspects:

The estimated_length tends to be shorter than the true length. We therefore overestimate the step size.
The distance along a spline doesn't linearly correlate to the parameter t. There are sections where the distance grows slower or faster.
We don't want to advance the carrot by the given distance, but so far that it is farther away from the robot than the distance. Therefore we usually want to move it less.
And when the robot isn't located on the spline but next to it, moving the carrot only a little step might already be enough to reach the target distance.

A pull request would be very welcome. I just checked the repository settings: You should be able to post PRs. I actually don't understand why you should be lacking permissions. Maybe you can try again and, if the problem persists, provide a more detailed description of the error you're seeing? Thanks!


bug htpasswd grafana

Is there an existing issue for this?

[X] I have searched the existing issues

What happened?
When it is configured with traefik the authentication is requested on the home but not on /grafana
I have already followed all the steps and everything works -> https://docs.teslamate.org/docs/guides/traefik
But authentication if I go directly to the url: mioteslamate.domain.net/grafana doesn't ask me for any htpasswd authentication
Expected Behavior
No response
Steps To Reproduce
No response
Relevant log output
teslamate_1  | 2023-01-10 13:05:51.788 [info] Migrations already up
teslamate_1  | 2023-01-10 13:05:55.371 [info] System Info: Erlang/OTP 24 (jit)
teslamate_1  | 2023-01-10 13:05:55.371 [info] Version: 1.27.1
teslamate_1  | 2023-01-10 13:05:56.355 [info] POST https://auth.tesla.com/oauth2/v3/token -> 200 (498.528 ms)
teslamate_1  | 2023-01-10 13:05:56.355 [info] Refreshed api tokens
teslamate_1  | 2023-01-10 13:05:56.361 [info] Scheduling token refresh in 6 h
teslamate_1  | 2023-01-10 13:05:56.363 [info] Running TeslaMateWeb.Endpoint with cowboy 2.9.0 at :::4000 (http)
teslamate_1  | 2023-01-10 13:05:56.367 [info] Access TeslaMateWeb.Endpoint at http://tomcat.anondns.net
teslamate_1  | 2023-01-10 13:05:57.097 [info] Starting logger for 'Kyra'
teslamate_1  | 2023-01-10 13:05:57.217 [info] MQTT connection has been established
teslamate_1  | 2023-01-10 13:05:57.641 car_id=1 [info] Start / :asleep
teslamate_1  | 2023-01-10 13:06:09.125 [info] GET /
teslamate_1  | 2023-01-10 13:06:09.227 [info] Sent 200 in 101ms
teslamate_1  | 2023-01-10 13:18:15.358 [info] GET /
teslamate_1  | 2023-01-10 13:18:15.529 [info] Sent 200 in 170ms
teslamate_1  | 2023-01-10 13:18:17.926 [info] GET /settings
teslamate_1  | 2023-01-10 13:18:18.104 [info] Sent 200 in 177ms

Screenshots
No response
Additional data
No response
Type of installation
Docker
Version
1.27.1

That seems to be working as documented:

The TeslaMate service is protected by HTTP Basic Authentication
Grafana is configured to require a login

The "login" is Grafana's own authentication, not HTTP Basic Authentication.

Is it possible to add this other layer to it? Since via docker is not constantly updated it would be safer

Yes, it should be possible, but I don't know about traefik.  I do it with Apache similar to how Grafana document it: https://grafana.com/docs/grafana/latest/setup-grafana/configure-security/configure-authentication/auth-proxy/


WIP [Room retention] Support unlimited room history

#697
Room settings:

rename the parameter with "Durée de l'historique"
remove some useless strings
the values are predefined: "illimitée", "1 an", "6 mois", "1 mois", "1 semaine", "1 jour".
As soon as a value doesn't match with one of the predefined values, we use a count of days (jours)

The new settings display:

Screenshot of the new messages in the room history:

Here is the previous and new resulting room creation screen:

new room header:

@yostyle : FYI this PR is ready to be reviewed (You may consider the commits one by one)


Remove ascii doc generated section header

Fixes #743
Section header generation is hardcoded in picocli ManPageGenerator and it's not possible to configure it so I've added task which removes section header.
Checklist

[x] Documented
[x] release_notes.md updated

Codecov Report

Merging #755 into master will not change coverage.
The diff coverage is n/a.

@@            Coverage Diff            @@
##             master     #755   +/-   ##
=========================================
  Coverage     78.22%   78.22%
  Complexity      665      665
=========================================
  Files           125      125
  Lines          2774     2774
  Branches        399      399
=========================================
  Hits           2170     2170
  Misses          350      350
  Partials        254      254


Contact Mechanics Download enhancement

The contact mechanics download seems to work nicely, but I have a small issue with the files. When opening the .nc files, the user needs to specify the variable to read in. The readme file was helpful in providing the default "pressure" variable, but I found myself guessing for the names of variables such as "gap", since the "pressure" variable is not identical to what the website shows (it lists "contact pressure").
it might make sense to list in the readme file what the names of the variables are that the user has access to in the .nc files.

In the meanwhile, the names of the variables have been included. Excerpt of readme file:
So each line also refers to one NetCDF file in the directory, it corresponds to
one external pressure. Inside the NetCDF file you'll find the variables

* `contact_points`: boolean array, true if point is in contact
* `pressure`: floating-point array containing local pressure (in units of `E*`)
* `gap`: floating-point array containing the local gap
* `displacement`: floating-point array containing the local displacements

as well as the attributes

* `mean_pressure`: mean pressure (in units of `E*`)
* `total_contact_area`: total contact area (fractional)

So I'm closing this.


Update gpu.Dockerfile

added missing /usr/local/cuda/lib64 in LD_LIBRARY_PATH
fixes library not found errors in images based off tensorflow

I signed it

@angersson updated partials


Package Update: Transmission.Transmission version 4.0.3

[x] Have you signed the Contributor License Agreement?
[x] Have you checked that there aren't other open pull requests for the same manifest update/change?
[x] This PR only modifies one (1) manifest
[x] Have you validated your manifest locally with winget validate --manifest <path>?

[x] Does your manifest conform to the 1.4 schema?

Note: <path> is the name of the directory containing the manifest you're submitting.

Microsoft Reviewers: Open in CodeFlow

I try the executing  /quiet /passive /qn It look like it work  Can you add this switch into the manifest?

@BrandonWanHuanSheng
The installer validation always fails on this package due to its dependency on Microsoft Visual C++ Redistributable (ever since version 4.0.0-beta 3 where the installation of the libraries were removed from the MSI package). A moderator will have to approve the pull request will only 4 out of 6 checks passed as has been the case for all 4.x versions.


Using slow RoPE2D version?

Hi, when trying to run the project locally I encounter the following warning:
Warning, cannot find cuda-compiled version of RoPE2D, using a slow pytorch version instead

does this impose a significant slowdown?
if so, how can I install the optimized verison?

