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Redvirex
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eflic-icml2026-repro-results

Tags:
icml2026-repro
image-compression
trackio
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Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    EmptyDataError
Message:      No columns to parse from file
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4379, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2661, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2839, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/csv/csv.py", line 196, in _generate_tables
                  csv_file_reader = pd.read_csv(file, iterator=True, dtype=dtype, **self.config.pd_read_csv_kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/streaming.py", line 73, in wrapper
                  return function(*args, download_config=download_config, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1279, in xpandas_read_csv
                  return pd.read_csv(xopen(filepath_or_buffer, "rb", download_config=download_config), **kwargs)
                         ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1026, in read_csv
                  return _read(filepath_or_buffer, kwds)
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 620, in _read
                  parser = TextFileReader(filepath_or_buffer, **kwds)
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1620, in __init__
                  self._engine = self._make_engine(f, self.engine)
                                 ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1898, in _make_engine
                  return mapping[engine](f, **self.options)
                         ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 93, in __init__
                  self._reader = parsers.TextReader(src, **kwds)
                                 ~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "pandas/_libs/parsers.pyx", line 581, in pandas._libs.parsers.TextReader.__cinit__
              pandas.errors.EmptyDataError: No columns to parse from file

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EF-LIC ICML 2026 reproduction

This folder contains an independent verification wrapper for paper 654, Efficient Learned Image Compression without Entropy Coding (arXiv 2605.23323, OpenReview sfroJn43YY). It never modifies the authors' CC BY-NC-ND source: the GPU script clones commit b45653d77c0e03bf184a1b2d7b0f577ebc2956c9 into a temporary directory and imports it unchanged.

The published Trackio logbook, interactive poster, and claim-by-claim evidence are at https://huggingface.co/spaces/Redvirex/eflic-icml2026-repro-logbook.

Contents

  • smoke_mechanisms.py: deterministic NumPy-only toy smoke test for entropy shaping and invertible conditional affine normalization.
  • run_official_repro.py: released-checkpoint A100 evaluation, VQ entropy instrumentation, affine-decorrelation diagnostic, and latency benchmark.
  • paper_claims.json: exact source-reported values and baseline correction.
  • outputs/: captured local outputs and Hugging Face Job submission diagnostics.
  • figures/: raw-data-backed figures added to the Trackio logbook.

The official checkpoint and benchmark images are downloaded at runtime and are not redistributed. The output manifest records source URLs, upstream commit, file sizes, and SHA-256 checksums. This respects the upstream and dataset terms while keeping the run auditable.

Outcome

The released-checkpoint entropy result reproduces at the highest-rate setting on all 24 Kodak images: 3.4346% weighted entropy gap versus 3.4200% reported. At that same rate, the affine transform reduces the diagnostic correlation with predicted context by 60.7% and lowers same-codebook latent MSE by 14.1%. The exact BD-rates remain source-only because raw MS-ILLM curves and integration details are unavailable. A100 latency remains source-only because the available HF credentials could not schedule a Job. EF-LIC-s remains source-only because no lightweight code or checkpoint was released.

Local smoke test 

python repro_eflic/smoke_mechanisms.py \
  --output repro_eflic/outputs/smoke_results.json

Hugging Face A100 run 

hf jobs uv run --flavor a100-large --timeout 1h --detach --secrets HF_TOKEN \
  repro_eflic/run_official_repro.py \
  --datasets all \
  --trackio-space Redvirex/eflic-icml2026-metrics \
  --results-repo Redvirex/eflic-icml2026-repro-results

The paper's exact BD-rates cannot be independently recomputed because neither the raw MS-ILLM curves nor the entropy-coded ablation checkpoints are released. The script therefore emits new EF-LIC R-D points but never substitutes them for a two-curve BD-rate calculation.

Licensing

This is a mixed-license bundle; see LICENSING.md. The original reproduction wrapper is MIT-licensed. poster/poster.html is a derivative of Posterly's AGPL-3.0 template and retains Posterly's license and notices. The authors' EF-LIC source, checkpoint, and benchmark images are not redistributed.

If GPU Job authorization or credit is unavailable, a clearly labelled reduced CPU run can exercise the real released checkpoint:

uv run repro_eflic/run_official_repro.py \
  --allow-cpu --datasets kodak --max-images 1 --skip-perceptual \
  --skip-batch-benchmark --warmups 0 \
  --trackio-space "" --results-repo "" \
  --output-dir repro_eflic/outputs/cpu_subset
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