Error during time_diff_keeper polling: usb device disconnected！！

$:roslaunch realsense2_camera demo_pointcloud.launch
... logging to /home/wang/.ros/log/5dd829a8-a5f7-11ea-90d9-00d861d2211d/roslaunch-wang-MS-7B98-20609.log
Checking log directory for disk usage. This may take awhile.
Press Ctrl-C to interrupt
Done checking log file disk usage. Usage is <1GB.
started roslaunch server http://wang-MS-7B98:46269/
SUMMARY
PARAMETERS

/camera/realsense2_camera/accel_fps: 0
/camera/realsense2_camera/accel_frame_id: camera_accel_frame
/camera/realsense2_camera/accel_optical_frame_id: camera_accel_opti...
/camera/realsense2_camera/align_depth: False
/camera/realsense2_camera/aligned_depth_to_color_frame_id: camera_aligned_de...
/camera/realsense2_camera/aligned_depth_to_fisheye1_frame_id: camera_aligned_de...
/camera/realsense2_camera/aligned_depth_to_fisheye2_frame_id: camera_aligned_de...
/camera/realsense2_camera/aligned_depth_to_fisheye_frame_id: camera_aligned_de...
/camera/realsense2_camera/aligned_depth_to_infra1_frame_id: camera_aligned_de...
/camera/realsense2_camera/aligned_depth_to_infra2_frame_id: camera_aligned_de...
/camera/realsense2_camera/allow_no_texture_points: False
/camera/realsense2_camera/base_frame_id: camera_link
/camera/realsense2_camera/calib_odom_file:
/camera/realsense2_camera/clip_distance: -1.0
/camera/realsense2_camera/color_fps: 30
/camera/realsense2_camera/color_frame_id: camera_color_frame
/camera/realsense2_camera/color_height: 720
/camera/realsense2_camera/color_optical_frame_id: camera_color_opti...
/camera/realsense2_camera/color_width: 1280
/camera/realsense2_camera/depth_fps: 30
/camera/realsense2_camera/depth_frame_id: camera_depth_frame
/camera/realsense2_camera/depth_height: 720
/camera/realsense2_camera/depth_optical_frame_id: camera_depth_opti...
/camera/realsense2_camera/depth_width: 1280
/camera/realsense2_camera/device_type:
/camera/realsense2_camera/enable_accel: False
/camera/realsense2_camera/enable_color: True
/camera/realsense2_camera/enable_depth: True
/camera/realsense2_camera/enable_fisheye1: True
/camera/realsense2_camera/enable_fisheye2: True
/camera/realsense2_camera/enable_fisheye: False
/camera/realsense2_camera/enable_gyro: False
/camera/realsense2_camera/enable_infra1: False
/camera/realsense2_camera/enable_infra2: False
/camera/realsense2_camera/enable_pointcloud: True
/camera/realsense2_camera/enable_sync: True
/camera/realsense2_camera/filters:
/camera/realsense2_camera/fisheye1_frame_id: camera_fisheye1_f...
/camera/realsense2_camera/fisheye1_optical_frame_id: camera_fisheye1_o...
/camera/realsense2_camera/fisheye2_frame_id: camera_fisheye2_f...
/camera/realsense2_camera/fisheye2_optical_frame_id: camera_fisheye2_o...
/camera/realsense2_camera/fisheye_fps: 30
/camera/realsense2_camera/fisheye_frame_id: camera_fisheye_frame
/camera/realsense2_camera/fisheye_height: 0
/camera/realsense2_camera/fisheye_optical_frame_id: camera_fisheye_op...
/camera/realsense2_camera/fisheye_width: 0
/camera/realsense2_camera/gyro_fps: 0
/camera/realsense2_camera/gyro_frame_id: camera_gyro_frame
/camera/realsense2_camera/gyro_optical_frame_id: camera_gyro_optic...
/camera/realsense2_camera/imu_optical_frame_id: camera_imu_optica...
/camera/realsense2_camera/infra1_frame_id: camera_infra1_frame
/camera/realsense2_camera/infra1_optical_frame_id: camera_infra1_opt...
/camera/realsense2_camera/infra2_frame_id: camera_infra2_frame
/camera/realsense2_camera/infra2_optical_frame_id: camera_infra2_opt...
/camera/realsense2_camera/infra_fps: 30
/camera/realsense2_camera/infra_height: 480
/camera/realsense2_camera/infra_width: 640
/camera/realsense2_camera/initial_reset: False
/camera/realsense2_camera/json_file_path:
/camera/realsense2_camera/linear_accel_cov: 0.01
/camera/realsense2_camera/odom_frame_id: camera_odom_frame
/camera/realsense2_camera/pointcloud_texture_index: 0
/camera/realsense2_camera/pointcloud_texture_stream: RS2_STREAM_COLOR
/camera/realsense2_camera/pose_frame_id: camera_pose_frame
/camera/realsense2_camera/pose_optical_frame_id: camera_pose_optic...
/camera/realsense2_camera/publish_odom_tf: True
/camera/realsense2_camera/publish_tf: True
/camera/realsense2_camera/rosbag_filename:
/camera/realsense2_camera/serial_no:
/camera/realsense2_camera/tf_publish_rate: 0.0
/camera/realsense2_camera/topic_odom_in: camera/odom_in
/camera/realsense2_camera/unite_imu_method: none
/camera/realsense2_camera/usb_port_id:
/rosdistro: kinetic
/rosversion: 1.12.14

NODES
/camera/
realsense2_camera (nodelet/nodelet)
realsense2_camera_manager (nodelet/nodelet)
ROS_MASTER_URI=http://localhost:11311
process[camera/realsense2_camera_manager-1]: started with pid [20626]
process[camera/realsense2_camera-2]: started with pid [20627]
[ INFO] [1591248675.666288455]: Initializing nodelet with 8 worker threads.
[ INFO] [1591248675.697156755]: RealSense ROS v2.2.13
[ INFO] [1591248675.697174853]: Running with LibRealSense v2.33.1
[ INFO] [1591248675.704049698]:
04/06 13:31:15,802 WARNING [140199275263744] (uvc-device.cpp:664) interrupt event received: 1, 3, 0, 7, 0, 13,
04/06 13:31:15,806 WARNING [140199275263744] (uvc-device.cpp:664) interrupt event received: 1, 3, 0, 7, 0, 20,
[ INFO] [1591248676.055894797]: Device with serial number<PHONE_NUMBER>12 was found.
[ INFO] [1591248676.055915627]: Device with physical ID 2-2-13 was found.
[ INFO] [1591248676.055922954]: Device with name Intel RealSense D435 was found.
[ INFO] [1591248676.056234641]: Device with port number 2-2 was found.
[ INFO] [1591248676.057566317]: getParameters...
[ INFO] [1591248676.101274154]: setupDevice...
[ INFO] [1591248676.101292902]: JSON file is not provided
[ INFO] [1591248676.101301723]: ROS Node Namespace: camera
[ INFO] [1591248676.101310802]: Device Name: Intel RealSense D435
[ INFO] [1591248676.101318799]: Device Serial No:<PHONE_NUMBER>12
[ INFO] [1591248676.101325535]: Device physical port: 2-2-13
[ INFO] [1591248676.101333247]: Device FW version: <IP_ADDRESS>
[ INFO] [1591248676.101340388]: Device Product ID: 0x0B07
[ INFO] [1591248676.101346974]: Enable PointCloud: On
[ INFO] [1591248676.101354368]: Align Depth: Off
[ INFO] [1591248676.101363301]: Sync Mode: On
[ INFO] [1591248676.101392006]: Device Sensors:
[ INFO] [1591248676.101424186]: Stereo Module was found.
[ INFO] [1591248676.101438658]: RGB Camera was found.
[ INFO] [1591248676.101454917]: (Fisheye, 1) sensor isn't supported by current device! -- Skipping...
[ INFO] [1591248676.101462577]: (Fisheye, 2) sensor isn't supported by current device! -- Skipping...
[ INFO] [1591248676.101469876]: (Pose, 0) sensor isn't supported by current device! -- Skipping...
[ INFO] [1591248676.101485558]: Add Filter: pointcloud
[ INFO] [1591248676.101802568]: num_filters: 1
[ INFO] [1591248676.101812913]: Setting Dynamic reconfig parameters.
[ INFO] [1591248681.023335534]: Done Setting Dynamic reconfig parameters.
[ INFO] [1591248681.055454498]: depth stream is enabled - width: 1280, height: 720, fps: 30, Format: Z16
[ INFO] [1591248681.078775351]: color stream is enabled - width: 1280, height: 720, fps: 30, Format: RGB8
[ INFO] [1591248681.078805906]: setupPublishers...
[ INFO] [1591248681.080659996]: Expected frequency for depth = 30.00000
[ INFO] [1591248681.098494623]: Expected frequency for color = 30.00000
[ INFO] [1591248681.113088966]: setupStreams...
[ INFO] [1591248681.215079655]: insert Depth to Stereo Module
[ INFO] [1591248681.215114494]: insert Color to RGB Camera
04/06 13:31:21,303 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
[ INFO] [1591248681.460607898]: SELECTED BASE:Depth, 0
[ INFO] [1591248681.468159419]: RealSense Node Is Up!
04/06 13:31:21,500 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:21,560 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:21,732 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:21,813 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:21,907 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
[ WARN] [1591248682.033829260]: Hardware Notification:RT IC2 Config error,1.59125e+12,Error,Hardware Error
[ERROR] [1591248682.033856734]: Performing Hardware Reset.
04/06 13:31:22,044 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:22,125 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:22,306 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:22,605 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:22,675 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:22,936 ERROR [140198964864768] (uvc-streamer.cpp:106) uvc streamer watchdog triggered on endpoint: 132
04/06 13:31:23,104 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:23,114 ERROR [140198443935488] (uvc-streamer.cpp:106) uvc streamer watchdog triggered on endpoint: 130
04/06 13:31:23,115 WARNING [140198964864768] (messenger-libusb.cpp:30) reset_endpoint returned error, index: 132, error: Protocol error, number: 71
04/06 13:31:23,129 WARNING [140198443935488] (messenger-libusb.cpp:30) reset_endpoint returned error, index: 130, error: Protocol error, number: 71
04/06 13:31:23,129 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:23,188 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:23,199 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:23,258 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:23,269 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:23,328 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:23,339 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No data available, number: 61
04/06 13:31:23,374 WARNING [140198964864768] (messenger-libusb.cpp:92) usb_request_queue returned error, endpoint: 132 error: No such device, number: 19
04/06 13:31:23,374 ERROR [140198964864768] (uvc-streamer.cpp:138) failed to submit UVC request, error: -13
04/06 13:31:23,374 WARNING [140198964864768] (messenger-libusb.cpp:92) usb_request_queue returned error, endpoint: 132 error: No such device, number: 19
04/06 13:31:23,374 ERROR [140198964864768] (uvc-streamer.cpp:138) failed to submit UVC request, error: -13
04/06 13:31:23,374 WARNING [140199250085632] (messenger-libusb.cpp:92) usb_request_queue returned error, endpoint: 135 error: No such device, number: 19
04/06 13:31:23,374 WARNING [140198443935488] (messenger-libusb.cpp:92) usb_request_queue returned error, endpoint: 130 error: No such device, number: 19
04/06 13:31:23,374 ERROR [140198443935488] (uvc-streamer.cpp:138) failed to submit UVC request, error: -13
04/06 13:31:23,374 WARNING [140198443935488] (messenger-libusb.cpp:92) usb_request_queue returned error, endpoint: 130 error: No such device, number: 19
04/06 13:31:23,374 ERROR [140198443935488] (uvc-streamer.cpp:138) failed to submit UVC request, error: -13
04/06 13:31:23,389 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:23,399 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:23,399 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:23,409 ERROR [140199224907520] (error-handling.cpp:68) Error during polling error handler: usb device disconnected
04/06 13:31:23,499 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:23,509 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:23,609 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:23,620 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:23,720 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:23,730 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:23,830 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:23,840 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:23,940 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:23,950 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:24,050 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:24,061 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:24,161 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:24,171 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:24,271 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:24,281 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:24,381 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:24,391 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:24,409 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:24,419 ERROR [140199224907520] (error-handling.cpp:68) Error during polling error handler: usb device disconnected
04/06 13:31:24,492 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:24,502 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:24,602 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:24,612 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:24,712 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:24,722 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:24,822 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:24,833 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:24,933 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:24,943 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:25,043 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:25,053 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:25,153 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:25,163 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:25,264 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:25,274 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:25,374 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:25,384 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:25,419 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:25,429 ERROR [140199224907520] (error-handling.cpp:68) Error during polling error handler: usb device disconnected
04/06 13:31:25,484 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:25,494 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:25,594 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:25,605 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:25,705 WARNING [140199250085632] (messenger-libusb.cpp:42) control_transfer returned error, index: 768, error: No such device, number: 19
04/06 13:31:25,715 ERROR [140199266871040] (global_timestamp_reader.cpp:188) Error during time_diff_keeper polling: usb device disconnected
04/06 13:31:25,718 WARNING [140198443935488] (messenger-libusb.cpp:105) usb_request_cancel returned error, endpoint: 130 error: No such device, number: 19
04/06 13:31:25,718 WARNING [140198443935488] (messenger-libusb.cpp:105) usb_request_cancel returned error, endpoint: 130 error: No such device, number: 19
04/06 13:31:25,718 WARNING [140198443935488] (messenger-libusb.cpp:30) reset_endpoint returned error, index: 130, error: No such device, number: 19
04/06 13:31:25,728 WARNING [140199250085632] (messenger-libusb.cpp:105) usb_request_cancel returned error, endpoint: 135 error: No such device, number: 19
04/06 13:31:25,749 WARNING [140198964864768] (messenger-libusb.cpp:105) usb_request_cancel returned error, endpoint: 132 error: No such device, number: 19
04/06 13:31:25,749 WARNING [140198964864768] (messenger-libusb.cpp:105) usb_request_cancel returned error, endpoint: 132 error: No such device, number: 19
04/06 13:31:25,749 WARNING [140198964864768] (messenger-libusb.cpp:30) reset_endpoint returned error, index: 132, error: No such device, number: 19
[camera/realsense2_camera-2] process has finished cleanly
log file: /home/wang/.ros/log/5dd829a8-a5f7-11ea-90d9-00d861d2211d/camera-realsense2_camera-2*.log

