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name: graph-and-embedding-plugins description: "Operate tensorboardX graph visualization and embedding projector workflows." metadata: disco-role: operating disable-model-invocation: true license: MIT

Graph And Embedding Plugins

Use this sub-skill when a task involves tensorboardX graph visualization or the TensorBoard projector plugin:

• SummaryWriter.add_graph for PyTorch torch.nn.Module graphs, including CPU-only tracing, tuple/list inputs, verbose, and use_strict_trace decisions.
• SummaryWriter.add_onnx_graph for an existing local ONNX model file.
• SummaryWriter.add_openvino_graph for an existing local OpenVINO IR XML file.
• SummaryWriter.add_embedding for projector tensors, metadata, metadata headers, label-image sprites, global_step, and tag layout.
• Troubleshooting graph/plugin failures, optional dependencies, and projector file layout mistakes.

Route Boundaries

• Route writer creation, log directory policy, flushing, closing, purging, and event-file lifecycle to logging-core.
• Route general image, audio, video, figure, mesh, or rich-media encoding to rich-media-summaries; keep only projector label_img sprite handling here.
• Route remote projector paths such as S3 or GCS buckets, cloud credentials, and parallel writers to remote-and-parallel-integrations.
• Do not depend on source checkout examples, tests, network model downloads, or external fixtures for runtime use. Use the bundled scripts in this sub-skill for local smoke checks.

Operating Map

1. Identify the target plugin path: PyTorch graph, ONNX graph, OpenVINO graph, or projector embedding.
2. Check the method contract and optional dependencies in references/api-reference.md.
3. Follow an end-to-end workflow in references/workflows.md.
4. For projector output paths, metadata/header rules, and label-image sprite constraints, use references/data-formats.md.
5. For failures, use references/troubleshooting.md before changing the model, tensors, metadata, or log directory.

Bundled Smoke Scripts

• scripts/tbx_graph_smoke.py: tiny CPU PyTorch graph smoke with dependency guards.
• scripts/tbx_projector_smoke.py: tiny embedding projector smoke with metadata header and square label images.
• scripts/tbx_onnx_openvino_smoke.py: local OpenVINO XML smoke plus optional local ONNX-file smoke; performs no network access.

CPU is enough for these workflows unless the user deliberately traces a GPU model or passes GPU tensors. If GPU is used, keep the module parameters and every input tensor on the same device.