Instructions to use hacnho/keras-compile-config-callback-poc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use hacnho/keras-compile-config-callback-poc with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://hacnho/keras-compile-config-callback-poc") - Notebooks
- Google Colab
- Kaggle
Keras compile_config learning_rate callback PoC
This repository contains bounded proof-of-concept .keras archives for the
already-open Keras Native compile_config learning_rate callbacks root-cause
family.
These are not new-report artifacts by themselves. They are intended to strengthen the already-open bounty:
https://huntr.com/bounties/b6ae18b3-51bf-4607-8366-58f3448f5911
Files
MobileNetV3Large.patched.kerasfashion_mnist_load_data.patched.kerasreuters_get_word_index.patched.kerasreproduce_compile_callback_variants.pyverify_remote_poc.pysummary.jsonapp-probe-summary.jsonSHA256SUMS.txtrequirements.txt
What the files do
The patched .keras archives keep the same general root cause:
safe_mode=Trueload succeeds- a later benign
fit(...)path reaches a deserializedcompile_config.optimizer.config.learning_ratecallable
Variant 1: keras.datasets.fashion_mnist.load_data
Observed side effect during later benign fit(...):
- writes four files under
datasets/fashion-mnist/
Variant 2: keras.datasets.reuters.get_word_index
Observed side effect during later benign fit(...):
- writes
datasets/reuters_word_index.json
Strongest current application-constructor variant
Local strengthening evidence also includes:
MobileNetV3Large.patched.keras- benign
fit(...)triggers:keras.applications.MobileNetV3Large - observed side effect:
models/weights_mobilenet_v3_large_224_1.0_float.h5
See:
app-probe-summary.json
Reproduce
python3 -m venv /tmp/keras-compile-callback-poc
. /tmp/keras-compile-callback-poc/bin/activate
pip install --upgrade pip
pip install -r requirements.txt
python reproduce_compile_callback_variants.py
Expected:
- both
.kerasfiles load withsafe_mode=True - later benign
fit(...)triggers the configured callable fashion_mnistwrites four gzip membersreuters_get_word_indexwrites one JSON file
Verify the public HF artifacts
You can also verify the exact public artifacts after unauthenticated download:
python verify_remote_poc.py
Expected:
- all three patched
.kerasfiles load withsafe_mode=True - later benign
fit(...)reaches the configured callable MobileNetV3Largewrites:models/weights_mobilenet_v3_large_224_1.0_float.h5fashion_mnistwrites four gzip membersreuters_get_word_indexwrites one JSON file- all three variants fail later benign
fit(...)as non-scalar learning-rate callbacks
Safety note
This is a bounded research PoC:
- no ACE claim
- no arbitrary file path control
- only Keras dataset-helper writes inside an isolated
KERAS_HOME - intended to strengthen an existing Keras MFV bounty, not to create a fresh duplicate report
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