boson | task framework similar to rake and thor built | Bot library

Distribution strategies were introduced as part of TF2 to help distribute training across multiple GPUs, multiple machines or TPUs with minimal code changes. I'd recommend this guide to distributed training for starters.

Specifically creating a model under the TPUStrategy will place the model in a replicated (same weights on each of the cores) manner on the TPU and will keep the replica weights in sync by adding appropriate collective communications (all reducing the gradients). For more information check the API doc on TPUStrategy as well as this intro to TPUs in TF2 colab notebook.

As per the official documentation of Land Marks Classifier,

Inputs are expected to be 3-channel RGB color images of size 321 x 321, scaled to [0, 1].

But from Your Dataset, file format is tfrecord.

When we use Transfer Learning and when we want to reuse the Models either from TF Hub or from tf.keras.applications, our data should be in the predefined-format as mentioned in the documentation.

So, please ensure that your Dataset comprises of Images and resize Image Array to (321,321,3) for the TF Hub Module to work.

I think you need to replace site with page in your second code snippet, see the handling for variables.

• site: global website (e.g. _config.yml)
• page: current page

Additional I dropped the array index [0].

The problem is with your registration of the routes in app/views.py when you register them with current_app as app. I'm not sure how you would apply the application factory pattern without using blueprints as the pattern description in the documentation implies they are mandatory for the pattern:

If you are already using packages and blueprints for your application [...]

So I adjusted your code to use a blueprint instead:

app/main/__init__.py:

here is one way to do the job. [grin] it presumes that you only want to 1st connection type found. if you want all of them [for instance, JBloggs has all 3 types listed], you will need to concatenate them.

what it does ...

• fakes reading in the CSV files
  when ready to use real data, comment out or remove the entire #region/#endregion section and use Get-Content.
• iterates thru the main collection
• uses a switch to test for membership in each connection type list
  this breaks out of the switch when it finds a match since it presumes you only want the 1st match. if you want all of them, then you will need to accumulate them instead of breaking out of the switch block.
• sets the $ConnectionType as appropriate
• builds a PSCO with all the wanted props
  this likely could be shortened by using Select-Object, a wildcard property selector, and a calculated property.
• sends it out to the $Results collection
• shows it on screen
• saves it to a CSV file

the code ...

By calling new TTree(&chain) you're trying to call a constructor for a TTree and you provide it with a TChain * (the type of chain is TChain, so &chain is a pointer to a TChain).

The constructors for TTree https://root.cern/doc/v618/classTTree.html take either no argument or two const char* (usually string literals or .Data() of a TString or .c_str() of a std::string or the output of ROOT's Form …).

It looks like you try to call the deleted constructor TTree(const TTree&tt)=delete, which doesn't work for several reasons:

• you're providing a pointer to a TTree instead of a TTree by reference (not even sure from the top of my head if casting from TChain to TTree would work if the & wasn't there.
• the constructor is deleted, so it doesn't actually exist and cannot be called.

However, from the looks of it, you want to use your TChain as a TTree*, which doesn't require any code from your side to begin with because a TChain already is a TTree by inheritance. So, you can use chain. instead of tree->, or (if having a pointer variable is really more desirable for reasons that I don't see in the example) create a TTree* (i.e. create only the pointer to a TTree, instead of creating the actual TTree on the heap and get a pointer to it from the new operator) by doing something like

One option to get the data is to use a negative lookahead (if supported) to match the digit format at the start and repeat matching all the lines that do not start with either that same digit format or Please find

Then you can either match the whole line using .* (which will also match an empty line) or use a character class to specify what you would allow to match.

Python 2 and 3 differ in their treatment of byte strings versus unicode strings: Python 2 implicitly converts (weakly, dynamically typed), but Python 3 complains (strongly, dynamically typed).

Names that come from ROOT files are byte strings because ROOT provides no encodings. They're all just "char *". The appropriate Python type is byte string.

OAMap just doesn't want to deal with this— array names are strings, meaning anything in unicode. In Python 2, an encoding is implicitly assigned to make this true; Python 3 is stricter about how the encoding is assigned. Its connector to ROOT might be missing cases to handle unencoded byte strings.

Switch to Python 2 for an easy fix.

It seems server sends information that it will send data encoded ISO-8859-1