Corrected syntax for interface.

Corrected syntax of interface. From Interface to interface (lowercase on first letter).
If the first letter on the word interface is uppercase, this will produce an error on Visual Studio stating that:
The type or namespace name 'Interface' could not be found (are you missing a using directive or an assembly reference?)

[x] I have read freeCodeCamp's contribution guidelines.
[x] My pull request has a descriptive title (not a vague title like Update index.md)
[x] My pull request targets the master branch of freeCodeCamp.
[x] None of my changes are plagiarized from another source without proper attribution.
[x] My article does not contain shortened URLs or affiliate links.

If your pull request closes a GitHub issue, replace the XXXXX below with the issue number.
Closes #XXXXX

Closed and Reopened this PR to attempt to resolve a specific Travis build failure.


Trade Metrics are wrong as they require trade data instead of just returns

Several trade metrics are incorrectly computed using only returns data.
Using only returns data to compute trade metrics does not make any sense!
For accurate trade analysis, the following metrics require actual trade data:

Max Consecutive Wins
Max Consecutive Losses
Gain/Pain Ratio
Gain/Pain
Payoff Ratio
Profit Factor
Common Sense Ratio
CPC Index
Tail Ratio
Outlier Win Ratio
Outlier Loss Ratio

Additionally, any formulas dependent on the above metrics, such as:

Kelly Criterion
Risk of Ruin

should also utilize trade data for correct computation.
Proposed Solution

Integrate trade data input alongside returns data.
Use a trade data format compatible with Backtrader, a widely-used backtesting framework.
Modify the affected metrics to utilize the provided trade data for accurate computation.
Ensure compatibility and seamless use of Quantstats within the Backtrader environment.

Who Can Help
Anyone with experience in Backtrader or Lumibot is welcome to contribute to fixing this issue.

these have now been removed


Limit visualization to some size of MDP

Currently, if the visualization of some huge CMDP is requested, this can kill the process. We can limit the size to 50 states or so. But users should be able to change this.

Closed by 961180b


Error while running a test run with an image

I've followed the instructions provided for all the dependencies, but using pip instead of conda. I've received the following error while running the pose estimation on an image.
Type of Issue: Help required
AttributeError: module 'tensorflow._api.v1.initializers' has no attribute 'GlorotUniform'
Has anyone faced this issue or does anyone have any insights to what might be happening?
Executed Command : python run.py --model=mobilenet_thin --resize=432x368 --image=./images/p1.jpg
Operating system (Ubuntu): Ubuntu 18.04

I got same error. I think this occurs due to incomplete version migration in some of the scripts of this project.
This solved the error for me:

Open network_base.py which is in tf_pose directory , and replace the line where GlorotUniform is initialized with this line :  _init_xavier = tf.initializers.glorot_uniform()

I've followed the instructions provided for all the dependencies, but using pip instead of conda. I've received the following error while running the pose estimation on an image.
Type of Issue: Help required
AttributeError: module 'tensorflow._api.v1.initializers' has no attribute 'GlorotUniform'
Has anyone faced this issue or does anyone have any insights to what might be happening?
Executed Command : python run.py --model=mobilenet_thin --resize=432x368 --image=./images/p1.jpg
Operating system (Ubuntu): Ubuntu 18.04

I got same error. I think this occurs due to incomplete version migration in some of the scripts of this project.
This solved the error for me:
Open network_base.py which is in tf_pose directory , and replace the line where GlorotUniform is initialized with this line : _init_xavier = tf.initializers.glorot_uniform()

Hey @SarangChougs  thanks for the reply. Will try that out for sure!

Hello guys,
I'm also encountering issues running the test run scripts.
When I run
python3 run.py --model=mobilenet_thin --resize=432x368 --image=./images/p1.jpg

it fails after some time with
...
Openpose/MConv_Stage6_L2_5_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage6_L2_5_pointwise/BatchNorm/FusedBatchNorm
Openpose/concat_stage7/axis
Openpose/concat_stage7
Traceback (most recent call last):
  File "run.py", line 39, in <module>
    e = TfPoseEstimator(get_graph_path(args.model), target_size=(w, h))
  File "/home/jetson/git/Realtime-Action-Recognition/src/githubs/tf-pose-estimation/tf_pose/estimator.py", line 337, in __init__
    self.tensor_image = self.graph.get_tensor_by_name('TfPoseEstimator/image:0')
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py", line 3902, in get_tensor_by_name
    return self.as_graph_element(name, allow_tensor=True, allow_operation=False)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py", line 3726, in as_graph_element
    return self._as_graph_element_locked(obj, allow_tensor, allow_operation)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py", line 3768, in _as_graph_element_locked
    "graph." % (repr(name), repr(op_name)))
KeyError: "The name 'TfPoseEstimator/image:0' refers to a Tensor which does not exist. The operation, 'TfPoseEstimator/image', does not exist in the graph."

I have ubuntu 18.04 on a Jetson Xavier AGX, with tensorflow 2.4
By the way, I also tried the other test script with the webcam:
python3 run_webcam.py --model=mobilenet_thin --resize=432x368 --camera=0 --tensorrt=True

and met my demise with
2021-03-21 20:25:59.620475: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.10.2
[2021-03-21 20:26:04,924] [TfPoseEstimator-WebCam] [DEBUG] initialization mobilenet_thin : /home/jetson/git/Realtime-Action-Recognition/src/githubs/tf-pose-estimation/models/graph/mobilenet_thin/graph_opt.pb
2021-03-21 20:26:04,924 DEBUG initialization mobilenet_thin : /home/jetson/git/Realtime-Action-Recognition/src/githubs/tf-pose-estimation/models/graph/mobilenet_thin/graph_opt.pb
[2021-03-21 20:26:04,924] [TfPoseEstimator] [INFO] loading graph from /home/jetson/git/Realtime-Action-Recognition/src/githubs/tf-pose-estimation/models/graph/mobilenet_thin/graph_opt.pb(default size=432x368)
2021-03-21 20:26:04,924 INFO loading graph from /home/jetson/git/Realtime-Action-Recognition/src/githubs/tf-pose-estimation/models/graph/mobilenet_thin/graph_opt.pb(default size=432x368)
Traceback (most recent call last):
  File "run_webcam.py", line 45, in <module>
    e = TfPoseEstimator(get_graph_path(args.model), target_size=(w, h), trt_bool=str2bool(args.tensorrt))
  File "/home/jetson/git/Realtime-Action-Recognition/src/githubs/tf-pose-estimation/tf_pose/estimator.py", line 327, in __init__
    use_calibration=True,
TypeError: create_inference_graph() got an unexpected keyword argument 'use_calibration'

If someone had a hint to share with me as to which direction I could try and follow to make this work, that would be really appreciated.
Cheers

Hello @lweingart  checkout the reply by @SarangChougs  I've not tried it yet but doing the following seems working for him
" Open network_base.py which is in tf_pose directory, and replace the line where GlorotUniform is initialized with this line: _init_xavier = tf.initializers.glorot_uniform()"

