Python High Performance
Build robust applications by implementing concurrent and
distributed processing techniques
BIRMINGHAM - MUMBAI
Python High Performance
Copyright © 2017 Packt Publishing
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First published: December 2013
Second edition: May 2017
Production reference: 2250517
Published by Packt Publishing Ltd.
35 Livery Street
B3 2PB, UK.
Tejal Daruwale Soni
Content Development Editor
About the Author
Dr. Gabriele Lanaro has been conducting research to study the formation and growth of
crystals using medium and large-scale computer simulations. In 2017, he obtained his PhD
in theoretical chemistry. His interests span machine learning, numerical computing
visualization, and web technologies. He has a sheer passion for good software and is the
author of the chemlab and chemview open source packages. In 2013, he authored the first
edition of the book “High Performance Python Programming”.
I'd like to acknowledge the support from Packt editors, including Vikas Tiwari. I would also
like to thank my girlfriend, Harani, who had to tolerate the way-too-long writing nights,
and friends who provided company and support throughout. Also, as always, I’d love to
thank my parents for giving me the opportunity to pursue my ambitions.
Lastly, I would like to thank Blenz coffee for powering the execution engine of this book
through electricity and caffeine.
Traceback (most recent call last): File "F:\python3.7.9\python_work\克隆声音\MockingBird\toolbox\__init__.py", line 143, in <lambda> func = lambda: self.synthesize() or self.vocode() File "F:\python3.7.9\python_work\克隆声音\MockingBird\toolbox\__init__.py", line 293, in vocode wav, sample_rate = vocoder.infer_waveform(spec, progress_callback=vocoder_progress) File "F:\python3.7.9\python_work\克隆声音\MockingBird\vocoder\wavernn\inference.py", line 63, in infer_waveform wav = _model.generate(mel, batched, target, overlap, hp.mu_law, progress_callback) File "F:\python3.7.9\python_work\克隆声音\MockingBird\vocoder\wavernn\models\fatchord_version.py", line 253, in generate output[-20 * self.hop_length:] *= fade_out ValueError: operands could not be broadcast together with shapes (2200,) (4000,) (2200,)
def dist_for_float(p1, p2): p1 = DTW.numpy_num_to_python_num(p1) p2 = DTW.numpy_num_to_python_num(p2) if (type(p1) == float or type(p1) == int) and \ (type(p2) == float or type(p2) == int): dist = float(abs(p1 - p2)) return dist else: sum_val = 0.0 for i in range(len(p1)): sum_val += pow(p1[i] - p2[i], 2) dist = pow(sum_val, 0.5) return dist怎样实现将这段函数里的欧氏距离改成马氏距离
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