Fvd++ Tutorial

[Stephany Tousley]

Thisis the overview page for the torch.distributed package. The goal ofthis page is to categorize documents into different topics and brieflydescribe each of them. If this is your first time building distributed trainingapplications using PyTorch, it is recommended to use this document to navigateto the technology that can best serve your use case.

DeviceMesh abstracts the accelerator device communicators into a multi-dimensional array, which manages the underlying ProcessGroup instances for collective communications in multi-dimensional parallelisms. Try out our Device Mesh Recipe to learn more.

and all_gather)and P2P communication APIs (e.g.,sendand isend),which are used under the hood in all of the parallelism implementations.Writing Distributed Applications with PyTorchshows examples of using c10d communication APIs.

Data Parallelism is a widely adopted single-program multiple-data training paradigmwhere the model is replicated on every process, every model replica computes local gradients fora different set of input data samples, gradients are averaged within the data-parallel communicator group before each optimizer step.

&nbsp This tutorial describes a prototype feature. Prototype features are typically not available as part of binary distributions like PyPI or Conda, except sometimes behind run-time flags, and are at an early stage for feedback and testing.

Copyright The Linux Foundation. The PyTorch Foundation is a project of The Linux Foundation. For web site terms of use, trademark policy and other policies applicable to The PyTorch Foundation please see www.linuxfoundation.org/policies/. The PyTorch Foundation supports the PyTorch open source project, which has been established as PyTorch Project a Series of LF Projects, LLC. For policies applicable to the PyTorch Project a Series of LF Projects, LLC, please see www.lfprojects.org/policies/.

I want to use TF to transform a PoseStamped into a frame, perform some operations, and then transform it back to its original frame. The frame is not published to TF, so I set it as a TransformStamped in the TfListener:

I cannot find documentation for the TF2 Python API. The TF Python documentation is only generated up until Melodic(?), so the link in the wiki is broken. The TF2 source code is not human-readable unless you know how Python bindings are generated from C++.

I know I should port to TF2, but I didn't have a pressing reason yet. I only need to use the TF tree here, no extrapolation or time lookup. Is there a "please don't bother me about time" setting in Python? Where is the TF2 Python documentation? How else could I solve this issue without much hassle?

edit:

The tf2 Python API is the C++ documentation, and the tf2_ros API is available here and here for Melodic. It looks like this is not as visible as it should be, but I'm not sure what to do about that.

There's a known issue with the epydoc based documentation in noetic. However since this package is deprecated there's been no API changes since melodic and you can use that documentation. It's actually barely changed for years before that too. You can just use the melodic documentation that you already linked to.

However it's not necessarily going to solve your problem because it still needs a "common" time. Aka for all links in the chain it need information at a "common" time aka the same time. tf does interpolation between different samples in time.

The simple solution is that you need to make sure that you have data in your listener from before and after the requested timestamp for all links in the chain. If you use TIme(0) you only have to make sure that you have any timepoint that's consistent and it will return the latest.

And although you don't want to move to tf2 in tf2 we added static transform support which does exactly what you want letting you not worry about time for a link because a static transform is considered to be valid for all times. So if that's what you want, you may actually want to look at moving forward to tf2.

PS As a side note your question makes a lot more assertions than asking for help and a lot of those assertions are inaccurate which means that you end up digging further afield. You may find that being a little more thorough in each step of your investigation may help you get what you want faster.

I have some questions though:

1) In the tutorial, Time(0) is passed to lookupTransform, but not to transformPose. Can you confirm that transformPose does not accept Time in TF1, or if I am missing something?