In your log, there is repeated occurrence of the control_transfer returned error.  When these errors occur continuously (because the launch program is re-trying the connection until it works), it can suggest that there is a serious problem with communication between the code and the device.
Sometimes topics are able to be correctly published in RViz despite the continuous errors.  Is there any camera imagery viewable in RViz whilst the errors are occurring, please?

Hi @WaWoWaWa  Do you require further assistance with this case please?   Thanks!

Case closed due to no further comments received.

why close this issue?
Is there any update? Still meet the exact same problem and need help!

@haoyuanz13  If there is no further comments received on a case after a certain period of time after we have responded then the case is closed.  If you have a similar issue, please create a new case on the front page of the GitHub by clicking the New Issue button.  Thanks!
https://github.com/IntelRealSense/librealsense/issues


Enhance provoc with GLM and Flexible Data Handling

Refactored provoc to support formula-based inputs and user-defined lineages, improving data handling flexibility and alignment with binomial glm.

General:

[x] Remove "Imports" Section:
[x] Use provoc::: for any internal function calls within the source code.

Default Parameter:

[x] Ensure the function can operate with by = NULL as the default parameter setting for better handling of multiple samples in a file

Function Optimization:

[x] Replace glm() with provoc::provoc_optim() for fitting purposes. This change is essential to ensure estimates are positive, sum to less than 1 through constrained optimization, and use a linear link function instead of the logistic link function.

@examples Chunk:

[x] Make sure the @examples section in docs can run in a clean environment, assuming the package is loaded. Include basic code applying this function to Baaijens as part of the examples.

Handling of mutation_defs:

[x] Review the implementation of mutation_defs to ensure it matches mutation names in the data correctly. This involves checking the matrix dimensions are correctly indexed by mutation and variant names and utilizing provoc::fuse() or a better implementation for this purpose.
[x] Implement a check to confirm that lineage names in mutation_defs are present to catch potential typos from the user.

Data and Lineage Names Handling:

[x] Modify the code to not expect lineage names as columns in the input data unless mutation_defs is provided, considering most users won't have lineage-related columns in their original datasets -> met through fuse

Output Object Requirements:

[x] Ensure the output object contains all necessary information for the predict.provoc(), to facilitate accurate predictions.

Parse_Mutations Improvements:

[x] Initialize new_muts vector before loop
[x] Turn new_muts into a dataframe


StartsWith/Contains/EndsWith/Like - .NET Core 3.1 Doesn't seem to work even following examples in other tickets

I have an entity with a string Name property.
I'm trying to use dynamic linq to do a contains.
dbSet.Where(p => p.Name.Contains("somestring") works fine.
I've tried adding the static method for Like and doing this (with config having a customtypeprovider that includes the context as a type)
dbSet.Where(config, "dbContextName.Like(Name, "somestring"))
This fails saying that it can't interpret it.
I looked here from the sources: https://stackoverflow.com/questions/46212704/how-do-i-write-ef-functions-extension-method
but couldn't figure out how that applied in this case because the original wasn't tagged as a DbFunction.
Can someone once and for all answer how this is supposed to be done correctly with Dynamic Linq? (and perhaps the different variations for different versions of EF Core/EF full?)
Thanks!

Why would you need a custom function?
In EF3, these statements are already translated correctly?

Because I'm building up oData queries based on custom parsing since the odata package is completely borked and useless for .NET Core 3.1 STILL and we're out of support for .NET Core 2.2 so I don't have time to wait for them to get around to doing what they should have done 6 months ago.

1] Did you see these examples (for EF 2.x)?

https://github.com/StefH/System.Linq.Dynamic.Core/blob/6fc7fcc43b248940560a0728c4d181e191f9eec1/src-console/ConsoleAppEF2.0/Database/TestContext.cs#L24
https://github.com/StefH/System.Linq.Dynamic.Core/blob/6fc7fcc43b248940560a0728c4d181e191f9eec1/src-console/ConsoleAppEF2.0/Program.cs#L104

2] Does Microsoft.AspNetCore.OData "7.3.0" not work for you when using Microsoft.EntityFrameworkCore.SqlServer "3.1.1" ?
3] Actually I was also thinking on writing a OData parser which uses this project to dynamically generate the where clauses. Do you plan to release this as an open source project ?

4] I see your point. When using in EF 3, I get:
System.InvalidOperationException: 'The LINQ expression 'DbSet<Car>
    .Where(c => TestContext.Like(
        matchExpression: c.Brand,
        pattern: "%a%"))' could not be translated. Either rewrite the query in a form that can be translated, or switch to client evaluation explicitly by inserting a call to either AsEnumerable(), AsAsyncEnumerable(), ToList(), or ToListAsync(). See https://go.microsoft.com/fwlink/?linkid=2101038 for more information.'

@StefH   so, I'm using this https://github.com/codecutout/StringToExpression to parse the odata syntax. The one built in only works for odatav4, I have some bugs in there and am working on PRs to get OData4 working. So far I have essentially everything working for $filter.
The order by is the tricky part. It fails when I try and generate them using expressions. I'm trying to figure out why, and realized that all of the examples in this project are commented out for .net Core 3.1 so I can't use them to generate my order bys although they do work. I'd just rather not have a dependency on this project entirely because then my coders will use it instead of doing the right thing and we'll get SQL Injections... (been there, seen the movie.)

I think this is what was being asked here but I'm trying to do something like so:
IQueryable<T> results = source.Where($"{column} LIKE \"%@0\"", value);

Right now, it appears there is no support for this. I tried your example above using EF.Functions.Like, but it won't work. I see you use a custom parser config but I would prefer not do that since that seems like a lot of work for our app just to get a dynamic LIKE operation. It would be nice for this to be an out-of-the-box functionality in here.

Never mind, Just tried:
IQueryable<T> results = source.Where($"{column}.Contains(\"{value}\")");

That worked.


