Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use deepjazz for legacy MIDI jazz generation with music21 preprocessing, abstract grammar tokens, Keras/Theano LSTM training, safe diagnostics, and modernization guidance.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Use this skill when a task involves the deepjazz repository or a deepjazz-style workflow: symbolic MIDI jazz generation, Metheny-style MIDI preprocessing, abstract grammar tokens, note cleanup, Keras/Theano LSTM generation, optional Theano GPU commands, or modernizing the legacy code.
This skill is self-contained. Do not rely on reading original repo scripts at runtime to recover constants, signatures, or workflow boundaries; use the bundled references and scripts below.
| User task | Route |
|---|---|
| Inspect whether a MIDI file can work with deepjazz, change melody/accompaniment parts, or debug corpus extraction | sub-skills/midi-preprocessing/ |
| Explain or validate grammar tokens, run parse/unparse/cleanup smoke checks, or debug malformed generated grammar | sub-skills/grammar-and-qa/ |
| Run, adapt, or port the LSTM generation path; avoid playback/training hazards; inspect model settings | sub-skills/lstm-generation/ |
| Diagnose install/import/backend problems that cut across all workflows | references/troubleshooting.md |
| Check whether this skill matches a checkout/source revision | references/repo-provenance.md |
Treat deepjazz as a legacy script collection, not a modern installable package.
For faithful execution, use a Python 2.7-era environment with NumPy/SciPy, music21, Keras 1.x, and Theano. Read references/dependency-environment.md before installing.
Set KERAS_BACKEND=theano before importing legacy Keras.
Run the bundled no-training environment check:
python scripts/check_deepjazz_environment.py --expect-theano
Validate MIDI structure before training:
python sub-skills/midi-preprocessing/scripts/inspect_midi_structure.py --midi-file <input.mid>
Validate grammar/QA behavior without training:
python sub-skills/grammar-and-qa/scripts/grammar_roundtrip_smoke.py --seed 7
Only run full generation after environment, data, and grammar checks pass. The original generation flow trains an LSTM, attempts realtime MIDI playback, and writes MIDI output.
generator, grammar, preprocess, qa, and lstm.generate(data_fn, out_fn, N_epochs), build_model(corpus, val_indices, max_len, N_epochs=128), get_musical_data(data_fn), get_corpus_data(abstract_grammars), parse_melody(fullMeasureNotes, fullMeasureChords), unparse_grammar(m1_grammar, m1_chords), prune_grammar(curr_grammar), prune_notes(curr_notes), clean_up_notes(curr_notes).max_len=20, max_tries=1000, diversity=0.5, bpm=130, default epochs 128.5, accompaniment parts 0,1,6,7, and solo window offsets 476..548.references/dependency-environment.md: public legacy dependency guidance and safe command sequence.references/troubleshooting.md: cross-cutting install, Python compatibility, data, playback, speed, and optional CUDA troubleshooting.references/repo-provenance.md: source commit, branch, evidence paths, and refresh baseline.references/repo-routing-metadata.json: structured router metadata used only if this skill is later imported into the managed repo-skills library.scripts/check_deepjazz_environment.py: safe dependency/backend/module-signature diagnostic; accepts optional --repo-root for inspecting a local deepjazz-style source tree without training.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Guide 3DDFA Python inference, geometry rendering, training/evaluation, and optional C++ ONNX workflows for 3D dense face alignment.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Routes 3DDFA_V2 face-alignment setup, still-image demos, video tracking, and ONNX benchmarking workflows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Operate AB3DMOT 3D multi-object tracking workflows for KITTI and nuScenes data, tracking, evaluation, and visualization.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.