Hello @djramakrishna,
I tried the change proposed by @SarangChougs, but it did not solve the problem.
The result is exactly the same as I had the first time.
Also, my error is not the same as you had at the beginning.
It apparently fails when trying to build the neural network.
Let me paste the full stacktrace, even if it's a bit long :-p
$ python3 run.py --model=mobilenet_thin --resize=432x368 --image=./images/p1.jpg
2021-03-25 17:33:20.937201: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.10.2
[2021-03-25 17:33:26,361] [TfPoseEstimator] [INFO] loading graph from /home/jetson/git/Realtime-Action-Recognition/src/githubs/tf-pose-estimation/models/graph/mobilenet_thin/graph_opt.pb(default size=432x368)
2021-03-25 17:33:26,361 INFO loading graph from /home/jetson/git/Realtime-Action-Recognition/src/githubs/tf-pose-estimation/models/graph/mobilenet_thin/graph_opt.pb(default size=432x368)
2021-03-25 17:33:27.055279: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-03-25 17:33:27.057905: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2021-03-25 17:33:27.091002: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] ARM64 does not support NUMA - returning NUMA node zero
2021-03-25 17:33:27.091256: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Found device 0 with properties:
pciBusID: 0000:00:00.0 name: Xavier computeCapability: 7.2
coreClock: 1.377GHz coreCount: 8 deviceMemorySize: 31.17GiB deviceMemoryBandwidth: 82.08GiB/s
2021-03-25 17:33:27.091425: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.10.2
2021-03-25 17:33:27.091665: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.10
2021-03-25 17:33:27.091812: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.10
2021-03-25 17:33:27.091971: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-03-25 17:33:27.095614: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-03-25 17:33:27.103971: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2021-03-25 17:33:27.109720: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.10
2021-03-25 17:33:27.109951: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-03-25 17:33:27.110290: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] ARM64 does not support NUMA - returning NUMA node zero
2021-03-25 17:33:27.110569: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] ARM64 does not support NUMA - returning NUMA node zero
2021-03-25 17:33:27.110687: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1888] Adding visible gpu devices: 0
2021-03-25 17:33:27.113394: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-03-25 17:33:27.113794: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] ARM64 does not support NUMA - returning NUMA node zero
2021-03-25 17:33:27.113968: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Found device 0 with properties:
pciBusID: 0000:00:00.0 name: Xavier computeCapability: 7.2
coreClock: 1.377GHz coreCount: 8 deviceMemorySize: 31.17GiB deviceMemoryBandwidth: 82.08GiB/s
2021-03-25 17:33:27.114105: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.10.2
2021-03-25 17:33:27.114146: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.10
2021-03-25 17:33:27.114230: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.10
2021-03-25 17:33:27.114270: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-03-25 17:33:27.114383: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-03-25 17:33:27.114470: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2021-03-25 17:33:27.114561: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.10
2021-03-25 17:33:27.114623: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-03-25 17:33:27.114837: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] ARM64 does not support NUMA - returning NUMA node zero
2021-03-25 17:33:27.115166: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] ARM64 does not support NUMA - returning NUMA node zero
2021-03-25 17:33:27.115246: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1888] Adding visible gpu devices: 0
2021-03-25 17:33:27.115786: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.10.2
2021-03-25 17:33:28.892477: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1287] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-03-25 17:33:28.892563: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1293]      0
2021-03-25 17:33:28.892596: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1306] 0:   N
2021-03-25 17:33:28.893111: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] ARM64 does not support NUMA - returning NUMA node zero
2021-03-25 17:33:28.894199: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] ARM64 does not support NUMA - returning NUMA node zero
2021-03-25 17:33:28.894474: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] ARM64 does not support NUMA - returning NUMA node zero
2021-03-25 17:33:28.894638: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1432] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 27238 MB memory) -> physical GPU (device: 0, name: Xavier, pci bus id: 0000:00:00.0, compute capability: 7.2)
MobilenetV1/Conv2d_0/weights
image
MobilenetV1/Conv2d_0/Conv2D
MobilenetV1/Conv2d_0/Conv2D_bn_offset
MobilenetV1/Conv2d_0/BatchNorm/FusedBatchNorm
MobilenetV1/Conv2d_0/Relu
MobilenetV1/Conv2d_1_depthwise/depthwise_weights
MobilenetV1/Conv2d_1_pointwise/weights
MobilenetV1/Conv2d_1_depthwise/depthwise
MobilenetV1/Conv2d_1_pointwise/Conv2D
MobilenetV1/Conv2d_1_pointwise/Conv2D_bn_offset
MobilenetV1/Conv2d_1_pointwise/BatchNorm/FusedBatchNorm
MobilenetV1/Conv2d_1_pointwise/Relu
MobilenetV1/Conv2d_2_depthwise/depthwise_weights
MobilenetV1/Conv2d_2_pointwise/weights
MobilenetV1/Conv2d_2_depthwise/depthwise
MobilenetV1/Conv2d_2_pointwise/Conv2D
MobilenetV1/Conv2d_2_pointwise/Conv2D_bn_offset
MobilenetV1/Conv2d_2_pointwise/BatchNorm/FusedBatchNorm
MobilenetV1/Conv2d_2_pointwise/Relu
MobilenetV1/Conv2d_3_depthwise/depthwise_weights
MobilenetV1/Conv2d_3_pointwise/weights
MobilenetV1/Conv2d_3_depthwise/depthwise
MobilenetV1/Conv2d_3_pointwise/Conv2D
MobilenetV1/Conv2d_3_pointwise/Conv2D_bn_offset
MobilenetV1/Conv2d_3_pointwise/BatchNorm/FusedBatchNorm
MobilenetV1/Conv2d_3_pointwise/Relu
MobilenetV1/Conv2d_4_depthwise/depthwise_weights
MobilenetV1/Conv2d_4_pointwise/weights
MobilenetV1/Conv2d_4_depthwise/depthwise
MobilenetV1/Conv2d_4_pointwise/Conv2D
MobilenetV1/Conv2d_4_pointwise/Conv2D_bn_offset
MobilenetV1/Conv2d_4_pointwise/BatchNorm/FusedBatchNorm
MobilenetV1/Conv2d_4_pointwise/Relu
MobilenetV1/Conv2d_5_depthwise/depthwise_weights
MobilenetV1/Conv2d_5_pointwise/weights
MobilenetV1/Conv2d_5_depthwise/depthwise
MobilenetV1/Conv2d_5_pointwise/Conv2D
MobilenetV1/Conv2d_5_pointwise/Conv2D_bn_offset
MobilenetV1/Conv2d_5_pointwise/BatchNorm/FusedBatchNorm
MobilenetV1/Conv2d_5_pointwise/Relu
MobilenetV1/Conv2d_6_depthwise/depthwise_weights
MobilenetV1/Conv2d_6_pointwise/weights
MobilenetV1/Conv2d_6_depthwise/depthwise
MobilenetV1/Conv2d_6_pointwise/Conv2D
MobilenetV1/Conv2d_6_pointwise/Conv2D_bn_offset
MobilenetV1/Conv2d_6_pointwise/BatchNorm/FusedBatchNorm
MobilenetV1/Conv2d_6_pointwise/Relu
MobilenetV1/Conv2d_7_depthwise/depthwise_weights
MobilenetV1/Conv2d_7_pointwise/weights
MobilenetV1/Conv2d_7_depthwise/depthwise
MobilenetV1/Conv2d_7_pointwise/Conv2D
MobilenetV1/Conv2d_7_pointwise/Conv2D_bn_offset
MobilenetV1/Conv2d_7_pointwise/BatchNorm/FusedBatchNorm
MobilenetV1/Conv2d_7_pointwise/Relu
MobilenetV1/Conv2d_8_depthwise/depthwise_weights
MobilenetV1/Conv2d_8_pointwise/weights
MobilenetV1/Conv2d_8_depthwise/depthwise
MobilenetV1/Conv2d_8_pointwise/Conv2D
MobilenetV1/Conv2d_8_pointwise/Conv2D_bn_offset
MobilenetV1/Conv2d_8_pointwise/BatchNorm/FusedBatchNorm
MobilenetV1/Conv2d_8_pointwise/Relu
MobilenetV1/Conv2d_9_depthwise/depthwise_weights
MobilenetV1/Conv2d_9_pointwise/weights
MobilenetV1/Conv2d_9_depthwise/depthwise
MobilenetV1/Conv2d_9_pointwise/Conv2D
MobilenetV1/Conv2d_9_pointwise/Conv2D_bn_offset
MobilenetV1/Conv2d_9_pointwise/BatchNorm/FusedBatchNorm
MobilenetV1/Conv2d_9_pointwise/Relu
MobilenetV1/Conv2d_10_depthwise/depthwise_weights
MobilenetV1/Conv2d_10_pointwise/weights
MobilenetV1/Conv2d_10_depthwise/depthwise
MobilenetV1/Conv2d_10_pointwise/Conv2D
MobilenetV1/Conv2d_10_pointwise/Conv2D_bn_offset
MobilenetV1/Conv2d_10_pointwise/BatchNorm/FusedBatchNorm
MobilenetV1/Conv2d_10_pointwise/Relu
MobilenetV1/Conv2d_11_depthwise/depthwise_weights
MobilenetV1/Conv2d_11_pointwise/weights
MobilenetV1/Conv2d_11_depthwise/depthwise
MobilenetV1/Conv2d_11_pointwise/Conv2D
MobilenetV1/Conv2d_11_pointwise/Conv2D_bn_offset
MobilenetV1/Conv2d_11_pointwise/BatchNorm/FusedBatchNorm
MobilenetV1/Conv2d_11_pointwise/Relu
Conv2d_3_pool
feat_concat/axis
feat_concat
Openpose/MConv_Stage1_L1_1_depthwise/depthwise_weights
Openpose/MConv_Stage1_L1_1_pointwise/weights
Openpose/MConv_Stage1_L1_1_depthwise/depthwise
Openpose/MConv_Stage1_L1_1_pointwise/Conv2D
Openpose/MConv_Stage1_L1_1_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage1_L1_1_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage1_L1_1_pointwise/Relu
Openpose/MConv_Stage1_L1_2_depthwise/depthwise_weights
Openpose/MConv_Stage1_L1_2_pointwise/weights
Openpose/MConv_Stage1_L1_2_depthwise/depthwise
Openpose/MConv_Stage1_L1_2_pointwise/Conv2D
Openpose/MConv_Stage1_L1_2_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage1_L1_2_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage1_L1_2_pointwise/Relu
Openpose/MConv_Stage1_L1_3_depthwise/depthwise_weights
Openpose/MConv_Stage1_L1_3_pointwise/weights
Openpose/MConv_Stage1_L1_3_depthwise/depthwise
Openpose/MConv_Stage1_L1_3_pointwise/Conv2D
Openpose/MConv_Stage1_L1_3_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage1_L1_3_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage1_L1_3_pointwise/Relu
Openpose/MConv_Stage1_L1_4_depthwise/depthwise_weights
Openpose/MConv_Stage1_L1_4_pointwise/weights
Openpose/MConv_Stage1_L1_4_depthwise/depthwise
Openpose/MConv_Stage1_L1_4_pointwise/Conv2D
Openpose/MConv_Stage1_L1_4_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage1_L1_4_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage1_L1_4_pointwise/Relu
Openpose/MConv_Stage1_L1_5_depthwise/depthwise_weights
Openpose/MConv_Stage1_L1_5_pointwise/weights
Openpose/MConv_Stage1_L1_5_depthwise/depthwise
Openpose/MConv_Stage1_L1_5_pointwise/Conv2D
Openpose/MConv_Stage1_L1_5_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage1_L1_5_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage1_L2_1_depthwise/depthwise_weights
Openpose/MConv_Stage1_L2_1_pointwise/weights
Openpose/MConv_Stage1_L2_1_depthwise/depthwise
Openpose/MConv_Stage1_L2_1_pointwise/Conv2D
Openpose/MConv_Stage1_L2_1_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage1_L2_1_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage1_L2_1_pointwise/Relu
Openpose/MConv_Stage1_L2_2_depthwise/depthwise_weights
Openpose/MConv_Stage1_L2_2_pointwise/weights
Openpose/MConv_Stage1_L2_2_depthwise/depthwise
Openpose/MConv_Stage1_L2_2_pointwise/Conv2D
Openpose/MConv_Stage1_L2_2_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage1_L2_2_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage1_L2_2_pointwise/Relu
Openpose/MConv_Stage1_L2_3_depthwise/depthwise_weights
Openpose/MConv_Stage1_L2_3_pointwise/weights
Openpose/MConv_Stage1_L2_3_depthwise/depthwise
Openpose/MConv_Stage1_L2_3_pointwise/Conv2D
Openpose/MConv_Stage1_L2_3_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage1_L2_3_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage1_L2_3_pointwise/Relu
Openpose/MConv_Stage1_L2_4_depthwise/depthwise_weights
Openpose/MConv_Stage1_L2_4_pointwise/weights
Openpose/MConv_Stage1_L2_4_depthwise/depthwise
Openpose/MConv_Stage1_L2_4_pointwise/Conv2D
Openpose/MConv_Stage1_L2_4_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage1_L2_4_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage1_L2_4_pointwise/Relu
Openpose/MConv_Stage1_L2_5_depthwise/depthwise_weights
Openpose/MConv_Stage1_L2_5_pointwise/weights
Openpose/MConv_Stage1_L2_5_depthwise/depthwise
Openpose/MConv_Stage1_L2_5_pointwise/Conv2D
Openpose/MConv_Stage1_L2_5_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage1_L2_5_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage2_concat/axis
Openpose/MConv_Stage2_concat
Openpose/MConv_Stage2_L1_1_depthwise/depthwise_weights
Openpose/MConv_Stage2_L1_1_pointwise/weights
Openpose/MConv_Stage2_L1_1_depthwise/depthwise
Openpose/MConv_Stage2_L1_1_pointwise/Conv2D
Openpose/MConv_Stage2_L1_1_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage2_L1_1_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage2_L1_1_pointwise/Relu
Openpose/MConv_Stage2_L1_2_depthwise/depthwise_weights
Openpose/MConv_Stage2_L1_2_pointwise/weights
Openpose/MConv_Stage2_L1_2_depthwise/depthwise
Openpose/MConv_Stage2_L1_2_pointwise/Conv2D
Openpose/MConv_Stage2_L1_2_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage2_L1_2_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage2_L1_2_pointwise/Relu
Openpose/MConv_Stage2_L1_3_depthwise/depthwise_weights
Openpose/MConv_Stage2_L1_3_pointwise/weights
Openpose/MConv_Stage2_L1_3_depthwise/depthwise
Openpose/MConv_Stage2_L1_3_pointwise/Conv2D
Openpose/MConv_Stage2_L1_3_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage2_L1_3_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage2_L1_3_pointwise/Relu
Openpose/MConv_Stage2_L1_4_depthwise/depthwise_weights
Openpose/MConv_Stage2_L1_4_pointwise/weights
Openpose/MConv_Stage2_L1_4_depthwise/depthwise
Openpose/MConv_Stage2_L1_4_pointwise/Conv2D
Openpose/MConv_Stage2_L1_4_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage2_L1_4_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage2_L1_4_pointwise/Relu
Openpose/MConv_Stage2_L1_5_depthwise/depthwise_weights
Openpose/MConv_Stage2_L1_5_pointwise/weights
Openpose/MConv_Stage2_L1_5_depthwise/depthwise
Openpose/MConv_Stage2_L1_5_pointwise/Conv2D
Openpose/MConv_Stage2_L1_5_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage2_L1_5_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage2_L2_1_depthwise/depthwise_weights
Openpose/MConv_Stage2_L2_1_pointwise/weights
Openpose/MConv_Stage2_L2_1_depthwise/depthwise
Openpose/MConv_Stage2_L2_1_pointwise/Conv2D
Openpose/MConv_Stage2_L2_1_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage2_L2_1_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage2_L2_1_pointwise/Relu
Openpose/MConv_Stage2_L2_2_depthwise/depthwise_weights
Openpose/MConv_Stage2_L2_2_pointwise/weights
Openpose/MConv_Stage2_L2_2_depthwise/depthwise
Openpose/MConv_Stage2_L2_2_pointwise/Conv2D
Openpose/MConv_Stage2_L2_2_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage2_L2_2_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage2_L2_2_pointwise/Relu
Openpose/MConv_Stage2_L2_3_depthwise/depthwise_weights
Openpose/MConv_Stage2_L2_3_pointwise/weights
Openpose/MConv_Stage2_L2_3_depthwise/depthwise
Openpose/MConv_Stage2_L2_3_pointwise/Conv2D
Openpose/MConv_Stage2_L2_3_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage2_L2_3_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage2_L2_3_pointwise/Relu
Openpose/MConv_Stage2_L2_4_depthwise/depthwise_weights
Openpose/MConv_Stage2_L2_4_pointwise/weights
Openpose/MConv_Stage2_L2_4_depthwise/depthwise
Openpose/MConv_Stage2_L2_4_pointwise/Conv2D
Openpose/MConv_Stage2_L2_4_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage2_L2_4_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage2_L2_4_pointwise/Relu
Openpose/MConv_Stage2_L2_5_depthwise/depthwise_weights
Openpose/MConv_Stage2_L2_5_pointwise/weights