Build fails with NativeScript 6.5 ./gradlew (failed with exit code 1)

The build process of my NS-Vue project started failing after I updated NativeScript (from 6.2 to 6.5) and it seems to have something to do with this library. I've also written a Stack Overflow post about the problem. However, I could now verify that the error occurs only when nativescript-sqlite is installed in the project. When I remove the library, the error disappears.
I've been having difficulties debugging the problem. At first I thought it was a webpack problem (as I was only running tns run android and getting exit code 0 from webpack) but after running the build command with the debug flag I noticed that gradlew build fails. This is the stack trace, which is not very informative:
Error: Command ./gradlew failed with exit code 1
    at Errors.failWithOptions (/usr/local/lib/node_modules/nativescript/lib/common/errors.js:149:28)
    at Errors.fail (/usr/local/lib/node_modules/nativescript/lib/common/errors.js:120:21)
    at GradleCommandService.<anonymous> (/usr/local/lib/node_modules/nativescript/lib/services/android/gradle-command-service.js:42:30)
    at Generator.throw (<anonymous>)
    at rejected (/usr/local/lib/node_modules/nativescript/lib/services/android/gradle-command-service.js:5:65)
    at process._tickCallback (internal/process/next_tick.js:68:7)

I figured it might have something to do with the library trying to import non-existent optional plugins so I tried removing the function definitions of and calls to TryLoadingEncryptionPlugin and TryLoadingSyncPlugin (as the project is only using the Commercial one), but to no avail. I have also tried adding the non-used plugins to webpack externals as per the docs but that never seemed to have any effect (the warnings remain despite pushing to externals even when the project is using NativeScript 6.2.1, in which case the build doesn't fail).
So far I haven't been able to get any more specific info as to what actually causes the error, only that it doesn't occur if nativescript-sqlite isn't installed. Any ideas what it could be about or how to debug?
Here are the parts I thought are relevant from my current package.json:
  "nativescript": {
    ...
    "tns-ios": {
      "version": "6.5.0"
    },
    "tns-android": {
      "version": "6.5.0"
    }
  },
  "dependencies": {
    ...
    "@nativescript/core": "^6.5.1",
    "@vue/devtools": "^5.3.3",
    "nativescript": "^6.5.0",
    "nativescript-sqlite": "file:nativescript-sqlite",
    "nativescript-sqlite-commercial": "file:commercial-sqlite-2.4.0/nativescript-sqlite-commercial-1.3.2.tgz",
    "nativescript-vue": "^2.6.1",
    "nativescript-vue-devtools": "^1.4.0",
    "tns-core-modules-widgets": "^6.5.0",
    ...
  }
  "devDependencies": {
    ...
    "nativescript-dev-webpack": "~1.5.1",
    "nativescript-vue-template-compiler": "^2.6.0",
    "vue-loader": "^15.9.1"
    ...
  },

The package nativescript-sqlite is also version 2.4.0.

Actually this is a bug in the NS-Webpack loader 0.11.    You need to downgrade it to v0.10 and it will work.  I already have a PR to fix the loader; but it hasn't been pushed out yet...

Great, thanks, this solved my problem! :slightly_smiling_face:
In case anyone else reads this and has the same problem, the actual name of the package that needs to be downgraded to v0.10 is nativescript-worker-loader

Another thing that caused this for me, was not putting quotes around the keystore passwords on release. Drove me insane.


Updating QoS details

The details around apple-based systems was provided by root tools team.
More info can be found in IcM 255743269

@JohanFreelancer9 Copy editing is needed for this PR. Thanks.

@cichur PR has been copyedited and is ready for final review, could you please check and merge? Thanks!


Bump Node version from 16.X to 18.16.X

Bumps Node version from 16.X to 18.16.X (the latest LTS available)

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+0.02%) to 92.106%

Totals

Change from base Build<PHONE_NUMBER>:
0.02%

Covered Lines:
4145

Relevant Lines:
4391

💛  - Coveralls


running fine tuning on a custom dataset

Hello, congratulations on your work and thanks for sharing your code.
I'm currently trying to run fine-tuning using a single GPU and a custom dataset (around 3k samples), but I keep getting CUDA out of memory error. Is there any parameter I can adjust for the code to require less memory?
Thanks!

I was able to successfully run fine-tuning after a few modifications in the code to fit my dataset, and also decreasing batch_size.

Hi Amanda, can you share how more about the way you set up your train/val data as well as what code modifications you focused on for a custom dataset? I'm trying to do this using the CUB-200-2011 (birds) dataset.

Hi @uthillaivasan :) I implemented a custom pytorch dataset class to be able to load my data as it is on the docs. That way, I was able to re-use some classes implemented by the authors. Also, in my case, I'm dealing with a multi-label dataset, so I had to make adjustments to the loss functions etc. Currently I am able to successfully run the supervised supervised fine-tuning proposed by the authors with these changes I mentioned; but I am still working on properly adjusting the code to run the pre-training step. Do you plan to run pre-training or fine-tuning?
In case of running the pre-training, I believe we have to also implement a new sampler for the support set, as recommended by the author in https://github.com/facebookresearch/suncet/issues/19#issuecomment-900403043. I'm still working on this, but will be glad to share what changes were necessary once I'm done :)


fix wrong link to using.md from helm-get-started.md

They are both in the same folder.

Thanks for the fix @tlvu - my bad.


Sts assume role is not working for "privesc-cfUpdateStack"

I am unable to run aws cli commands as this role "privesc-cfUpdateStack"

OS, Desktop/Mobile, Browser, Date/Time,

There is a typo in credentials file. Creating a pull request for the same.


Is is possible to automatically disconnect old device when pushing stream from a new device with Airplay?

Hi if you mean disconnecting from AirPlay I don't think that's possible because the airplay interface is very limited. Let me know if I misunderstood the question.


Functionality of writing back Tflite model with multiple subgraphs that is currently loaded in the Tflite Interpreter.

Please make sure that this is a feature request. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:feature_template
System information

TensorFlow version (you are using): 2.3.1
Are you willing to contribute it (Yes/No): No

Describe the feature and the current behavior/state.
We can currently write model that have single subgraph using tflite::SubgraphWriter present in  tensorflow/lite/experimental/writer/writer_lib.h . For my use case I need to update some model weights without converting a new model. So I load model in interpreter, update its weights and write it back to the disk.
Below is example of loading a model and writing it back. And I can use the rewritten model for future inference.
//load model
std::unique_ptr<tflite::FlatBufferModel> model =
tflite::FlatBufferModel::BuildFromFile("model.tflite");

//build interpreter
tflite::ops::builtin::BuiltinOpResolver resolver;
std::unique_ptr<tflite::Interpreter> interpreter;
tflite::InterpreterBuilder(*model,resolver)(&interpreter);

interpreter->AllocateTensors();

//write out subgraph
std::cout<<"writing out single subgraph"<<std::endl;

tflite::SubgraphWriter(interpreter->subgraph(0)).Write("model.tflite");

But problem occurs when the model has multiple subgraphs e.g when model contains while_loop. In that case I am unable to write it back completely as writer api is made to write a single subgraph. If I write back a model containing while_loop  same code as above and load the model again and allocate tensors I get following error.
   ERROR: tensorflow/lite/kernels/while.cc:136 op_data->cond_subgraph_index < subgraphs->size() was not true.
   ERROR: Node number 0 (WHILE) failed to prepare.

The script for model containing while is:
import tensorflow as tf
import tensorflow.compat.v1 as tfv1

tfv1.disable_eager_execution()
with tfv1.Session(graph = tf.Graph()) as sess:
   i = tfv1.placeholder(shape = (5,1),dtype = tf.float32)
   a = tfv1.placeholder(shape = (5,1),dtype = tf.float32)
   z = np.zeros(1)
   k = tf.constant(z,dtype = tf.int32,shape=(1,))
   c = lambda i,a,k: tf.less(k,10)
   b = lambda i,a,k:(tf.add(i,a),tf.add(a,a),(k+1),)
   r = tf.while_loop(c,b,[i,a,k])
   converter = tfv1.lite.TFLiteConverter.from_session(sess,[i,a],[r[0]])
   model = converter.convert()
   with open('model.tflite','wb') as model_file:
      model_file.write(model)

Will this change the current api? How?
In the writer_lib there would be an extra api that would take interpreter as input (or all interpreter subgraphs), and write back a tflite model that is represented by its subgraphs.
@abattery, @tensorflower-gardener could be please give any insights in this or any workaround to this problem.
Who will benefit with this feature?
Use cases that needs to update weights of the model can do that by just passing updated parameters instead of converting and downloading the whole model.
Any Other info.

Hi @jvishnuvardhan, could you please provide any insights or workaround to this problem.

@abattery, @tensorflower-gardener could be please give any suggestion on how to solve this problem.

Hey @ramanps05 we don't have a concrete timeline for this yet, but I will take a look at this next week or so.

Hi @srjoglekar246 , thanks for the update. I also wanted to ask if functionality to do this task is already there but I can't figure it out.

It essentially boils down to making the writer write all subgraphs in the Interpreter, instead of just the primary_subgraph. The TFLite Interpreter has subgraph(index) & subgraphs_size() methods that we can use to accomplish this.
Feel free to give it a try if feel inclined :-).

I tried the following method -
    FILE * fp = fopen("while_rewrite.tflite","wb");
    if(!fp)
        std::cout<<"file open failed"<<std::endl;
    // the current model has 3 subgraphs
    for(int i=0;i<3;i++){
        tflite::SubgraphWriter writerx(interpreter->subgraph(i));
        std::unique_ptr<uint8_t[]> temp_buffer;
        size_t temp_size =0;
        writerx.GetBuffer(&temp_buffer,&temp_size);
        if(fwrite(temp_buffer.get(),1,temp_size,fp)!=temp_size){
            std::cout<<"writer failed"<<std::endl;
        }
        temp_buffer.reset();

    }
    fclose(fp);

But it didn't work, when I am loading the model again I a still getting the same error.
ERROR: tensorflow/lite/kernels/while.cc:136 op_data->cond_subgraph_index < subgraphs->size() was not true.
ERROR: Node number 0 (WHILE) failed to prepare.

Here I have written all subgraphs in a single file. I think I am missing out on some key information about subgraphs in implementing it.

Hmm. This looks like a bug with the writer. Lemme take a look and get back to you.

Hi @srjoglekar246, were you able to resolve this.

Started looking into this.
For your Control Flow conversion to work, you need to use the TF2 converter like this:
class CFModel(tf.Module):
  @tf.function(
      input_signature=(
          tf.TensorSpec(shape=[5, 1], dtype=tf.float32, name='i'),
          tf.TensorSpec(shape=[5, 1], dtype=tf.float32, name='a'),
      ))
  def cf_model(self, i, a):
    z = np.zeros(1)
    k = tf.constant(z,dtype = tf.int32,shape=(1,))
    c = lambda i,a,k: tf.math.less(k,10)
    b = lambda i,a,k: (tf.add(i,a),tf.add(a,a),(k+1),)
    r = tf.while_loop(c,b,[i,a,k])
    return r[0]

def main(argv):
  to_save = tf.saved_model.save(
      CFModel(), '/path/to/folder')
  converter = lite.TFLiteConverterV2.from_saved_model(
      '/path/to/folder')
  tflite_model = converter.convert()
  open('/path/to/folder/model.tflite',
       'wb').write(tflite_model)

Now the writer tool needs to be refactored to write multiple subgraphs into a single flatbuffer builder. Working on that...

Does changing converter method from from_session to from_saved_modelchange how tflite flatbuffer represents while?
because I think it will have a difference in that case.

It shouldn't change how WHILE is represented, its just that the TF1 converter may not use our new MLIR converter that converts WHILE (if it does for you in float, maybe you are already using the new converter).
Technically, the code I posted should produce the same TFLite model for you (in terms of what it does).

Okay, but I think that TF1 from_session converter use mlir converter because during converstion process I see logs with tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc

Aah, then great. It safer to use from_saved_model though, since we usually update that API with newer conversion features (mainly because SavedModel is now TF's recommended model format).

