AI | artificial intelligence on python | Machine Learning library

If you are trying to create the AI notebook instance in a region that does not contain any subnetwork, it will throw this error[1].

In order to resolve your issue, try one of the following:

1. For creating a Notebook instance in the same region, you need to create a subnet in that region for the VPC network you are using. To create a new subnet you can follow this documentation [2].

2. Or else you can create a Notebook instance in some other region where the subnet is available. To create a notebook instance you can follow this documentation [3].

[1]- ‘There are no available networks. Make sure there is at least a network within this region’.

[2]- https://cloud.google.com/vpc/docs/using-vpc#add-subnets

[3]- https://cloud.google.com/notebooks/docs/create-new

Multiple things could cause this behaviour, because the pipeline runs fine with less Data, analysing what has changed could lead us to a resolution.

The third line of the logs you provide might indicate that you're processing unclean data in your bigger pipeline mmap(NULL, could mean that | "Get Content" >> beam.Map(lambda x: x.read_utf8()) is trying to read a null value.

Is there an empty file somewhere ? Are your files utf8 encoded ?

I'm guessing using the fileio.ReadMatches() will try to load into memory the whole file, if your file is bigger than your memory, this could lead to errors. Can you split your data into smaller files ?

If files are too big for your current machine with a DirectRunner you could try to use an on-demand infrastructure using another runner on the Cloud such as DataflowRunner

No sequential-across-lanes pack until AVX-512, unfortunately. (And even then only for 1 register, or not with saturation.)

The in-lane behaviour of shuffles like vpacksswd and vpalignr is one of the major warts of AVX2 that make the 256-bit versions of those shuffles less useful than their __m128i versions. But on Intel, and Zen2 CPUs, it is often still best to use __m256i vectors with a vpermq at the end, if you need the elements in a specific order. (Or vpermd with a vector constant after 2 levels of packing: How do I efficiently reorder bytes of a __m256i vector (convert int32_t to uint8_t)?)

If your 32-bit elements came from unpacking narrower elements, and you don't care about order of the wider elements, you can widen with in-lane unpacks, which sets you up to pack back into the original order.

This is cheap for zero-extending unpacks: _mm256_unpacklo/hi_epi16 (with _mm256_setzero_si256()). That's as cheap as vpmovzxwd (_mm256_cvtepu16_epi32), and is actually better because you can do 256-bit loads of your source data and unpack two ways, instead of narrow loads to feed vpmovzx... which only works on data at the bottom of an input register. (And memory-source vpmovzx... ymm, [mem] can't micro-fuse the load with a YMM destination, only for the 128-bit XMM version, on Intel CPUs, so the front-end cost is the same as separate load and shuffle instructions.)

But that trick doesn't work work quite as nicely for data you need to sign-extend. vpcmpgtw to get high halves for vpunpckl/hwd does work, but vpermq when re-packing is about as good, just different execution-port pressure. So vpmovsxwd is simpler there.

Slicing up your data into odd/even instead of low/high can also work, e.g. to get 16 bit elements zero-extended into 32-bit elements:

I believe your goal as follows.

• You want to set the conditional format rules for each range with each formula.
• The range is created by the for loop of for (let i = 3; i < 25; i++) {,,,}.
• The formula is created by const formula = '=sum($' + columnStart[z] + '6:$' + columnEnd[z + 6] + '6)>=40';.

• When I saw your script, it seems that range of Logger.log(range) is the string value. But when setRanges(range) is used, range is required to be the Range object. I think that this might be the reason of your issue.
• And, in your situation, how about the following flow?
  1. Put each range to an array of rules of rules = sheet.getConditionalFormatRules().
     • For this, in my answer, I used RangeList.
  2. Use rules with sheet.setConditionalFormatRules(rules) put outside of the loop.

When above points are reflected to your script, it becomes as follows.

Try with set_index + mul then sum on axis=1:

Even though the types are sealed and seemingly you provided all type class instances

(one for each Ai, Bj)

this does not cover all the possible cases specified by type bounds in

In case anyone else runs into this problem.

The fix was to add a Rigidbody2D to my AI Agent and set the gravity scale to 0.

Even though my game doesn't use Unity's physics system for movement and the Astar package can move AI agents by transform, for some reason it requires a Rigidbody to keep the Z position at 0.

I'm still not really sure why this solves the problem because, when I was debugging the third-party Astar code, it always returned nextPosition values with a Z position of 0 yet the actual position that the AI Agent was updated to had varying Z positions...

If you have more info, leave a comment and I'll add it to the answer.

Instead of loading the resource to memory temporarily, directly load it to the local file using a TFileStream:

I think there is two ways of trying to solve this

1- Try Restarting your Editor

2- Try this:

python -m pip install SpeechRecognition

then restart the Editor.