The group vector measurement of three phase transformer. The polarity measurement of single phase transformer or CT/PT(CT that knee-point voltage should be more than 80V) Voltage ratio error calculation Voltage ratio range calculation of three phase transformer ...
The group vector measurement of three phase transformer. The polarity measurement of single phase transformer or CT/PT (CT that knee-point voltage should be more than 80V) 4. Voltage ratio error calculation 5.Voltage ratio range calculation of three phase transformer ...
The calculation of unbalanced currents and voltages due, for example, to short-circuit faults requires correct and practical modelling of power transformers. In this section, we present the theory of modelling single-phase transformers, and three-phase power transformers having various numbers of windin...
In speech recognition, the input speech signal is first processed by anencoder, generating a series of vector representations. These vectors are then passed to thedecoder. To initiate the decoding process, the decoder receives a specialbegin tokenas input. The decoder outputs a vector, with its ...
Online normalizer calculation for softmax,TaurusMoon:一心二用的Online Softmax Online-softmax计算结果与softmax完全等价 Flash Attention 为什么那么快?原理讲解_哔哩哔哩_bilibili Civ:万字长文详解FlashAttention v1/v2 FlashAttention-2: Faster Attention with Better Parallelism and Work PartitioningFlashAttention-...
corresponding to a pixel value.HPAis to divide the pixel value of each patch by the sum of all pixel values on its row. It generates some new weights, which are assigned to each patch respectively. The horizontal attention weight update calculation Eq. (2) of the\(\left( {w_{i} ,h...
张量显存复用的分析,LightSeq 借鉴了论文 [3] 中提出的 Greedy by Size for Offset Calculation 方法,做了三个改进: 支持了整个训练过程的显存复用(forward/backward); 不同数据类型能做到显存复用(int8/fp16/fp32); 在多段显存空间上容纳所有张量,而非一段非常大的显存空间,这样能有效提升显存利用率。 自动GE...
The output of the temporary layers was used directly for loss calculation and back propagation. The two modules were assigned 128 and 64 channels (i.e., the parameter “L” in Supplementary Fig. 1), respectively, based on the difference in tissue numbers. In the second stage, the temporary...
Scale-aware attention consists of global pooling layer, 1 × 1 convolutional layer, ReLU activation function layer and Hard Sigmoid activation function layer, and its main calculation formula is shown in the following Eq. (1)27, where \(f\) is the linear function similar to 1 × ...
Following the shape of the matrices through the attention calculation helps to track what it's doing. The queries and keys matrices, Q and K, both come in with shape [n x d_k]. Thanks to K being transposed before multiplication, the result of Q K^T, gives a matrix of [n x d_k...