Thanks in advance!

Hi, you can follow the instructions here https://github.com/naver/dust3r to compile the cuda kernels for RoPE. We haven't tested whether it will bring a significant speedup.


Severity TASK for method invocation and execution

Camunda Community Hub Pull Request Template

In case the process model contains JUEL expressions with execution keyword or invoke Java methods with .get..(..), the severity of the check is now TASK instead of REVIEW before.
The expression is converted to FEEL syntax as before.
Description

Closes #189
Additional context

We are quite good converting simple expressions from JUEL to FEEL. But recently I checked a huge diagram and the few expressions that require some change were hard to detect.
Now they are visible on the process diagram with the different color for TASK.
Testing your changes

Process model and Unit test is added in the code base.
I did it test driven.
Types of changes

[ ] Bug fix (non-breaking change which fixes an existing open issue)
[X] New feature (non-breaking change which adds functionality to an extension)
[ ] Breaking change (fix or feature that would cause existing functionality of an extension to change)
[ ] Documentation update (changes made to an existing piece of documentation)

Checklist:

[X] My code adheres to the syntax used by this extension.
[ ] My pull request requires a change to the documentation.
[ ] I have updated the documentation accordingly.
[X] I have read the Camunda Community Hub documentation.
[X] I have read the Pull Request Process documentation.
[X] I have added or suggested tests to cover my changes suggested in this pull request.
[X] All new and existing CI/CD tests passed.
[ ] I will /assign myself this issue, and add the relevant [issue labels] to it if they are not automatically generated by Probot.
[ ] I will tag @camunda-community-hub/devrel in a new comment on this issue if 30 days have passed since my pull request was opened and I have not received a response from the extension's maintainer.

Hi @jonathanlukas, what do you think?

@jonathanlukas, please check my changes.

Another pattern to apply: "\.[\w]*\(.*\)"
would find ${leistungsdatenIds.size() eq 1}

@jonathanlukas, could you please have a look at my changes?

@ingorichtsmeier one thing is still open for me. Can you please have a look?

Results/Examples from our discussion:
            testAgainstExecution("${execution.getVariable(\"a\")}", false),

            test("${execution.getVariable(\"a\")}", "a");
            test("${!dauerbuchungVoat21Ids.isEmpty()}", "not(dauerbuchungVoat21Ids == null)");
            testAgainstMethodInvocation("var.getSomething()", true),


[fixBug] yarnUtil restRequest error,illegal character in RM url bug

What changes were proposed in this pull request
Issue Number: close #3379

Brief change log

Verifying this change

This change is a trivial rework / code cleanup without any test coverage.
(or)
This change is already covered by existing tests, such as (please describe tests).
(or)
This change added tests and can be verified as follows:

Does this pull request potentially affect one of the following parts

Dependencies (does it add or upgrade a dependency): (yes / no)

@Dsrong Thanks for your contribution, you don't seem to have a code format


User logged in with Google doesn't have "Disconnect G+ account" in settings

Flag google_sign_in is set up to false.
User doesn't use new dashboard neither belongs to an organisation.
SB/4934473

I think this is gonna be fixed in the new dashboard. If so, this is duplicated.

Not sure... @juanignaciosl?

Yep, it's a WIP from #1720, now user account page is in the box same code should work for orgs and non-orgs. I've added a remainder in that issue just in case we don't realise it.


webpack2

https://webpack.js.org/guides/get-started/

webpack 2 new
https://github.com/xgqfrms-GitHub/webgeeker/blob/gh-pages/webpack2/readme.md
https://gist.github.com/xgqfrms-GitHub/73b3f046af20556a61ba07cdfc77a155
起步
https://doc.webpack-china.org/guides/get-started/#-npm-
https://doc.webpack-china.org/guides/get-started/#-webpack
https://github.com/webpack/webpack.js.org/edit/master/content/guides/code-splitting-async.md

JS文件压缩
https://doc.webpack-china.org/guides/production-build/#js-

https://doc.webpack-china.org/guides/production-build/#js-

https://doc.webpack-china.org/api/cli/
$ webpack --config example.config.js

# 配置文件默认为 webpack.config.js
$ webpack
# ===
$ webpack --config webpack.config.js

~~this~~


Additional views button in high contrast theme shifts the position of the icon

VSCode Version: Code - Insiders 1.18.0-insider (8dfa696a1eb6ff67eb68925ddaa9e83d3c56b791, 2017-10-31T16:36:35.429Z)
OS Version: Linux x64 4.13.0-16-generic
Extensions:

Extension
Author (truncated)
Version

EditorConfig
Edi
0.11.1

lorem-ipsum
Tyr
1.0.0

sort-lines
Tyr
1.3.0

vscode-svgviewer
css
1.4.3

tslint
eg2
1.0.14

git-project-manager
fel
1.4.0

md-navigate
jri
0.0.1

theme-monokai-pro-vscode
mon
1.1.2

vscode-scss
mrm
0.6.2

seti-icons
qin
0.1.3

Ruby
reb
0.15.0

vim
vsc
0.10.2

(1 theme extensions excluded)

#36571

Also fix the outline on focus of elipsis

This seems to be fixed in latest.
Please note that the bottom hover focus line is missing due to a rendering glitch which is an unrelated issue.


⚠ Bofrost.lu has degraded performance

In 5e1aaab, Bofrost.lu (https://www.bofrost.lu) experienced degraded performance:

HTTP code: 200
Response time: 1531 ms

Resolved: Bofrost.lu performance has improved in 636029d after 8 minutes.


mutiple typedefs causing compile problems

A couple of people have reported that the multiple definitions of
typedef struct DCEparsestate
near lines 10 and 42 causes compiler
problems with some versions of gcc.
remove the second typedef.

Looks good, no issue on Windows either!


Can it work with python package "adb-shell" ?

The package "adb-shell" is easy to connect a device like
from adb_shell.adb_device import AdbDeviceTcp
device1 = AdbDeviceTcp('<IP_ADDRESS>', 5666, default_transport_timeout_s=9.)

Then I got an object to control the device.
In this way, I cannot found device in adb devices using system terminal.

Any links about adb-shell package you have mentioned?
Lots of packages may use this name :)


Respect the user addressbook label

This PR allows the user to have any label they like (iOS allows for
custom labels).
It also fixes a bug here if the user’s label contained a capital letter (i.e. "Home" instead of "home", this
check did not correctly match the label.
Lastly if fixes a bug that completely erases the user's label if it did not match one of the preformatted options.

Awesome!
Question: Does iOS save their iPhone labels as "iPhone" or "iphone"? And, looking at the code change, this accounts for both anyway, correct?

iPhone and iCloud are both capitalized.
This PR changes both the user input and the Apple strings to lowercase while checking only. The actual label itself is not transformed and capitals are maintained.

