PyTorch Release NotesFramework containers are no longer tested on Pascal GPU architectures. ‣ Transformer Engine is a library for accelerating Transformer models on NVIDIA GPUs. It includes support for 8-bit floating point Framework containers are no longer tested on Pascal GPU architectures. ‣ Transformer Engine is a library for accelerating Transformer models on NVIDIA GPUs. It includes support for 8-bit floating point Framework containers will no longer be tested on Pascal GPU architectures. ‣ Transformer Engine is a library for accelerating Transformer models on NVIDIA GPUs. It includes support for 8-bit floating point0 码力 | 365 页 | 2.94 MB | 1 年前3
keras tutorialTheano, TensorFlow, Caffe, Mxnet etc., Keras is one of the most powerful and easy to use python library, which is built on top of popular deep learning libraries like TensorFlow, Theano, etc., for creating or Cognitive Toolkit (CNTK). Theano is a python library used for fast numerical computation tasks. TensorFlow is the most famous symbolic math library used for creating neural networks and deep learning Linux or Mac) Python version 3.5 or higher. Python Keras is python based neural network library so python must be installed on your machine. If python is properly installed on your machine, then0 码力 | 98 页 | 1.57 MB | 1 年前3
《Efficient Deep Learning Book》[EDL] Chapter 5 - Advanced Compression Techniquesmodel and wraps the prunable blocks for sparse training using TFMOT (Tensorflow Model Optimization) library. In this case, we prune the 50% of the weights in each prunable block using magnitude-based pruning performance. Let's go ahead and strip the pruning weights from the model that were added by the TFMOT library as shown below. # Strip the pruning wrappers from the model. stripped_model = tfmot.sparsity.keras sparsity, we will use the Tensorflow Model Optimization Toolkit (TFMOT) library to cluster our model’s weights. Installing the library is fairly simple as we saw earlier. ! pip install -q tensorflow-model-optimization0 码力 | 34 页 | 3.18 MB | 1 年前3
《Efficient Deep Learning Book》[EDL] Chapter 3 - Learning Techniquesup the required libraries, and loading the training and validation sets. We leverage the nlpaug library to perform the augmentations. It provides a simple 5 Maas, Andrew, et al. "Learning word vectors technologies. 2011. mechanism to chain multiple augmentations. It can be replaced with any other library per individual preference. %%capture # We will use nlpaug to augment the text samples. !pip install function. Now, let’s add some text augmentations to the mix and see if that helps. The nlpaug python library offers concise ways to apply sentence, word and character augmentations. We shuffle sentences, substitute0 码力 | 56 页 | 18.93 MB | 1 年前3
《Efficient Deep Learning Book》[EDL] Chapter 6 - Advanced Learning Techniques - Technical Reviewtest_dataset.shuffle(test_dataset.cardinality()).batch(BATCH_SIZE) We will import the tensorflow_text library so that we can use the BERT model which relies on certain tensorflow ops. import os # tensorflow_text ops used in our model. import tensorflow_text as tf_text Next we will import the tensorflow_hub library so that we can import pre-trained BERT models directly from Tensorflow Hub. import tensorflow_hub0 码力 | 31 页 | 4.03 MB | 1 年前3
Experiment 2: Logistic Regression and Newton's Methodfunction is hθ(x) = g(θT x) = 1 1 + e−θT x = P(y = 1 | x; θ) (1) Matlab/Octave does not have a library function for the sigmoid, so you will have to define it yourself. The easiest way to do this is through0 码力 | 4 页 | 196.41 KB | 1 年前3
PyTorch Tutoriallines to code in comparison. • It is easy to debug and understand the code. • Python usage − This library is considered to be Pythonic which smoothly integrates with the Python data science stack. • It0 码力 | 38 页 | 4.09 MB | 1 年前3
《TensorFlow 快速入门与实战》6-实战TensorFlow验证码识别模型服务部署 • flask $ pip install Pillow captcha pydot flask Pillow (PIL Fork) PIL(Python Imaging Library) 为 Python 解释器添加了图像处理功能。但是,在 2009 年发布 1.1.7 版本后,社区便停止更新和维护。 Pillow 是由 Alex Clark 及社区贡献者 一起开发和维护的一款分叉自0 码力 | 51 页 | 2.73 MB | 1 年前3
亚马逊AWSAI Services Overview640x480 resolution 处处可部署 Beyond BlindTool by Joseph Paul Cohen, demo on Nexus 4 Fit the core library with all dependencies into a single C++ source file Easy to compile on …0 码力 | 56 页 | 4.97 MB | 1 年前3
《TensorFlow 快速入门与实战》7-实战TensorFlow人脸识别�������� �������� �� API – �AI���� �� API – �AI���� OpenCV ���������Open Source Computer Vision Library, OpenCV���BSD����� ���C ++�Python�Java�����Windows�Linux�Mac OS�iOS�Android� OpenCV��������������������0 码力 | 81 页 | 12.64 MB | 1 年前3
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