Python Software Foundation: The 2021 Python Language Summit: Fuzzing and Testing Python With Properties
Link: http://feedproxy.google.com/~r/PythonSoftwareFoundationNews/~3/4JkUDb_sHRc/the-2021-python-language-summit-fuzzing.html
At the 2021 Python Language Summit, Zac Hatfield-Dodds gave a presentation about fuzzing and testing with Python properties. This presentation tied in with the one he gave at the 2020 Python Language
Link: http://feedproxy.google.com/~r/PythonSoftwareFoundationNews/~3/4JkUDb_sHRc/the-2021-python-language-summit-fuzzing.html
At the 2021 Python Language Summit, Zac Hatfield-Dodds gave a presentation about fuzzing and testing with Python properties. This presentation tied in with the one he gave at the 2020 Python Language
Blogspot
The 2021 Python Language Summit: Fuzzing and Testing Python With Properties
At the 2021 Python Language Summit , Zac Hatfield-Dodds gave a presentation about fuzzing and testing with Python properties. This presenta...
Mike Driscoll: PyDev of the Week: Fernando Masanori
Link: https://www.blog.pythonlibrary.org/2021/06/07/pydev-of-the-week-fernando-masanori/
This week we welcome Fernando Masanori (@fmasanori) as our PyDev of the Week! Fernando is a Professor at FATEC São José dos Campos in Brazil. He is the creator of the first Brazilian MOOC to teach pro
Link: https://www.blog.pythonlibrary.org/2021/06/07/pydev-of-the-week-fernando-masanori/
This week we welcome Fernando Masanori (@fmasanori) as our PyDev of the Week! Fernando is a Professor at FATEC São José dos Campos in Brazil. He is the creator of the first Brazilian MOOC to teach pro
Mouse Vs Python
PyDev of the Week: Fernando Masanori - Mouse Vs Python
Gain practical, real-world Python skills with our resources and pathway
Stack Abuse: Python's itertools – count(), cycle() and chain()
Link: https://stackabuse.com/pythons-itertools-count-cycle-and-chain
Introduction
Python has a lot of built-in tools that allow us to iterate and transform data. A great example is the itertools module, which offers several convenient iteration functions. Each of these
Link: https://stackabuse.com/pythons-itertools-count-cycle-and-chain
Introduction
Python has a lot of built-in tools that allow us to iterate and transform data. A great example is the itertools module, which offers several convenient iteration functions. Each of these
Stack Abuse
Python's itertools – count(), cycle() and chain()
In this tutorial, we'll be taking a look at the `itertools` module in Python - and take a look at examples of count(), cycle() and eval().
Real Python: Python Community Interview With Sebastián Ramírez
Link: https://realpython.com/interview-sebastian-ramirez/
Today, I’m joined by Sebastián Ramírez, a software developer at Explosion AI. He is also the creator of the popular frameworks FastAPI and Typer. In this interview, we discuss typing in Python, his mo
Link: https://realpython.com/interview-sebastian-ramirez/
Today, I’m joined by Sebastián Ramírez, a software developer at Explosion AI. He is also the creator of the popular frameworks FastAPI and Typer. In this interview, we discuss typing in Python, his mo
Realpython
Python Community Interview With Sebastián Ramírez – Real Python
Sebastián Ramírez is a software developer at Explosion AI and is the creator of the popular frameworks FastAPI and Typer. In this interview, we discuss typing in Python, his motivations for creating FastAPI and the future of the framework, and much more.
PyCharm: PyCharm 2021.2 EAP Has Started!
Link: http://feedproxy.google.com/~r/Pycharm/~3/NOaEWB5FWHk/
Time to try new features and weight in with your active feedback!
We are opening a new cycle of the Early Access Program for those of you eager to try, discuss, and maybe even contribute to new PyChar
Link: http://feedproxy.google.com/~r/Pycharm/~3/NOaEWB5FWHk/
Time to try new features and weight in with your active feedback!
We are opening a new cycle of the Early Access Program for those of you eager to try, discuss, and maybe even contribute to new PyChar
JetBrains Blog
PyCharm 2021.2 EAP Has Started! | The PyCharm Blog
Time to try new features and weight in with your active feedback!