I use from_session mainly because it is easier to have inputs with varying first dimensions, and in case of multiple outputs I can easily name them according to my choice. I am not able to name outputs in the case of from_saved_model, according to my choice.
Were you able to write multiple subgraphs with your approach. I feel like in while_loop one of the subgraphs is inherently different (I think it's cond_subgraph) from others, because if I write them separately, I am able to view two of them in netron but not the middle one.

@srjoglekar246 , were you able to resolve the bug in writer tool.

Hi @srjoglekar246 , I am also facing this issue with writing back while loop op since it has multiple subgraphs.
When writing subgraphs in loop using the SubgraphWriter, i am not able to wrige the conditional subgraph alone.
Were you able to solve the bug ?

I am currently on vacation, but I have made progress on this. There are
some internal usages of this tool, so I have to be careful not to break
anyone. This should be fixed within a week once I come back in office
Tuesday. Sorry about the delay :(
On Fri, Nov 27, 2020 at 8:17 AM prasan001<EMAIL_ADDRESS>wrote:

Hi @srjoglekar246 https://github.com/srjoglekar246 , I am also facing
this issue with writing back while loop op since it has multiple subgraphs.
When writing subgraphs in loop using the SubgraphWriter, i am not able to
wrige the conditional subgraph alone.
Were you able to solve the bug ?
—
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Thanks @srjoglekar246 for the update.

Hi @srjoglekar246 , how is the issue resolution coming along.

The code is under active review, so should be submitted soon :-)

Thanks @srjoglekar246 ,

Hey @srjoglekar246,
Great to hear that you made progress.
Is the patch ready ?
I tried by looping around each subgraph but still i am not able to write the conditional subgraph properly.
Could you please tell how did you approach or share the patch.

@prasan001 The patch requires more work than simply looping over the subgraphs :-).
The end result is an API like ModelWriter, similar to SubgraphWriter, that takes in an Interpreter* ptr. We need to maintain common data structures for entities common to the graph (op codes, buffers, etc)
Will report back once the code changes are in.

Hi @srjoglekar246, thanks for the details. Are the changes in.

The changes just went in.

@ramanps05  or @prasan001 could you check if the solution works? I also added a README to the directory, so that might be helpful.

Thanks @srjoglekar246 ,
Though the model writer is still not working for me when I tested using a while loop tflite model.
This was my script for testing writing back the model
tflite::FlatBufferModel::BuildFromFile("model_while.tflite");

//build interpreter
tflite::ops::builtin::BuiltinOpResolver resolver;
std::unique_ptr<tflite::Interpreter> interpreter;
tflite::InterpreterBuilder(*model,resolver)(&interpreter);

interpreter->AllocateTensors();

//write out subgraph
tflite::ModelWriter writer(interpreter.get());
std::string filename = "model_while_rewrite.tflite";
writer.Write(filename);

When I try to load the rewritten model, I get the error

ERROR: Invalid tensor index 7 in node outputs. The subgraph has 7 tensors

ERROR: tensorflow/lite/kernels/while.cc:144 cond_subgraph->outputs().size() != 1 (0 != 1)
ERROR: Node number 0 (WHILE) failed to prepare.

Also, the written model is slightly smaller in shape. Original model, which I converted using the following script

Started looking into this.
For your Control Flow conversion to work, you need to use the TF2 converter like this:
class CFModel(tf.Module):
  @tf.function(
      input_signature=(
          tf.TensorSpec(shape=[5, 1], dtype=tf.float32, name='i'),
          tf.TensorSpec(shape=[5, 1], dtype=tf.float32, name='a'),
      ))
  def cf_model(self, i, a):
    z = np.zeros(1)
    k = tf.constant(z,dtype = tf.int32,shape=(1,))
    c = lambda i,a,k: tf.math.less(k,10)
    b = lambda i,a,k: (tf.add(i,a),tf.add(a,a),(k+1),)
    r = tf.while_loop(c,b,[i,a,k])
    return r[0]

def main(argv):
  to_save = tf.saved_model.save(
      CFModel(), '/path/to/folder')
  converter = lite.TFLiteConverterV2.from_saved_model(
      '/path/to/folder')
  tflite_model = converter.convert()
  open('/path/to/folder/model.tflite',
       'wb').write(tflite_model)

Now the writer tool needs to be refactored to write multiple subgraphs into a single flatbuffer builder. Working on that...

has size 2712 bytes while the rewritten model has size 1948 bytes. So it looks like it is not writing the whole model.

@ramanps05 The smaller size is expected, mainly because the tool skips writing parts of the model that are unnecessary or default (like strings, empty quantization params, etc).
I re-ran the tool on the model generated from that script, and it seems to run fine with our benchmark tool. I saw a visualization of the re-written model & it seems to have one input on the subgraph. See the attached re-written model.
Can you post your inference code?
rewritten.tflite.zip

Hi @srjoglekar246,
I tried generating the model using the sample script you shared above for while loop, and got the same error as @ramanps05.
The below is the code i was running:
tflite::FlatBufferModel::BuildFromFile("while_model.tflite");

tflite::ops::builtin::BuiltinOpResolver res;

std::unique_ptr<tflite::Interpreter> interpreter;

tflite::InterpreterBuilder(*model, res)(&interpreter);

interpreter->AllocateTensors();

writer(interpreter.get()); std::string filename = "rewritten_while_model.tflite";

writer.Write(filename);

First time, i load the while model and write the model using your ModelWriter as above.
Then if I try to build interpreter on the rewritten while model, i was also getting same error as @ramanps05
ERROR: Invalid tensor index 7 in node outputs. The subgraph has 7 tensors.
ERROR: tensorflow/lite/kernels/while.cc:144 cond_subgraph->outputs().size() != 1 (0 != 1)
ERROR: Node number 0 (WHILE) failed to prepare.

I suspect we are missing something while handling the outputs of conditional subgraph.

@ramanps05 The smaller size is expected, mainly because the tool skips writing parts of the model that are unnecessary or default (like strings, empty quantization params, etc).
I re-ran the tool on the model generated from that script, and it seems to run fine with our benchmark tool. I saw a visualization of the re-written model & it seems to have one input on the subgraph. See the attached re-written model.
Can you post your inference code?
rewritten.tflite.zip

@srjoglekar246  I am attaching my inference code.
while_test.zip
It runs fine for the first time. But gives the error as mentioned above if I run it again.

hi @srjoglekar246 , could you look at whether we are using ModelWriter correctly or not.

Yup, taking a look...

@ramanps05 @prasan001 Could you try the model in the zipped file on the above comment? Does that also give an error, like your re-written model?
Also, could you try with a different file-name for the rewritten model?

HI @srjoglekar246 ,

yes I used your model that you have sent. I was able to run it for the first run, i.e load and execute but when I rewrote the model using https://github.com/tensorflow/tensorflow/files/5714929/while_test.zip I was not able to load it again.
Also, even if I try using a different file name, I am still getting the same issue.

If you were able to rewrite it and there is no issue in my model writing approach, than there might be difference in the way we are building the intrepreter or/and generating the model. I am using python api to convert the model to tflite.

Attached is the model I got from serializing the rewritten model. If that doesn't work for you, then there might be an issue with your model-running code. I get an output like this:
Output of the model is -
0
0
0
0
0

is that correct?
Note that my scripts for serialization & evaluating are different. (I don't see how that should affect things if you use different file names for loading & serializing the interpreter). My inference code:
  std::string model_file_path = ".../rewritten2.tflite";
  std::unique_ptr<FlatBufferModel> model;
  std::unique_ptr<ops::builtin::BuiltinOpResolver> resolver;
  std::unique_ptr<Interpreter> interpreter;
  model = FlatBufferModel::BuildFromFile(model_file_path.c_str());
  resolver.reset(new ops::builtin::BuiltinOpResolver);
  InterpreterBuilder(*model, *resolver)(&interpreter);
  if (!interpreter) {
    return kTfLiteError;
  }

  interpreter->AllocateTensors();

  float* input_1 = interpreter->typed_input_tensor<float>(0);
  float* input_2 = interpreter->typed_input_tensor<float>(1);

  for (int i = 0; i < 5; i++) {
    input_1[i] = 0;
    input_2[i] = i + 1;
  }

  // print outputs
  float* inf_output = interpreter->typed_output_tensor<float>(0);
  std::cout << "\nOutput of the model is - \n";
  for (int i = 0; i < 5; i++) {
    LOG(INFO)  << inf_output[i] << ' ';
  }

For serializing, I use tensorflow/lite/tools/serialization/writer.cc
rewritten2.tflite.zip

@srjoglekar246 you are getting 0 output because you are not doing interpreter->Invoke() before reading the outputs.
Though I am still getting the error while loading the rewritten model.

Tf workspace - tf master, cloned about an hour before, with head on commit b220d07eab20c869a31cc660bf497552d710cfc9

Build file and cpp - tflite_test.zip

Model writer include path - #include "tensorflow/lite/tools/serialization/writer_lib.h"

Model writer usage - tflite::ModelWriter writer(interpreter.get()); std::string filename = "model_while.tflite"; writer.Write(filename);

Error on running second time -

ERROR: Invalid tensor index 7 in node outputs. The subgraph has 7 tensors

ERROR: tensorflow/lite/kernels/while.cc:144 cond_subgraph->outputs().size() != 1 (0 != 1)
ERROR: Node number 0 (WHILE) failed to prepare.

Segmentation fault (core dumped)```

Model is same as this https://github.com/tensorflow/tensorflow/files/5731247/rewritten2.tflite.zip

I think I found whats wrong. The original authors of the tool added a condition that prevents writing tensors whose allocation type doesn't match some pre-set values. The model in question contains a dynamic tensor (whose output shape isn't known until runtime), and it doesn't get serialized because of that condition.
Maybe you could try remove this if- block in writer_lib.cc:
if (tensor->allocation_type != kTfLiteArenaRw &&
          tensor->allocation_type != kTfLiteMmapRo &&
          tensor->allocation_type != kTfLiteArenaRwPersistent)
        continue;

Does that fix the issue?
I will send a change that should hopefully fix this.

Hi @srjoglekar246 , I tried the above method. It worked for the simple while loop that I have shared with you. But I got segmentaion fault while writing another model using it. The model has while loops as well as many other operations. I will not be able to share the model with you due to privacy reasons.
But simply commenting if loop is breaking something else, at least that I can say.
I will further try to test in which operation it is causing the problem, and let you know if I find anything.

We found a another bug related to variable tensors (for LSTMs etc), which we are about to fix.
Since this tool was written a while back for some limited use-cases, unfortunately you would need to debug where the error is yourself :-(
I don't have too many cycles to debug myself, but I can help landing any bug-fixes you figure out.

