This again shows significiant improvement, even greater than in EfficientNets, which roughly corresponds to the original ~30% improvement reported in the original github comment. Lastly, we can also see improvements w.r.t the size of a single featuremap. This is due to the fact that bigger models have both bigger as well as more featuremaps. The improvement is significant, especially for bigger EfficientNet models. How much GPU memory is saved?įinally, let’s look at how much improvement in memory allocation we can have with this simple trick.įor different EfficientNet models we see a significant improvement in memory requirements: Efficient-B0 to B7 with/without MemEffSwish Notice this equation only depends on input \(x\) and hence in our forward pass we only need to preserve \(x\). Mathematically, Swish function is defined as: It is showing some remarkable performance increase in the networks like Inception-ResNet-v2 by 0.6 and Mobile NASNet-A. swish activation function that was defined earlier in the example. A swish activation layer applies the swish function on the layer inputs. Chapter 3 / Importing Caffe Models into SAS Deep Learning. I have written the following script to report memory usage in this post:įirst proposed in paper from Google Brain team, Swish is an activation function that has recently been used in deep learning models, including MobileNetV3 and EfficientNets. Recently, Google Brain has proposed a new activation function called Swish. For importing a pretrained network from Caffe, see importCaffeNetwork (Deep. All codes discussed below are written using current PyTorch release and hence I assume the reader has basic knowledge of how simple modules can be written in PyTorch. Activation Function ReLU, Swish and Mish for Facial Mask Detection Using Convolutional Neural Network Rupshali Dasgupta, Yuvraj Sinha Chowdhury, and Sarita Nanda 1 Introduction In the eld of image processing and computer vision, face detection has been a compelling nodus. To benchmark the memory usage, I use EfficientNet implementation from MONAI. Çelebi et al. The content of this post is largely based on the original github comment. What makes this implementation save GPU memory?.How is the memory efficient version Swish implemented?.Why simple Swish implementation is inefficient?. More precisely in this post I will cover: In this (short) blog post I will briefly go over the details of this implementation and explain what enables this implementation to save GPU memory. Note: Bans will not be reversed if the post/comment in question has been deleted from your history.Recently, while implementing EfficientNet networks I came across a github comment detailing an implementation of Swish activation function that promises saving upto 30% GPU memory usage for EfficientNets. Relu, Leaky-relu, sigmoid, tanh are common among them. Some of the activation functions which are already in the buzz. You may appeal this initial ban by messaging the moderators and agreeing not to break the rules again. In this blog post we will be learning about two of the very recent activation functions Mish and Swift. Note that moderators will use their own discretion to remove any post that they believe is low-quality or not considered a LPT.īans are given out immediately and serve as a warning. Posts or comments that troll and/or do not substantially contribute to the discussion may be removed.Do not post tips that are advertisements or recommendations of products or services.Do not post tips in reaction to other posts.Posts concerning the following are not allowed: religion, politics, relationships, law and legislation, parenting, driving, medicine or hygiene (including mental health).Do not post tips that are based on spurious, unsubstantiated, or anecdotal claims.Do not post tips that could be considered common sense, common courtesy, unethical, or illegal.The tip and the problem it solves must be explained thoroughly. Posts must begin with "LPT" or "LPT Request” and be flaired.No rude, offensive, racist, homophobic, sexist, aggressive or hateful posts/comments."No snowflake in an avalanche ever feels responsible." Keep in mind that an aphorism is not a LPT.Īn aphorism is a a short clever saying that is intended to express a general truth or a concise statement of a principle. “A marriage proposal should not come as a big surprise, despite what you may have seen in the movies.” “Always be prepared to leave your employer because they are prepared to leave you.” Advice is offering someone guidance or offering someone a recommendation. Keep in mind that giving someone advice is not the same as giving someone a LPT. A Life Pro Tip (or an LPT) is a specific action with definitive results that improves life for you and those around you in a specific and significant way.
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