Justin Chu justinchuby

To allow the Hugging Face version of Whisper to predict word-level timestamps, a new property alignment_heads must be added to the GenerationConfig object. This is a list of [layer, head] pairs that select the cross-attention heads that are highly correlated to word-level timing.

If your Whisper checkpoint does not have the alignment_heads property yet, it can be added in two possible ways.

Method 1. Change the model.generation_config property:

# load the model
model = WhisperForConditionalGeneration.from_pretrained("your_checkpoint")

Best practice for importing in Python

1. Import at top level only

Allow imports at the module toplevel only, unless (1) it is too expensive to load the module or (2) module may not be available.

It is clear what a module needs when all imports are grouped in a single place. This makes refactoring easy.
Otherwise, any import errors will be raised only when the code executes. Erroneous imports may go undetected until the code path is hit at runtime.
Doing so reduces code duplication and improves consistency when we don't have the same import lines spread across the file.
Pylint has rule that checks for this: https://pylint.readthedocs.io/en/latest/user_guide/messages/convention/import-outside-toplevel.html

Part 1: Adopt the Right Mindsets

Focus on High-Leverage Activities

How should we decide what actually to work on in order to more effectively achieve our goals? Assess the activities' leverage:

Leverage =  (Impact Produce) / (Time Invested)

Another way of thinking about leverage is the commonly-mentioned Pare- to principle, or 80–20 rule—the notion that for many activities, 80% of the im- pact comes from 20% of the work.

	import torch
	from torch.nn.attention._flex_attention import _create_block_mask, _create_mask
	from functools import partial
	from torch.nn.attention._flex_attention import _flex_attention
	from triton.testing import do_bench
	import torch.nn.functional as F
	from functools import lru_cache
	torch.set_default_device('cuda')

	# Example usage

	/*
	Program to demonstrate using one session and multiple threads to call Run on that session.
	g++ -std=c++17 -o test_ort_one_session_multiple_threads test_ort_one_session_multiple_threads.cc -I onnxruntime-linux-x64-1.15.1/include/ -lonnxruntime -Lonnxruntime-linux-x64-1.15.1/lib/ -lpthread -Wl,-rpath,/home/pranav/onnxruntime-linux-x64-1.15.1/lib/
	Author: Github id: pranavsharma)
	*/

	#include <onnxruntime_cxx_api.h>
	#include <vector>
	#include <string>
	#include <iostream>

	/**
	* The implementation of unification-based type inference algorithm in simply typed lambda calculus with Let-Polymorphism
	*
	* The unification-based type inference algorithm is widely used in a huge variety of programming languages, where the most
	* famous one is the Hindley-Milner Type System (a.k.a Damas-Milner Type System) of the ML-Family which permits the programmer
	* to omit almost all of the type annotations, the algorithm is based on two concepts: Constraint Set and Unifier.
	*
	* A constraint set consist of several constraints, a constraints is basically a type equation, e.g., X = T, where both X and
	* T are types
	* A unifier is a set of type substitutions [X -> T1, Y -> T2, ...], it replaces all the type variables in its domain to the

	I've tested it on Fedora 23 and Ubuntu 16.04. I'm using gcc-5.3.1, python-3.4, VS Code-1.14.0
	You can debug mixed Python/C++ in the same GUI. It also works for MPI applications. You can switch between the debuggers and corresponding call stacks.

	1. Packages needed
	1) Visual Studio Code

	2) Extensions for VS Code:
	"Python" from Don Jayamanne (I'm using 0.6.7)
	This allows VS Code act as the front end to debug python.
	This gives VS Code ability to attach to a python script that uses module "ptvsd".

	#!/bin/bash
	#
	# This script filters rustfmt output for format-on-save workflows in text
	# editors.
	#
	# Usage:
	#
	# rustfmt-skip-children /path/to/source
	#
	# In particular, it:

	# Copyright 2019 Google LLC.
	# SPDX-License-Identifier: Apache-2.0

	# Author: Anton Mikhailov

	turbo_colormap_data = [[0.18995,0.07176,0.23217],[0.19483,0.08339,0.26149],[0.19956,0.09498,0.29024],[0.20415,0.10652,0.31844],[0.20860,0.11802,0.34607],[0.21291,0.12947,0.37314],[0.21708,0.14087,0.39964],[0.22111,0.15223,0.42558],[0.22500,0.16354,0.45096],[0.22875,0.17481,0.47578],[0.23236,0.18603,0.50004],[0.23582,0.19720,0.52373],[0.23915,0.20833,0.54686],[0.24234,0.21941,0.56942],[0.24539,0.23044,0.59142],[0.24830,0.24143,0.61286],[0.25107,0.25237,0.63374],[0.25369,0.26327,0.65406],[0.25618,0.27412,0.67381],[0.25853,0.28492,0.69300],[0.26074,0.29568,0.71162],[0.26280,0.30639,0.72968],[0.26473,0.31706,0.74718],[0.26652,0.32768,0.76412],[0.26816,0.33825,0.78050],[0.26967,0.34878,0.79631],[0.27103,0.35926,0.81156],[0.27226,0.36970,0.82624],[0.27334,0.38008,0.84037],[0.27429,0.39043,0.85393],[0.27509,0.40072,0.86692],[0.27576,0.41097,0.87936],[0.27628,0.42118,0.89123],[0.27667,0.43134,0.90254],[0.27691,0.44145,0.913

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