Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
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Operate Fugue workflows, FugueSQL, backend selection, and notebook magics for pandas and distributed dataframe execution.
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See how to installReview the instructions the agent will receive before you install.
Use this skill when a request is about Fugue's unified dataframe and SQL workflow API. Fugue wraps pandas-style code and runs it on Native, Spark, Dask, Ray, DuckDB, Ibis, and Polars backends.
references/overview.md for install choices and the top-level API map.references/troubleshooting.md for generic import, extra, and runtime failures.references/repo-provenance.md when you need to judge staleness.scripts/inspect_install.py --help or scripts/inspect_install.py to confirm the installed package.sub-skills/workflow/ for FugueWorkflow, transform, process, output, partitioning, checkpoints, module, and dataframe helpers.sub-skills/sql/ for fugue_sql, fsql, fugue_sql_flow, raw_sql, YIELD, PRINT, TRANSFORM USING, OUTPUT USING, and SQL templating.sub-skills/backends/ for execution-engine selection, registration, plugin imports, and backend extras.sub-skills/notebook/ for %load_ext fugue_notebook, %%fsql, NotebookSetup, and Jupyter display behavior.Install the smallest extra that matches the task:
pip install fugue for core dataframe and workflow helpers.pip install "fugue[sql]" for FugueSQL.pip install "fugue[duckdb]", "fugue[spark]", "fugue[dask]", "fugue[ray]", "fugue[ibis]", "fugue[polars]", or "fugue[notebook]" for a single backend or notebook support.pip install "fugue[all]" when you want the broad runtime set.python -c "import fugue, fugue.api as fa; print(fugue.__version__)"
If the request mentions a backend, notebook, or FugueSQL syntax error, open the matching sub-skill before writing code.
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Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
The English summary is being prepared. Showing the original description.
Guide 3DDFA Python inference, geometry rendering, training/evaluation, and optional C++ ONNX workflows for 3D dense face alignment.
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Routes 3DDFA_V2 face-alignment setup, still-image demos, video tracking, and ONNX benchmarking workflows.
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Operate AB3DMOT 3D multi-object tracking workflows for KITTI and nuScenes data, tracking, evaluation, and visualization.
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Use Hugging Face Accelerate for PyTorch training-loop migration, distributed launch/configuration, DeepSpeed/FSDP/TPU backend setup, big-model inference/offload, checkpointing, tracking, and troubleshooting.
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Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.
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