My model has LSTMs too, so that might be the bug. Though there could also be something else too. I will try to find if any other bug is there.

FYI, we just landed the fix for LSTMs. Do check your model again, to see if the issue is fixed?

Hi @srjoglekar246 , I checked the new fix with my model. It was same as before i.e not working for my model. I did some debugging and found that the model is failing for matmul operation.

If I use current model_writer in tf master, while_loop is written back fine but for any model involving matmul op I am getting following during model writing.
seg fault - nullptr dereference in ExportTensor
I am attaching two models that I used for testing one is a single matmul operation and other is matmul followed by while loop.

I think the library isn't handling optional tensors right (the 3rd input to Matmul is optional for TFLite).
Can you try to add the following line here:
if (!tensor->bytes && !tensor->dims) continue;

This skips trying to write a null tensor.

HI @srjoglekar246 , thanks it worked. But would it cause any problem with other operations ?

HI @srjoglekar246 , thanks it worked. But would it cause any problem with other operations ?

I don't think so; it only fixes behavior for optional tensors

I don't think so; it only fixes behavior for optional tensors

Hi @ramanps05 !
We are checking to see whether you still need help in this issue . It seems to be resolved from above comment.
Can you share the working script on splitting the lite model into subgraphs for other community members with same need.
Thank you!

@ramanps05,
The mentioned functionality of writing back TFlite model with subgraphs was implemented with the 93cbb14 commit.
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/kernels/subgraph_test_util.cc#L117
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/tools/serialization/writer.cc#L37
Also please take a look at this commit file for the reference.
https://github.com/tensorflow/tensorflow/commit/6de1358c3398428c2c55aa36302235a076393fc9
int node_index;
subgraph->AddNodeWithParameters({kInput1, kInput2}, {kOutput}, {}, nullptr, 0,
                                params, add_reg, &node_index);

tflite::InterpreterBuilder(*model, builtin_op_resolver)(&interpreter);
  tflite::ModelWriter writer(interpreter.get());

Also please take a look at the comment from the developer where it was asked to add the lines with the code
https://github.com/tensorflow/tensorflow/issues/44606#issuecomment-752218244
Thank you!

Closing this as stale. Please reopen if this is still a valid request. Thank you!


Implement improved court finder with no map. #131.

Add some new court finder features - radio button list of court choices. Addresses #131, which also has other items in it.
Test 1 (does not complete):

0 codefs
User enters a valid address
User gets to court finder and sees a radio button list of court choices

I only saw two choices for my court when I went through. I thought there were supposed to be three, so I was confused. Let me know if what I saw was a problem.
[Edit: The address for that was 12 Dudley Street, Boston, Massachusetts 02127]

I now realize that we only have in-state defendants, so I'll get rid of all that complexity.

@mariahjr we should discuss this UX to keep it consistent across interviews. Bentley also pointed out a problem with how the "disable others" interacts with choosing a court, but I don't think using "None of the above" is a good solution. It needs to be more specific.
One idea: Add a labeled "None of the above" option that says "A court not listed above" or something similar.
The note should never be hidden, because it is meant to encourage someone to realize they don't need to select one of the above courts. But I think a correctly worded replacement for "None of the above" can replace the purpose of the note.

I now realize that we only have in-state defendants, so I'll get rid of all that complexity.

The user should have entered the address of their rental unit, but if they moved temporarily we want to at least make sure they don't get an error page. There could be ways to handle that validation when they enter their address, but it needs to be tested.

Good point about a temporary address @nonprofittechy. I will implement a fallback for out-of-state addresses. When this PR is accepted, someone else can handle a new issue for the wording of that fallback page.

instead of "None of the above" use "My case is in another court"
Replace the note with  " Choose your court below"
We think this solves the issues @nonprofittechy raised and we can still make the new note and drop down conditional on the My case is on another court radio button.

Please run new tests @mariahjr , @CaroRob :

[ ] Test 1:

[ ] 0 codefs
[ ] User enters in-state address
[ ] User selects RADIO BUTTON choice
[ ] User gets to end and all is shown correctly

[ ] Test 2:

[ ] 0 codefs
[ ] User enters in-state address
[ ] User chooses "My case is in another court" but DOES NOT SELECT A DROPDOWN CHOICE
[ ] User tries to continue, but cannot continue
[ ] User selects DROPDOWN choice
[ ] User gets to end and all is shown correctly

[ ] Test 3:

[ ] 0 codefs
[ ] User enters OUT-OF-STATE address
[ ] User selects DROPDOWN choice
[ ] User gets to end and all is shown correctly

The drop down choices show F&P and Juvenile courts-- all the courts when they should just show Superior, Housing and District/BMC courts.

Test done so merged, but see comment re: too many court choices.


The delete button does not work

The delete button does not work:

The problem has been solved. Thank you.


New UI: Unable to accept CAL/CLA licencing agreement

Describe the bug
Accepting an agreement doesn't work if you click to the link to the portion via the holding item it's linked to. Can't see any errors in the javascript console or openEquella logs
To Reproduce
Steps to reproduce the behavior:

Ensure you have the new ui enabled
Create/publish item in the Books or Journals collection
Create an item in the eReserve articles collection, and link it to the Books item you created
Go to the item summary page for the item that you created in step 2
In the copyright panel, click Activate, and follow the prompts
Once the attachment has been activated, click the attachment link

In the Copyright agreement dialog that appears, try to click the green Accept button

Expected behavior
Clicking the accept button should display the attachment
Stacktrace
If applicable, a stacktrace to help explain your problem.
Platform:

OpenEquella Version: 2019.1
OS: WIndows
Browser Chrome

This was fixed and tested yeah @mrblippy ?

Oops, i missed this one. Yep, the Accept button now works
@


Add Forceful Trait Weapon Damage Modifiers

Adds options for adding extra damage for forceful weapons. The addition of the _source dice and strikingDice allows for it to account for both striking rune and runic weapon changes.
I believe this will resolve #5974.
The only thing I'm unsure about is if I have add the language template changes in the right place.

We prefer to not add localization keys to the top level without good reason. Those can go somewhere in PF2E.Item.Weapon.

We prefer to not add localization keys to the top level without good reason. Those can go somewhere in PF2E.Item.Weapon.

All adjusted!


tests: move to jest

I simplified the WatcherDetection tests a bit as they take forever to run and make it look like the runner is hanging. Now it just tests orders of magnitude of time (0, 10, 100, 1000)ms and completes much more quickly.
Looking into some small stuff - the benchmark code doesn't seem to be console logging the results properly.
Closes #4499

@cpojer When you get a chance, there are some particularly difficult test suites that make use of process spawning, etc and seem to have issues in CI (though they work okay for me locally.) Wondering if you guys have any tips & tricks for dealing with that sort of thing.

@cpojer When you get a chance, there are some particularly difficult test suites that make use of process spawning, etc and seem to have issues in CI (though they work okay for me locally.) Wondering if you guys have any tips & tricks for dealing with that sort of thing.

If the process is terminated, something bad happens in your test, like process.exit() or something. I recommend running Jest with -i and only the tests that fail, for example.

Going to close this until I have some time to get it up to speed again.


added Incident report History

⚠⚠⚠ Since we do not accept all types of pull requests and do not want to waste your time. Please be sure that you have read pull request rules:
https://github.com/louislam/uptime-kuma/blob/master/CONTRIBUTING.md#can-i-create-a-pull-request-for-uptime-kuma
Tick the checkbox if you understand [x]:

[x] I have read and understand the pull request rules.

Description
Added Incident Report History for the #1100
Fixes #1100
Type of change
Feature addition
Please delete any options that are not relevant.

New feature (non-breaking change which adds functionality)
Other
This change requires a documentation update

Checklist

[x] My code follows the style guidelines of this project
[x] I ran ESLint and other linters for modified files
[x] I have performed a self-review of my own code and tested it
[x] I have commented my code, particularly in hard-to-understand areas (including JSDoc for methods)
[x] My changes generates no new warnings
[ ] My code needed automated testing. I have added them (this is optional task)

Screenshots (if any)
Incident report history list

Incident report history button

Great work! I took a look at the merge guidelines. Will this merge request be accepted?

this feature is i want

if Incident history configurable to be visible on the status page would be even better

if Incident history configurable to be visible on the status page would be even better

definitely able to add this later on just trying to ge tthe base feature out

The status page currently manages incidents.
I would prefer to leave this as a status page concept and add the history there instead.
Having this as a concept like maintenance has advantages and downsides. Without the infra needed, this is currently somewhat confusing to new users as they have likely not figured out where incidents can be created.
If you want to add this to the admin UI as well, this needs better UX from this side. (split error+empty, add a helptext that incidents can be created on status pages)

ok understandable i can do all of this however im not a ui-ux designer would you be able to more in depth describe how this should look

There are a few designs in

#862
(also in this one) #579

There are a few designs in
* [[Feature]: Incident Timeline #862](https://github.com/louislam/uptime-kuma/issues/862)

* (also in this one) [Feature Req: Multiple Incidents on Status Page #579](https://github.com/louislam/uptime-kuma/issues/579)

alot of enterprise solutions look something along the lines of this https://jira-service-management.status.atlassian.com/ would you be willing to use this or no?

alot of enterprise solutions look something

I think you are talking about the difference of having the incident history on a separate page vs on the same page but below.
I don't think that matters that much.
I would prefer that to be tucked away on a separeate page (I suspect that the regular user does not need to have this avaliable) and linked from the page, but if it is below that is fine by me.

alot of enterprise solutions look something

I think you are talking about the difference of having the incident history on a separate page vs on the same page but below. I don't think that matters that much.
I would prefer that to be tucked away on a separeate page (I suspect that the regular user does not need to have this avaliable) and linked from the page, but if it is below that is fine by me.

sounds good i will fix it up and put it on the status page instead

@CommanderStorm what do we think of it now... good to merge?

whats the status of this pr im considering closing and reopening

Sorry
I did not re-review this earlier, because this does not seem done.
You also did not address some of the other changes I requested. For example the request to do i18n...
Also: the API you are calling does not exist => have you tested the code?...
If you are asking about a merge or reject decision, that would be reject.
I can't nurture this to health in master (among other things, because I am going on vacation next month) or fix the things that are left via code reviews.

Sorry
I did not re-review this earlier, because this does not seem done.
You also did not address some of the other changes I requested. For example the request to do i18n...
Also: the API you are calling does not exist => have you tested the code?...
If you are asking about a merge or reject decision, that would be close, but things are not final.. the issues left are fixable, but require work..
I can't nurture this to health in master (among other things, because I am going on vacation next month) or fix the things that are left via code reviews.

ok i will fix this up again thank you very much for understanding

any news about this? Having this will be amazing and it seemed to be stuck in limbo to some degree.
@MasonColoretti are you planning to finish this PR? if not, hopefully, I can try and take over

any news about this? Having this will be amazing and it seemed to be stuck in limbo to some degree.
@MasonColoretti are you planning to finish this PR? if not, hopefully, I can try and take over

Sorry for the late reply...  i am more then willing to let you take this over.


