generators | Laravel 5 Generators | Build Tool library

You need to explicitly create the object for that test suite & execute it. In IDE you're relying on specific runner, but it doesn't work in the notebook environment.

You can use either the .execute function of create object (docs):

It is a requirement of the ECMAScript specification for generators to allocate a new object for each yield, so all compliant JS engines have to do it.

It is possible in theory for a JS engine to reuse a generator's result object if it can prove that the program's observable behavior would not change as a result of this optimization, such as when the only use of the generator is in a const {value, done} = generatorObject.next() statement. However, I am not aware of any engines (at least those that are used in popular web browsers) that do this. Optimizations like this are a very hard problem in JavaScript because of its dynamic nature.

Raster or bitmap fonts are represented in a number of different ways and there are bitmap font file standards that have been developed for both Linux and Windows. However raw data representation of bitmap fonts in programming language source code seems to vary depending on:

• the memory architecture of the target computer,
• the architecture and communication pathways to the display controller,
• character glyph height and width in pixels and
• the amount of memory for bitmap storage and what measures are taken to make that as small as possible.

A brief overview of bitmap fonts

A generic bitmap is a block of data in which individual bits are used to indicate a state of either on or off. One use of a bitmap is to store image data. Character glyphs can be created and stored as a collection of images, one for each character in the character set, so using a bitmap to encode and store each character image is a natural fit.

Bitmap fonts are bitmaps used to indicate how to display or print characters by turning on or off pixels or printing or not printing dots on a page. See Wikipedia Bitmap fonts

A bitmap font is one that stores each glyph as an array of pixels (that is, a bitmap). It is less commonly known as a raster font or a pixel font. Bitmap fonts are simply collections of raster images of glyphs. For each variant of the font, there is a complete set of glyph images, with each set containing an image for each character. For example, if a font has three sizes, and any combination of bold and italic, then there must be 12 complete sets of images.

A brief history of using bitmap fonts

The earliest user interface terminals such as teletype terminals used dot matrix printer mechanisms to print on rolls of paper. With the development of Cathode Ray Tube terminals bitmap fonts were readily transferable to that technology as dots of luminescence turned on and off by a scanning electron gun.

Earliest bitmap fonts were of a fixed height and width with the bitmap acting as a kind of stamp or pattern to print characters on the output medium, paper or display tube, with a fixed line height and a fixed line width such as the 80 columns and 24 lines of the DEC VT-100 terminal.

With increasing processing power, a more sophisticated typographical approach became available with vector fonts used to improve displayed text quality and provide improved scaling while also reducing memory required to describe the character glyphs.

In addition, while a matrix of dots or pixels worked fairly well for languages such as English, written languages with complex glyph forms were poorly served by bitmap fonts.

Representation of bitmap fonts in source code

There are a number of bitmap font file formats which provide a way to represent a bitmap font in a device independent description. For an example see Wikipedia topic - Glyph Bitmap Distribution Format

The Glyph Bitmap Distribution Format (BDF) by Adobe is a file format for storing bitmap fonts. The content takes the form of a text file intended to be human- and computer-readable. BDF is typically used in Unix X Window environments. It has largely been replaced by the PCF font format which is somewhat more efficient, and by scalable fonts such as OpenType and TrueType fonts.

Other bitmap standards such as XBM, Wikipedia topic - X BitMap, or XPM, Wikipedia topic - X PixMap, are source code components that describe bitmaps however many of these are not meant for bitmap fonts specifically but rather other graphical images such as icons, cursors, etc.

As bitmap fonts are an older format many times bitmap fonts are wrapped within another font standard such as TrueType in order to be compatible with the standard font subsystems of modern operating systems such as Linux and Windows.

However embedded systems that are running on the bare metal or using an RTOS will normally need the raw bitmap character image data in the form similar to the XBM format. See Encyclopedia of Graphics File Formats which has this example:

Following is an example of a 16x16 bitmap stored using both its X10 and X11 variations. Note that each array contains exactly the same data, but is stored using different data word types:

You can make generator in various ways

inline

The module fractions is part of the Python standard library. There used to be a function gcd, which, as the linked documentation says, is:

Deprecated since version 3.5: Use math.gcd() instead.

Since the function gcd was removed from the module fractions in Python 3.9, it seems that the question uses Python 3.9, not Python 3.7.6 as the question notes, because that Python version still had fractions.gcd.

The error is raised by networkx. Upgrading to the latest version of networkx is expected to avoid this issue:

383 on the log is not the batch size. It's the number of steps which is data_size / batch_size.

The problem that training does not work properly is probably because of very low or high learning rate. Try adjusting the learning rate.

You should export the axios instance like :

There are many small errros in your code:

• You are using string path instead of variable path while using generators.
• Also train path, validation path and test path should be different.
• You have not specified input_tensor for VGG19 model.

Your piece of code should be like this: