torchsummary
Model summary in PyTorch similar to `model.summary()` in Keras
Decision gist · record as of 2026-08-14
No—the package is dormant and its own documentation recommends torchinfo as the maintained successor. Install torchsummary only if you are maintaining legacy code that already depends on it; for new projects, use torchinfo instead.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a forward pass through the model; input_size parameter must match the expected tensor dimensions for the model's input.
- Installation is frictionless with no runtime dependencies.
- However, the package is dormant—last release was 2018-09-26 and last commit 2024-03-02—so it receives no active maintenance.
License · maintenance · safety
(unclear) — License treatment is unclear; the description mentions MIT licensing but the metadata lacks formal SPDX declaration. Verify the actual license terms in the repository before relying on it in proprietary or license-sensitive contexts.
last release 2018-09-26 (2879 days) · last repo commit 2024-03-02 · 4,054 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 101,495 downloads/mo, #12,930 on PyPI
Alternatives
Verify before relying
pip install torchsummary
from torchsummary import summary
summary(your_model, input_size=(channels, H, W))- Compatibility with recent PyTorch versions—last release predates many breaking changes in the PyTorch API.
- Whether torchinfo is a direct drop-in replacement or requires code changes for existing torchsummary users.
- Current state of maintenance and whether the archived repository flag affects long-term usability.
What it is and what it does
torchsummary provides a quick way to inspect neural network models by printing a formatted table of layers, output shapes, and parameter counts—similar to Keras's built-in `model.summary()` method. It works by running a forward pass through the network with dummy input of the specified size and capturing layer information along the way.
The package has no runtime dependencies and installs easily, but it is no longer actively maintained. The original author's description explicitly directs users to torchinfo as a newer, updated alternative. Use torchsummary only if you are working with legacy code or have a specific reason to avoid migrating.
Use it for
- Quickly inspect the architecture of a custom neural network during development and debugging.
- Estimate total model size in parameters and memory footprint before training or deployment.
- Verify that layer output shapes match expectations when designing a new network.
- Document model structure in notebooks or reports with a clean, readable summary table.
- Check parameter counts across different model variants to compare complexity.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
No—the package is dormant and its own documentation recommends torchinfo as the maintained successor.
Install torchsummary only if you are maintaining legacy code that already depends on it; for new projects, use torchinfo instead.
Install
torchsummary on PyPI
Before you install
Installation is frictionless with no runtime dependencies. However, the package is dormant—last release was 2018-09-26 and last commit 2024-03-02—so it receives no active maintenance. The description itself recommends migrating to torchinfo.
Requires a forward pass through the model; input_size parameter must match the expected tensor dimensions for the model's input.
License in practice
License treatment is unclear; the description mentions MIT licensing but the metadata lacks formal SPDX declaration. Verify the actual license terms in the repository before relying on it in proprietary or license-sensitive contexts.
Quickstart
pip install torchsummary
from torchsummary import summary
summary(your_model, input_size=(channels, H, W))Verify before relying
- Compatibility with recent PyTorch versions—last release predates many breaking changes in the PyTorch API.
- Whether torchinfo is a direct drop-in replacement or requires code changes for existing torchsummary users.
- Current state of maintenance and whether the archived repository flag affects long-term usability.
Package facts
| License | Not declared unclear |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Dormant 2,879 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 101,495 / month, #12,930 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: torchsummary-1.5.1-py3-none-any.whl
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