Config File missing

The bsec config is missing from the source files, and as a result when I run any of the BSEC examples a missing file error is generated ,and the IAQ value remains unchanged at 25 with accuracy at 0.
I believe it is this line in bme68xmodule.c that is raising the error.
const char *bsec_conf_path =     "BSEC_<IP_ADDRESS>_Generic_Release_04302021/config/bsec_sel_iaq_33v_4d/2021_04_29_02_51_bsec_h2s_nonh2s_2_0_6_1 .config";
There is no such file in this repository.
In the BSEC library from Bosch the configuration folder has a number of predefined configurations
bsec_serialized_configurations_selectivity (.h and .c)
Perhaps the "bsec_sel_iaq_33v_4d" example "bsec_config_selectivity[2277]" array of ints could be added as a default configuration in  bme68xmodule.c.
Regards
Keith

Did you download the licensed BSEC2.0 library from BOSCH and unzip to the bme68x-python-library-main folder?

Yes of course.
I see that the issue is fixed in the 'Meat and Cheese' version.
Also there is much better BSEC support.
Keith


Execute block on receiver together with exclusive mode

This has been rebased on 0.17.5-release. See #604 for previous discussion.

@Burgestrand thank you very much for doing this!

Can we merge this?

Shouldn't we merge this?

It needs a rebase to be mergeable. I can push it back up and reopen the PR.

Ah yep, perhaps I will have time next week I will take a look if nothing has happened by then.


boards: Move -fno-strict-aliasing from Make.defs to Toolchain.defs

Summary
and migrate MAXOPTIMIZATION into ARCHOPTIMIZATION
Impact
Code refactor
Testing
Pass CI

ping @pkarashchenko

ping @pkarashchenko

PR had merge conflict, so I was not able to merge yesterday. I will merge as soon as CI finishes

@xiaoxiang781216 This is a broken commit, my custom boards can't working properly after i merged with master branch. I'm revert by dichotomy, and finally positioned on this commit.
i delete the following code
ifneq ($(CONFIG_DEBUG_NOOPT),y)
ARCHOPTIMIZATION += $(MAXOPTIMIZATION) -fno-strict-aliasing
endif
in my custom boards Make.defs, but the problem remains

@zouboan So the code building is fine and the behavior of the board is changed? Or it is a build issue that you are reporting?
If it is a build issue then maybe you can share some more details (base arch and base board that you used initially, Make.defs and maybe some parts of the Makefile), so we can identify the root cause.

@pkarashchenko the behavior of the board is changed, It seems that the board to run very slowly, It seems that the optimization doesn't work. my custom boards config as follow:

Debug Options

CONFIG_NDEBUG=y
CONFIG_DEBUG_ALERT is not set
CONFIG_DEBUG_FEATURES is not set
CONFIG_DEBUG_TCBINFO is not set
CONFIG_ARCH_HAVE_STACKCHECK=y
CONFIG_STACK_COLORATION=y
CONFIG_STACK_CANARIES is not set
CONFIG_ARCH_HAVE_HEAPCHECK=y
CONFIG_HEAP_COLORATION is not set
CONFIG_DEBUG_SYMBOLS=y
CONFIG_FRAME_POINTER is not set
CONFIG_ARCH_HAVE_CUSTOMOPT=y
CONFIG_DEBUG_NOOPT is not set
CONFIG_DEBUG_CUSTOMOPT is not set
CONFIG_DEBUG_FULLOPT=y
CONFIG_DEBUG_OPT_UNUSED_SECTIONS=y
CONFIG_DEBUG_LINK_MAP=y

@zouboan could you run "make V=1" and compare the command line difference between the bad output and the good one?

@xiaoxiang781216
before this commit:
CC:  irq/irq_attach.c
arm-none-eabi-gcc -c -fno-common -fno-builtin -ffunction-sections -fdata-sections -funwind-tables -Wall -Wstrict-prototypes -Wshadow -Wundef -g -Os -fomit-frame-pointer -ffunction-sections -fdata-sections -g -fno-strict-aliasing -march=armv7e-m -mtune=cortex-m4 -mthumb -mfpu=fpv4-sp-d16 -mfloat-abi=hard -isystem "/home/zouboan/G/NuttX/nuttx/include" -D__NuttX__ -DNDEBUG -D__KERNEL__  -pipe -I "/home/zouboan/G/NuttX/nuttx/sched"   irq/irq_attach.c -o  irq_attach.o
after this commit:
CC:  group/group_find.c
arm-none-eabi-gcc -c -fno-common -fno-builtin -ffunction-sections -fdata-sections -funwind-tables -Wall -Wstrict-prototypes -Wshadow -Wundef -g  -fno-strict-aliasing -march=armv7e-m -mtune=cortex-m4 -mthumb -mfpu=fpv4-sp-d16 -mfloat-abi=hard -isystem "/home/zouboan/G/NuttX/nuttx/include" -D__NuttX__ -DNDEBUG -D__KERNEL__  -pipe -I "/home/zouboan/G/NuttX/nuttx/sched"   group/group_find.c -o  group_find.o

The setting come from:
https://github.com/apache/incubator-nuttx/blob/master/arch/arm/src/armv7-m/Toolchain.defs#L60-L68
Please ensure you use ARCHOPTIMIZATION += instead of ARCHOPTIMIZATION = in your Make.defs.

@xiaoxiang781216 Thanks for your help, there's a ARCHOPTIMIZATION = -g in my Make.defs , and the problem has been solved now.


Add population frequencies and adjust rank model to accomodate for Exac, 1000G

ExaC
ExaC (0.3) does not provide calculated AF for subpopulation. To avoid calculating this over and over the reference used in MIP should be modified to include sub populations and then MIP can collect this. However, this infomration is readilly available "just a click away" in Scout with the link to the Exac homepage. I think this should be enough.
1000G
@Måns Magnusson: To avoid querying the same database twice and parsing the output twice in MIP -  the most efficient way to get each sub popluations AF is if genmod filter can take a list of keys i.e. AF, EAS_AF, EUR_AF, AFR_AF, AMR_AF and add these to the VCF prefixing it with a "1000G" as is already done with the "AF" key. We can then modify teh rank model to look for more keys.

MIP now includes additional two scripts: maxAF.pl (for generating the MAX_AF for across populations) and calculateAF.pl (for calculating AF for each population in the INFO field). MIP will check that these two scripts have processed the relevant references. If not MIP will prepare the refererences before launching the rest of the analysis.


Update epoch to fix validation problems

Signed-off-by: Daniel J Walsh<EMAIL_ADDRESS>

LGTM and apologies for the mess the rogue space made.   I'm not sure how that got through the test suites initially.

@TomSweeneyRedHat Me neither.

@rh-atomic-bot r=TomSweeneyRedHat


[FLINK-18635][docs] Fix typo on website

What is the purpose of the change
This PR fix typo in 'concepts/timely stream processing' part of the website.
Brief change log

change Timely steam processing to Timely stream processing

Verifying this change
This change is a trivial rework / code cleanup without any test coverage.
Does this pull request potentially affect one of the following parts:

Dependencies (does it add or upgrade a dependency): no
The public API, i.e., is any changed class annotated with @Public(Evolving): no
The serializers: no
The runtime per-record code paths (performance sensitive): no
Anything that affects deployment or recovery: JobManager (and its components), Checkpointing, Kubernetes/Yarn/Mesos, ZooKeeper: no
The S3 file system connector: no

Documentation

Does this pull request introduce a new feature? no
If yes, how is the feature documented? not applicable

Hi,I'm a starter on contributing.At first,I was working on release-1.11 to fix this typo .
I see some suggestion that I should always make a contribution on master one minute later,
but I didnot find a way to change the from branch to the forked master.
Is it OK that I force pushed the forked master to the forked release-1.11 ?Or there is a better way?

Thanks a lot for your fix. I'll merge it to both master and release-1.11 branch.


Update MockServer Image: mockserver/mockserver:5.13.2

jamesdbloom/mockserver is deprecated and moved to mockserver/mockserver.

thanks @moqimoqidea! insead of replacing can you add a new one, please? Similar to toxiproxy

thanks @moqimoqidea! insead of replacing can you add a new one, please? Similar to toxiproxy

ok, wait me.

sorry, I was at my mobile and didn't check the class. So, nothing to be done. Thanks for the contribution anyway!


oneshot record image error

Required Info

Camera Model
D415

Firmware Version
<IP_ADDRESS>

Operating System & Version
Win 10 64bit

Kernel Version (Linux Only)

Platform
PC

SDK Version
2.24.0

Language
C++

Segment
VR/AR/others

Issue Description
i have modified librealsense code like below to record image only 1 frame:
once recorded, i opened bag file with realsense viewer, sometimes it fine, but sometimes it shows like this(which is color image is just white), how i can get fine (always!) 1 frame recorded bag file with librealsense?

// record 1 frame
void librealsense::record_device::write_data_once(size_t sensor_index, librealsense::frame_holder frame, std::function<void(std::string const&)> on_error)
{
    //write_data is called from the sensors, when the live sensor raises a frame

    LOG_DEBUG("write frame " << (frame ? std::to_string(frame.frame->get_frame_number()) : "") <<  " from sensor " << sensor_index);

    std::call_once(m_first_call_flag, [this]()
    {
        initialize_recording();
    });