Openpose/MConv_Stage2_L2_5_depthwise/depthwise
Openpose/MConv_Stage2_L2_5_pointwise/Conv2D
Openpose/MConv_Stage2_L2_5_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage2_L2_5_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage3_concat/axis
Openpose/MConv_Stage3_concat
Openpose/MConv_Stage3_L1_1_depthwise/depthwise_weights
Openpose/MConv_Stage3_L1_1_pointwise/weights
Openpose/MConv_Stage3_L1_1_depthwise/depthwise
Openpose/MConv_Stage3_L1_1_pointwise/Conv2D
Openpose/MConv_Stage3_L1_1_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage3_L1_1_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage3_L1_1_pointwise/Relu
Openpose/MConv_Stage3_L1_2_depthwise/depthwise_weights
Openpose/MConv_Stage3_L1_2_pointwise/weights
Openpose/MConv_Stage3_L1_2_depthwise/depthwise
Openpose/MConv_Stage3_L1_2_pointwise/Conv2D
Openpose/MConv_Stage3_L1_2_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage3_L1_2_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage3_L1_2_pointwise/Relu
Openpose/MConv_Stage3_L1_3_depthwise/depthwise_weights
Openpose/MConv_Stage3_L1_3_pointwise/weights
Openpose/MConv_Stage3_L1_3_depthwise/depthwise
Openpose/MConv_Stage3_L1_3_pointwise/Conv2D
Openpose/MConv_Stage3_L1_3_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage3_L1_3_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage3_L1_3_pointwise/Relu
Openpose/MConv_Stage3_L1_4_depthwise/depthwise_weights
Openpose/MConv_Stage3_L1_4_pointwise/weights
Openpose/MConv_Stage3_L1_4_depthwise/depthwise
Openpose/MConv_Stage3_L1_4_pointwise/Conv2D
Openpose/MConv_Stage3_L1_4_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage3_L1_4_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage3_L1_4_pointwise/Relu
Openpose/MConv_Stage3_L1_5_depthwise/depthwise_weights
Openpose/MConv_Stage3_L1_5_pointwise/weights
Openpose/MConv_Stage3_L1_5_depthwise/depthwise
Openpose/MConv_Stage3_L1_5_pointwise/Conv2D
Openpose/MConv_Stage3_L1_5_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage3_L1_5_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage3_L2_1_depthwise/depthwise_weights
Openpose/MConv_Stage3_L2_1_pointwise/weights
Openpose/MConv_Stage3_L2_1_depthwise/depthwise
Openpose/MConv_Stage3_L2_1_pointwise/Conv2D
Openpose/MConv_Stage3_L2_1_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage3_L2_1_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage3_L2_1_pointwise/Relu
Openpose/MConv_Stage3_L2_2_depthwise/depthwise_weights
Openpose/MConv_Stage3_L2_2_pointwise/weights
Openpose/MConv_Stage3_L2_2_depthwise/depthwise
Openpose/MConv_Stage3_L2_2_pointwise/Conv2D
Openpose/MConv_Stage3_L2_2_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage3_L2_2_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage3_L2_2_pointwise/Relu
Openpose/MConv_Stage3_L2_3_depthwise/depthwise_weights
Openpose/MConv_Stage3_L2_3_pointwise/weights
Openpose/MConv_Stage3_L2_3_depthwise/depthwise
Openpose/MConv_Stage3_L2_3_pointwise/Conv2D
Openpose/MConv_Stage3_L2_3_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage3_L2_3_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage3_L2_3_pointwise/Relu
Openpose/MConv_Stage3_L2_4_depthwise/depthwise_weights
Openpose/MConv_Stage3_L2_4_pointwise/weights
Openpose/MConv_Stage3_L2_4_depthwise/depthwise
Openpose/MConv_Stage3_L2_4_pointwise/Conv2D
Openpose/MConv_Stage3_L2_4_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage3_L2_4_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage3_L2_4_pointwise/Relu
Openpose/MConv_Stage3_L2_5_depthwise/depthwise_weights
Openpose/MConv_Stage3_L2_5_pointwise/weights
Openpose/MConv_Stage3_L2_5_depthwise/depthwise
Openpose/MConv_Stage3_L2_5_pointwise/Conv2D
Openpose/MConv_Stage3_L2_5_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage3_L2_5_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage4_concat/axis
Openpose/MConv_Stage4_concat
Openpose/MConv_Stage4_L1_1_depthwise/depthwise_weights
Openpose/MConv_Stage4_L1_1_pointwise/weights
Openpose/MConv_Stage4_L1_1_depthwise/depthwise
Openpose/MConv_Stage4_L1_1_pointwise/Conv2D
Openpose/MConv_Stage4_L1_1_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage4_L1_1_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage4_L1_1_pointwise/Relu
Openpose/MConv_Stage4_L1_2_depthwise/depthwise_weights
Openpose/MConv_Stage4_L1_2_pointwise/weights
Openpose/MConv_Stage4_L1_2_depthwise/depthwise
Openpose/MConv_Stage4_L1_2_pointwise/Conv2D
Openpose/MConv_Stage4_L1_2_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage4_L1_2_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage4_L1_2_pointwise/Relu
Openpose/MConv_Stage4_L1_3_depthwise/depthwise_weights
Openpose/MConv_Stage4_L1_3_pointwise/weights
Openpose/MConv_Stage4_L1_3_depthwise/depthwise
Openpose/MConv_Stage4_L1_3_pointwise/Conv2D
Openpose/MConv_Stage4_L1_3_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage4_L1_3_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage4_L1_3_pointwise/Relu
Openpose/MConv_Stage4_L1_4_depthwise/depthwise_weights
Openpose/MConv_Stage4_L1_4_pointwise/weights
Openpose/MConv_Stage4_L1_4_depthwise/depthwise
Openpose/MConv_Stage4_L1_4_pointwise/Conv2D
Openpose/MConv_Stage4_L1_4_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage4_L1_4_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage4_L1_4_pointwise/Relu
Openpose/MConv_Stage4_L1_5_depthwise/depthwise_weights
Openpose/MConv_Stage4_L1_5_pointwise/weights
Openpose/MConv_Stage4_L1_5_depthwise/depthwise
Openpose/MConv_Stage4_L1_5_pointwise/Conv2D
Openpose/MConv_Stage4_L1_5_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage4_L1_5_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage4_L2_1_depthwise/depthwise_weights
Openpose/MConv_Stage4_L2_1_pointwise/weights
Openpose/MConv_Stage4_L2_1_depthwise/depthwise
Openpose/MConv_Stage4_L2_1_pointwise/Conv2D
Openpose/MConv_Stage4_L2_1_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage4_L2_1_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage4_L2_1_pointwise/Relu
Openpose/MConv_Stage4_L2_2_depthwise/depthwise_weights
Openpose/MConv_Stage4_L2_2_pointwise/weights
Openpose/MConv_Stage4_L2_2_depthwise/depthwise
Openpose/MConv_Stage4_L2_2_pointwise/Conv2D
Openpose/MConv_Stage4_L2_2_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage4_L2_2_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage4_L2_2_pointwise/Relu
Openpose/MConv_Stage4_L2_3_depthwise/depthwise_weights
Openpose/MConv_Stage4_L2_3_pointwise/weights
Openpose/MConv_Stage4_L2_3_depthwise/depthwise
Openpose/MConv_Stage4_L2_3_pointwise/Conv2D
Openpose/MConv_Stage4_L2_3_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage4_L2_3_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage4_L2_3_pointwise/Relu
Openpose/MConv_Stage4_L2_4_depthwise/depthwise_weights
Openpose/MConv_Stage4_L2_4_pointwise/weights
Openpose/MConv_Stage4_L2_4_depthwise/depthwise
Openpose/MConv_Stage4_L2_4_pointwise/Conv2D
Openpose/MConv_Stage4_L2_4_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage4_L2_4_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage4_L2_4_pointwise/Relu
Openpose/MConv_Stage4_L2_5_depthwise/depthwise_weights
Openpose/MConv_Stage4_L2_5_pointwise/weights
Openpose/MConv_Stage4_L2_5_depthwise/depthwise
Openpose/MConv_Stage4_L2_5_pointwise/Conv2D
Openpose/MConv_Stage4_L2_5_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage4_L2_5_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage5_concat/axis
Openpose/MConv_Stage5_concat
Openpose/MConv_Stage5_L1_1_depthwise/depthwise_weights
Openpose/MConv_Stage5_L1_1_pointwise/weights
Openpose/MConv_Stage5_L1_1_depthwise/depthwise
Openpose/MConv_Stage5_L1_1_pointwise/Conv2D
Openpose/MConv_Stage5_L1_1_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage5_L1_1_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage5_L1_1_pointwise/Relu
Openpose/MConv_Stage5_L1_2_depthwise/depthwise_weights
Openpose/MConv_Stage5_L1_2_pointwise/weights
Openpose/MConv_Stage5_L1_2_depthwise/depthwise
Openpose/MConv_Stage5_L1_2_pointwise/Conv2D
Openpose/MConv_Stage5_L1_2_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage5_L1_2_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage5_L1_2_pointwise/Relu
Openpose/MConv_Stage5_L1_3_depthwise/depthwise_weights
Openpose/MConv_Stage5_L1_3_pointwise/weights
Openpose/MConv_Stage5_L1_3_depthwise/depthwise
Openpose/MConv_Stage5_L1_3_pointwise/Conv2D
Openpose/MConv_Stage5_L1_3_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage5_L1_3_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage5_L1_3_pointwise/Relu
Openpose/MConv_Stage5_L1_4_depthwise/depthwise_weights
Openpose/MConv_Stage5_L1_4_pointwise/weights
Openpose/MConv_Stage5_L1_4_depthwise/depthwise
Openpose/MConv_Stage5_L1_4_pointwise/Conv2D
Openpose/MConv_Stage5_L1_4_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage5_L1_4_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage5_L1_4_pointwise/Relu
Openpose/MConv_Stage5_L1_5_depthwise/depthwise_weights
Openpose/MConv_Stage5_L1_5_pointwise/weights
Openpose/MConv_Stage5_L1_5_depthwise/depthwise
Openpose/MConv_Stage5_L1_5_pointwise/Conv2D
Openpose/MConv_Stage5_L1_5_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage5_L1_5_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage5_L2_1_depthwise/depthwise_weights
Openpose/MConv_Stage5_L2_1_pointwise/weights
Openpose/MConv_Stage5_L2_1_depthwise/depthwise
Openpose/MConv_Stage5_L2_1_pointwise/Conv2D
Openpose/MConv_Stage5_L2_1_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage5_L2_1_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage5_L2_1_pointwise/Relu
Openpose/MConv_Stage5_L2_2_depthwise/depthwise_weights
Openpose/MConv_Stage5_L2_2_pointwise/weights
Openpose/MConv_Stage5_L2_2_depthwise/depthwise
Openpose/MConv_Stage5_L2_2_pointwise/Conv2D
Openpose/MConv_Stage5_L2_2_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage5_L2_2_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage5_L2_2_pointwise/Relu
Openpose/MConv_Stage5_L2_3_depthwise/depthwise_weights
Openpose/MConv_Stage5_L2_3_pointwise/weights
Openpose/MConv_Stage5_L2_3_depthwise/depthwise
Openpose/MConv_Stage5_L2_3_pointwise/Conv2D
Openpose/MConv_Stage5_L2_3_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage5_L2_3_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage5_L2_3_pointwise/Relu
Openpose/MConv_Stage5_L2_4_depthwise/depthwise_weights
Openpose/MConv_Stage5_L2_4_pointwise/weights
Openpose/MConv_Stage5_L2_4_depthwise/depthwise
Openpose/MConv_Stage5_L2_4_pointwise/Conv2D
Openpose/MConv_Stage5_L2_4_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage5_L2_4_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage5_L2_4_pointwise/Relu
Openpose/MConv_Stage5_L2_5_depthwise/depthwise_weights
Openpose/MConv_Stage5_L2_5_pointwise/weights
Openpose/MConv_Stage5_L2_5_depthwise/depthwise
Openpose/MConv_Stage5_L2_5_pointwise/Conv2D
Openpose/MConv_Stage5_L2_5_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage5_L2_5_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage6_concat/axis
Openpose/MConv_Stage6_concat
Openpose/MConv_Stage6_L1_1_depthwise/depthwise_weights
Openpose/MConv_Stage6_L1_1_pointwise/weights
Openpose/MConv_Stage6_L1_1_depthwise/depthwise
Openpose/MConv_Stage6_L1_1_pointwise/Conv2D
Openpose/MConv_Stage6_L1_1_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage6_L1_1_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage6_L1_1_pointwise/Relu
Openpose/MConv_Stage6_L1_2_depthwise/depthwise_weights
Openpose/MConv_Stage6_L1_2_pointwise/weights
Openpose/MConv_Stage6_L1_2_depthwise/depthwise
Openpose/MConv_Stage6_L1_2_pointwise/Conv2D
Openpose/MConv_Stage6_L1_2_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage6_L1_2_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage6_L1_2_pointwise/Relu
Openpose/MConv_Stage6_L1_3_depthwise/depthwise_weights
Openpose/MConv_Stage6_L1_3_pointwise/weights
Openpose/MConv_Stage6_L1_3_depthwise/depthwise
Openpose/MConv_Stage6_L1_3_pointwise/Conv2D
Openpose/MConv_Stage6_L1_3_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage6_L1_3_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage6_L1_3_pointwise/Relu
Openpose/MConv_Stage6_L1_4_depthwise/depthwise_weights
Openpose/MConv_Stage6_L1_4_pointwise/weights
Openpose/MConv_Stage6_L1_4_depthwise/depthwise
Openpose/MConv_Stage6_L1_4_pointwise/Conv2D
Openpose/MConv_Stage6_L1_4_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage6_L1_4_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage6_L1_4_pointwise/Relu
Openpose/MConv_Stage6_L1_5_depthwise/depthwise_weights
Openpose/MConv_Stage6_L1_5_pointwise/weights
Openpose/MConv_Stage6_L1_5_depthwise/depthwise
Openpose/MConv_Stage6_L1_5_pointwise/Conv2D
Openpose/MConv_Stage6_L1_5_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage6_L1_5_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage6_L2_1_depthwise/depthwise_weights
Openpose/MConv_Stage6_L2_1_pointwise/weights
Openpose/MConv_Stage6_L2_1_depthwise/depthwise
Openpose/MConv_Stage6_L2_1_pointwise/Conv2D
Openpose/MConv_Stage6_L2_1_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage6_L2_1_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage6_L2_1_pointwise/Relu
Openpose/MConv_Stage6_L2_2_depthwise/depthwise_weights
Openpose/MConv_Stage6_L2_2_pointwise/weights
Openpose/MConv_Stage6_L2_2_depthwise/depthwise
Openpose/MConv_Stage6_L2_2_pointwise/Conv2D
Openpose/MConv_Stage6_L2_2_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage6_L2_2_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage6_L2_2_pointwise/Relu
Openpose/MConv_Stage6_L2_3_depthwise/depthwise_weights
Openpose/MConv_Stage6_L2_3_pointwise/weights
Openpose/MConv_Stage6_L2_3_depthwise/depthwise
Openpose/MConv_Stage6_L2_3_pointwise/Conv2D
Openpose/MConv_Stage6_L2_3_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage6_L2_3_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage6_L2_3_pointwise/Relu
Openpose/MConv_Stage6_L2_4_depthwise/depthwise_weights
Openpose/MConv_Stage6_L2_4_pointwise/weights
Openpose/MConv_Stage6_L2_4_depthwise/depthwise
Openpose/MConv_Stage6_L2_4_pointwise/Conv2D
Openpose/MConv_Stage6_L2_4_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage6_L2_4_pointwise/BatchNorm/FusedBatchNorm
Openpose/MConv_Stage6_L2_4_pointwise/Relu
Openpose/MConv_Stage6_L2_5_depthwise/depthwise_weights
Openpose/MConv_Stage6_L2_5_pointwise/weights
Openpose/MConv_Stage6_L2_5_depthwise/depthwise
Openpose/MConv_Stage6_L2_5_pointwise/Conv2D
Openpose/MConv_Stage6_L2_5_pointwise/Conv2D_bn_offset
Openpose/MConv_Stage6_L2_5_pointwise/BatchNorm/FusedBatchNorm
Openpose/concat_stage7/axis
Openpose/concat_stage7
Traceback (most recent call last):
  File "run.py", line 39, in <module>
    e = TfPoseEstimator(get_graph_path(args.model), target_size=(w, h))
  File "/home/jetson/git/Realtime-Action-Recognition/src/githubs/tf-pose-estimation/tf_pose/estimator.py", line 337, in __init__
    self.tensor_image = self.graph.get_tensor_by_name('TfPoseEstimator/image:0')
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py", line 3902, in get_tensor_by_name
    return self.as_graph_element(name, allow_tensor=True, allow_operation=False)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py", line 3726, in as_graph_element
    return self._as_graph_element_locked(obj, allow_tensor, allow_operation)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py", line 3768, in _as_graph_element_locked
    "graph." % (repr(name), repr(op_name)))
KeyError: "The name 'TfPoseEstimator/image:0' refers to a Tensor which does not exist. The operation, 'TfPoseEstimator/image', does not exist in the graph."

