Finally, A BetterTransformer
The newly released PyTorch 1.12 has introduced BetterTransformer which implements a backwards-compatible fastpath of torch.nn.TransformerEncoder for Transformer Encoder Inference. It helps in 2x in speedup and throughput for many common execution scenarios. Image: Transformer Encoder architecture BetterTransformer launches with accelerated native implementations of MultiHeadAttention and TransformerEncoderLayer for CPUs and GPUs. These fast paths are integrated into the standard PyTorch Transformer APIs and help in accelerating TransformerEncoder, TransformerEncoderLayer and MultiHeadAttention nn.modules. Source: pytorch.org These new modules implement two types of optimizations: Fused kernels combine multiple individual operators normally used to implement Transformers to provide a more efficient implementation.Take advantage of sparsity in the inputs to avoid performing unnecessary operations on padding tokens. Padding tokens frequently account for a large fraction of input batches in many Transformer models used for Natural Language Processing. Backwards Compatibility Advantageously, BetterTransformer does not need any model change. To benefit from fast path execution, inputs and operating conditions must satisfy some access conditions. While the internal implementation of Transformer APIs has changed, PyTorch 1.12 maintains strict compatibility with Transformer modules shipped in previous versions, enabling PyTorch users to use models created and trained with previous PyTorch releases while benefiting from BetterTransformer improvements.For more details, click here
To use BetterTransformer, install PyTorch 1.12 and start using high-quality, high-performance Transformer models with the PyTorch API today.
To use BetterTransformer, install PyTorch 1.12 and start using high-quality, high-performance Transformer models with the PyTorch API today.
["Generative Pre-Trained Transformer", "Pytorch"]
["Pytorch", "API", "programming_languages:R", "PyTorch", "AI", "ai_frameworks:Transformers", "Transformers", "ai_frameworks:PyTorch", "Generative Pre-Trained Transformer", "R"]
["AI", "PyTorch", "Transformers", "R", "API", "ai_frameworks:PyTorch", "ai_frameworks:Transformers", "programming_languages:R"]
A writer by passion, Kartik strives to get a deep understanding of AI, Data analytics and its implementation on all walks of life. As a Senior Technology Journalist, Kartik looks forward to writing about the latest technological trends that transform the way of life!