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#!/bin/bash | |
# Verify if GPU is CUDA-enabled | |
lspci | grep -i nvidia | |
# Remove previous NVIDIA driver installation | |
sudo apt-get purge nvidia* -y | |
sudo apt remove nvidia-* -y | |
sudo rm /etc/apt/sources.list.d/cuda* -y | |
sudo apt-get autoremove && sudo apt-get autoclean -y |
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# Sebastian Raschka 09/24/2022 | |
# Create a new conda environment and packages | |
# conda create -n whisper python=3.9 | |
# conda activate whisper | |
# conda install mlxtend -c conda-forge | |
# Install ffmpeg | |
# macOS & homebrew | |
# brew install ffmpeg | |
# Ubuntu |
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import numpy as np | |
from numpy.linalg import solve | |
import logging | |
logging.basicConfig(level = logging.DEBUG) | |
from scipy.stats import moment,norm | |
def fleishman(b, c, d): | |
"""calculate the variance, skew and kurtois of a Fleishman distribution | |
F = -c + bZ + cZ^2 + dZ^3, where Z ~ N(0,1) | |
""" |
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class Leaf { | |
constructor() { | |
this.pos = createVector(random(width), random(height)); | |
this.reached = false; | |
} | |
show() { | |
fill(255, 255, 0); | |
noStroke(); | |
ellipse(this.pos.x, this.pos.y, 8, 8); |
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import torch | |
from torch import LongTensor | |
from torch.nn import Embedding, LSTM | |
from torch.autograd import Variable | |
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence | |
## We want to run LSTM on a batch of 3 character sequences ['long_str', 'tiny', 'medium'] | |
# | |
# Step 1: Construct Vocabulary | |
# Step 2: Load indexed data (list of instances, where each instance is list of character indices) |
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import numpy as np | |
EPSILON = 1e-10 | |
def _error(actual: np.ndarray, predicted: np.ndarray): | |
""" Simple error """ | |
return actual - predicted | |
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