I have no idea how to fix this unfortunately.
Did you get better results (if you had time to give it a try) ?
Cheers

Hey, @lweingart it seems the network graph doesn't contain or support the tensor that it's looking for, that's just my wild guess from your output. I will try working on it, and get back to you if I've found a work around!

I have the same problem.@Iweingart

@WXY-kt  @lweingart  i had the same issue and resolved.
In estimatory.py under the line that imports tensorflow add the following line
 tf.compat.v1.disable_eager_execution()
this sort out my issue.

I also resolged with @mithelan 's solution!!!
Thanks!!


Add 256 color options

Thanks a lot! The background colors are wrong (should be tput setab insteaf of tput setaf). I've fixed it and committed to the repo.


🐛 Disable nestif linter

What this PR does / why we need it:
Now linter complains if we add more items to customizeDeployment function, so it's easier to temporarily disable it for now until we find a better way to reorganize the code.
Which issue(s) this PR fixes (optional, in fixes #<issue number>(, fixes #<issue_number>, ...) format, will close the issue(s) when PR gets merged):
Fixes #

/lgtm

This PR is not superseded by https://github.com/kubernetes-sigs/cluster-api-operator/pull/175 where I had to comment out nestif in order to make golangci-lint happy.


[Failing Test]: XVR test flaky build python SDK container imager: "/target/launcher/linux_amd64/boot" not found

What happened?
Saw this a couple of times before.
e.g. https://ci-beam.apache.org/job/beam_PostCommit_XVR_Flink_PR/299/consoleFull
12:53:21 #2 [internal] load .dockerignore
12:53:21 #2 transferring context: 2B done
12:53:21 #2 DONE 0.5s
12:53:21
12:53:21 #3 [internal] load metadata for docker.io/library/python:3.8-bullseye
12:53:21 #3 DONE 0.5s
12:53:21
12:53:21 #4 [beam 1/5] FROM docker.io/library/python:3.8-bullseye@sha256:5598a0361e5a1e6fc0bcf942208ac47bf17b1865ea7767c2f1e6d572f7917736
12:53:21 #4 CACHED
12:53:21
12:53:21 #5 [internal] load build context
12:53:21 #5 transferring context: 2.49MB 0.2s done
12:53:21 #5 DONE 0.3s
12:53:21
12:53:21 #6 [beam 3/5] COPY target/apache-beam.tar.gz /opt/apache/beam/tars/
12:53:21 #6 CACHED
12:53:21
12:53:21 #7 [beam 4/5] COPY target/launcher/linux_amd64/boot target/LICENSE target/NOTICE target/LICENSE.python /opt/apache/beam/
12:53:21 #7 ERROR: "/target/launcher/linux_amd64/boot" not found: not found
12:53:21
12:53:21 #8 [beam 2/5] COPY target/base_image_requirements.txt /tmp/base_image_requirements.txt
12:53:21 #8 CANCELED
12:53:21 ------
12:53:21  > [beam 4/5] COPY target/launcher/linux_amd64/boot target/LICENSE target/NOTICE target/LICENSE.python /opt/apache/beam/:
12:53:21 ------
12:53:21 ERROR: failed to solve: failed to compute cache key: "/target/launcher/linux_amd64/boot" not found: not found

Issue Failure
Failure: Test is flaky
Issue Priority
Priority: 2 (backlog / disabled test but we think the product is healthy)
Issue Components

[X] Component: Python SDK
[ ] Component: Java SDK
[ ] Component: Go SDK
[ ] Component: Typescript SDK
[ ] Component: IO connector
[ ] Component: Beam YAML
[ ] Component: Beam examples
[ ] Component: Beam playground
[ ] Component: Beam katas
[ ] Component: Website
[ ] Component: Spark Runner
[ ] Component: Flink Runner
[ ] Component: Samza Runner
[ ] Component: Twister2 Runner
[ ] Component: Hazelcast Jet Runner
[ ] Component: Google Cloud Dataflow Runner

The failed test has
Task :sdks:python:container:py38:copyLauncherDependencies NO-SOURCE

which means this copy job had no source, i.e. :sdks:python:container:goBuild not producing the launcher or it gets immediately deleted?

This is likely a gradle bug, see https://github.com/apache/beam/pull/23785#issuecomment-1789324871
It is now flaky on both Jenkins and GitHub Actions. It affects a couple of XVR jobs Flink,Spark,etc
A reproduce: https://ci-beam.apache.org/job/beam_PostCommit_XVR_Flink_PR/324/console

At gradle configuration time, configurations.pythonHarnessLauncher is indeed set:

13:04:47 > Configure project :sdks:python:container:py38
13:04:47 print----- /home/jenkins/jenkins-slave/workspace/beam_PostCommit_XVR_Flink_PR/src/sdks/python/container/build/target/launcher
13:04:48 System Go installation: /snap/bin/go is go version go1.16.15 linux/amd64; Preparing to use /home/jenkins/go/bin/go1.21.3
13:04:48 go1.21.3: already downloaded in /home/jenkins/sdk/go1.21.3
13:04:48 GOCMD=/home/jenkins/go/bin/go1.21.3
13:04:49 print+++++ /home/jenkins/jenkins-slave/workspace/beam_PostCommit_XVR_Flink_PR/src/sdks/python/container/build/target/launcher

Then, :sdks:python:container:goBuild indeed produced the binary:

13:05:39 > Task :sdks:python:container:goBuild
13:05:39 print:::::  /home/jenkins/jenkins-slave/workspace/beam_PostCommit_XVR_Flink_PR/src/sdks/python/container/build/target/launcher/linux_amd64/boot name:::: boot

However, sdks:python:container:py38:copyLauncherDependencies skipped as NO-SOURCE
13:05:39 > Task :sdks:python:container:py38:copyLauncherDependencies NO-SOURCE

which caused binary not copied into the folder for docker prepare

Possibly related to https://github.com/gradle/gradle/issues/24368


Improve File picker

Ability to select multiple files
Remember last folder opened
Default to obfuscator working directory instead of JRE location

I fixed the working directory in a recent commit, it will feature in the next release. Other ideas are good, will see about them. I think number 1 might be a limitation of Swings file picker though.

As to 1 you might want to look at JFileChooser#setMultiSelectionEnabled


Command Line Configuration

I'd love some command line (or config file) configuration to be able to done, at least for the API key and event ID, and preferably scoring system IP.

Arguments:
-skip-config : Skip Dialog asking for config file
-event-key=<toa_event_key> : TOA Event Key
-api-key=<toa_api_key> : TOA API Key
-scoring-ip=<scoring_ip> : IP address for scoring system
-scoring-event=<first_event_key> : Event Key from FIRST scoring system
-test-toa : attempt connection to TOA with given credentials
-test-first : attempt connection to Scoring System with given data
-load-first : attempt to load event from FIRST provided the IP was correct

I can probably take on this feature over the next few days (I really want this feature).  It looks like the suggested arguments were specific to the old datasync tool and I am not sure if they are all relevant here.  Also, since you are now using firebase credentials rather than API keys I am not sure the best way to handle that.  If anyone has an idea how to handle this problem I would gladly hear it.  If there is no better idea I'll just have -username and -password flags, but that feels wrong for some reason.
Flags I am thinking:

-config=<config.json>: provide a config file that would have all these flags as fields
-event-key=<toa_event_key>: the TOA Event Key
-scoring-ip=<scoring_ip>: IP address of the score system
-scoring-event=<first_event_key>: Event Key from the FIRST scoring system
-username=<username>: TOA username
-password=<password>: TOA password

If anyone disputes any of these flags or would like additional flags let me know.