We are opening a new cycle of the Early Access Program for those of you eager to try, discuss, and maybe even contribute to new PyChar
We are opening a new cycle of the Early Access Program for those of you eager to try, discuss, and maybe even contribute to new PyChar
Reuven Lerner: Python parameters primer
Link: https://lerner.co.il/2021/06/07/python-parameters-primer/
Python makes it easy to write functions. For example, I can write:
def hello(name):
return f'Hello, {name}!'
I can then run the function with:
hello('world')
which will then, not surprisingly, ret
Link: https://lerner.co.il/2021/06/07/python-parameters-primer/
Python makes it easy to write functions. For example, I can write:
def hello(name):
return f'Hello, {name}!'
I can then run the function with:
hello('world')
which will then, not surprisingly, ret
Reuven Lerner
Python parameters primer
Python makes it easy to write functions. For example, I can write: def hello(name): return f'Hello, {name}!' I can then run the function with: hello('world') which will then, not surprisingly, return the string 'Hello, world'
AI Pool: Dropout can't be converted into tflite
Link: https://ai-pool.com/d/dropout_can_t_be_converted_into_tflite
I'm using Keras 2.1 with TensorFlow backend 1.13. I tried to convert my model into tflite, but found out that dropout layers can't be converted. It does not matter I have Keras dropout or TensorFlow
Link: https://ai-pool.com/d/dropout_can_t_be_converted_into_tflite
I'm using Keras 2.1 with TensorFlow backend 1.13. I tried to convert my model into tflite, but found out that dropout layers can't be converted. It does not matter I have Keras dropout or TensorFlow
Ai-Pool
Dropout can't be converted into tflite
I'm using Keras 2.1 with TensorFlow backend 1.13. I tried to convert my model into tflite, but found out that dropout layers can't be converted. It does not matter I have Keras dropout or TensorFlow dropout layer. how to skip this issue?
AI Pool: Keras model to tflite
Link: https://ai-pool.com/d/keras_model_to_tflite
I've got a Keras model in the hdf5 file and wanted to convert it into tflite, but I've got an issue like this model = 'model.h5'
converter = tf.lite.TFLiteConverter.from_keras_model_file(model)
tfl
Link: https://ai-pool.com/d/keras_model_to_tflite
I've got a Keras model in the hdf5 file and wanted to convert it into tflite, but I've got an issue like this model = 'model.h5'
converter = tf.lite.TFLiteConverter.from_keras_model_file(model)
tfl
Ai-Pool
Keras model to tflite
I've got a Keras model in the hdf5 file and wanted to convert it into tflite, but I've got an issue like this model = 'model.h5'
converter = tf.lite.TFLiteConverter.from_keras_model_file(model)
tflite_model = converter.convert()
open("converted/model.tflite"…
converter = tf.lite.TFLiteConverter.from_keras_model_file(model)
tflite_model = converter.convert()
open("converted/model.tflite"…
AI Pool: Self normalized networks in Tensorflow
Link: https://ai-pool.com/d/self_normalized_networks_in_tensorflow
Is there an implementation in self normalized networks in TensorFlow ? I saw that it's implemented in Keras called Selu as an activation function but I can't find it is implemented in TensorFlow or
Link: https://ai-pool.com/d/self_normalized_networks_in_tensorflow
Is there an implementation in self normalized networks in TensorFlow ? I saw that it's implemented in Keras called Selu as an activation function but I can't find it is implemented in TensorFlow or
Ai-Pool
Self normalized networks in Tensorflow
Is there an implementation in self normalized networks in TensorFlow ? I saw that it's implemented in Keras called Selu as an activation function but I can't find it is implemented in TensorFlow or not.
AI Pool: Module 'tensorboard.util' has no attribute 'Retrier'
Link: https://ai-pool.com/d/module__tensorboard_util__has_no_attribute__retrier_
I upgraded my TensorFlow to 1.13, upgraded Cuda from 9 -> 10 also had to upgrade Tensorboard. All processes went well, but now I've got an issue like this AttributeError: module 'tensorboard.util'
Link: https://ai-pool.com/d/module__tensorboard_util__has_no_attribute__retrier_
I upgraded my TensorFlow to 1.13, upgraded Cuda from 9 -> 10 also had to upgrade Tensorboard. All processes went well, but now I've got an issue like this AttributeError: module 'tensorboard.util'
Ai-Pool
Module 'tensorboard.util' has no attribute 'Retrier'
I upgraded my TensorFlow to 1.13, upgraded Cuda from 9 -> 10 also had to upgrade Tensorboard. All processes went well, but now I've got an issue like this AttributeError: module 'tensorboard.util' has no attribute 'Retrier'
Python Pool: Know About Numpy Heaviside in Python
Link: https://www.pythonpool.com/numpy-heaviside/?utm_source=rss&utm_medium=rss&utm_campaign=numpy-heaviside
The post Know About Numpy Heaviside in Python appeared first on Python Pool.