    //TODO: restore: uint64_t data_size = frame.frame->get_frame_data_size();
    uint64_t cached_data_size = m_cached_data_size; //TODO: restore: (+ data_size)
    if (cached_data_size > MAX_CACHED_DATA_SIZE)
    {
        LOG_WARNING("Recorder reached maximum cache size, frame dropped");
        on_error("Recorder reached maximum cache size, frame dropped");
        return;
    }

    m_cached_data_size = cached_data_size;
    auto capture_time = get_capture_time();
    //TODO: remove usage of shared pointer when frame_holder is copyable
    auto frame_holder_ptr = std::make_shared<frame_holder>();
    *frame_holder_ptr = std::move(frame);
    (*m_write_thread)->invoke([this, frame_holder_ptr, sensor_index, capture_time/*, data_size*/, on_error](dispatcher::cancellable_timer t) {
        if (m_is_recording == false)
        {
            return; //Recording is paused
        }
		int device_count = 0;
		std::call_once(m_first_frame_flag, [&]()
		{
			try
			{
				write_header();
			}
			catch (const std::exception& e)
			{
				LOG_ERROR("Failed to write header. " << e.what());
				on_error(to_string() << "Failed to write header. " << e.what());
			}
		});

		switch (sensor_index)
		{
		case 0:
			std::call_once(m_first_color_flag, [&]()
			{
				try
				{
					const uint32_t device_index = 0;
					auto stream_type = frame_holder_ptr->frame->get_stream()->get_stream_type();
					auto stream_index = static_cast<uint32_t>(frame_holder_ptr->frame->get_stream()->get_stream_index());
					m_ros_writer->write_frame({ device_index, static_cast<uint32_t>(sensor_index), stream_type, stream_index }, capture_time, std::move(*frame_holder_ptr));
					//TODO: restore: std::lock_guard<std::mutex> locker(m_mutex);  m_cached_data_size -= data_size;
				}
				catch (std::exception& e)
				{
					on_error(to_string() << "Failed to write frame. " << e.what());
				}
			});
			break;
		default:
			std::call_once(m_first_depth_flag, [&]()
			{
				try
				{
					const uint32_t device_index = 0;
					auto stream_type = frame_holder_ptr->frame->get_stream()->get_stream_type();
					auto stream_index = static_cast<uint32_t>(frame_holder_ptr->frame->get_stream()->get_stream_index());
					m_ros_writer->write_frame({ device_index, static_cast<uint32_t>(sensor_index), stream_type, stream_index }, capture_time, std::move(*frame_holder_ptr));
					//TODO: restore: std::lock_guard<std::mutex> locker(m_mutex);  m_cached_data_size -= data_size;
				}
				catch (std::exception& e)
				{
					on_error(to_string() << "Failed to write frame. " << e.what());
				}
			});
			break;
		}

    });
}

If you are recording the very first frame, it is recommended that you allow the camera's auto-exposure to settle down first for the first several frames before beginning capture.

Under rs_export.hpp there is a processing block that creates .bag from a single rs2::frameset, it might be useful if I understand the requirement correctly.

@MartyG-RealSense , @dorodnic  i found that bag file itself is fine, but realsense viewer has bug.

i opened bag filed with "Load Recorded Sequence"
showing color image is white and depth image is normal.
close both image windows by click close icon.
toggle to start streaming data (depth and color) of "1-frame recorded bag file"
re-opened image windows are just fine! (depth and color)

so i think my write_data_once function is fine.

@dorodnic  i have tried save_single_frameset method, the result is like below:
color and depth image is abnormal.
std::thread video_processing_thread([&]() {
    while (alive)
    {
         // Fetch frames from the pipeline and send them for processing
         rs2::frameset data;
         if (pipe.poll_for_frames(&data))
         {
             if (b_save)
             {
                 b_save = false;
                 rs2::save_single_frameset single_saver;
                 data.apply_filter(single_saver);
                 printf("single bag file saved!!!\n");
             }
         }
    // ...
    }
}

these 1 frame bag file rendering solutions seems to be problematic, so i found and solved my request by using another method. so currently, i don't need this issue to be solved right now.

this is not a solution, but work around:
in realsense viewer, when open 1 frame bag file, keep the specific device_model in viewer_model,
and make some bool variable flags(for run once) to close color stream channel.
then  in show_stream_header(), read the bool flag, and for color stream_type, dev->stop(viewer), and dev->play(...) again using the specific device_model from viewer_model.
basically, this just close color stream window, and play the stream channel again.

Thanks so much for all the feedback you have provided about your workaround so that the community can benefit from the knowledge!

found the reason, frameset size is fine. the cause is about frame timing. logically, write_data_once() function itself fine. but physically must have to wait sensor does it's job.


Testing base job

As a pull request owner and reviewers, I checked that:

[x] Appropriate testing is done and actually running
[x] Appropriate documentation exists and/or is up-to-date:

[x] README in the role
[x] Content of the docs/source is reflecting the changes

cifmw-test-base-job-tp https://review.rdoproject.org/zuul/build/49cff1456d6d4e8080c709a6f9e047f6 : SUCCESS in 4m 06s
job passing on testproject: https://review.rdoproject.org/r/c/testproject/+/48781/42

/approve

/lgtm

similar role #580

No @raukadah - It is a more simple thing, just to test how the new job layout will work, it will be reverted afterwards

/lgtm

/lgtm
re-adding label, since we pushed a rebase.


perf: replace GetDenomMetaData to HasDenomMetaData

Summary by CodeRabbit

New Features

Enhanced the ERC20 token registration process to include a more efficient check for token metadata existence.

Refactor

Optimized metadata existence verification in ERC20 token handling.

mg


Updated obsolete Paket API use

generate-include-scripts is obsolete, replaced by generate-load-scripts
https://fsprojects.github.io/Paket/paket-generate-include-scripts.html
https://fsprojects.github.io/Paket/paket-generate-load-scripts.html
Didn't try to build and test, sorry.

It also needs changes in package.json, since you've changed commandID

Roger that. Will do after working day is done.

Duh, thanks for the reminder.


Add option to specify NIC MODEL when (hot-)adding a NIC through CLI / API

Author Name: Stefan Kooman (Stefan Kooman)
Original Redmine Issue: 4988, https://dev.opennebula.org/issues/4988
Original Date: 2017-01-20

onevm
...
nic-attach
Attaches a NIC to a running VM. When using --file add only one
NIC instance.
    States: RUNNING, POWEROFF
    valid options: file, network, ip

There's currently no possibility to specify the NIC MODEL when adding a NIC through CLI / API. You can however specify this with Sunstone. Although you can configure a default NIC in vmm_exec_kvm.conf: NIC = [ model="virtio" ] (KVM) this setting is not used during (hot-) added NICs. Because the default MODEL on the hypervisor will be used (most often realtek) it's currently not possible to hot-add specific NIC. A partial workaround we have in place to set a default NIC MODEL is a small change in the driver (../one/remotes/vmm/kvm/attach_nic):
if [ "$THE_MODEL" = "-" ]; then
MODEL=""     <- these lines were added
else                                   <-|
MODEL=""
fi

Original Redmine Comment
Author Name: Stefan Kooman (Stefan Kooman)
Original Date: 2017-08-31T08:48:31Z

This issue relates to #4821 and has been fixed in #4821. Fixed in commit 75dcfd601f1fcf5253d0a47be7cdfe0845d804db.


Support HTTP request method fallback

Some misconfigured webservers don't accept HEAD requests, but using HEAD is more efficient and appropriate in general. As a rough but effective work-around, allow the configuration key method to be a list ["head", "get"] instead of a string, where Lychee's checking algorithm falls back to the subsequent HTTP method in the list if the former gives an error response. Regrettably, in practice the response codes returned upon HEAD requests by these misconfigured webservers vary (404, 403, etc.), so don't bother to implement a fallback condition evaluator.

That's a great idea! What counts as an error response? For connection errors, both methods shouldn't work. Currently, errors are defined as
https://github.com/lycheeverse/lychee/blob/a8e9f04d8c6ed7b4e4be32cab77b61e6d42fb2fd/lychee-lib/src/types/status.rs#L159-L164
where
https://github.com/lycheeverse/lychee/blob/a8e9f04d8c6ed7b4e4be32cab77b61e6d42fb2fd/lychee-lib/src/types/status.rs#L22-L43
and
https://github.com/lycheeverse/lychee/blob/a8e9f04d8c6ed7b4e4be32cab77b61e6d42fb2fd/lychee-lib/src/types/error.rs#L12-L148
Does that include all the cases we need to cover? I am wondering specifically about 5XX status codes. These wouldn't be covered by the fallback.

@sanmai-NL ping, in case you have any thoughts on this.

I think your design makes sense. And if some adjustments turn out to be needed later, I don't expect those to have a high cost of change.


fix: FitsInSquare for case with 0 messages

Closes https://github.com/informalsystems/audit-celestia/issues/16

Codecov Report

Merging #853 (7c29ac6) into main (a3830e3) will increase coverage by 0.05%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##             main     #853      +/-   ##
==========================================
+ Coverage   25.59%   25.64%   +0.05%
==========================================
  Files          75       75
  Lines        9273     9272       -1
==========================================
+ Hits         2373     2378       +5
+ Misses       6677     6673       -4
+ Partials      223      221       -2

Impacted Files
Coverage Δ

pkg/shares/non_interactive_defaults.go
100.00% <100.00%> (+5.17%)
:arrow_up:

pkg/prove/proof.go
83.56% <0.00%> (-0.12%)
:arrow_down:

pkg/da/data_availability_header.go
81.14% <0.00%> (+2.45%)
:arrow_up:

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.


Informative error message when directory is not writeable

This PR contains:

[x] New features
[ ] Changes to dev-tools e.g. CI config / github tooling
[ ] Docs
[ ] Bug fixes
[ ] Code refactor

What is the current behavior? (You can also link to an open issue here)
You get an obscure error message if you try to run inspect in a devcontainer or other CI context without a login session.
What is the new behavior?
You get a better error message.
Does this PR introduce a breaking change? (What changes might users need to make in their application due to this PR?)
Other information:

(I need to test this before merging - please hold off)

Closing as we are handling by having a more ironclad fallback in ~/.local: https://github.com/UKGovernmentBEIS/inspect_ai/pull/761


Resolve radio browse issue

Part of the issue #2553 I have updated the way the system look for the country code.
Previously the limit was not allowing to search in the whole list of countries.
I have updated the way we retrive the countries to have a true order since the radios package is not doing it correctly, for example United Kingdom was after Switzerland instead of being on the bottom with United states.
I have reduced the cache since it is a bit odd to have a 7 day cache, which could be helpful but since there is not API limit we can query a bit more frequent

Thanks for the effort but this really needs more thought

No worries, this is working but I am happy to make amends to ensure you are happy with the changes

I actually found an easier way to solve the issue by just ignoring the paging of RadioBrowser - fixed in next release.
Can you give the next beta a try ?

I actually found an easier way to solve the issue by just ignoring the paging of RadioBrowser - fixed in next release. Can you give the next beta a try ?

Ok will try,

When I go to "browse by country" and select "Denmark" I get a single station, which appears to be from Guatemala, but it has the letters "DK" in its name. I am on 2.1.0rc1. Denmark should have a list of 73 stations.


Set AccountingStorageHost correctly in galaxy slurm_config

This fixes sacct on dev. The galaxy user can see all of the jobs. Should stop jobs failing when 'scontrol' can no longer bring up the job info.


Barcode scan should return barcode type

When a barcode is scanned , Scanner should return  barcode type along with barcode value, e.g Code128, PDF417, QRCode, etc.

yes but the original lib of Google used here has not that feature...so may be impossible

https://github.com/teslamotors/react-native-camera-kit/pull/633
Added this enhancement on my PR, please test post if any issues


[ADAP-517] [Bug] latest and 1.x.latest tags for ghcr Docker releases are stale

Is this a new bug in dbt-snowflake?