Now that it is web-based this should either be closed or changed in scope to be an uploaded config file instead of command line arguments.  Unless you want to pass them in as a query string which seems not very useful to me personally, and I refuse to pass a password as a query string since that is human readable to anyone watching network traffic.


Add option to set cwd in Liftoff constructor

This way the appropriate cwd can be set when all register hooks get hooked in. This is an issue in, for example, gulp when using ts-node in a subdirectory with --cwd. The cwd passed is not respected by the require hooks included by liftoff since the cwd is only set during launch (so it is not set when the require hook is loaded).

The require hooks are loaded with node's require which doesn't take into account a cwd parameter and instead use process.cwd().  Liftoff should not be responsible for changing that (although, gulp decides to do that in its CLI).  @tkellen do you agree?

So the correct fix would instead be, in gulp, before it's construction of Liftoff, using process.chdir?

@weswigham that would be the only place where we'd consider it.  If you open an issue on gulp-cli, we can discuss over there.  It would effect this chunk of code: https://github.com/gulpjs/gulp-cli/blob/master/index.js#L131-L137
Closing this.

Agreed @phated! If we wind up thinking this is a best practice, we should consider updating hacker to  do it as well.


Figure 1 description is not correct in walrus.pdf

Description
Figure 1 description is not correct in walrus.pdf, the description does not match Figure 1.
Now
Figure 1: Encoding a Blob in one dimension. First the blob is split into 2f + 1  systematic slivers and then a further f  repair slivers are encoded.
Should Be:
Figure 1: Encoding a Blob in one dimension. First the blob is split into f + 1 systematic slivers and then a further 2f repair slivers are encoded.

Code of Conduct

[X] I agree to follow this project's Code of Conduct.

Thanks for creating this issue, I believe you are right. We'll fix this and update the whitepaper.


CONTRIBUTING.rst wrong CI link

General

pyfar version: 0.5.1

Description
In CONTRIBUTING.rst under Pull Request Guidelines it links to travis CI instead of circle CI. I am guessing this is wrong as it geves a 404 page error.

I think that is already fixed in develop

As far as I can see, not on the develop currently online.

Oh, yes sorry. Its here #407

Ah yes, I didn't see that one.


Minor fixes

Remove unused field from Forwarder struct
Only forward messages when to is_bridged flag on a room is set to true
Set is_bridged flag when the room is bridged after it was unbridged before

Coverage increased (+0.06%) to 98.382% when pulling 4c77c143783a029616a31b421182f0152aaf96ff on minor-fixes into 18c4326ffaee07fe3ebd5a39acd7346124c665d5 on master.


error in chapter 8

@avigad  and @leodemoura, we have at least one error in the tutorial. Could you check?
ERROR executing 08_Building_Theories_and_Proofs.org.27.lean, for in_code_block block starting at 1007, produced output:
08_Building_Theories_and_Proofs.org.27.lean:17:31: error: unknown identifier 'iff.mp''
mod_refl : ∀ (m a : ℤ), mod_equiv m a a
mod_symm : ∀ (m a b : ℤ), mod_equiv m a b → mod_equiv m b a
mod_trans : ∀ (m a b c : ℤ), mod_equiv m a b → mod_equiv m b c → mod_equiv m a c

This is fixed in my pull request:
https://github.com/leanprover/tutorial/pull/122/files
I tested everything, so it should be o.k.

Thanks. It's just merged.


raft: fix deadlock during PreVote migration process

Fixes https://github.com/coreos/etcd/issues/8501

/cc @irfansharif

Please see https://github.com/coreos/etcd/issues/8501#issuecomment-328223679.

Codecov Report

:exclamation: No coverage uploaded for pull request base (master@80aa810). Click here to learn what that means.
The diff coverage is 100%.

@@           Coverage Diff            @@
##             master   #8525   +/-   ##
========================================
  Coverage          ?   65.9%
========================================
  Files             ?     360
  Lines             ?   29527
  Branches          ?       0
========================================
  Hits              ?   19459
  Misses            ?    8399
  Partials          ?    1669

Impacted Files
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raft/raft.go
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withParentSize no longer delays rendering until size is known

Previously, withParentSize would only render its children when the size was known. However, since commit https://github.com/hshoff/vx/commit/b05a17fbc92a698b036c64886b8679ee2475be0e, the children are initially rendered without size. This breaks components that expect parentWidth and parentHeight to be available.
The problem is that the state is initialized with undefined, while the render method checks for null.

@dson thanks for checking out vx and reporting this issue + triaging, I will post a fix asap 👍


Create a typescript kafka template

TODO:

[x] Initiate Kafka connection
[x] Build constructors

[x] Producer
[x] Consumer

[x] Create a RESTful API for health checks

[x] Create an ExpressJS server that runs alongside Kafka
[x] Create endpoints:

[x] /heath --> are the internal servers up?
[ ] /topicHealth --> how many topics are available.... can this be done by consumption vs production?
[ ] /info --> describe the service?

Leaving the rest as tech dept. There are higher priorities to get done.


[dvm] fix for dep loading to work again in the new location

Ths unbreaks (to an extent) project dep loading, like 'dvm load oc_erchef sqerl' and 'dvm unload omnibus private-chef-cookbooks'

:+1: This fixed the problem I was having.


[EN] Feedback for: /fundamentals/getting-started/your-first-multi-screen-site/content.html

Positive feedback.
thanks a lot for this resources guys. Really appreciate the language level and the videos are useful.  As a marketer and designer coming into front-end dev, I am trying to achieve blazingly fast google page speed insight scores on the projects i am developing because users demand it. i am 100% self-taught and these videos arent too code-jargony - T H A N K S.  i realise now my development environment sucks.  im editing on brackets on my mac, then uploading my files via ftp and testing. this last process is overly time consuming so I really appreciate sharing some insights around setting up a development environment, workflow and tools. i can see with automation its faster and things like concenation (or whatever that word is for binding files together) and creating unique version names for css uploads allows faster revisions due to avoiding cahcing issue and in the end a way better result for web projects.
these tips and tricks here are awesome.  its gonna take me a while to get my head around grunt and the other one with the coke bottle logo, but hopefully ill figure it out.

glad you like!


Operator scorecard test fails with timeout when docker.io/busybox:1.33.0 pull limit reached for the day

Bug Description
Operator scorecard test fails with timeout error
Version and Command Invocation
preflight -v
preflight version 0.0.0 <commit: 333adaf7672ba41988bd9ad75dc6da2cba6974b2>
Steps to Reproduce:
(How can we reproduce this?)