Numpy, which stands for Numerical Python, is a python library used to work with multi-dimensional arrays and matrices. With
Link: https://www.pythonpool.com/numpy-heaviside/?utm_source=rss&utm_medium=rss&utm_campaign=numpy-heaviside
The post Know About Numpy Heaviside in Python appeared first on Python Pool.
Numpy, which stands for Numerical Python, is a python library used to work with multi-dimensional arrays and matrices. With
Python Pool
Know About Numpy Heaviside in Python
Numpy, which stands for Numerical Python, is a python library used to work with multi-dimensional arrays and matrices. With the numpy library, we can
Python Pool: Numpy ix_ Function: Things You Need to Know
Link: https://www.pythonpool.com/numpy-ix_/?utm_source=rss&utm_medium=rss&utm_campaign=numpy-ix_
The post Numpy ix_ Function: Things You Need to Know appeared first on Python Pool.
The numpy library in python is used for working with multi-dimensional arrays and matrices while performing logical
Link: https://www.pythonpool.com/numpy-ix_/?utm_source=rss&utm_medium=rss&utm_campaign=numpy-ix_
The post Numpy ix_ Function: Things You Need to Know appeared first on Python Pool.
The numpy library in python is used for working with multi-dimensional arrays and matrices while performing logical
Python Pool
Numpy ix_ Function: Things You Need to Know
The numpy library in python is used for working with multi-dimensional arrays and matrices while performing logical and mathematical operations on them.
Python Pool: Discovering The Numpy ifft Function in Python
Link: https://www.pythonpool.com/numpy-ifft/?utm_source=rss&utm_medium=rss&utm_campaign=numpy-ifft
The post Discovering The Numpy ifft Function in Python appeared first on Python Pool.
Numpy, which is short for Numerical Python, is a library that helps work with multi-dimensional arrays and matrice
Link: https://www.pythonpool.com/numpy-ifft/?utm_source=rss&utm_medium=rss&utm_campaign=numpy-ifft
The post Discovering The Numpy ifft Function in Python appeared first on Python Pool.
Numpy, which is short for Numerical Python, is a library that helps work with multi-dimensional arrays and matrice
Python Pool
Discovering The Numpy ifft Function in Python - Python Pool
The Numpy ifft is a function in python's numpy library which is used for obtaining the one dimensional inverse discrete Fourier Transform.
Python Pool: All about Numpy Piecewise Function
Link: https://www.pythonpool.com/numpy-piecewise/?utm_source=rss&utm_medium=rss&utm_campaign=numpy-piecewise
The post All about Numpy Piecewise Function appeared first on Python Pool.
Numpy is a library in python that is used for working with multi-dimensional arrays and matrices. With numpy, we can perform
Link: https://www.pythonpool.com/numpy-piecewise/?utm_source=rss&utm_medium=rss&utm_campaign=numpy-piecewise
The post All about Numpy Piecewise Function appeared first on Python Pool.
Numpy is a library in python that is used for working with multi-dimensional arrays and matrices. With numpy, we can perform
Python Pool
All about Numpy Piecewise Function
Numpy is a library in python that is used for working with multi-dimensional arrays and matrices. With numpy, we can perform several logical and
Real Python: Python Basics: Setting Up Python
Link: https://realpython.com/courses/setting-up-python/
Setting up Python is the first step to becoming a Python programmer. In this course, you’ll learn how to download and install Python for Windows, macOS, and Ubuntu Linux and how to open Python’s Integ
Link: https://realpython.com/courses/setting-up-python/
Setting up Python is the first step to becoming a Python programmer. In this course, you’ll learn how to download and install Python for Windows, macOS, and Ubuntu Linux and how to open Python’s Integ
Realpython
Python Basics: Setting Up Python – Real Python
The first step to getting started with Python is to set it up on your machine. In this course, you'll learn how to download Python for Windows, macOS, and Ubuntu Linux and how to open Python's Integrated Development and Learning Environment, IDLE.
