Datasets:

bumblebeer
/

dgg2-code-graph-benchmarks

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
meta: struct<format: string, n: int64, seed: int64, arg_bank: string, site_counts: list<item: int64>, n_sl (... 83 chars omitted)
  child 0, format: string
  child 1, n: int64
  child 2, seed: int64
  child 3, arg_bank: string
  child 4, site_counts: list<item: int64>
      child 0, item: int64
  child 5, n_slots: int64
  child 6, repos: list<item: string>
      child 0, item: string
  child 7, commits: list<item: string>
      child 0, item: string
  child 8, n_texts: int64
texts: list<item: string>
  child 0, item: string
sources: list<item: struct<repo: int64, k: int64, n_files: int64, slot_node: list<item: int64>, slot_text: li (... 435 chars omitted)
  child 0, item: struct<repo: int64, k: int64, n_files: int64, slot_node: list<item: int64>, slot_text: list<item: in (... 423 chars omitted)
      child 0, repo: int64
      child 1, k: int64
      child 2, n_files: int64
      child 3, slot_node: list<item: int64>
          child 0, item: int64
      child 4, slot_text: list<item: int64>
          child 0, item: int64
      child 5, sites: list<item: struct<primary_slot: int64, primary_id: string, primary_kind: string, true: int64, instr_ (... 203 chars omitted)
          child 0, item: struct<primary_slot: int64, primary_id: string, primary_kind: string, true: int64, instr_seen: list< (... 191 chars omitted)
              child 0, primary_slot: int64
              child 1, primary_id: string
              child 2, primary_kind: string
              child 3, true: int64
  
...
child 0, item: string
              child 6, cands: list<item: struct<edit: string, args: struct<new: string, p: string, d: string, dec: string>, change (... 34 chars omitted)
                  child 0, item: struct<edit: string, args: struct<new: string, p: string, d: string, dec: string>, changes: list<ite (... 22 chars omitted)
                      child 0, edit: string
                      child 1, args: struct<new: string, p: string, d: string, dec: string>
                          child 0, new: string
                          child 1, p: string
                          child 2, d: string
                          child 3, dec: string
                      child 2, changes: list<item: list<item: int64>>
                          child 0, item: list<item: int64>
                              child 0, item: int64
      child 6, changes: list<item: list<item: int64>>
          child 0, item: list<item: int64>
              child 0, item: int64
      child 7, instr_seen: list<item: string>
          child 0, item: string
      child 8, instr_unseen: list<item: string>
          child 0, item: string
seed: int64
repos: list<item: string>
  child 0, item: string
min_diff_required: int64
n: int64
strict_edges: bool
name: string
node_ids: list<item: list<item: string>>
  child 0, item: list<item: string>
      child 0, item: string
n_nodes: int64
targets: list<item: string>
  child 0, item: string
open: bool
sha256: string
commits: list<item: string>
  child 0, item: string
to
{'name': Value('string'), 'n': Value('int64'), 'seed': Value('int64'), 'repos': List(Value('string')), 'commits': List(Value('string')), 'targets': List(Value('string')), 'min_diff_required': Value('int64'), 'strict_edges': Value('bool'), 'n_nodes': Value('int64'), 'open': Value('bool'), 'sha256': Value('string'), 'node_ids': List(List(Value('string')))}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 544, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3052, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 558, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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/json/json.py", line 361, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              meta: struct<format: string, n: int64, seed: int64, arg_bank: string, site_counts: list<item: int64>, n_sl (... 83 chars omitted)
                child 0, format: string
                child 1, n: int64
                child 2, seed: int64
                child 3, arg_bank: string
                child 4, site_counts: list<item: int64>
                    child 0, item: int64
                child 5, n_slots: int64
                child 6, repos: list<item: string>
                    child 0, item: string
                child 7, commits: list<item: string>
                    child 0, item: string
                child 8, n_texts: int64
              texts: list<item: string>
                child 0, item: string
              sources: list<item: struct<repo: int64, k: int64, n_files: int64, slot_node: list<item: int64>, slot_text: li (... 435 chars omitted)
                child 0, item: struct<repo: int64, k: int64, n_files: int64, slot_node: list<item: int64>, slot_text: list<item: in (... 423 chars omitted)
                    child 0, repo: int64
                    child 1, k: int64
                    child 2, n_files: int64
                    child 3, slot_node: list<item: int64>
                        child 0, item: int64
                    child 4, slot_text: list<item: int64>
                        child 0, item: int64
                    child 5, sites: list<item: struct<primary_slot: int64, primary_id: string, primary_kind: string, true: int64, instr_ (... 203 chars omitted)
                        child 0, item: struct<primary_slot: int64, primary_id: string, primary_kind: string, true: int64, instr_seen: list< (... 191 chars omitted)
                            child 0, primary_slot: int64
                            child 1, primary_id: string
                            child 2, primary_kind: string
                            child 3, true: int64
                
