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Datasets:
reachjalil
/
nottyduck-training-runs

Tags:
robotics
reinforcement-learning
evaluation
License:
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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
$schema: string
$id: string
title: string
type: string
additionalProperties: bool
required: list<item: string>
  child 0, item: string
properties: struct<runId: struct<type: string, minLength: int64>, createdAt: struct<type: string, format: string (... 528 chars omitted)
  child 0, runId: struct<type: string, minLength: int64>
      child 0, type: string
      child 1, minLength: int64
  child 1, createdAt: struct<type: string, format: string>
      child 0, type: string
      child 1, format: string
  child 2, gesture: struct<type: string, minLength: int64>
      child 0, type: string
      child 1, minLength: int64
  child 3, taskId: struct<type: string, minLength: int64>
      child 0, type: string
      child 1, minLength: int64
  child 4, sourceCommit: struct<type: string, pattern: string>
      child 0, type: string
      child 1, pattern: string
  child 5, status: struct<enum: list<item: string>>
      child 0, enum: list<item: string>
          child 0, item: string
  child 6, evaluation: struct<type: string, additionalProperties: bool, required: list<item: string>, properties: struct<se (... 220 chars omitted)
      child 0, type: string
      child 1, additionalProperties: bool
      child 2, required: list<item: string>
          child 0, item: string
      child 3, properties: struct<seedCount: struct<type: string, minimum: int64>, successRate: struct<type: list<item: string> (... 128 chars omitted)
          child 0, seedCount: struct<type: string, minimum: int64
...
nimumPassingSeeds: int64, maxSuccessRateStdDev: double>
      child 0, minimumCompletedSeeds: int64
      child 1, minimumPassingSeeds: int64
      child 2, maxSuccessRateStdDev: double
seeds: list<item: int64>
  child 0, item: int64
task: string
profiles: struct<smoke: struct<environments: int64, iterations: int64, saveInterval: int64, evaluationEpisodes (... 214 chars omitted)
  child 0, smoke: struct<environments: int64, iterations: int64, saveInterval: int64, evaluationEpisodes: int64>
      child 0, environments: int64
      child 1, iterations: int64
      child 2, saveInterval: int64
      child 3, evaluationEpisodes: int64
  child 1, pilot: struct<environments: int64, iterations: int64, saveInterval: int64, evaluationEpisodes: int64>
      child 0, environments: int64
      child 1, iterations: int64
      child 2, saveInterval: int64
      child 3, evaluationEpisodes: int64
  child 2, full: struct<environments: int64, iterations: int64, saveInterval: int64, evaluationEpisodes: int64>
      child 0, environments: int64
      child 1, iterations: int64
      child 2, saveInterval: int64
      child 3, evaluationEpisodes: int64
evaluation: struct<successRateMin: double, fallRateMax: double, medianCloseSecondsMax: double, p95LidSpeedMax: d (... 33 chars omitted)
  child 0, successRateMin: double
  child 1, fallRateMax: double
  child 2, medianCloseSecondsMax: double
  child 3, p95LidSpeedMax: double
  child 4, p95ImpactForceMax: double
preset: string
schemaVersion: int64
to
{'schemaVersion': Value('int64'), 'id': Value('string'), 'title': Value('string'), 'preset': Value('string'), 'task': Value('string'), 'hypothesis': Value('string'), 'seeds': List(Value('int64')), 'profiles': {'smoke': {'environments': Value('int64'), 'iterations': Value('int64'), 'saveInterval': Value('int64'), 'evaluationEpisodes': Value('int64')}, 'pilot': {'environments': Value('int64'), 'iterations': Value('int64'), 'saveInterval': Value('int64'), 'evaluationEpisodes': Value('int64')}, 'full': {'environments': Value('int64'), 'iterations': Value('int64'), 'saveInterval': Value('int64'), 'evaluationEpisodes': Value('int64')}}, 'evaluation': {'successRateMin': Value('float64'), 'fallRateMax': Value('float64'), 'medianCloseSecondsMax': Value('float64'), 'p95LidSpeedMax': Value('float64'), 'p95ImpactForceMax': Value('float64')}, 'promotion': {'smoke': {'minimumCompletedSeeds': Value('int64'), 'minimumPassingSeeds': Value('int64')}, 'pilot': {'minimumCompletedSeeds': Value('int64'), 'minimumPassingSeeds': Value('int64'), 'maxSuccessRateStdDev': Value('float64')}, 'full': {'minimumCompletedSeeds': Value('int64'), 'minimumPassingSeeds': Value('int64'), 'maxSuccessRateStdDev': Value('float64')}}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, 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 127, 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 483, 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 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 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/json/json.py", line 343, 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 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              $schema: string