Perfect. 👌


Request: Make SAML configuration optional

Hello UAA friends,
My pair and I from the Release Integration team are cleaning up our UAA config for the default minimal installation included in cf-for-k8s and ran into an issue trying to remove the certificate used for SAML, which we don't think is required for a minimal standalone UAA. Note that we suspect falling back to the defaults provided by UAA is sufficient for our immediate goal of cleaning up the cf-for-k8s user interface, so we don't feel a strong sense of urgency on the request. We just wanted to let you all know in case this behavior is something you would want to change. Also mentioned in the CloudFoundry Slack channel here.
What version of UAA are you running?
v74.22.0
What output do you see from curl <YOUR_UAA>/info -H'Accept: application/json'
N.A. The UAA app container does not start up successfully
How are you deploying the UAA?
I am deploying the UAA in cf-for-k8s with the provided k8s templates.
What did you do?

Generate values for cf-for-k8s as specified in [its deploy guide].(https://github.com/cloudfoundry/cf-for-k8s/blob/master/docs/deploy.md).
Manually use empty values for the service_provider configuration values.

login:
  service_provider:
    key: ""
    key_password: ""
    certificate: ""

Map those values into the UAA ConfigMap (which matches the BOSH job spec)

login:
  url: #@ "https://login." + <system_domain>
  entityBaseURL: #@ "https://uaa." + <system_domain>
  entityID: cloudfoundry-saml-login
  serviceProviderKey: ""
  serviceProviderKeyPassword: ""
  serviceProviderCertificate: ""

Run the UAA image with the above configuration mounted as part of cf-for-k8s following the deploy guide linked 1.

What did you expect to see? What goal are you trying to achieve with the UAA?
UAA started up successfully. We would like to stand up a minimal UAA for use with a fresh Cloud Foundry running on Kubernetes to validate integration and basic workflows.
What did you see instead?
UAA failed to start up with a bean initialization error:
org.springframework.beans.factory.UnsatisfiedDependencyException: Error creating bean with name 'idpInitiatedLoginController'

Thanks,
Andrew and @cloudfoundry/cf-release-integration

I did some exploration on this story and discovered that these properties are not part of an external SAML Identity Provider integration.
Instead, they are keys which the UAA uses in its role as a SAML Identity Provider.
For better or worse, the UAA's SAML Identity Provider behavior is not something that can be turned off, and so these properties are required.
Evidence
In the UAA docs, there is a section called Service Providers, which, slightly confusingly, describes how the UAA acts as a SAML IdP (it actually makes some sense b/c the UAA SAML IdP keeps track of its known Service Providers and most of the endpoints deal with managing this relationship).  It contains the paragraph:
In order to establish trust, a SAML IdP and SAML SP exchange SAML metadata which contains pulbic certificates as well as the endpoints used to communicate amongst each other. Your SAML SP will likely require the UAA SAML IdP metadata in order to make authentication requests to UAA. You can obtain this metadata by making a GET request to the /saml/idp/metadata endpoint.

When we curl /saml/idp/metadata, you will get the certificate provided at the login.serviceProviderCertificate property.


[DI] Try make create fuction can get params from resolve()

$app->resolve(Class, [...args]);

$app->bind(Class, create(function (/* get args here */) {
...
}))

bind() will wrap ObjectDefinition into CallbackDefinition and StoreDefinition,
so we must implement this feature after #875


Fix more redundant imports.

The latest nightly has started warning about redundant imports. This removes those warnings.
Presumably these were casualties of merging between #13464 and #13409.

@bors r+
Thanks!

:pushpin: Commit b59333a316bf1ea9040c935bade028ddac2c9be7 has been approved by weihanglo
It is now in the queue for this repository.

:hourglass: Testing commit b59333a316bf1ea9040c935bade028ddac2c9be7 with merge 3fcbf73c5c20c0d609cd50463e39376e6f814bae...

:sunny: Test successful - checks-actions
Approved by: weihanglo
Pushing 3fcbf73c5c20c0d609cd50463e39376e6f814bae to master...

:sunny: Test successful - checks-actions
Approved by: weihanglo
Pushing 3fcbf73c5c20c0d609cd50463e39376e6f814bae to master...

:eyes: Test was successful, but fast-forwarding failed: 422 Changes must be made through a pull request.


Add instructions for how to run community calls

This PR's function is to add instructions for how community members can host community calls.
PR adds in the following docs to the community repo

How to for hosting a community call - how to collaborate to create an agenda, and what to consider on the day-of hosting
Community call slide deck template - general template that can be circulated to community call speakers to add their content
List of existing community hosts - list of existing hosts. Many of the materials needed for hosting a community call need to be accessed by existing hosts with appropriate credentials (e.g., zoom call, community call sign up form etc.)
running-dapr directory. This directory will house all files related to running different aspects of the dapr project (e.g., dapr releases, community calls etc.). Release cycle docs have been moved to this new running-dapr directory.

@msfussell could you take a look at this PR?


Update srdf, srdf4j, srdfjena to 0.1.87

Updates

es.weso:srdf
es.weso:srdf4j
es.weso:srdfjena

from 0.1.86 to 0.1.87.
I'll automatically update this PR to resolve conflicts as long as you don't change it yourself.
If you'd like to skip this version, you can just close this PR. If you have any feedback, just mention me in the comments below.
Configure Scala Steward for your repository with a .scala-steward.conf file.
Have a fantastic day writing Scala!

Ignore future updates
Add this to your .scala-steward.conf file to ignore future updates of this dependency:
updates.ignore = [ { groupId = "es.weso" } ]

labels: library-update, semver-patch

Superseded by #173.


moved pbs scripts in to the azurehpc repo

Moved pbs hooks in to the azurehpc repo and updated the pbsserverhooks.sh file to reflect the change.

The reason I use the job hook is because /mnt/resource on normal VMs is not user readable. I believe that we make /mnt/resource world writable in azhpc so maybe it is not needed. But on the other hand it creates a dir with the job id and the user permissions on mount resource if they need the local resource.

Where do we currently put documentation for our scripts? Should I create a readme.md file in the pbshooks dir?

I think a readme in the pbshooks dir is good

If you were to move the pbshooks into the scripts directory you would already have them on all the nodes as all scripts get copied. This would solve the wget issue raised below.
We need to start adding some documentation for this as well. I understand stopping waagent but I'm not sure why you would want the setup_jobdir hook.

@edwardsp I have added a readme. Are you satisfied with the commit and ready to approve it or do you have other concerns?


handling of Process ID Controllers (PID) (IDFGH-11034)

Answers checklist.

[X] I have read the documentation ESP-IDF Programming Guide and the issue is not addressed there.
[X] I have updated my IDF branch (master or release) to the latest version and checked that the issue is present there.
[X] I have searched the issue tracker for a similar issue and not found a similar issue.

