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Source channel @githubtrending · Post #15141 · Sep 13

#python#large_language_models#machine_learning_systems#natural_language_processing Flash Linear Attention (FLA) is a fast, memory-efficient library for advanced linear attention models used in transformers, written in PyTorch and Triton, and compatible with NVIDIA, AMD, and Intel GPUs. It offers many state-of-the-art linear attention models and fused modules that speed up training and reduce memory use. You can easily replace standard attention layers in your models with FLA’s efficient versions, improving training and inference speed, especially for long sequences. FLA supports hybrid models mixing linear and standard attention, and integrates with Hugging Face Transformers for easy use and evaluation. This helps you train and run large language models faster and with less memory, making your AI projects more efficient and scalable. https://github.com/fla-org/flash-linear-attention

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djangoproject

@djangoproject · Post #575 · 02/26/2018, 03:06 AM

#Functions are first-class citizens in Python: # They can be passed as arguments to other functions, # returned as values from other functions, and # assigned to variables and stored in data structures. »> def myfunc(a, b): ... return a + b ... »> funcs = [myfunc] »> funcs[0] <function myfunc at 0x107012230> »> funcs[0](2, 3) 5

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djangoproject

@djangoproject · Post #409 · 08/12/2017, 03:01 AM

# You can use Python's built-in "dis" # module to disassemble #functions and # inspect their CPython VM bytecode: »> def greet(name): ... return 'Hello, ' + name + '!' »> greet('Dan') 'Hello, Dan!' »> import dis »> dis.dis(greet) 2 0 LOAD_CONST 1 ('Hello, ') 2 LOAD_FAST 0 (name) 4 BINARY_ADD 6 LOAD_CONST 2 ('!') 8 BINARY_ADD 10 RETURN_VALUE

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djangoproject

@djangoproject · Post #340 · 05/23/2017, 05:21 AM

# Functions are first-class citizens in Python. # They can be passed as arguments to other functions, # returned as values from other #functions, and # assigned to variables and stored in data structures. »> def myfunc(a, b): ... return a + b ... »> funcs = [myfunc] »> funcs[0] <function myfunc at 0x107012230> »> funcs[0](2, 3) 5

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djangoproject

@djangoproject · Post #430 · 09/02/2017, 03:23 AM

https://docs.python.org/3/library/subprocess.html The #subprocess module allows you to spawn new #processes, connect to their input/output/error pipes, and obtain their return codes. This module intends to replace several older #modules and #functions. #python

djangoproject

@djangoproject · Post #159 · 09/12/2016, 05:37 PM

https://docs.python.org/3/library/atexit.html The #atexit module defines #functions to #register and #unregister cleanup functions. Functions thus registered are automatically executed upon normal interpreter termination. atexit runs these functions in the reverse order in which they were registered; if you register A, B, and C, at #interpreter#termination time they will be run in the order C, B, A.

djangoproject

@djangoproject · Post #513 · 11/30/2017, 10:00 PM

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