XLA (Xtreme Linear Algorithm)


There is no direct implementation of “Hello World!” in XLA, as it is a compilation target for TensorFlow MLIR and not a general-purpose programming language. However, you can use the TensorFlow framework to write “Hello World!” using XLA. Here’s an example code snippet:

import tensorflow as tf
tf.enable_xla_application()  # Enable XLA compilation for TensorFlow

@tf.function(jit_compile=True)  # Mark the function to be compiled with XLA
def hello_world():
    return tf.constant("Hello World!")

# Call the hello_world() function and print the result
print(hello_world())

This code snippet uses TensorFlow’s JIT (just-in-time) compiler to compile the hello_world() function using XLA. The @tf.function decorator enables JIT compilation, and the jit_compile=True argument explicitly requests XLA compilation. The hello_world() function simply returns a constant string “Hello World!”. Finally, the code prints the result of calling the hello_world() function.

Prompt
beautiful woman, in full height, great body, gorgeous figure, beautiful face, learns XLA (Xtreme Linear Algorithm) programming language, beautiful background, magnificent scenery, colorful, very detailed, HD, highly detailed, sharp focus, stunningly beautiful, cinematic photo 35mm photograph, film, professional, 4k, highly detailed

Negative prompt
bokeh, drawing, painting, crayon, sketch, graphite, impressionist, noisy, blurry, soft, deformed, ugly

Text model: silicon-masha

Image model: ProtoVisionXL

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