Conv1D

As explained in Natural Language Processing in Action, Second Edition

Conv1d is PyTorch's one-dimensional convolution layer for applying learned or specified kernels along a sequence dimension.

>>> import torch
>>> x = torch.tensor(
...     df.iloc[1:].astype(float).values,
...     dtype=torch.float32)             #1
>>> x = x.unsqueeze(0)        #2

How Natural Language Processing in Action, Second Edition covers it

How deep it goes

Explains tensor shaping, hardcoded weights, forward execution, and interpreting the maximum output, but not learned-kernel training.

Examples

Uses a part-of-speech-tagged sentence, a four-channel tensor, and a handcrafted three-position kernel.

What you can do after

Apply it via PyTorch to reshape sequence data, load weights, run a convolution, and locate a detected pattern.

How it connects

Connects convolutional layers with tensors, kernels, embedding layers, CNNs, and parts-of-speech representations.

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Related concepts

• neural network layerkind of · A neural network layer is a computational stage or component that transforms input representations into outputs within a neural network.
• token iduses · A token ID is a numeric identifier assigned to a token in a vocabulary so it can be represented and processed numerically.
• convolutional layerimplements · A convolutional layer is a neural-network layer that applies shared learned filters to local regions of structured input to produce feature representations.
• linear layercontrasts with · A linear layer is a neural-network layer that maps input features to outputs by a learned affine transformation, typically connecting each output to every input feature.
• convolutional neural networkused by · A convolutional neural network is a neural-network architecture that applies learned convolutional operations to extract patterns from structured data.

This explainer was generated by Manning's knowledge graph from the text of Natural Language Processing in Action, Second Edition. The section links point to the parts of the book it draws on.