[X] I believe this is a new bug in dbt-snowflake
[X] I have searched the existing issues, and I could not find an existing issue for this bug

Current Behavior
1.3.0 container image is still tagged as "latest"
Expected Behavior
The most recent stable image version should be tagged as "latest"
Steps To Reproduce

Look at https://github.com/dbt-labs/dbt-snowflake/pkgs/container/dbt-snowflake
1.3.0 is tagged as latest.

Relevant log output
No response
Environment
- OS:
- Python:
- dbt-core:
- dbt-snowflake:

Additional Context
This is related to https://github.com/dbt-labs/dbt-snowflake/issues/564
I posted a question in the discussions section on March 17 inquiring about this.

Thanks for reaching out @scotthenley !
I'm not sure if this got fixed in the last couple hours, but this is showing 1.5.0 for me:

And so is here:

Could you take a look again and see if this is fixed for you as well?

Hi @dbeatty10
I am still seeing the "latest" on the 1.3 image. We use the tag to pull the most recent version for various CI processes rather than bumping the version in our pipelines.
https://github.com/dbt-labs/dbt-snowflake/pkgs/container/dbt-snowflake/versions?filters[version_type]=tagged

@dbeatty10 It is still showing latest as v1.3.0.

From what we can tell, this tag is being deprecated and we cannot adjust it. Closing as "can't do".

https://github.com/dbt-labs/dbt-core/pull/9495 fixes the underlying issue (thank you @mikealfare !), and this particular issue will be resolved for each 1.x version of this adapter upon its next patch release.
We are choosing not to address any un-supported versions at this time, so <=1.4.x will not be updated.
Here are the most recent ones for the supported versions of dbt-snowflake in PyPI:

1.7.1
1.6.6
1.5.6

So this will be completely resolved for >=1.5.x when each of the following are released (but only if each is released prior to falling out of support):

1.7.2
1.6.7
1.5.7

Screenshot of latest and 1.7.latest:


Init new project and stuck on Installing NPM Dependencies

How much time npm install dependencies is suppose to take?
There is no progress, just a rotating bar. It feels like its  #stuck

With Electron Forge v5, if you run with the --verbose flag, the NPM/Yarn output will also be displayed.
For example: electron-forge --verbose init /path/to/my/new/app
I suspect that for whatever reason, it's taking a while for the Electron prebuilt binary to download.


Triage phantom room presence

Doesn't fix us getting into the phantom room presence state but it'll
eventually boot them out on heartbeat.

I think this is good!
If we run into performance issues (either Redis usage spikes or excessively long function execution time, neither of which I'm really worried about), low-hanging fruit would be to aggregate all of the removeUserFromRoomPresence calls for a single room into a single Redis call to update the array for that room instead of making 1 redis call per user.


Double check x1dints with real data as soon as possible.

[x] Make sure it still works on real data.
[x] Make sure it gets as much useful metadata as possible, including from the headers.
[x] Add astropy Time axis to timelike, check its definition, and validate it's ~correct with a transit.

I've tried to use chromatic to read MIRI's x1dints, but it doesn't seem to work. Here is the error I got
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
Input In [2], in <cell line: 1>()
----> 1 r = Rainbow("/home/patcharapol/work/summer_2022/MIRI/jw01033/jw01033005001/*_x1dints.fits",format="x1dints")

File ~/anaconda3/envs/starry/lib/python3.9/site-packages/chromatic/rainbows/rainbow.py:153, in Rainbow.__init__(self, filepath, format, wavelength, time, flux, uncertainty, wavelike, timelike, fluxlike, metadata, name, **kw)
    151 # then try to initialize from a file
    152 elif isinstance(filepath, str) or isinstance(filepath, list):
--> 153     self._initialize_from_file(filepath=filepath, format=format, **kw)
    155 # finally, tidy up by guessing the scales
    156 self._guess_wscale()

File ~/anaconda3/envs/starry/lib/python3.9/site-packages/chromatic/rainbows/rainbow.py:384, in Rainbow._initialize_from_file(self, filepath, format, **kw)
    382 # pick the appropriate reader
    383 reader = guess_reader(filepath=filepath, format=format)
--> 384 reader(self, filepath, **kw)
    386 # validate that something reasonable got populated
    387 self._validate_core_dictionaries()

File ~/anaconda3/envs/starry/lib/python3.9/site-packages/chromatic/rainbows/readers/x1dints.py:102, in from_x1dints(rainbow, filepath, order, **kw)
     96 rainbow.wavelike["wavelength"] = (
     97     hdu[e].data["wavelength"] * wavelength_unit * 1
     98 )
    100 # make up a time grid (this is still a little kludgy; it'd be better to have int_times)
    101 first_mjd_barycentric_integration_midpoint = (
--> 102     hdu["sci"].header["TDB-BEG"] * u.day
    103     + hdu["primary"].header["EFFINTTM"] / 2 * u.second
    104 )
    105 last_mjd_barycentric_integration_midpoint = (
    106     hdu["sci"].header["TDB-END"] * u.day
    107     - hdu["primary"].header["EFFINTTM"] / 2 * u.second
    108 )
    109 mjd_barycentric_integration_midpoints = np.linspace(
    110     first_mjd_barycentric_integration_midpoint,
    111     last_mjd_barycentric_integration_midpoint,
    112     n_integrations_total,
    113 )

File ~/anaconda3/envs/starry/lib/python3.9/site-packages/astropy/io/fits/hdu/hdulist.py:323, in HDUList.__getitem__(self, key)
    318 # Originally this used recursion, but hypothetically an HDU with
    319 # a very large number of HDUs could blow the stack, so use a loop
    320 # instead
    321 try:
    322     return self._try_while_unread_hdus(super().__getitem__,
--> 323                                        self._positive_index_of(key))
    324 except IndexError as e:
    325     # Raise a more helpful IndexError if the file was not fully read.
    326     if self._read_all:

File ~/anaconda3/envs/starry/lib/python3.9/site-packages/astropy/io/fits/hdu/hdulist.py:780, in HDUList._positive_index_of(self, key)
    765 def _positive_index_of(self, key):
    766     """
    767     Same as index_of, but ensures always returning a positive index
    768     or zero.
   (...)
    777     inefficient.
    778     """
--> 780     index = self.index_of(key)
    782     if index >= 0:
    783         return index

File ~/anaconda3/envs/starry/lib/python3.9/site-packages/astropy/io/fits/hdu/hdulist.py:761, in HDUList.index_of(self, key)
    758         break
    760 if (found is None):
--> 761     raise KeyError(f'Extension {key!r} not found.')
    762 else:
    763     return found

KeyError: "Extension 'sci' not found."

What version of chromatic are you using here, @Pat-Wachiraphan ? I think it's possible this already got fixed in 0.3.3?

What version of chromatic are you using here, @Pat-Wachiraphan ? I think it's possible this already got fixed in 0.3.3?

Fixed!

Works for me!

I've tested this out on a lot of the ERS + ERO data, and it all seems to work. However, it doesn't fail gracefully if someone tries to load one of multiple segments. We should allow it to read a single segment and/or at least provide a warning or more informative error messages about reasons why a read might fail and suggestions for what could be done about them.

OK, I'm going to call this one closed for now. #191 just updated the x1dints reader a little bit, but with the main change of trying give users a little more guidance not to try to use Stage 3 output files (because sometimes they seem to stitch segments together in weird ways, among other problems).
I suspect we'll continue to have more problems as the jwst pipeline continues to evolve, so we'll probably need to nudge this again frequently in the future.


Fixed image link for AddToSearchPaths.png

AddToSearchPaths.png failed to load properly. Fixed link to load same image from "react-native/website/src/react-native/img". Did not touch source code.

This is working for the official page, but not in GitHub.
https://github.com/facebook/react-native/blob/master/docs/LinkingLibraries.md

@vjeux This change fixed the image problem on GitHub, but have inadvertently broke the one on the official page. Sent and email to your<EMAIL_ADDRESS>regarding this.


Add initial vscode devcontainer definition

Allows a developer to quickly develop the bot using Visual Studio Code's "Remote - Containers" feature, or GitHub Codespaces.
Currently uses Alpine to ensure the environment is the same as the production Dockerfile.
Later (After this PR) I aim to further improve vscode integration by defining debug profiles and similar.
Reference: https://code.visualstudio.com/docs/remote/devcontainerjson-reference

Done pushing now, sorry about that.

Probably a good idea to squash merge this since I had to push so much to test the action.

Sounds good - thanks!


Determine and/or create test coverage

Once test coverage is in place, add it to CI as a GitHub Action.

@acuarica @chriske1337 @PaterSantyago @lclc @pitkevich Hello everyone ! Can I provide my help to increase test coverage for this project ?


impl std::error::Error for FieldParseError

Thanks for the PR!
I cherrypicked most of the commits, resulting in https://github.com/ferrumfix/ferrumfix/pull/26. I had two minor concerns which are explained in the PR description. I tried adding you as a co-author to them, but GitHub isn't picking up the Co-Author field in the commit description (either that, or I messed something up). I hope that's okay, I'll try to make sure your name is in the commit next time.


Exit on BrokenPipeError (shallow fix)

Just wrap BrokenPipeError in try / except block and quit since the output pipe is probably closed.

Thanks!  On python 2 BrokenPipeError doesn't seem to exist and I get this stacktrace instead:
Traceback (most recent call last):
  File "/usr/local/bin/x_x", line 9, in <module>
    load_entry_point('x-x==0.7', 'console_scripts', 'x_x')()
  File "/usr/local/lib/python2.7/site-packages/click/core.py", line 610, in __call__
    return self.main(*args, **kwargs)
  File "/usr/local/lib/python2.7/site-packages/click/core.py", line 590, in main
    rv = self.invoke(ctx)
  File "/usr/local/lib/python2.7/site-packages/click/core.py", line 782, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/usr/local/lib/python2.7/site-packages/click/core.py", line 416, in invoke
    return callback(*args, **kwargs)
  File "/usr/local/lib/python2.7/site-packages/x_x/x_x.py", line 46, in cli
    asciitable.draw(XCursor(sheet, heading), out=out)
  File "/usr/local/lib/python2.7/site-packages/x_x/asciitable.py", line 157, in draw
    write_bytes(value, out)
  File "/usr/local/lib/python2.7/site-packages/x_x/asciitable.py", line 20, in write_bytes
    out.write(s)
IOError: [Errno 32] Broken pipe

so I widened the error caught to be an IOError and it seems to work in both python 2 and 3.

Amazing, I totally forgot to test on python 2.

I couldn't find a mention of workarounds in and of the 2 to 3 libraries on a workaround for using the new specific errors in python 3 and falling back to catching the generic errors in python 2.  So as far as I know, just using the python 2/3 common errors is the way to go.