update APPLIED run index
Browse files
applied/_index/APPLIED_RUNS_INDEX.json
CHANGED
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@@ -1,245 +1,106 @@
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[
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{
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| 9 |
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"duration_s":
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| 13 |
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| 14 |
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{
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"key": "opt01_ttfs_dta/
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"tag": "
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"script": "opt01_ttfs_dta.py",
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"hf_folder": "applied/opt01_ttfs_dta",
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"status": "ok",
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"reference": "Software-Level Optimizations for Spiking Neural Network Inference on ARM Architectures: A Deep-Dive into the Jetson Nano Ecosystem (research.md SS2)",
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"script": "opt01_ttfs_dta.py",
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{
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"layer": 2,
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"neurons": 256,
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{
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"layer": 3,
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"mean_first_spike_tick":
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"mean_halt_tick":
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"effective_ticks":
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"ticks_saved_frac": 0.
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"num_ticks": 100,
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"config": {
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"method": "harmonic_matched",
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@@ -267,7 +128,7 @@
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"no_batchnorm": false,
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"binary_input": false,
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"beta": 1.0,
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"thresh":
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"window": 0.5,
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"gain": 1.0,
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"alpha": 0.9,
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@@ -279,13 +140,13 @@
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"decision_margin": 2.0,
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"export": false,
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"seed": 1234,
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"hub_dir": "/kaggle/working/hub/opt01_ttfs_dta/
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"repo_id": "UWU-R-13/SSVEP-SNN",
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"push_hf": false,
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"keep_epoch_weights": 1,
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"no_resume": true,
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"selftest": false,
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"baseline":
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"bench": true,
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"bench_warmup": 10,
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"bench_iters": 50,
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@@ -293,7 +154,7 @@
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"ttfs": true,
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"ttfs_halt_k": 1,
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"dta": true,
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"dta_target_rate": 0.
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"dta_readout_rate": 0.95,
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"ttfs_logit_scale": 10.0,
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"dta_momentum": 0.1,
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@@ -304,11 +165,11 @@
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}
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},
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"zip": {
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"name": "
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"MB":
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"sha256": "
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}
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}
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]
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[
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{
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"key": "original/baseline_reference",
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"tag": "baseline_reference",
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"script": "train_ssvep_event_snn.py",
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"hf_folder": "applied/original",
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"phase": 1,
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"status": "ok",
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"duration_s": 576.1,
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"optimization_summary": null,
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"zip": {
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{
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"key": "opt01_ttfs_dta/control_baseline",
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"tag": "control_baseline",
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"phase": 1,
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"optimization": "ttfs_dta",
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"research_section": "2. Temporal-Dimension Reduction (TTFS coding / DTA-TTFS)",
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| 30 |
"reference": "Software-Level Optimizations for Spiking Neural Network Inference on ARM Architectures: A Deep-Dive into the Jetson Nano Ecosystem (research.md SS2)",
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"script": "opt01_ttfs_dta.py",
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"baseline_mode": true,
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