intel | - An abbreviation of intelligence

It seems it can't be used with Flutter yet, as seen in:

Apple Silicon support in the Dart SDK

[...] Note that the Dart SDK bundled in the Flutter SDK doesn’t have these improvements yet.

https://medium.com/dartlang/announcing-dart-2-14-b48b9bb2fb67

[Announcing Dart 2.14][ScreenShot]: https://i.stack.imgur.com/N8Qcc.png

And:

Get the Dart SDK

[...] As of Flutter 1.21, the Flutter SDK includes the full Dart SDK. So if you have Flutter installed, you might not need to explicitly download the Dart SDK. Consider downloading the Dart SDK if any of the following are true:

• You don’t use Flutter.
• You use a pre-1.21 version of Flutter.
• You want to reduce disk space requirements or download time, and your use case doesn’t require Flutter. For example, you might have a continuous integration (CI) setup that requires Dart but not Flutter.

https://dart.dev/get-dart

[Get the Dart SDK][ScreenShot]: https://i.stack.imgur.com/rawJV.png

This seems to be caused by a JVM intrinsic function for Math.cos, which is described in the related issue JDK-8242461. The behavior experienced there is not considered an issue:

The returned results reported in this bug are indeed adjacent floating-point values [this is the case here as well]

[...]

Therefore, while it is possible one or the other of the returned values is outside of the accuracy bounds, just have different return values for Math.cos is not in and of itself evidence of a problem.

For reproducible results, use the StrictMath.cos instead.

And indeed, disabling the intrinsics using -XX:+UnlockDiagnosticVMOptions -XX:DisableIntrinsic=_dcos (as proposed in the linked issue), causes Math.cos to have the same (expected) result as StrictMath.cos.

So it appears the behavior you are seeing here is most likely compliant with the Math documentation as well.

I have found the issue so marking this as solved, however, if anyone knows why this solves the problem, please share!

I found an issue opened on Google's anroid-emulator-m1-preview repo with this answer https://github.com/google/android-emulator-m1-preview/issues/76#issuecomment-1023563846

Turns out, I just needed to uncheck 'Launch in a tool window' but again, not sure why that fixed the issue.

This is what solved it for me on my M1.

1. Go to Android Studio Preview and download the latest Canary build for Apple chip (Chipmunk). Don't worry this is just to get through the initial setup.
2. Unpack it, run it, let it install all the SDK components, accept licenses, etc as usual.
3. Once it's done, simply close it and delete it.

Now when you start your stable Android Studio (Arctic Fox) you should not see the error.

[temp.names]/5 says that a name prefixed by template must be a template-id, meaning that it must have a template argument list. (Or it can refer to a class/alias template without template argument list, but this is deprecated in the current draft as a result of P1787R6 authored by @DavisHerring.)

There is even an example almost identical to yours under it, identifying your use of template as ill-formed.

The requirement and example comes from CWG defect report 96, in which the possible ambiguity without the requirement is considered.

Open GCC bug report for this is here. I was not able to find a Clang bug report, but searching for it isn't that easy. Its implementation status page for defect reports however does list the defect report as unimplemented.

Generally, Tensorflow is the only network with the shape NHWC while most others use NCHW. Thus, the OpenVINO Inference Engine satisfies the majority of networks and uses the NCHW layout. Model must be converted to NCHW layout in order to work with Inference Engine.

The conversion of the native model format into IR involves the process where the Model Optimizer performs the necessary transformation to convert the shape to the layout required by the Inference Engine (N,C,H,W). Using the --input_shape parameter with the correct input shape of the model should suffice.

Besides, most TensorFlow models are trained with images in RGB order. In this case, inference results using the Inference Engine samples may be incorrect. By default, Inference Engine samples and demos expect input with BGR channels order. If you trained your model to work with RGB order, you need to manually rearrange the default channels order in the sample or demo application or reconvert your model using the Model Optimizer tool with --reverse_input_channels argument.

I suggest you validate this by inferring your model with the Hello Classification Python Sample instead since this is one of the official samples provided to test the model's functionality.

You may refer to this "Intel Math Kernel Library for Deep Neural Network" for deeper explanation regarding the input shape.

I found and tested in shorter toggle mechanism.

The configuration for Windows Feature:

• Windows Subsystem for Linux is installed.
• Windows Hypervisor Platform is installed.
• Hyper-V is installed.

If you need the Emulator, you only need to turn off Hypervisor + Restart. Run: bcdedit /set hypervisorlaunchtype off

If you need the Docker back, you can run the hypervisor hence disabling Emulator. Run: bcdedit /set hypervisorlaunchtype auto

You need to restart after setting Hypervisor

You cannot run both at the same time. Another forum worth checking in How about running docker? in my older answer below.

I think I solved this issue, tested to run from CMD / Android Studio and ran perfectly as before installing WSL. There are several step we go:

1. Removed Windows Subsystem for Linux
2. Removed Windows Hypervisor Platform
3. Removed Hyper-V

Here is my current setup:

I know after removing there are some odds because the AVD still get the same error as before and expected to get into WSL. I stumbled and found something when ran:

C:\Users\[NAME]\AppData\Local\Android\Sdk\emulator\emulator-check.exe accel

That command will check the current accel. It explains that the Hypervisor need to be set off and give specific help: run bcdedit /set hypervisorlaunchtype off.

After running the bcdedit, I restarted and all is reverted. Now I can run emulator both from CMD and Android Studio perfectly.

Sad truth, yeah you cannot run both pararel. There are several workaround in this forum:

How can I run both Docker and Android Studio Emulator on Windows?

Several option ranging from changing emulator, add & remove docker when in need using above step, created nested vm, etc. My personal choice right now is using another Emulator for the time being and removed docker for the latter.

Not an answer, but this might help someone else answer this. I coded this to re-create a data.frame of the size @Eric is working with.

Old x86-64 CPUs don't support lzcnt, so rustc/llvm won't emit it by default. (They would execute it as bsr but the behavior is not identical.)

Use -C target-feature=+lzcnt to enable it. Try.

More generally, you may wish to use -C target-cpu=XXX to enable all the features of a specific CPU model. Use rustc --print target-cpus for a list.

In particular, -C target-cpu=native will generate code for the CPU that rustc itself is running on, e.g. if you will run the code on the same machine where you are compiling it.