              ...
              child 0, item: string
                            child 6, cands: list<item: struct<edit: string, args: struct<new: string, p: string, d: string, dec: string>, change (... 34 chars omitted)
                                child 0, item: struct<edit: string, args: struct<new: string, p: string, d: string, dec: string>, changes: list<ite (... 22 chars omitted)
                                    child 0, edit: string
                                    child 1, args: struct<new: string, p: string, d: string, dec: string>
                                        child 0, new: string
                                        child 1, p: string
                                        child 2, d: string
                                        child 3, dec: string
                                    child 2, changes: list<item: list<item: int64>>
                                        child 0, item: list<item: int64>
                                            child 0, item: int64
                    child 6, changes: list<item: list<item: int64>>
                        child 0, item: list<item: int64>
                            child 0, item: int64
                    child 7, instr_seen: list<item: string>
                        child 0, item: string
                    child 8, instr_unseen: list<item: string>
                        child 0, item: string
              seed: int64
              repos: list<item: string>
                child 0, item: string
              min_diff_required: int64
              n: int64
              strict_edges: bool
              name: string
              node_ids: list<item: list<item: string>>
                child 0, item: list<item: string>
                    child 0, item: string
              n_nodes: int64
              targets: list<item: string>
                child 0, item: string
              open: bool
              sha256: string
              commits: list<item: string>
                child 0, item: string
              to
              {'name': Value('string'), 'n': Value('int64'), 'seed': Value('int64'), 'repos': List(Value('string')), 'commits': List(Value('string')), 'targets': List(Value('string')), 'min_diff_required': Value('int64'), 'strict_edges': Value('bool'), 'n_nodes': Value('int64'), 'open': Value('bool'), 'sha256': Value('string'), 'node_ids': List(List(Value('string')))}
              because column names don't match

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DiffusionGemma 2: Latent Code-Graph Benchmarks & Raw Predictions

Standardized AST code-graph benchmark packs, continuous symbol embeddings, pre-registration (PREREG.json), linear evaluation probes, and raw .npy and .npz model prediction arrays for independent CPU rescoring of Latent Roadmaps: Soft-Token Re-Feeding in DiffusionGemma for Code Graphs.

Author: bumblebeers (GitHub)
License: Apache-2.0
Code & Scoring Harness: bumblebeers/dgg2-latent-code-graphs
Trained Two-Seed LoRA Adapters & Readout Heads: bumblebeer/dgg2-latent-code-graphs-adapters
Standalone Libraries (v0.1.0): dgg-latent | dgg-codebook | dgg-vit-decoder
Upstream transformers Multimodal Mask Fix: huggingface/transformers#50684

Repository Contents

1. Experiment A: 16x16 Visual Adjacency Grid Benchmark Packs (`data/gridA_*`)

data/gridA_train1608.npz: 1,608 16-symbol Python AST subgraphs extracted across 3 training repositories (fastapi, requests, rich) with 22 fixed candidate states and 3 open-ended edit families.
data/gridA_test360_httpx.npz: 360 held-out 16-symbol AST subgraphs from encode/httpx across seen, shuffled, unseen paraphrase, indirect intent, held-out single-pass, 2-step re-feeding, 3-step chain, and open-ended manifests.
data/gridA_test360_click.npz: 360 held-out 16-symbol AST subgraphs from pallets/click for zero-shot cross-repository transfer.
data/gridA_n32_*.npz & data/gridA_n48_*.npz: Multi-resolution 32x32 and 48x48 subgraph packs testing sub-patch packing limits (Gate A1).
data/*.nodes.json: Per-subgraph AST symbol and line metadata.
reader.npz (outputs/m1/reader.npz): Gate A1 closed-form Ridge probe mapping clean SigLIP latents h_v (256 x 1152) to the 8 discrete palette classes (1.000 clean cell accuracy across all 8 classes).