preflight check operator quay.io/opdev/simple-demo-operator-bundle:v0.0.2

Expected Result
Scorecard test should pass
Actual Result
[vagrant@fedora34 preflight]$ export PFLT_INDEXIMAGE=quay.io/vmulaje/simple-demo-index:0.1.1 [vagrant@fedora34 preflight]$ export PFLT_LOGLEVEL=trace [vagrant@fedora34 preflight]$ preflight check operator quay.io/opdev/simple-demo-operator-bundle:v0.0.2 time="2021-10-01T10:05:30Z" level=info msg="config file not found, proceeding without it" time="2021-10-01T10:05:30Z" level=info msg="certification library version 0.0.0 <commit: 333adaf7672ba41988bd9ad75dc6da2cba6974b2>" time="2021-10-01T10:05:30Z" level=info msg="target image: quay.io/opdev/simple-demo-operator-bundle:v0.0.2" time="2021-10-01T10:05:30Z" level=info msg="pulling image from target registry" time="2021-10-01T10:05:32Z" level=debug msg="temporary directory is /tmp/preflight-1614532185" time="2021-10-01T10:05:32Z" level=debug msg="exporting and flattening image" time="2021-10-01T10:05:32Z" level=debug msg="extracting container filesystem to /tmp/preflight-1614532185/fs" time="2021-10-01T10:05:32Z" level=debug msg="writing container filesystem to output dir/tmp/preflight-1614532185/fs" time="2021-10-01T10:05:35Z" level=info msg="executing checks" time="2021-10-01T10:05:35Z" level=info msg="running check: ValidateOperatorBundle" time="2021-10-01T10:05:35Z" level=debug msg="Command being run: [operator-sdk bundle validate -b none --output json-alpha1 --select-optional name=community --select-optional name=operatorhub --verbose /tmp/preflight-1614532185/fs]" time="2021-10-01T10:05:36Z" level=warning msg="Warning: Value : (simple-demo-operator.v0.0.2) csv.Spec.minKubeVersion is not informed. It is recommended you provide this information. Otherwise, it would mean that your operator project can be distributed and installed in any cluster version available, which is not necessarily the case for all projects." time="2021-10-01T10:05:36Z" level=info msg="check completed: ValidateOperatorBundle" result=PASSED time="2021-10-01T10:05:36Z" level=info msg="running check: OperatorPackageNameIsUnique" time="2021-10-01T10:05:36Z" level=trace msg="reading annotations file from the bundle" time="2021-10-01T10:05:36Z" level=debug msg="mounted directory is /tmp/preflight-1614532185/fs" time="2021-10-01T10:05:36Z" level=trace msg="searching for package key (operators.operatorframework.io.bundle.package.v1) in bundle" time="2021-10-01T10:05:36Z" level=trace msg="bundle data: map[operators.operatorframework.io.bundle.channel.default.v1:stable operators.operatorframework.io.bundle.channels.v1:stable operators.operatorframework.io.bundle.manifests.v1:manifests/ operators.operatorframework.io.bundle.mediatype.v1:registry+v1 operators.operatorframework.io.bundle.metadata.v1:metadata/ operators.operatorframework.io.bundle.package.v1:simple-demo-operator operators.operatorframework.io.metrics.builder:operator-sdk-v1.11.0+git operators.operatorframework.io.metrics.mediatype.v1:metrics+v1 operators.operatorframework.io.metrics.project_layout:go.kubebuilder.io/v3 operators.operatorframework.io.test.config.v1:tests/scorecard/ operators.operatorframework.io.test.mediatype.v1:scorecard+v1]" time="2021-10-01T10:05:36Z" level=debug msg="operator package name is simple-demo-operator" time="2021-10-01T10:05:36Z" level=trace msg="making API request to https://catalog.redhat.com/api/containers/v1/operators/packages?filter=package_name%3D%3Dsimple-demo-operator" time="2021-10-01T10:05:40Z" level=trace msg="response code: 200 OK" time="2021-10-01T10:05:40Z" level=trace msg="response body: {\n  \"data\": [],\n  \"page\": 0,\n  \"page_size\": 100,\n  \"total\": 0\n}\n" time="2021-10-01T10:05:40Z" level=info msg="check completed: OperatorPackageNameIsUnique" result=PASSED time="2021-10-01T10:05:40Z" level=info msg="running check: ScorecardBasicSpecCheck" time="2021-10-01T10:05:40Z" level=debug msg="Running operator-sdk scorecard check for quay.io/opdev/simple-demo-operator-bundle:v0.0.2" time="2021-10-01T10:05:40Z" level=debug msg="--selector=[test=basic-check-spec-test]" time="2021-10-01T10:05:40Z" level=trace msg="running scorecard with the following invocation[operator-sdk scorecard --output json --selector=test=basic-check-spec-test --kubeconfig /home/vagrant/preflight/kubeconfig --namespace default --service-account default --config /tmp/scorecard-test-config-1018717604.yaml /tmp/preflight-1614532185/fs]" time="2021-10-01T10:06:12Z" level=error msg="stdout: " time="2021-10-01T10:06:12Z" level=error msg="stderr: Error: error running tests context deadline exceeded\nUsage:\n  operator-sdk scorecard [flags]\n\nFlags:\n  -c, --config string            path to scorecard config file\n  -h, --help                     help for scorecard\n      --kubeconfig string        kubeconfig path\n  -L, --list                     Option to enable listing which tests are run\n  -n, --namespace string         namespace to run the test images in\n  -o, --output string            Output format for results. Valid values: text, json (default \"text\")\n  -l, --selector string          label selector to determine which tests are run\n  -s, --service-account string   Service account to use for tests (default \"default\")\n  -x, --skip-cleanup             Disable resource cleanup after tests are run\n  -w, --wait-time duration       seconds to wait for tests to complete. Example: 35s (default 30s)\n\nGlobal Flags:\n      --plugins strings   plugin keys to be used for this subcommand execution\n      --verbose           Enable verbose logging\n\ntime=\"2021-10-01T10:06:12Z\" level=fatal msg=\"error running tests context deadline exceeded\"\n" time="2021-10-01T10:06:12Z" level=info msg="check completed: ScorecardBasicSpecCheck" ERROR="failed to run operator-sdk scorecard: exit status 1" result="failed to run operator-sdk scorecard: exit status 1" time="2021-10-01T10:06:12Z" level=info msg="running check: ScorecardOlmSuiteCheck" time="2021-10-01T10:06:12Z" level=debug msg="Running operator-sdk scorecard Check for quay.io/opdev/simple-demo-operator-bundle:v0.0.2" time="2021-10-01T10:06:12Z" level=debug msg="--selector=[suite=olm]" time="2021-10-01T10:06:12Z" level=trace msg="running scorecard with the following invocation[operator-sdk scorecard --output json --selector=suite=olm --kubeconfig /home/vagrant/preflight/kubeconfig --namespace default --service-account default --config /tmp/scorecard-test-config-21780141.yaml /tmp/preflight-1614532185/fs]" time="2021-10-01T10:06:44Z" level=error msg="stdout: " time="2021-10-01T10:06:44Z" level=error msg="stderr: Error: error running tests context deadline exceeded\nUsage:\n  operator-sdk scorecard [flags]\n\nFlags:\n  -c, --config string            path to scorecard config file\n  -h, --help                     help for scorecard\n      --kubeconfig string        kubeconfig path\n  -L, --list                     Option to enable listing which tests are run\n  -n, --namespace string         namespace to run the test images in\n  -o, --output string            Output format for results. Valid values: text, json (default \"text\")\n  -l, --selector string          label selector to determine which tests are run\n  -s, --service-account string   Service account to use for tests (default \"default\")\n  -x, --skip-cleanup             Disable resource cleanup after tests are run\n  -w, --wait-time duration       seconds to wait for tests to complete. Example: 35s (default 30s)\n\nGlobal Flags:\n      --plugins strings   plugin keys to be used for this subcommand execution\n      --verbose           Enable verbose logging\n\ntime=\"2021-10-01T10:06:44Z\" level=fatal msg=\"error running tests context deadline exceeded\"\n" time="2021-10-01T10:06:44Z" level=info msg="check completed: ScorecardOlmSuiteCheck" ERROR="failed to run operator-sdk scorecard: exit status 1" result="failed to run operator-sdk scorecard: exit status 1" time="2021-10-01T10:06:44Z" level=info msg="running check: DeployableByOLM" time="2021-10-01T10:06:44Z" level=trace msg="reading annotations file from the bundle" time="2021-10-01T10:06:44Z" level=debug msg="mounted directory is /tmp/preflight-1614532185/fs" time="2021-10-01T10:06:44Z" level=trace msg="searching for key (operators.operatorframework.io.bundle.channel.default.v1) in bundle" time="2021-10-01T10:06:44Z" level=trace msg="bundle data: map[operators.operatorframework.io.bundle.channel.default.v1:stable operators.operatorframework.io.bundle.channels.v1:stable operators.operatorframework.io.bundle.manifests.v1:manifests/ operators.operatorframework.io.bundle.mediatype.v1:registry+v1 operators.operatorframework.io.bundle.metadata.v1:metadata/ operators.operatorframework.io.bundle.package.v1:simple-demo-operator operators.operatorframework.io.metrics.builder:operator-sdk-v1.11.0+git operators.operatorframework.io.metrics.mediatype.v1:metrics+v1 operators.operatorframework.io.metrics.project_layout:go.kubebuilder.io/v3 operators.operatorframework.io.test.config.v1:tests/scorecard/ operators.operatorframework.io.test.mediatype.v1:scorecard+v1]" time="2021-10-01T10:06:44Z" level=trace msg="searching for key (operators.operatorframework.io.bundle.package.v1) in bundle" time="2021-10-01T10:06:44Z" level=trace msg="bundle data: map[operators.operatorframework.io.bundle.channel.default.v1:stable operators.operatorframework.io.bundle.channels.v1:stable operators.operatorframework.io.bundle.manifests.v1:manifests/ operators.operatorframework.io.bundle.mediatype.v1:registry+v1 operators.operatorframework.io.bundle.metadata.v1:metadata/ operators.operatorframework.io.bundle.package.v1:simple-demo-operator operators.operatorframework.io.metrics.builder:operator-sdk-v1.11.0+git operators.operatorframework.io.metrics.mediatype.v1:metrics+v1 operators.operatorframework.io.metrics.project_layout:go.kubebuilder.io/v3 operators.operatorframework.io.test.config.v1:tests/scorecard/ operators.operatorframework.io.test.mediatype.v1:scorecard+v1]" time="2021-10-01T10:06:45Z" level=debug msg="Namespace created: simple-demo-operator" time="2021-10-01T10:06:45Z" level=trace msg="Received Namespace object from API server: &Namespace{ObjectMeta:{simple-demo-operator    827df86d-d850-428a-827f-46914e475c3b 43371 0 2021-10-01 10:06:45 +0000 UTC <nil> <nil> map[kubernetes.io/metadata.name:simple-demo-operator] map[] [] []  [{preflight Update v1 2021-10-01 10:06:45 +0000 UTC FieldsV1 {\"f:metadata\":{\"f:labels\":{\".\":{},\"f:kubernetes.io/metadata.name\":{}}}} }]},Spec:NamespaceSpec{Finalizers:[kubernetes],},Status:NamespaceStatus{Phase:Active,Conditions:[]NamespaceCondition{},},}" I1001 10:06:47.958372    6524 request.go:665] Waited for 1.046186519s due to client-side throttling, not priority and fairness, request: GET:https://api.viksss.lab.upshift.rdu2.redhat.com:6443/apis/networking.k8s.io/v1?timeout=32s time="2021-10-01T10:06:50Z" level=debug msg="Creating CatalogSource simple-demo-operator in namespace simple-demo-operator" time="2021-10-01T10:06:50Z" level=debug msg="CatalogSource simple-demo-operator is created successfully in namespace simple-demo-operator" time="2021-10-01T10:06:54Z" level=debug msg="Creating OperatorGroup simple-demo-operator in namespace simple-demo-operator" time="2021-10-01T10:06:55Z" level=debug msg="OperatorGroup simple-demo-operator is created successfully in namespace simple-demo-operator" I1001 10:06:57.960206    6524 request.go:665] Waited for 1.890238313s due to client-side throttling, not priority and fairness, request: GET:https://api.viksss.lab.upshift.rdu2.redhat.com:6443/apis/tuned.openshift.io/v1?timeout=32s time="2021-10-01T10:06:59Z" level=debug msg="Creating Subscription simple-demo-operator in namespace simple-demo-operator" time="2021-10-01T10:06:59Z" level=debug msg="Subscription simple-demo-operator is created successfully in namespace simple-demo-operator" time="2021-10-01T10:06:59Z" level=debug msg="Waiting for Subscription.status.installedCSV to become ready..." time="2021-10-01T10:07:03Z" level=debug msg="fetching subscription simple-demo-operator from namespace simple-demo-operator " time="2021-10-01T10:07:03Z" level=debug msg="Subscription.status.installedCSV is not set yet, retrying..." time="2021-10-01T10:07:05Z" level=debug msg="Waiting for Subscription.status.installedCSV to become ready..." I1001 10:07:08.089717    6524 request.go:665] Waited for 1.038927215s due to client-side throttling, not priority and fairness, request: GET:https://api.viksss.lab.upshift.rdu2.redhat.com:6443/apis/extensions/v1beta1?timeout=32s time="2021-10-01T10:07:10Z" level=debug msg="fetching subscription simple-demo-operator from namespace simple-demo-operator " time="2021-10-01T10:07:10Z" level=debug msg="Subscription.status.installedCSV is not set yet, retrying..." time="2021-10-01T10:07:12Z" level=debug msg="Waiting for Subscription.status.installedCSV to become ready..." time="2021-10-01T10:07:16Z" level=debug msg="fetching subscription simple-demo-operator from namespace simple-demo-operator " time="2021-10-01T10:07:17Z" level=debug msg="Subscription.status.installedCSV is not set yet, retrying..." time="2021-10-01T10:07:19Z" level=debug msg="Waiting for Subscription.status.installedCSV to become ready..." I1001 10:07:21.749058    6524 request.go:665] Waited for 1.039766724s due to client-side throttling, not priority and fairness, request: GET:https://api.viksss.lab.upshift.rdu2.redhat.com:6443/apis/autoscaling.openshift.io/v1?timeout=32s time="2021-10-01T10:07:23Z" level=debug msg="fetching subscription simple-demo-operator from namespace simple-demo-operator " time="2021-10-01T10:07:24Z" level=debug msg="Subscription.status.installedCSV is not set yet, retrying..." time="2021-10-01T10:07:26Z" level=debug msg="Waiting for Subscription.status.installedCSV to become ready..." time="2021-10-01T10:07:30Z" level=debug msg="fetching subscription simple-demo-operator from namespace simple-demo-operator " time="2021-10-01T10:07:30Z" level=debug msg="Subscription.status.installedCSV is not set yet, retrying..." time="2021-10-01T10:07:32Z" level=debug msg="Waiting for Subscription.status.installedCSV to become ready..." I1001 10:07:35.138113    6524 request.go:665] Waited for 1.064203795s due to client-side throttling, not priority and fairness, request: GET:https://api.viksss.lab.upshift.rdu2.redhat.com:6443/apis/operators.coreos.com/v1alpha1?timeout=32s time="2021-10-01T10:07:37Z" level=debug msg="fetching subscription simple-demo-operator from namespace simple-demo-operator " time="2021-10-01T10:07:37Z" level=debug msg="Subscription.status.installedCSV is not set yet, retrying..." time="2021-10-01T10:07:39Z" level=debug msg="Waiting for Subscription.status.installedCSV to become ready..." time="2021-10-01T10:07:43Z" level=debug msg="fetching subscription simple-demo-operator from namespace simple-demo-operator " time="2021-10-01T10:07:44Z" level=debug msg="Subscription.status.installedCSV is simple-demo-operator.v0.0.2" time="2021-10-01T10:07:44Z" level=trace msg="Looking for csv simple-demo-operator.v0.0.2 in namespace simple-demo-operator" time="2021-10-01T10:07:44Z" level=debug msg="Waiting for ClusterServiceVersion to become ready..." I1001 10:07:45.976651    6524 request.go:665] Waited for 1.000626877s due to client-side throttling, not priority and fairness, request: GET:https://api.viksss.lab.upshift.rdu2.redhat.com:6443/apis/security.openshift.io/v1?timeout=32s time="2021-10-01T10:07:48Z" level=debug msg="fetching csv simple-demo-operator.v0.0.2 from namespace simple-demo-operator " time="2021-10-01T10:07:48Z" level=debug msg="CSV is not ready yet, retrying..." time="2021-10-01T10:07:50Z" level=debug msg="Waiting for ClusterServiceVersion to become ready..." time="2021-10-01T10:07:55Z" level=debug msg="fetching csv simple-demo-operator.v0.0.2 from namespace simple-demo-operator " time="2021-10-01T10:07:56Z" level=debug msg="CSV is not ready yet, retrying..." time="2021-10-01T10:07:58Z" level=debug msg="Waiting for ClusterServiceVersion to become ready..." I1001 10:08:00.446166    6524 request.go:665] Waited for 1.033364528s due to client-side throttling, not priority and fairness, request: GET:https://api.viksss.lab.upshift.rdu2.redhat.com:6443/apis/machineconfiguration.openshift.io/v1?timeout=32s time="2021-10-01T10:08:02Z" level=debug msg="fetching csv simple-demo-operator.v0.0.2 from namespace simple-demo-operator " time="2021-10-01T10:08:03Z" level=debug msg="CSV is created successfully: simple-demo-operator.v0.0.2" time="2021-10-01T10:08:03Z" level=debug msg="Dumping data in artifacts/ directory" time="2021-10-01T10:08:07Z" level=debug msg="fetching subscription simple-demo-operator from namespace simple-demo-operator " I1001 10:08:10.473187    6524 request.go:665] Waited for 2.101994876s due to client-side throttling, not priority and fairness, request: GET:https://api.viksss.lab.upshift.rdu2.redhat.com:6443/apis/batch/v1?timeout=32s time="2021-10-01T10:08:11Z" level=debug msg="fetching catalogsource: simple-demo-operator" time="2021-10-01T10:08:15Z" level=debug msg="fetching operatorgroup simple-demo-operator from namespace simple-demo-operator " time="2021-10-01T10:08:16Z" level=debug msg="fetching namespace: simple-demo-operator" time="2021-10-01T10:08:16Z" level=trace msg="Deleting the resources created by Check" time="2021-10-01T10:08:20Z" level=debug msg="Deleting Subscription simple-demo-operator in namespace simple-demo-operator" time="2021-10-01T10:08:20Z" level=debug msg="Subscription simple-demo-operator is deleted successfully from namespace simple-demo-operator" I1001 10:08:22.809508    6524 request.go:665] Waited for 1.047482348s due to client-side throttling, not priority and fairness, request: GET:https://api.viksss.lab.upshift.rdu2.redhat.com:6443/apis/operators.coreos.com/v1alpha2?timeout=32s time="2021-10-01T10:08:24Z" level=debug msg="Deleting CatalogSource simple-demo-operator in namespace simple-demo-operator" time="2021-10-01T10:08:25Z" level=debug msg="CatalogSource simple-demo-operator is deleted successfully from namespace simple-demo-operator" time="2021-10-01T10:08:29Z" level=debug msg="Deleting OperatorGroup simple-demo-operator in namespace simple-demo-operator" time="2021-10-01T10:08:29Z" level=debug msg="OperatorGroup simple-demo-operator is deleted successfully from namespace simple-demo-operator" time="2021-10-01T10:08:29Z" level=debug msg="Deleting namespace: simple-demo-operator" time="2021-10-01T10:08:30Z" level=info msg="check completed: DeployableByOLM" result=PASSED time="2021-10-01T10:08:30Z" level=debug msg="md5 sum: 1a44ac806b272418630c65cfa8ca1e94" {     "image": "quay.io/opdev/simple-demo-operator-bundle:v0.0.2",     "passed": false,     "certification_hash": "1a44ac806b272418630c65cfa8ca1e94",     "test_library": {         "name": "github.com/redhat-openshift-ecosystem/openshift-preflight",         "version": "0.0.0",         "commit": "333adaf7672ba41988bd9ad75dc6da2cba6974b2"     },     "results": {         "passed": [             {                 "name": "ValidateOperatorBundle",                 "elapsed_time": 1050,                 "description": "Validating Bundle image that checks if it can validate the content and format of the operator bundle"             },             {                 "name": "OperatorPackageNameIsUnique",                 "elapsed_time": 3727,                 "description": "Validating Bundle image package name uniqueness"             },             {                 "name": "DeployableByOLM",                 "elapsed_time": 105866,                 "description": "Checking if the operator could be deployed by OLM"             }         ],         "failed": [],         "errors": [             {                 "name": "ScorecardBasicSpecCheck",                 "elapsed_time": 31847,                 "description": "Check to make sure that all CRs have a spec block.",                 "help": "Check ScorecardBasicSpecCheck encountered an error. Please review the artifacts/operator_bundle_scorecard_BasicSpecCheck.json file for more information."             },             {                 "name": "ScorecardOlmSuiteCheck",                 "elapsed_time": 31948,                 "description": "Operator-sdk scorecard OLM Test Suite Check",                 "help": "Check ScorecardOlmSuiteCheck encountered an error. Please review the artifacts/operator_bundle_scorecard_OlmSuiteCheck.json file for more information."             }         ]     } }
Additional Context
looks like this is related to imagepull limit for docker busybox
https://github.com/operator-framework/operator-sdk/issues/4886
operator scorecard fails when executed manually without using preflight
[vagrant@fedora34 preflight]$ oc debug scorecard-test-h9gb Starting pod/scorecard-test-h9gb-debug, command was: scorecard-test basic-check-spec warning: Container scorecard-untar is unable to start due to an error: Back-off pulling image "docker.io/busybox:1.33.0"
[vagrant@fedora34 preflight]$ oc get pods NAME                  READY   STATUS                  RESTARTS   AGE scorecard-test-h9gb   0/1     Init:ImagePullBackOff   0          114s