IDF version.
idf 5
Operating System used.
Windows
How did you build your project?
Command line with Make
If you are using Windows, please specify command line type.
None
Development Kit.
ESP Wroom 32
Power Supply used.
USB
What is the expected behavior?
I'm focusing on the handling of Process ID Controllers (PID). Now, the PID is essentially a value that indicates the mode in which the system is operating.
Here's the situation broken down:

On boot-up, the ESP32 begins its operation in what is known as "kernel mode" with a PID set to 0. Think of the kernel mode as the core operating level of the system.

My objective is to transition the system to "user mode" by changing the PID to 4. User mode, as the name suggests, is a more restricted environment, typically used to run application tasks, keeping them separate from the core system tasks.

After completing certain tasks in user mode, I'd then like to revert the system back to the kernel mode by resetting the PID to 0.

What is the actual behavior?
It get restarted as i reaches to this function:
REG_WRITEE(PIDCTRL_NMI_MASK_DISABLE_REG, 1);
Steps to reproduce.
Code:
#include <stdio.h>
#include <stdbool.h>
#include <unistd.h>
#include "esp_system.h"
#include "freertos/FreeRTOS.h"
#include "freertos/task.h"
#include "esp_log.h"
#include <stdint.h>
#include "dport_access.h"
#define PID_CTRL_BASE_ADDR 0x3FF1F000
#define PIDCTRL_INTERRUPT_ENABLE_REG (PID_CTRL_BASE_ADDR + 0x000)
#define PIDCTRL_PID_DELAY_REG (PID_CTRL_BASE_ADDR + 0x020)
#define PIDCTRL_NMI_DELAY_REG (PID_CTRL_BASE_ADDR + 0x024)
#define PIDCTRL_PID_NEW_REG (PID_CTRL_BASE_ADDR + 0x048)
#define PIDCTRL_PID_CONFIRM_REG (PID_CTRL_BASE_ADDR + 0x04C)
#define PIDCTRL_NMI_MASK_ENABLE_REG (PID_CTRL_BASE_ADDR + 0x054)
#define PIDCTRL_NMI_MASK_DISABLE_REG (PID_CTRL_BASE_ADDR + 0x058)
#define PIDCTRL_LEVEL_REG (PID_CTRL_BASE_ADDR + 0x060)
#define PIDCTRL_FROM_0_REG (PID_CTRL_BASE_ADDR + 0x28 + 0x4 * 0) // 'n' is set to 0 as we're always switching from PID 4 in this demo
#define PIDCTRL_FROM_4_REG (PID_CTRL_BASE_ADDR + 0x28 + 0x4 * 4) // 'n' is set to 4 as we're always switching from PID 0 in this demo
#define DPORT_IMMU_PAGE_MODE_REG (0x3FF00080)
#define DPORT_DMMU_PAGE_MODE_REG (0x3FF00084)
// IMMU
#define DPORT_IMMU_TABLE0_REG (0x3FF00504)
#define DPORT_IMMU_TABLE1_REG (0x3FF00508)
#define DPORT_IMMU_TABLE2_REG (0x3FF0050C)
#define DPORT_IMMU_TABLE3_REG (0x3FF00510)
#define DPORT_IMMU_TABLE4_REG (0x3FF00514)
#define DPORT_IMMU_TABLE5_REG (0x3FF00518)
#define DPORT_IMMU_TABLE6_REG (0x3FF0051C)
#define DPORT_IMMU_TABLE7_REG (0x3FF00520)
#define DPORT_IMMU_TABLE8_REG (0x3FF00524)
#define DPORT_IMMU_TABLE9_REG (0x3FF00528)
#define DPORT_IMMU_TABLE10_REG (0x3FF0052C)
#define DPORT_IMMU_TABLE11_REG (0x3FF00530)
#define DPORT_IMMU_TABLE12_REG (0x3FF00534)
#define DPORT_IMMU_TABLE13_REG (0x3FF00538)
#define DPORT_IMMU_TABLE14_REG (0x3FF0053C)
#define DPORT_IMMU_TABLE15_REG (0x3FF00540)
static inline void IRAM_ATTR REG_WRITEE(uint32_t addr, uint32_t value)
{
*(volatile uint32_t *)(addr) = value;
}
static inline uint32_t IRAM_ATTR REG_READD(uint32_t addr)
{
return *(volatile uint32_t *)(addr);
}
void IRAM_ATTR enable_masking()
{
// Step 1 and 2 : Masking all interrupts except NMI
REG_WRITEE(PIDCTRL_NMI_MASK_ENABLE_REG, 1);
// vTaskDelay(pdMS_TO_TICKS(50));

// Step 3: Configuring delays
REG_WRITEE(PIDCTRL_PID_DELAY_REG, 20);
REG_WRITEE(PIDCTRL_NMI_DELAY_REG, 16);

}
void IRAM_ATTR step_6_to_8()
{
// Step 6 and 7: Confirming PID change
vTaskDelay(pdMS_TO_TICKS(1000));
REG_WRITEE(PIDCTRL_PID_CONFIRM_REG, 1);
vTaskDelay(pdMS_TO_TICKS(1000));
REG_WRITEE(PIDCTRL_NMI_MASK_DISABLE_REG, 1);
// Step 8: Switch to the new process and fetch instruction
vTaskDelay(pdMS_TO_TICKS(10)); // Short delay to simulate a context switch. Actual switching will be managed by the scheduler.

}
void IRAM_ATTR switch_to_pid_4()
{
enable_masking();
// Step 4: Setting the new PID
REG_WRITEE(PIDCTRL_PID_NEW_REG, 4);

// Step 4: Configure PIDCTRL_LEVEL_REG and PIDCTRL_FROM_n_REG
REG_WRITEE(PIDCTRL_LEVEL_REG, 0x1); // Setting to privileged mode
 vTaskDelay(pdMS_TO_TICKS(1000));
REG_WRITEE(PIDCTRL_FROM_4_REG, 4); // Setting the new PID at the current
 vTaskDelay(pdMS_TO_TICKS(1000));

step_6_to_8();

}
void IRAM_ATTR switch_to_pid_0()
{
enable_masking();

// Step 4: Setting the new PID
REG_WRITEE(PIDCTRL_PID_NEW_REG, 0);

// Step 4: Configure PIDCTRL_LEVEL_REG and PIDCTRL_FROM_n_REG
REG_WRITEE(PIDCTRL_LEVEL_REG, 0x1); // Setting to privileged mode
vTaskDelay(pdMS_TO_TICKS(1000));
REG_WRITEE(PIDCTRL_FROM_0_REG, 0); // Setting the new PID at the current
vTaskDelay(pdMS_TO_TICKS(1000));

step_6_to_8();

}
void IRAM_ATTR mmu_configure()
{
/* 8K page size for mappings both IRAM and DRAM */

REG_WRITEE(DPORT_IMMU_PAGE_MODE_REG, 0);
REG_WRITEE(DPORT_DMMU_PAGE_MODE_REG, 0);

