visualdl
Visualize Deep Learning
Decision gist · record as of 2026-08-14
No. The package is abandoned (last release 2023-06-05, 1166 days ago) with no active maintenance, meaning no security updates, bug fixes, or compatibility patches. While it has low install friction and permissive licensing, the 13 runtime dependencies and lack of ongoing support create maintenance risk. For active projects, use a maintained alternative like TensorBoard or Weights & Biases instead.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3 (Python 2 no longer supported); no minimum version specified in metadata.
- Low install friction with a pure-wheel distribution.
- However, the package is abandoned as of 1166 days since its last release (2023-06-05), meaning no active maintenance or security updates are forthcoming.
License · maintenance · safety
Apache License (permissive) — Licensed under Apache License with permissive treatment, allowing commercial and private use without restriction, though you assume responsibility for any future security or compatibility issues given the abandoned status.
last release 2023-06-05 (1166 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 223,250 downloads/mo, #9,248 on PyPI
Alternatives
Verify before relying
pip install visualdl
from visualdl import LogWriter
with LogWriter(logdir="./log/train") as writer:
writer.add_scalar(tag="loss", step=1, value=0.5)
writer.add_scalar(tag="loss", step=2, value=0.3)- Whether the 13 runtime dependencies (flask, numpy, protobuf, etc.) remain compatible with current Python and library versions given the package's abandoned status.
- Whether the web dashboard still functions with modern browsers beyond the stated support (Chrome ≥79, Firefox ≥67, Edge ≥79, Safari ≥11.1).
- Whether PaddlePaddle integration and model format support (ONNX, Caffe, Keras, Core ML) still work without active maintenance.
What it is and what it does
VisualDL is a web-based visualization dashboard for monitoring deep learning training. It accepts logged metrics, model structures, and tensor statistics from your training code via a Python SDK (LogWriter), writes them to local log files, and serves an interactive web interface to view trends, distributions, and model graphs in real time.
The package is designed primarily for PaddlePaddle users but claims support for ONNX, Caffe, Keras, and Core ML model formats. It provides scalar tracking, histogram visualization, PR and ROC curves, high-dimensional data projection, and model structure rendering. The tool runs as a local web server (default port 8040) and requires 13 runtime dependencies including Flask, NumPy, Pillow, Protobuf, and Pandas.
Use it for
- Monitor training loss and accuracy metrics in real-time during model training without writing custom logging code.
- Visualize neural network architecture and data flow for debugging model structure and understanding layer connectivity.
- Compare multiple training runs by pointing the dashboard at different log directories to identify which hyperparameters or configurations perform best.
- Export and share training visualizations with team members via the VDL.service integration mentioned in the documentation.
- Inspect tensor distributions and histograms during training to detect gradient issues or data anomalies.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
No.
The package is abandoned (last release 2023-06-05, 1166 days ago) with no active maintenance, meaning no security updates, bug fixes, or compatibility patches. While it has low install friction and permissive licensing, the 13 runtime dependencies and lack of ongoing support create maintenance risk. For active projects, use a maintained alternative like TensorBoard or Weights & Biases instead.
Install
visualdl on PyPI
Before you install
Low install friction with a pure-wheel distribution. However, the package is abandoned as of 1166 days since its last release (2023-06-05), meaning no active maintenance or security updates are forthcoming.
Requires Python 3 (Python 2 no longer supported); no minimum version specified in metadata.
License in practice
Licensed under Apache License with permissive treatment, allowing commercial and private use without restriction, though you assume responsibility for any future security or compatibility issues given the abandoned status.
Quickstart
pip install visualdl
from visualdl import LogWriter
with LogWriter(logdir="./log/train") as writer:
writer.add_scalar(tag="loss", step=1, value=0.5)
writer.add_scalar(tag="loss", step=2, value=0.3)Verify before relying
- Whether the 13 runtime dependencies (flask, numpy, protobuf, etc.) remain compatible with current Python and library versions given the package's abandoned status.
- Whether the web dashboard still functions with modern browsers beyond the stated support (Chrome ≥79, Firefox ≥67, Edge ≥79, Safari ≥11.1).
- Whether PaddlePaddle integration and model format support (ONNX, Caffe, Keras, Core ML) still work without active maintenance.
Package facts
| License | Apache License permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 13 packagesbce-python-sdkflaskFlask-BabelnumpyPillowprotobufrequestssixmatplotlibpandaspackagingrarfilepsutil |
| Maintenance | Abandoned 1,166 days since the last release |
| First released | |
| Downloads | 223,250 / month, #9,248 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: visualdl-2.5.3-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “deep learning visualization”
- visualdlVisualDL is a visualization tool for deep learning training that logs…
- tensorboardTensorBoard is a web-based visualization suite for inspecting…
- tb-nightlyTensorBoard is a web-based visualization suite for inspecting…
Give your agent the search over MCP, or paste the wish link into any chat.
More Artificial Intelligence packages
LiteLLM provides a unified Python interface to call 100+ LLM providers (OpenAI, Anthropic, Gemini, Bedrock, Azure, and others) using OpenAI-compatible API format, available as both a Python SDK and a self-hosted AI Gateway proxy server.
Install it if you need to work with multiple LLM providers or want to centralize LLM routing in your organization.
Client library and CLI tool for downloading, uploading, and managing models, datasets, and repositories on the Hugging Face Hub platform.
Install it if you work with Hugging Face Hub models or datasets.
LangChain provides a framework for building agents and LLM-powered applications by composing language models, tools, and memory through a unified API that abstracts over multiple model providers.
hf-xet provides chunk-based deduplication and efficient file transfer for the Hugging Face Hub, enabling faster uploads and downloads of large files with local disk caching.
Tokenizers converts raw text into token sequences for NLP models, with support for training custom vocabularies and using pre-built tokenizers (BPE, WordPiece) optimized for speed via Rust.
Transformers provides a unified framework for loading, fine-tuning, and running state-of-the-art pretrained models across text, vision, audio, video, and multimodal tasks using PyTorch, JAX, or TensorFlow.
Install it if you need to run or train any transformer-based model for NLP, vision, audio, or multimodal tasks.
See also tensorboard · tb-nightly · paddlepaddle · tensorboard-data-server · tensorboard-plugin-profile · ml-goodput-measurement · netron · xprof · neptune-scale