I have similar issue on openshift cluster in disconnected env when running operator-sdk scorecard directly
$ oc describe pod scorecard-test-l5k6

Events:
  Type     Reason          Age                 From               Message
  ----     ------          ----                ----               -------
  Normal   Scheduled       114s                default-scheduler  Successfully assigned default/scorecard-test-l5k6 to worker-3
  Warning  Failed          52s                 kubelet            Failed to pull image "docker.io/busybox:1.33.0": rpc error: code = Unknown desc = error pinging docker registry registry-1.docker.io: Get "https://registry-1.docker.io/v2/": dial tcp <IP_ADDRESS>:443: i/o timeout
  Warning  Failed          52s                 kubelet            Error: ErrImagePull
  Normal   BackOff         51s                 kubelet            Back-off pulling image "docker.io/busybox:1.33.0"
  Warning  Failed          51s                 kubelet            Error: ImagePullBackOff
  Normal   Pulling         40s (x2 over 112s)  kubelet            Pulling image "docker.io/busybox:1.33.0"

Seems like the newest release of operator-sdk 1.13.0 has removed the busybox image
https://github.com/operator-framework/operator-sdk/pull/5191
This makes me wonder if there is going to be any mapping of a preflight release to a operator-sdk release of some sort.
The change on image should mitigate the limit threshold imposed by docker to anonymous pulls but does not solve the problem with disconnected environments :crying_cat_face:


--dino-path "/home/outputs/dino/resnet/bld-det-pl-2023-06-22-19-53-11/checkpoint0011.pth"

--dino-path "/home/outputs/dino/resnet/bld-det-pl-2023-06-22-19-53-11/checkpoint0011.pth"
What is this model checkpoint and where can I download it

Is this the result of training with DINO on the xBD dataset


{Core} Stop using vendored SDK in core

Description
Stop using vendored subscription SDK in core as azure-mgmt-resource has been migrated to Track 2 (https://github.com/Azure/azure-cli/pull/17783).

Core


FrontendObserver use error

Describe the bug
Hello, I want pass FrontendObserver class get some AST data, so i compile swift5.6 source, I replaced the last parameter of performFrontend, just like swift-ast-script tool, but when i use instance.getMainModule() in  configuredCompiler  function, I compile and run bin/swift-frontend, the error is:
Assertion failed: (findOption(Name) == Values.size() && "Option already exists!"), function addLiteralOption, file CommandLine.h, line 860.
whats mean this error?  why i can't call instance.getMainModule(). thanks
Environment (please complete the following information):

OS: macbook pro m1 12.0.1

its worng issue..


Log ICommandManager.executeCommand telemetry

Seems VS code doesn't track our usage of this API so we need to add this ourselves.

Would be good to be able to tell why each call to this function occurs (to understand if the user explicitly did an action to call this or not).

Validated.
nfo Jupyter Extension: 2021-03-26 14:12:49: Telemetry Event : DS_INTERNAL.COMMAND_EXECUTED Measures: undefined Props: {"command":"jupyter.clearSavedJupyterUris","installSource":"marketPlace","VSCode.ABExp.Features":"invitationLink;installRecovery;livesharecontinuousaacf;reusableLinks;RemoveKernelToolbarInInteractiveWindowcf;pythonJediLSP;portForwardingServiceEnabled-development;portForwardingServiceEnabled-staging;portForwardingServiceEnabled-production;pythonDiscoveryModule;pythonFindInterpreter;presentWelcomePageByDefault","abexp.assignmentcontext":"vsliv695:30137379;vsins829:30139715;vsliv368cf:30146710;vsreu685:30147344;python383cf:30185419;pythonvspyt602:30280718;vspor879:30202332;vspor708:30202333;vspor363:30204092;pythonvsnew554:30265444;pythonvspyt943:30277000;vspre833:30267464;","isamlcompute":"false","isInsiderExtension":"true","ds_notebookeditor":"native","localOrRemoteConnection":"local","isPythonExtensionInstalled":"true","rawKernelSupported":"true"}


Decide where Distances should be located

Currently Distances is only copied code of Mathopshere. If the code is edited at one point, the two version might differ which can lead to problems.
The code already diverged recently: https://github.com/ag-gipp/MathMLSim/blob/master/src/main/java/com/formulasearchengine/mathmlsim/Distances.java#L40
vs
https://github.com/ag-gipp/MathMLSim/commit/e86d7aba75afd7bfe3a5abbd7b5df89a8c6c3092#diff-e2559fcca35ed055dedf08363f9b7a38R34

@physikerwelt The mathpd package contains some dependencies that I did not know before. If we combine the classes on MathMLSim, I would have to abstract or drag the pojos like ArvixDocument into MathMLSim. Here I would act according to what you like more?
Let's discuss that here https://github.com/ag-gipp/mathosphere/issues/167

Nevertheless, I'll do first a merge for MathMLSim, which will make everything smooth and then the one for mathosphere.

Where and when?

@vstange what is the status about this ticket. Is it still relevant? Should it be moved to JIRA?

@AndreG-P, do we have an approach for that? The problem was (if I remember correctly) that sonatype was somehow dysfunctional?

@physikerwelt This project is part of MathMLTools: https://github.com/gipplab/MathMLTools/tree/master/mathml-similarity
And mathosphere imports MathML tools.
If you mean the issue with deploy to maven central, I dont really know what the issue was.

So the most recent version is this repository. Thank you


Wrong expected results in Bonfire: Smallest Common Multiple

Either expected results or input arrays are wrong:

expect(smallestCommons([1,5])).to.equal(60);expected 5 to equal 60
expect(smallestCommons([5,1])).to.equal(60);expected 5 to equal 60

The 60 is true for smallestCommons([12,5]) but for the [1,5] it's 5.

expect(smallestCommons([1,13])).to.equal(360360);expected 13 to equal 360360

Here, perhaps, it's smallestCommons([27720,13])

Incorrect. The smallest number the range divides into is 60.
http://m.wolframalpha.com/input/?i=lcm(1%2C+2%2C3%2C4%2C5)&x=0&y=0
On Sun, Jun 21, 2015 at 12:35 PM Denis Shendrik<EMAIL_ADDRESS>wrote:

Either expected results or input arrays are wrong.
expect(smallestCommons([1,5])).to.equal(60);expected 5 to equal 60
expect(smallestCommons([5,1])).to.equal(60);expected 5 to equal 60
The 60 is true for smallestCommons([12,5]) but for the [1,5] it's 5.
expect(smallestCommons([1,13])).to.equal(360360);expected 13 to equal 360360
Here, perhaps, it's smallestCommons([27720,13])
—
Reply to this email directly or view it on GitHub
https://github.com/FreeCodeCamp/freecodecamp/issues/1047.

Oh.. the range. Sorry.

Thanks!

No worries, better to clarify! Enjoy
On Sun, Jun 21, 2015 at 12:47 PM Denis Shendrik<EMAIL_ADDRESS>wrote:

Thanks!
—
Reply to this email directly or view it on GitHub
https://github.com/FreeCodeCamp/freecodecamp/issues/1047#issuecomment-113926980
.

I also got confused the range with LCM. But why is the referral link given to https://www.mathsisfun.com/least-common-multiple.html ? which is basically LCM.
Maybe I'm wrong, better be more clear on the description?