// IMMU
REG_WRITEE(DPORT_IMMU_TABLE0_REG, 0x10);
REG_WRITEE(DPORT_IMMU_TABLE1_REG, 0x11);
REG_WRITEE(DPORT_IMMU_TABLE2_REG, 0x12);
REG_WRITEE(DPORT_IMMU_TABLE3_REG, 0x13);
REG_WRITEE(DPORT_IMMU_TABLE4_REG, 0x14);
REG_WRITEE(DPORT_IMMU_TABLE5_REG, 0x15);
REG_WRITEE(DPORT_IMMU_TABLE6_REG, 0x16);
REG_WRITEE(DPORT_IMMU_TABLE7_REG, 0x17);
REG_WRITEE(DPORT_IMMU_TABLE8_REG, 0x18);
REG_WRITEE(DPORT_IMMU_TABLE9_REG, 0x19);
REG_WRITEE(DPORT_IMMU_TABLE10_REG, 0x1a);
REG_WRITEE(DPORT_IMMU_TABLE11_REG, 0x1b);
REG_WRITEE(DPORT_IMMU_TABLE12_REG, 0x1c);
REG_WRITEE(DPORT_IMMU_TABLE13_REG, 0x1d);
REG_WRITEE(DPORT_IMMU_TABLE14_REG, 0x1e);
REG_WRITEE(DPORT_IMMU_TABLE15_REG, 0x1f);

}
void app_main(void)
{
ESP_LOGI("APP_MAIN", "Starting PID switch demo...");
mmu_configure();
// Switch to PID 4
ESP_LOGI("APP_MAIN", "Switching to PID 4...");
switch_to_pid_4();
 vTaskDelay(pdMS_TO_TICKS(5000));

// Switch back to default PID
switch_to_pid_0();

ESP_LOGI("APP_MAIN", "PID switch demo ended.");

}
Debug Logs.
I (54) boot: ESP-IDF v5.0.1-dirty 2nd stage bootloader
I (54) boot: compile time 19:05:14
I (54) boot: chip revision: v3.0
I (58) boot.esp32: SPI Speed      : 40MHz
I (63) boot.esp32: SPI Mode       : DIO
I (67) boot.esp32: SPI Flash Size : 2MB
W (72) boot.esp32: PRO CPU has been reset by WDT.
W (77) boot.esp32: WDT reset info: PRO CPU PC=0x400803c0
0x400803c0: _DoubleExceptionVector at C:/Users/Talha/esp/esp-idf-v5.0.1/esp-idf-v5.0.1/components/freertos/FreeRTOS-Kernel/portable/xtensa/xtensa_vectors.S:469

W (83) boot.esp32: WDT reset info: APP CPU PC=0x400d1516
0x400d1516: panic_handler at C:/Users/Talha/esp/esp-idf-v5.0.1/esp-idf-v5.0.1/components/esp_system/port/panic_handler.c:140 (discriminator 1)

I (89) boot: Enabling RNG early entropy source...
I (95) boot: Partition Table:
I (98) boot: ## Label            Usage          Type ST Offset   Length
I (106) boot:  0 nvs              WiFi data        01 02 00009000 00006000
I (113) boot:  1 phy_init         RF data          01 01 0000f000 00001000
I (121) boot:  2 factory          factory app      00 00 00010000 00100000
I (128) boot: End of partition table
I (133) esp_image: segment 0: paddr=00010020 vaddr=3f400020 size=08274h ( 33396) map
I (153) esp_image: segment 1: paddr=0001829c vaddr=3ffb0000 size=01e7ch (  7804) load
I (157) esp_image: segment 2: paddr=0001a120 vaddr=40080000 size=05ef8h ( 24312) load
I (170) esp_image: segment 3: paddr=00020020 vaddr=400d0020 size=159d4h ( 88532) map
I (202) esp_image: segment 4: paddr=000359fc vaddr=40085ef8 size=05af4h ( 23284) load
I (218) boot: Loaded app from partition at offset 0x10000
I (218) boot: Disabling RNG early entropy source...
I (230) cpu_start: Pro cpu up.
I (230) cpu_start: Starting app cpu, entry point is 0x400810b8
0x400810b8: call_start_cpu1 at C:/Users/Talha/esp/esp-idf-v5.0.1/esp-idf-v5.0.1/components/esp_system/port/cpu_start.c:142

I (0) cpu_start: App cpu up.
I (244) cpu_start: Pro cpu start user code
I (244) cpu_start: cpu freq: 160000000 Hz
I (244) cpu_start: Application information:
I (249) cpu_start: Project name:     main
I (254) cpu_start: App version:      1
I (258) cpu_start: Compile time:     Sep  9 2023 19:04:50
I (264) cpu_start: ELF file SHA256:  0618b5789314aed7...
I (270) cpu_start: ESP-IDF:          v5.0.1-dirty
I (276) cpu_start: Min chip rev:     v0.0
I (280) cpu_start: Max chip rev:     v3.99
I (285) cpu_start: Chip rev:         v3.0
I (290) heap_init: Initializing. RAM available for dynamic allocation:
I (297) heap_init: At 3FFAE6E0 len 00001920 (6 KiB): DRAM
I (303) heap_init: At 3FFB2770 len 0002D890 (182 KiB): DRAM
I (309) heap_init: At 3FFE0440 len 00003AE0 (14 KiB): D/IRAM
I (316) heap_init: At 3FFE4350 len 0001BCB0 (111 KiB): D/IRAM
I (322) heap_init: At 4008B9EC len 00014614 (81 KiB): IRAM
I (330) spi_flash: detected chip: generic
I (333) spi_flash: flash io: dio
W (337) spi_flash: Detected size(4096k) larger than the size in the binary image header(2048k). Using the size in the binary image header.
I (351) cpu_start: Starting scheduler on PRO CPU.
I (0) cpu_start: Starting scheduler on APP CPU.
I (361) APP_MAIN: Starting PID switch demo...
I (371) APP_MAIN: Switching to PID 4...
ets Jul 29 2019 12:21:46

rst:0x8 (TG1WDT_SYS_RESET),boot:0x13 (SPI_FAST_FLASH_BOOT)
configsip: 0, SPIWP:0xee
clk_drv:0x00,q_drv:0x00,d_drv:0x00,cs0_drv:0x00,hd_drv:0x00,wp_drv:0x00
mode:DIO, clock div:2
load:0x3fff0030,len:6944
load:0x40078000,len:15500
load:0x40080400,len:3844
0x40080400: _init at ??:?

More Information.
No response

I have try to debug it more and found that when it cpu reaches to REG_WRITEE(PIDCTRL_PID_CONFIRM_REG, 1) in function void IRAM_ATTR step_6_to_8(). The MCU get restart.