2. Experiment B: 256-Symbol Continuous Embedding Packs (`data/nodeB_*`)

data/nodeB_train1608.json.gz: 1,608 256-symbol AST windows for single-site and multi-site symbol refactoring.
data/nodeB_test360_httpx.json.gz & data/nodeB_test360_click.json.gz: Held-out httpx (N=360) and zero-shot click (N=360) evaluation packs (chance = 12.5%, mean-vector floor = 25.0%).
data/nodeB_test360_httpx_unseenargs.json.gz & data/nodeB_test180_httpx_renameclass.json.gz: Unseen argument and class-rename splits.
data/nodeB_multi_test360_httpx_k2.json.gz & k4.json.gz: 2-site and 4-site simultaneous and re-fed symbol-editing splits.
emb.npz & emb_train.npz: Frozen sentence-transformers/all-MiniLM-L6-v2 (d=384) symbol embeddings and train-only standardization statistics.

3. Raw Model Prediction Arrays (`predictions/` & `outputs/m2/decoded_grids_all_arms.npz`)

To enable full independent verification without requiring a 26B GPU, this dataset hosts both continuous latent .npy outputs and Ridge-decoded discrete (M, 16, 16) uint8 grid .npy/.npz files:

predictions/expA_hv/<arm>/preds_*.npy: Raw continuous predicted SigLIP latent tensors (360 x 256 x 1152, float32) emitted by stock_generate_with_readout for two-seed LoRA DG (cg_lora_dg_seed42_ep3, cg_lora_dg_seed1337_ep3), cg_frozen_dg_ep3, and Non-DG baselines.
predictions/expA_grids/<arm>/*.npy & outputs/m2/decoded_grids_all_arms.npz: Decoded (360, 16, 16) uint8 palette grids (0..7) across all evaluated arms — two-seed LoRA DG (httpx and two-seed zero-shot click), Frozen DG, two-seed Non-DG (Frozen Instr and Enc LoRA), and preliminary google/gemma-4-26B-A4B-it autoregressive references (2-shot gemma4_ar_prompted and 354-of-4,824-step single-seed gemma4_ar_lora_r64_s42 across all 4 primary splits).
predictions/expB_vec/<arm>/*.npy: Raw standardized continuous symbol-vector predictions (M x 256 x 384, float32) for two-seed Experiment B LoRA DG (cg_expB_lora_dg_seed42_ep3, cg_expB_lora_dg_seed1337_ep3) and two-seed Non-DG baselines.

Independent CPU Rescoring Quickstart

git clone https://github.com/bumblebeers/dgg2-latent-code-graphs.git
cd dgg2-latent-code-graphs

# Rescore Experiment A directly from raw continuous h_v (.npy, shape 360x256x1152) + Ridge probe:
python3 cg/cg_score_preds.py \
  --pack data/gridA_test360_httpx.npz \
  --reader reader.npz \
  --manifest seen_bal360 \
  --pred predictions/expA_hv/cg_lora_dg_seed42_ep3/preds_cg_lora_dg_seed42_ep3_seen_bal360.npy

# Rescore decoded (360, 16, 16) uint8 palette grids (.npy), including Gemma 4 AR LoRA:
python3 cg/cg_score_preds.py \
  --pack data/gridA_test360_httpx.npz \
  --manifest refeed_heldout_comp_bal360 \
  --grids predictions/expA_grids/gemma4_ar_lora_r64_s42/refeed_heldout_comp_bal360.npy

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Total file size:

5.41 GB

DiffusionGemma 2: Latent Code-Graph Benchmarks & Raw Predictions

Repository Contents

1. Experiment A: 16x16 Visual Adjacency Grid Benchmark Packs (data/gridA_*)

2. Experiment B: 256-Symbol Continuous Embedding Packs (data/nodeB_*)

3. Raw Model Prediction Arrays (predictions/ & outputs/m2/decoded_grids_all_arms.npz)

Independent CPU Rescoring Quickstart

1. Experiment A: 16x16 Visual Adjacency Grid Benchmark Packs (`data/gridA_*`)

2. Experiment B: 256-Symbol Continuous Embedding Packs (`data/nodeB_*`)

3. Raw Model Prediction Arrays (`predictions/` & `outputs/m2/decoded_grids_all_arms.npz`)