Mod+P runs dmenu but doesn't execute any application

I've an arch linux installation and current git reposistory has been cloned., and xmonad/xmobar works perfect. But the default dmenu-with-yeganesh doesn't do anything it appears but doesn't launch the app. The following modificaiton solves the problem for my case. I'm not sure if this problem is glabal and effects all users:
in the ~/.xmonad/bin/dmenu-with-yeganesh the execution command should be added i.e.:
this line: dmenu_path | ~/.cabal/bin/yeganesh -- -nb ....
should be modifedi to this:
exec $(dmenu_path | ~/.cabal/bin/yeganesh -- nb .......)
best regards

Fixed w/ latest merge. Thanks @vohof


Generalize PEFT state dict filter

What does this PR do?
In the original PEFT integration PR, I copied some of the logic from PEFT for state dict filtering. My logic at the time was a bit flawed (I thought passing the model to this function would be an issue for some reason, but realized its not), so updating now to use the PEFT utility directly.

Does not work because the built in function removes the adapter names from the state dict


Drops for enemies? Drop Table (weapons, things to sell?)

Enemies have a chance to drop health packs and coins (100) when killed.


error line 1 ^ SyntaxError: invalid syntax )

JsException(PythonError: Traceback (most recent call last): File "/lib/python3.10/site-packages/_pyodide/_base.py", line 421, in eval_code CodeRunner( File "/lib/python3.10/site-packages/_pyodide/_base.py", line 237, in init self.ast = next(self._gen) File "/lib/python3.10/site-packages/_pyodide/_base.py", line 141, in _parse_and_compile_gen mod = compile(source, filename, mode, flags | ast.PyCF_ONLY_AST) File "", line 1 ^ SyntaxError: invalid syntax )
I tried running as html locally.
It failed with above error.

I use the VS Code Live Server Preview, that does work.


Making the chunk size not constant for real-time audio purposes

Hello, sorry for giving you more work again and creating a new issue since I already made a PR today, but there is a feature missing in your crate that I would like to add by PR, it would be a pretty huge breaking change probably because it would require some huge changes in the code base.
I would like to suggest making the chunk_size a value in the VoiceActivityDetector struct instead of a generic value since it is otherwise impossible to write code like this:
let sample_rate: u32 = default_config.sample_rate().0;
let buffer_size = sample_rate / 16;
let _work_channels = 1; // Stereo doesn't work at the moment (will fix in the future or never)
let mic_channels = default_config.channels();
let config: StreamConfig = StreamConfig {
    channels: mic_channels,
    sample_rate: cpal::SampleRate(sample_rate),
    buffer_size: cpal::BufferSize::Fixed(buffer_size),
};

let mut vad = VoiceActivityDetector::<buffer_size>::try_with_sample_rate(
    default_config.sample_rate().0,
)
.expect("how dare you");

The above code will error because buffer_size isn't constant, and there is no way to make it constant since it has to be computed every time this code runs. Since this code always gets a different sample rate, I would like to be able to compute the chunk_size based on the sample rate. If I just set a constant, it will error with different sample rates as well, just like when going with something as low as 256 as a constant for the chunk_size the code errors when passing in a sample_rate above 44100 (that's what I tested with). It would be cool to be able to compute this on the fly using something like I have shown in the example here. The only way to currently work around this is to have different recorders for different sample rates, meaning you write the same code like 5 times just to get this value to change. If there is another way that fixes this issue, please let me know, I'm kind of new to Rust, so I'm sorry if there's something basic I'm overlooking here.
Thanks for your work and I hope we can get this resolved,
Julian.

Just for reference, something like this would also error, because it doesn't have the same types:
let mut vad = if default_config.sample_rate().0 > 32000 {
    VoiceActivityDetector::<512>::try_with_sample_rate(default_config.sample_rate().0)
        .expect("how dare you")
} else {
    VoiceActivityDetector::<256>::try_with_sample_rate(default_config.sample_rate().0)
        .expect("how dare you")
};

I've made a potential draft for this at https://github.com/Liphium/voice_activity_detector_fixed. Adding a DynamicVoiceActivityDetector to fix this particular use case. I just couldn't get the normal API to work with the iterators due to issues with the constant usize for the LabeledAudio struct. Probably just a skill issue, but I don't know. The thing is that this is probably just a temporary fix for something that needs better addressing in the future. I also added a test called wave_file_dynamic_detector to test the thing. Let me know if you want me to make a pull request with this, because this is a pretty big modification and I don't know what vision you have for this library.

I've already implemented an extra struct called ``DynamicVoiceActivityDetector``` at https://github.com/Liphium/voice_activity_detector_fixed that has a chunk_size value in it. I've not implemented it for iterators and all the other stuff cause I didn't know how far we should go and I think that just the VAD is enough for testing for now. I managed to make this thing work and confirmed that with a test case I added. I'm going to make a PR with this thing now.

After evaluating, I think one struct without any const generics would be best. We may be sacrificing some possible optimizations with the compile-time size guarantees, but those differences would be incredibly minor. I'd rather keep the surface of this library simple and only expose a single VoiceActivityDetector. Two structs would also require multiple implementations of the iterator and stream extensions (or incomplete features).
In the future, if we wanted a very optimized VAD with these compile time guarantees, it could be added back. I'd rather the default one be the more flexible and user friendly option.
Also, breaking changes in this library are okay for now until the 1.0.0 release is created.
If you'd like to take on the work of removing the const generic and replacing the arrays with Vecs throughout the crate, I'm happy to accept a PR. I'll get around to making the changes tonight otherwise.

Well that's this issue closed then, thanks for your work, you were really fast to implement this!


[NFC] Remove Unused SugarType::setUnderlyingType

Not sure when this stopped being used, but I'm happy to get rid of more public mutating accessors.

@swift-ci smoke test and merge


Enable loop from specific times

It's possible to detect end of video and loop from there: https://stackoverflow.com/questions/21271706/detect-in-javascript-when-html5-video-loop-restarts
Then we'd need to figure out a UI (maybe an alert in JS that asks for input?) to accept input... Then we'd need to figure out how to detect current time in video? I think that's possible, and we can do a while loop for every 100 milliseconds to stop video and replay at specific time.

https://www.w3schools.com/jsref/met_win_prompt.asp


First part of the licensing changes for the Czech law system.

These are the new licensing questions adapted to the Czech law
environment. What’s missing are the required certificate levels
and help texts, those will be added later.

@zoul do you have english translations for the bits that you've changed?
I'd like to merge it in using the new transifex based system if possible.

I’ll post the English translation as soon as possible – either later today or tomorrow.

See the latest commit (f3b950a). I took the original English legal file and replaced the licensing part with the Czech-specific questions translated back to English. I saved the file here:
prototype/jurisdictions/certificate.CZ.EN.xml

Feel free to move the content as you see fit.

This will be merged in in the changes for #1203 so that it's using the new Transifex system for translations too.


readyset: Fix create/drop cache methods

Readyset.create_cache! and Readyset.drop_cache! each quoted the query ID/name before sending the query to ReadySet. This was incorrect: ReadySet query IDs/names are not string literals but rather identifiers. This commit fixes the issue by creating the CREATE CACHE and DROP CACHE query strings using unquoted query IDs/names.

@ethan-readyset Just commented one question regarding test coverage. Otherwise, this looks good to go.


region flag for read_gem

read_gef() already supports passing a region to reduce the size of the data set. This is not supported by read_gem(), but would be greatly appreciated.
Is there a subset function that can be applied to StereoExpData objects?

Hi!
You can use the function data.tl.filter_coordinates to filter data by setting min_x, min_y, max_x and max_y.
For example:
data.tl.filter_coordinates(min_x=100, max_x=500, min_y=100, max_y=100)


nixos/mx-puppet-discord: add module

Motivation for this change
While we do have a discord-matrix bridge on nixpkgs, this bridge is guild only and isn't really actively maintained anymore, leading to main features such as replies left unimplemented.
mx-puppet-discord adds on top of appservice-discord puppeting features, allowing it to work with DMs, group DMs, and with user accounts, being able to mirror channels without needing a bot and, as such, bot permissions.
Things done

[X] Tested using sandboxing (nix.useSandbox on NixOS, or option sandbox in nix.conf on non-NixOS linux)
Built on platform(s)

[X] NixOS
[ ] macOS
[ ] other Linux distributions

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[X] Tested compilation of all pkgs that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review wip"
[X] Tested execution of all binary files (usually in ./result/bin/)
21.11 Release Notes (or backporting 21.05 Relase notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[X] (Module addition) Added a release notes entry if adding a new NixOS module

[X] Fits CONTRIBUTING.md.

Can be tested with the following configuration:
{ pkgs, lib, config, ... }:
let
  fqdn =
    let
      join = hostName: domain: hostName + lib.optionalString (domain != null) ".${domain}";
    in join config.networking.hostName config.networking.domain;
in {
  networking = {
    hostName = "example";
    domain = "example.com";
  };
  users = {
    mutableUsers = false;
    extraUsers = {
      root = {
        password = "toor";
      };
     };
  };
    networking.firewall.allowedTCPPorts = [ 80 443 ];

  services.postgresql.enable = true;
  services.postgresql.initialScript = pkgs.writeText "synapse-init.sql" ''
    CREATE ROLE "matrix-synapse" WITH LOGIN PASSWORD 'synapse';
    CREATE DATABASE "matrix-synapse" WITH OWNER "matrix-synapse"
      TEMPLATE template0
      LC_COLLATE = "C"
      LC_CTYPE = "C";
  '';

  security.acme.email =<EMAIL_ADDRESS>  security.acme.acceptTerms = true;
  services.nginx = {
    enable = true;
    # only recommendedProxySettings and recommendedGzipSettings are strictly required,
    # but the rest make sense as well
    recommendedTlsSettings = true;
    recommendedOptimisation = true;
    recommendedGzipSettings = true;
    recommendedProxySettings = true;

    virtualHosts = {
      # This host section can be placed on a different host than the rest,
      # i.e. to delegate from the host being accessible as ${config.networking.domain}
      # to another host actually running the Matrix homeserver.
      "${config.networking.domain}" = {
        enableACME = true;
        forceSSL = true;

        locations."= /.well-known/matrix/server".extraConfig =
          let
            # use 443 instead of the default 8448 port to unite
            # the client-server and server-server port for simplicity
            server = { "m.server" = "${fqdn}:443"; };
          in ''
            add_header Content-Type application/json;
            return 200 '${builtins.toJSON server}';
          '';
        locations."= /.well-known/matrix/client".extraConfig =
          let
            client = {
              "m.homeserver" =  { "base_url" = "https://${fqdn}"; };
              "m.identity_server" =  { "base_url" = "https://vector.im"; };
            };
          # ACAO required to allow element-web on any URL to request this json file
          in ''
            add_header Content-Type application/json;
            add_header Access-Control-Allow-Origin *;
            return 200 '${builtins.toJSON client}';
          '';
      };

      # Reverse proxy for Matrix client-server and server-server communication
      ${fqdn} = {
        enableACME = true;
        forceSSL = true;

        # Or do a redirect instead of the 404, or whatever is appropriate for you.
        # But do not put a Matrix Web client here! See the Element web section below.
        locations."/".extraConfig = ''
          return 404;
        '';

        # forward all Matrix API calls to the synapse Matrix homeserver
        locations."/_matrix" = {
          proxyPass = "http://[::1]:8008"; # without a trailing /
        };
      };
    };
  };
  services.matrix-synapse = {
    enable = true;
    app_service_config_files = [
      "/var/lib/mx-puppet-discord/discord-registration.yaml"
    ];
    server_name = config.networking.domain;
    listeners = [
      {
        port = 8008;
        bind_address = "::1";
        type = "http";
        tls = false;
        x_forwarded = true;
        resources = [
          {
            names = [ "client" "federation" ];
            compress = false;
          }
        ];
      }
    ];
  };
  services.mx-puppet-discord = {
    enable = true;
    settings = {
        bridge = {
            bindAddress = "localhost";
            domain = "example.com";
            homeserverUrl = "https://example.com";
        };
        provisioning.whitelist = [ "@admin:example.com" ];
        relay.whitelist = [ "@.*:example.com" ];
    };
  };
}

Relevant log and registration file auto-generated by this config:

The manual test fail seems to be related to cachix acting up fwiw

@aanderse Thanks! I applied your suggestions.

apropos of nothing I solved the merge conflicts :)

Thank you @GovanifY! This module looks very helpful

@GovanifY please resolve the next never conflict