Please have a look at the esp-privilege-separation framework which should help you for the privilege based code execution. This framework is supported on ESP32-C3 and ESP32-S3. Regarding the PID controller in ESP32, unfortunately we do not support this peripheral. There were certain limitations associated with this peripheral and they have been addressed through newer world controller and permission control peripherals in ESP32-C3/ESP32-S3 SoCs.
Hope this helps!


Desire a "Not" feature for a path (BTW We love this plugin - thank you!!!)

We have 1 path that we Don't want to open in our app (especially when we're already in the app).
For ex, we have a link to a "Printable" version of a form, that we want to force the user to open in a browser.  A link to this "Printable" form is within our app, so there might be another way to force the user to open it with a browser (preventing our app from being one of the choices in Android's Open App list).  ios permits this:   "To specify an area that should not be handled as a universal link, add “NOT ” (including a space after the T) to the beginning of the path string.".  Perhaps Android doesn't support it.

Thanks :)
I'm afraid this is iOS-only feature, no such option for Android. In Android you can only define regex for the url, and that's it. Maybe you can play with that, but, probably, you already did that.
I'm afraid you'll either have to change the url of the "Printable" to something totally different, or let the app to be opened, but on the JS side capture that and then open the browser from the app.
But I would say, that changing the "Printable" link on the website is the easiest solution. Or just define more detailed urls in the <path /> preference.


Register missing redirects [static]

This call was missed in #2519.

Warnings

:warning:

This PR modified helper functions in lib/ but not accompanying tests. That's okay so long as it's refactoring existing code.

Messages

:book:
:sparkles: Thanks for your contribution to Shields, @paulmelnikow!

  Generated by :no_entry_sign: dangerJS against a1b0d48e147a9a77104d54207e4b3f9f777b32b2


bug: failed using <C-d> to quit shell in floating terminal, leaving an empty window

Did you check docs and existing issues?

[X] I have read all the LazyVim docs
[X] I have searched the existing issues of LazyVim
[X] I have searched the existing issues of plugins related to this issue

Neovim version (nvim -v)
NVIM v0.10.0-dev-2121+g06aebfa99
Operating system/version
Ubuntu 22
Describe the bug
If I press C-d in shell in float terminal, there's a chance that the float terminal can not quit completely and will leave the float window there which can quit using :close.
Also, if I open the float terminal on dashboard right after startup ( no buffers opened), this problem can be easily reproduced.
Steps To Reproduce

install lazyvim starter
start nvim
press <C-/> to open float term
press <C-d> to close it
issue reproduced.

Expected Behavior
after press <C-d>, the float term closed completely.
Repro
No response

I can't reproduce this issue, but !!!
ctrl+d is standart code/shell exit for terminal emulators like Control-C to break etc. Not the nvim command.
So, if you command promt is clear - C+d will close the terminal (not only in nvim), but if you have some symbols in your promt, this command not works. You can try it by open terminal emulator outside the neovim and try to press Control+d
with/without clear promt.
So, use C-/ for open/hide the terminal like toggle.

@kobzar Thanks for your advice. I have found the cause but don't know why, maybe an upstream issue from neovim or vim?
It seems that this is a issue related with SHELL or cmd, if it starts with /, the issue will always show up.
-- INFO: always use powershell on windows
if jit.os == "Windows" then
vim.cmd[[
  let &shell = executable('pwsh') ? 'pwsh' : 'powershell'
  let &shellcmdflag = '-NoLogo -ExecutionPolicy RemoteSigned -Command [Console]::InputEncoding=[Console]::OutputEncoding=[System.Text.UTF8Encoding]::new();$PSDefaultParameterValues[''Out-File:Encoding'']=''utf8'';Remove-Alias -Force -ErrorAction SilentlyContinue tee;'
  let &shellredir = '2>&1 | %%{ "$_" } | Out-File %s; exit $LastExitCode'
  let &shellpipe  = '2>&1 | %%{ "$_" } | tee %s; exit $LastExitCode'
  set shellquote= shellxquote=
]]
else
vim.cmd[[
  " let &shell = "/usr/bin/fish"    " not working
  " let &shell = "/bin/bash"        " not working
  " let &shell = "zsh"              " working
  let &shell = "bash"             " working
]]
end

or
local _lazyterm = function()
  -- _util.terminal("/bin/bash", {      -- not working
  _util.terminal("bash", {              -- working
    cwd = _util.root(),
    ctrl_hjkl = false,
    size = { width = 1.0, height = 1.0 },
  })
end

  vim.o.shell = os.getenv("SHELL"):match("([^"..package.config:sub(1,1).."]+)$")

one-liner workaround. extract bash from /bin/bash

Witch shell are you use?

Try this one in fish
bind \cd true
and make tests.
Nextone, read this
https://stackoverflow.com/questions/34216850/how-to-prevent-fish-shell-from-closing-when-typing-ctrl-d-eof

Try this one in fish bind \cd true and make tests.
Nextone, read this https://stackoverflow.com/questions/34216850/how-to-prevent-fish-shell-from-closing-when-typing-ctrl-d-eof

thanks but I found that even just typed exit to quit, this issue still happens, so maybe there's no relationship between this issue and the  keymap.

As i say before  isn't LazyVim keymap. Its Shell EOF signal.
Usually we are use terminal by toggle it
 for open and the same for hide.
Why are you try to close shell every time?
Ask waht are you want at end, maybe some one advice better solution for it.

As i say before isn't LazyVim keymap. Its Shell EOF signal.
Usually we are use terminal by toggle it for open and the same for hide. Why are you try to close shell every time? Ask waht are you want at end, maybe some one advice better solution for it.

Yes, I know Ctrl+d is not a nvim keymap, I use the word keymap referred to ctrl+d for convenience. As the reason for closing, there're so many, clearing the env is one of them. 😄

I can't reproduce this using fish on arch


cta section text updates

Related Ticket(s)
Closes #1197
Description
Update CTA section
Changelog
New

Added Variants section to cover CTA section with content items and CTA section with link list
Add Content guidance for With link list
Updated and added images

Changed

Updated page description

Removed

{{removed thing}}

@RichKummer
Things I am considering:

Should with content items and with link list be modifiers?

they both apply as modifiers (I think) for both components. I am torn on this and happy to stage it in our review tomorrow. It would change the hierarchy a bit.

Content block is missing from React 😢

Sad day, we might need a wrapper story to fix it, but I think we could update that later

Do we like the in-browser examples. I think they look nice myself!

Due to this PR being created before some directory changes, seems like the Deploy previews are using the outdated caches, which cause the build to fail.
Closed in favor of #1459 , which is the same branch but with the updated cache to use in the deploy preview process.


Update GMD CI config to run in parallel

Fixes #1479

Cannot auto-update because of conflicts.

Cannot auto-update because of conflicts.

Cannot auto-update because of conflicts.

Cannot auto-update because of conflicts.