Python for Beginners: Introduction to Deque module in Python
Link: https://www.pythonforbeginners.com/deque/introduction-to-deque-module-in-python
Double ended queue or Deque is a linear data structure in which we can insert or remove elements from both its ends i.e. It supports last in first out (LIFO) operations as well as first in first out
Link: https://www.pythonforbeginners.com/deque/introduction-to-deque-module-in-python
Double ended queue or Deque is a linear data structure in which we can insert or remove elements from both its ends i.e. It supports last in first out (LIFO) operations as well as first in first out
PythonForBeginners.com
Introduction to Deque module in Python - PythonForBeginners.com
Introduction to Deque module in Python will help you improve your python skills with easy to follow examples and tutorials.
PyCoder’s Weekly: Issue #476 (June 8, 2021)
Link: https://pycoders.com/issues/476
#476 – JUNE 8, 2021 View in Browser » PEP 654: Exception Groups and except* Currently, Python’s exception handling mechanisms only allow you to focus on a single exception at a time. PEP 654, wh
Link: https://pycoders.com/issues/476
#476 – JUNE 8, 2021 View in Browser » PEP 654: Exception Groups and except* Currently, Python’s exception handling mechanisms only allow you to focus on a single exception at a time. PEP 654, wh
Pycoders
PyCoder’s Weekly | Issue #476
Issue #476 of the PyCoder’s Weekly newsletter, published June 8, 2021.
AI Pool: Tensorflow 1.13 does not use GPU
Link: https://ai-pool.com/d/tensorflow-1-13-does-not-use-gpu
I'm using Keras 2.0 with TensorFlow 1.13 backend. I had to upgrade my Tensorflow. Solved all issues, but realized TensorFlow is not using GPU. Also CUDA_VISIBLE_DEVICES = 0 is set. When I try to print
Link: https://ai-pool.com/d/tensorflow-1-13-does-not-use-gpu
I'm using Keras 2.0 with TensorFlow 1.13 backend. I had to upgrade my Tensorflow. Solved all issues, but realized TensorFlow is not using GPU. Also CUDA_VISIBLE_DEVICES = 0 is set. When I try to print
Ai-Pool
Tensorflow 1.13 does not use GPU
I'm using Keras 2.0 with TensorFlow 1.13 backend. I had to upgrade my Tensorflow. Solved all issues, but realized TensorFlow is not using GPU. Also CUDA_VISIBLE_DEVICES = 0 is set. When I try to print all visible devices in TensorFlow, it prints CPU devices…
AI Pool: Multiple Graphs in Tensorflow Session
Link: https://ai-pool.com/d/multiple_graphs_in_tensorflow_session
Is there a way to have multiple graphs in one TensorFlow session? I just want to separate my network and create 2 different graphs, cause I need to use one graph for its outputs, and the other for sav
Link: https://ai-pool.com/d/multiple_graphs_in_tensorflow_session
Is there a way to have multiple graphs in one TensorFlow session? I just want to separate my network and create 2 different graphs, cause I need to use one graph for its outputs, and the other for sav
Ai-Pool
Multiple Graphs in Tensorflow Session
Is there a way to have multiple graphs in one TensorFlow session? I just want to separate my network and create 2 different graphs, cause I need to use one graph for its outputs, and the other for saving as my model.
AI Pool: Images in tensorboard
Link: https://ai-pool.com/d/images_in_tensorboard
I know that you can show your training result images inside Tensorboard, but can't find a way how to do it properly with Keras. What is the best way to show images? I'm using Keras 2.1.4 and Tens
Link: https://ai-pool.com/d/images_in_tensorboard
I know that you can show your training result images inside Tensorboard, but can't find a way how to do it properly with Keras. What is the best way to show images? I'm using Keras 2.1.4 and Tens
Ai-Pool
Images in tensorboard
I know that you can show your training result images inside Tensorboard, but can't find a way how to do it properly with Keras. What is the best way to show images? I'm using Keras 2.1.4 and Tensorflow 1.13.1