2) I added an explanation about the extrapolation error. Do you consider this a bug worth reporting, or a user error ...(more)

1) If you set the time to zero inside the trasnsformPose it will call lookupTransform with the timestamp from the input Pose which will then propagate back out in the resultant pose. 2) There are several corner cases in the future/past and this may be a case where we didn't conditionally change the print string. I haven't been in this code base in a while but if I remember correctly there may be issues when you have two or three links and potentially different levels of time continuity where there's no complete solution at any given time but some earlier history for some frames and some newer history for other frames. And thus some frames are in the future and some in the past. And in that case neither future nor past is correct, and I don't know a word for it.3) Adding transformPose ...(more)

I updated the tutorials with deprecation badges on each page and added a transformPose/transform example to the tf and tf2 listener tutorials, but I can't get either transformPose with Time(0), or the tf2 transform examples to work. If you can fix the problems in this PR I'll commit to updating the tutorial pages accordingly.

I use the max_velocity_scaling_factor from the MotionPlanRequest msg to set the velocity, and I use the MotionPlanResponse msg to read the path.I tried several "getDuration" functions from the RobotTrajectory ()class to read the path, but I always get a correct position vector, and a time vector filled with 0.

I didn't install Moveit from source as specified in the tuto because CHOMP is now part of the official release and I use it, plus another person had the same problem with a source build (but didn't get an answer) : -planning/movei...

Thank you for your answer fvd, I tried to run OMPL as a preprocessor for STOMP according to the tutorial about planning adapters, but It seems that it doesn't take these settings, I still get CHOMP messages while running the code, this is the console output :

Please edit your question with the extra information. In your code, I don't actually see where you are using the time parametrization. It looks like you are just reading the trajectory, but it's hard to read as is.

I edited your question. Please add new information to it yourself. Yes, you can call the time parametrization directly with a RobotTrajectory of your own. Look here for function of the IPTP algorithm. The others are analogous.

This video should provide enough guidance to understand the PWM signal on the Mach3 USB controller:

The PWM signal is provided by the AVI terminal, and the 10V terminal is an input and provides the reference for the top voltage for the PWM signal. The ACM is the analog common (analog ground)

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[575] Hello, I'm wondering if you can provide advice how to wire this USB board where for spindle I would like to use chinese servo motor and driver (TD3) - speed control mode. Especially how to connect - AVI, ACM and 10V (24V is clear). I am still not sure how to power on and off spindle itself. Thank you in advance. Vaclav

This controller does not have an encoder input for the spindle. The controller can output a PWM signal which causes the spindle VFD to spin at a specific RPM. That RPM is shown in Mach3 as long as the configuration has been applied properly. You can also calibrate the RPM of the spindle to match the RPM shown in Mach3 with the use of a tachometer and adjust the configuration in Mach3.

This was true for controllers that use the parallel port to communicate with the CNC as the CPU is sending signals to each of the parallel port pins (GPIO or General Purpose Input/Output). With newer types of controllers that use the USB connection, this is not a problem anymore since all of the signal processing happens on the controller rather than in the computer. The computer only needs to send high-level commands to the controller and the controller translates the simple commands to pulse trains that the drivers can accept.

Additional Information:

I don't believe that the board itself buffers. MAch3 however, does use an algorithm for look-ahead.

Additional Information:

Thank you for the information. I plan to use a second SSD with a minimal Windows 10 or 11 system.

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[575] Buffering. In former days, I used a MS DOS application to do the milling jobs. I was told that Windows sometimes does other jobs ans so my milling job would be ruined. Does this USB board buffer some of the CNC data to circumvent such errors?

Unfortunately, all of the attemps I have made to use this controller with a THC did not work, so I would not recommend this board for plasma machines that use a THC. THe Pokeys57CNC controller will work with several THC controllers. I have used the Proma and the PlasmaSens controllers with the Pokeys57CNC.

The Mach3 USB controller does not contain an onboard relay; however, you can use the output to control an external relay. Follow this tutorial to control an external relay on this controller:

Make sure the output port is set to port 3. I did not mention this in the tutorial.

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[575] Mach3 board only jearking the steppers not rotating, i tried many settings but no luck here is the video !AuEcOHVa1BRjg7Iqu9teAEjsd4fnTA

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