Avoid warning requires a peer of @angular/core^4.0.0 ...

When testing version 2.0.1 and to avoid:
[11:34:24] Starting 'link'...
npm WARN<EMAIL_ADDRESS>requires a peer of<EMAIL_ADDRESS>but none was installed.
npm WARN<EMAIL_ADDRESS>requires a peer of<EMAIL_ADDRESS>but none was installed.

shouldn't be:
"dependencies": {
    "@angular/core": "^4.0.0",
    "@angular/common": "^4.0.0"
   },
"peerDependencies": {
    "@angular/core": "^4.0.0",
    "@angular/common": "^4.0.0"
   },

Hi again @mlc-mlapis,
The warnings that appear during the linking phase (which is required only once during development) can just be ignored.
In fact, the package.json in the linked folder (dist/) declares your library's dependencies as peerDependencies (and not dependencies), so that end users can specify exactly which version of the dependent packages they want to use, without being tied to your library's ones. This is intended.
In practice, the end user's project will already declare Angular dependencies in its dependencies section of its package.json,  so it should be no warnings at all (provided those dependencies respect the range defined by the library ). See for example the built-in demo application.
Cheers!

Yeah, that's clear. Thanks for your notes.


examples: Use a nonprivileged nginx pod as well

What type of PR is this?
/kind cleanup
/kind failing-test

What this PR does / why we need it:
We use the example in the e2e tests, but the image we used was a
privileged one, which doesn't work by default on OCP.
Which issue(s) this PR fixes:
N/A

Does this PR have test?
N/A

Special notes for your reviewer:
I wasn't sure if this is the proper fix, becuase the policy used in
the example was created for the privileged container in the first
place. Alternatives:

use a custom workload in the test and just don't test the example
Decode() the YAML and overwrite the image on OCP only

Does this PR introduce a user-facing change?

NONE

/lgtm cancel

Closing per github discussion. Will either decode the pod and set the SA or something else so that we keep a test with the privileged container.


SVNAuthenticationException: svn: E170001: Authentication required

Hi Team,
I am getting error while connecting Hygieia to svn though i had put the username and password correct.
Below is my property file.
#Database Name
spring.data.mongodb.database=*******
#Database HostName - default is localhost
spring.data.mongodb.host=localhost
dbhost=localhost
#Database Port - default is 27017
spring.data.mongodb.port=27017
#Database Username - default is blank
spring.data.mongodb.username=*******
#Database Password - default is blank
spring.data.mongodb.password=*******
#Collector schedule (required)
subversion.cron=0 0/2 * * * *
#Shared subversion username and password
subversion.username=prod*****
subversion.password=*****
#Maximum number of days to go back in time when fetching commits
subversion.commitThresholdDays=5
Can any one please help me out.
Thanks
Ashish

@Ashissh021 - What error are you getting? Please post a screenshot of the error you are receiving.

@matthewbeasley: Thanks i have updated the application property as below now its working fine.
#Database Name
spring.data.mongodb.database=
#Database HostName - default is localhost
spring.data.mongodb.host=localhost
#Database Port - default is 27017
spring.data.mongodb.port=27017
#Database Username - default is blank
spring.data.mongodb.username=d
#Database Password - default is blank
spring.data.mongodb.password=
dbname=
dbhost=localhost
dbport=27017
dbusername=
dbpassword=
#Collector schedule (required)
subversion.cron=0 0/5 * * * *
#Shared subversion username and password
subversion.username=
subversion.password=
#Maximum number of days to go back in time when fetching commits
subversion.commitThresholdDays=15
Thank you :)

@Ashissh021 I'm glad you got it working! Thank you for closing this issue.


🌅 Add set view on bottom feature

Summary
- What I did
Addition of the possibility of set a view to the bottom
- How I did it
Add Gui.SetViewOnBottom function for that.
- How to verify it

Create three views and used Gui.SetViewOnTop and Gui.SetViewOnBottom to play :)

Questions

Q
A

Bug fix?
no

New feature?
yes

BC breaks?
no

Deprecations?
no

Tests?
no

Note
A big thanks for this amazing tool!

Merged via 93acb816a808ac62affc3d612a53c852426cbe96. I simplified a bit the function and also updated _examples/dynamic.go to include a call to *Gui.SetViewOnBottom.


Unable to Delete Custom Clusters from Rancher UI

Rancher Server Setup

Rancher version: v2.7-head (Commit ID: ab561bf), v2.6-head (Commit ID: 657d8ec), and v2.6.11-rc7
Installation option (Docker install/Helm Chart): Helm and Docker

If Helm Chart, Kubernetes Cluster and version (RKE1, RKE2, k3s, EKS, etc): RKE1

Proxy/Cert Details: N/A

Information about the Cluster

Kubernetes version: Confirmed on v1.25.6+rke2r1 and v1.24.10+rke2r1
Cluster Type (Local/Downstream): Downstream

If downstream, what type of cluster? (Custom/Imported or specify provider for Hosted/Infrastructure Provider): Custom

User Information

What is the role of the user logged in? (Admin/Cluster Owner/Cluster Member/Project Owner/Project Member/Custom) Cluster Owner and Admin

If custom, define the set of permissions: N/A

Describe the bug
When attempting to delete a Custom Cluster from Rancher, the cluster goes into a Removing state with the message "waiting for machine [machinename] to delete", but the machine is never deleted and the cluster will continue to persist in the UI.
To Reproduce

Spin up an Rancher server
Create an RKE2 or K3s Custom Cluster
Once the cluster comes up as Active, delete the custom cluster

Result
The cluster goes into a Removing state with the message "waiting for machine [machinename] to delete", but the machine is never deleted and the cluster will continue to persist in the UI.
Expected Result
The custom cluster is deleted without issue
Additional context
As a potential work around for this issue, if each of the cluster's nodes are manually deleted from Rancher, then the cluster will clean up from Rancher as expected.
Rancher Logs:
Rancher Logs.txt
Deletion API Information:
DELETE Request API Header and Response.txt
Screenshots

/forwardport v2.7.2

During testing on v2.6-head (Commit ID: ddecd1b), I was able to successfully delete custom clusters from the Rancher UI without issue when following the Test Steps. Therefore I am closing this ticket as Done.
Test Steps:

Spin up a Rancher server on v2.6-head (Commit ID: ddecd1b)
Provision an RKE2 custom cluster
Provision a K3s custom cluster
Provision an RKE2 custom cluster with Windows Nodes
Provision an RKE1 custom cluster
Wait for all of the provisioned clusters to become Active
Manually delete each of the Custom Clusters from the Rancher UI

Provisioned Clusters:

Clusters Deleted from the UI:

Rancher Logs during Deletion:
Rancher Logs.txt
Deletion API Information:
DELETE Request API Header and Response.txt


chore: adds the initial root README and code-generated favicon

also changes copy of 'framework' to 'library'
adds brand light & dark SVG logos to playground/public

:tada: This PR is included in version 1.0.15 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


fix #994 known strings should be read using ReadAsString() to prevent da...

