Conv1d Output Size Calculator
Calculate the output length and channels of a PyTorch Conv1d layer. Enter input shape, kernel size, stride, padding, and dilation for instant results.
Built by Michael Lip
Frequently Asked Questions
What is the Conv1d output size formula?
The formula is: L_out = floor((L_in + 2*padding - dilation*(kernel_size-1) - 1) / stride) + 1. Conv1d operates on 1D sequences, so there is only one spatial dimension to compute.
When should I use Conv1d vs Conv2d?
Use Conv1d for 1D sequence data like time series, audio waveforms, or text (after embedding). Use Conv2d for 2D spatial data like images. Conv1d input shape is [batch, channels, length], while Conv2d is [batch, channels, height, width].
What is the input shape for Conv1d?
Conv1d expects input shape [batch_size, in_channels, length]. For example, a batch of 32 audio signals with 1 channel and 16000 samples would be [32, 1, 16000].
Is this tool free?
Yes. All HeyTensor tools are free, run in your browser, and require no signup.
Does this work offline?
Once loaded, the tool runs entirely in your browser. No internet needed after the initial page load.
About This Tool
This tool is part of HeyTensor, a free suite of PyTorch and deep learning utilities. All calculations run entirely in your browser, no calculator inputs or results are sent to any server. The source code is open on GitHub.
Contact
HeyTensor is built and maintained by Michael Lip. For questions or feedback, email [email protected].
TENSOR PREFLIGHT · DOWNLOADABLE PYTORCH TOOLKIT
Take the next step in your own PyTorch model.
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Is this toolkit right for my problem?
Use the free calculator for a layer formula or a quick shape check.
Consider Tensor Preflight when you have a local PyTorch model and want a forward-pass report plus repeatable checks. Python 3.9+ and PyTorch 2.8+ are required. It does not run your model in this website or automatically repair it.
Open the sample report before buying to check the output format.
Python 3.9+ · PyTorch 2.8+ · Runs locally