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Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words.
TensorFlow.nn is a module for executing primitive neural network operations on models. [40] Some of these operations include variations of convolutions (1/2/3D, Atrous, depthwise), activation functions ( Softmax , RELU , GELU, Sigmoid , etc.) and their variations, and other operations ( max-pooling , bias-add, etc.).
The code is hosted on GitHub, and community support forums include the GitHub issues page, and a Slack channel. [citation needed] In addition to standard neural networks, Keras has support for convolutional and recurrent neural networks. It supports other common utility layers like dropout, batch normalization, and pooling. [12]
For example, an SSE instruction using the conventional two-operand form a ← a + b can now use a non-destructive three-operand form c ← a + b, preserving both source operands. Originally, AVX's three-operand format was limited to the instructions with SIMD operands (YMM), and did not include instructions with general purpose registers (e.g ...
A non-masked attention module can be thought of as a masked attention module where the mask has all entries zero. As an example of an uncommon use of mask matrix, the XLNet considers all masks of the form P M causal P − 1 {\displaystyle PM_{\text{causal}}P^{-1}} , where P {\displaystyle P} is a random permutation matrix .
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