...tes being parsed by json.net, ty @ashkandaie

LGTM


ocamlbuild plugin

The js_of_ocaml ocamlbuild plugin doesn't work with ocaml-vdom due to

the -no-check-prims flag
the use of gen_js_api

It would be very useful to have a fork of the plugin that added the correct flags.

Contributions are welcome!  I've never used ocamlbuild, so this is unlikely to happen otherwise.


[BUG] PHP 7.0 not really supported

Prerequisites

[ ] Able to reproduce the behaviour outside of your code, the problem is isolated to Laravel Excel.
[X] Checked that your issue isn't already filed.
[X] Checked if no PR was submitted that fixes this problem.

Versions

PHP version: 7.0.22
Laravel version: 5.5
Package version: 3.0

Description
At the moment of doing composer require maatwebsite/excel at the root folder or our project, compose complained with:
Your requirements could not be resolved to an installable set of packages.

  Problem 1
    - doctrine/annotations v1.5.0 requires php ^7.1 -> your PHP version (7.0.22) does not satisfy that requirement.
    - doctrine/annotations v1.5.0 requires php ^7.1 -> your PHP version (7.0.22) does not satisfy that requirement.
    - doctrine/annotations v1.5.0 requires php ^7.1 -> your PHP version (7.0.22) does not satisfy that requirement.
    - Installation request for doctrine/annotations == <IP_ADDRESS> -> satisfiable by doctrine/annotations[v1.5.0].

Installation failed, reverting ./composer.json to its original content.

As it seems, PHP 7.0 is not really supported because a dependency restricts this to PHP ^7.1. Is there a possibility of fixing this?
Steps to Reproduce
Just issuing composer require maatwebsite/excel in the context of a PHP ^7.0 project.
Expected behavior:
The plugin to be installed correctly.
Actual behavior:
Installation fails because a dependency of this plugin restricts the supported PHP version eve further than the range stated in this plugin's README.

@Darkeye9 The error is about doctrine/annotations not maatwebsite/excel. This seems to be a dependency of your own, as we don't use it.
As you can see here, the package is installable on PHP7.0 : https://travis-ci.org/Maatwebsite/Laravel-Excel/jobs/364606364


doc: Update doc building instructions

Instructions for generating documents locally needed some updates
because of build environment changes and use of newer tool versions.
Signed-off-by: David B. Kinder<EMAIL_ADDRESS>

Codecov Report

Merging #6245 into master will decrease coverage by <.01%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master    #6245      +/-   ##
==========================================
- Coverage   53.11%   53.11%   -0.01%
==========================================
  Files         414      414
  Lines       40260    40260
  Branches     7759     7759
==========================================
- Hits        21385    21384       -1
- Misses      15708    15709       +1
  Partials     3167     3167

Impacted Files
Coverage Δ

samples/philosophers/src/main.c
96.87% <0%> (-1.57%)
:arrow_down:

Continue to review full report at Codecov.

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Shoot Autoscaling

Documentation issue at https://gardener.cloud/docs/gardener/usage/shoot_autoscaling/:
In Vertical Pod Auto-Scaling section: https://gardener.cloud/docs/gardener/usage/shoot_autoscaling/#vertical-pod-auto-scaling there is a link to vertical-pod-autoscaler component, but actually gardener forked this repo and has its own in https://github.com/gardener/autoscaler.

Gardener does not use VPA from its fork, see https://github.com/gardener/gardener/blob/bc94ce9bd342f3c18f206018edeca7278fcb4cfc/imagevector/images.yaml#L551-L590. We only consume cluster-autoscaler from the fork. Hence, the link is correct.
/close

Gardener does not use VPA from its fork, see
https://github.com/gardener/gardener/blob/bc94ce9bd342f3c18f206018edeca7278fcb4cfc/imagevector/images.yaml#L551-L590
. We only consume cluster-autoscaler from the fork. Hence, the link is correct.
/close

@rfranzke great reference, thanks!
what is calico-node-vertical-autoscaler deployment which uses registry_k8s_io/cpa/cpvpa@sha256:5c67cd124f9f1c00c6dd39b7aefa41e651c2f8303ddeb8f4ee491715d3938080 image in shoot clusters? k8s version is 1.25.11, gardenlinux version is 934.9.0.
I can't find it in the images.yaml.

It should be https://github.com/gardener/gardener-extension-networking-calico/blob/cba69b7b5490f698af04f3d34dff5f590b6c4c8a/charts/images.yaml#L71

What is calico-node-vertical-autoscaler deployment which uses registry_k8s_io/cpa/cpvpa@sha256:5c67cd124f9f1c00c6dd39b7aefa41e651c2f8303ddeb8f4ee491715d3938080 image in shoot clusters? k8s version is 1.25.11, gardenlinux version is 934.9.0. I can't find it in the images.yaml.

It should be from https://github.com/gardener/gardener-extension-networking-calico/blob/cba69b7b5490f698af04f3d34dff5f590b6c4c8a/charts/images.yaml#L71-L74


[Suggestion] Add some way to use fertilizers from other mods in the Plant Fertilizer

Industrial Foregoing Version: 1.12.2-1.10.7-204
TeslaCoreLib Version: 1.12.2-1.0.15
Crashlog (If Any): None
Attempting to use Mystical Fertilizer from Mystical Agriculture in the Plant Fertilizer but it isn't compatible. Not sure if there is a specific reason for the incompatibility but it would be a nice thing to have.

You can add fertilizers by adding the item to the fertilizer OreDictionary entry


Registering TEAM Z3Nspyder

Application for Registering Team to CODE CAMP 1.0
This pull request template helps you complete an application to the CODE CAMP 1.0 HACKATHON. Use the checklist below to verify that you have followed the instructions correctly.
(Put x inside [] like [x])
Select the type of Pull Request
[x] Registration Pull request.
[] Submission Pull request.
Checklist ✅

[x] I have read the instructions on the README file before submitting my application and gone through CODE_OF_CONDUCT.
[x] I have Submitted my team's details by making a folder of my team as instructed in How to send Pull Request page.
[x] I have used the Markdown file template to add my information for the Hackathon.
[x] I have given all the necessary details as mentioned in template index.md file and the details are correct and best to my knowledge.
[x] I understand that a reviewer will merge my pull request after examining it or ask for changes in case needed.
[x] I understand I should not tag or add a reviewer to this Pull Request.
[x] I understand the Details added to the template will be used as a means of communication at the time of result declaration.
[x] I have added the event to my calendar.

@Uyadav207

I have made the changes you asked but for some reason I don't think they're getting reflected after I pull the code

@hanieljacob, can you DM me. we are having some isssue with your Pull Request. Do not close it. Will resolve is sooner.
t.me/utkarshyadav207