              $id: string
              title: string
              type: string
              additionalProperties: bool
              required: list<item: string>
                child 0, item: string
              properties: struct<runId: struct<type: string, minLength: int64>, createdAt: struct<type: string, format: string (... 528 chars omitted)
                child 0, runId: struct<type: string, minLength: int64>
                    child 0, type: string
                    child 1, minLength: int64
                child 1, createdAt: struct<type: string, format: string>
                    child 0, type: string
                    child 1, format: string
                child 2, gesture: struct<type: string, minLength: int64>
                    child 0, type: string
                    child 1, minLength: int64
                child 3, taskId: struct<type: string, minLength: int64>
                    child 0, type: string
                    child 1, minLength: int64
                child 4, sourceCommit: struct<type: string, pattern: string>
                    child 0, type: string
                    child 1, pattern: string
                child 5, status: struct<enum: list<item: string>>
                    child 0, enum: list<item: string>
                        child 0, item: string
                child 6, evaluation: struct<type: string, additionalProperties: bool, required: list<item: string>, properties: struct<se (... 220 chars omitted)
                    child 0, type: string
                    child 1, additionalProperties: bool
                    child 2, required: list<item: string>
                        child 0, item: string
                    child 3, properties: struct<seedCount: struct<type: string, minimum: int64>, successRate: struct<type: list<item: string> (... 128 chars omitted)
                        child 0, seedCount: struct<type: string, minimum: int64
              ...
              nimumPassingSeeds: int64, maxSuccessRateStdDev: double>
                    child 0, minimumCompletedSeeds: int64
                    child 1, minimumPassingSeeds: int64
                    child 2, maxSuccessRateStdDev: double
              seeds: list<item: int64>
                child 0, item: int64
              task: string
              profiles: struct<smoke: struct<environments: int64, iterations: int64, saveInterval: int64, evaluationEpisodes (... 214 chars omitted)
                child 0, smoke: struct<environments: int64, iterations: int64, saveInterval: int64, evaluationEpisodes: int64>
                    child 0, environments: int64
                    child 1, iterations: int64
                    child 2, saveInterval: int64
                    child 3, evaluationEpisodes: int64
                child 1, pilot: struct<environments: int64, iterations: int64, saveInterval: int64, evaluationEpisodes: int64>
                    child 0, environments: int64
                    child 1, iterations: int64
                    child 2, saveInterval: int64
                    child 3, evaluationEpisodes: int64
                child 2, full: struct<environments: int64, iterations: int64, saveInterval: int64, evaluationEpisodes: int64>
                    child 0, environments: int64
                    child 1, iterations: int64
                    child 2, saveInterval: int64
                    child 3, evaluationEpisodes: int64
              evaluation: struct<successRateMin: double, fallRateMax: double, medianCloseSecondsMax: double, p95LidSpeedMax: d (... 33 chars omitted)
                child 0, successRateMin: double
                child 1, fallRateMax: double
                child 2, medianCloseSecondsMax: double
                child 3, p95LidSpeedMax: double
                child 4, p95ImpactForceMax: double
              preset: string
              schemaVersion: int64
              to
              {'schemaVersion': Value('int64'), 'id': Value('string'), 'title': Value('string'), 'preset': Value('string'), 'task': Value('string'), 'hypothesis': Value('string'), 'seeds': List(Value('int64')), 'profiles': {'smoke': {'environments': Value('int64'), 'iterations': Value('int64'), 'saveInterval': Value('int64'), 'evaluationEpisodes': Value('int64')}, 'pilot': {'environments': Value('int64'), 'iterations': Value('int64'), 'saveInterval': Value('int64'), 'evaluationEpisodes': Value('int64')}, 'full': {'environments': Value('int64'), 'iterations': Value('int64'), 'saveInterval': Value('int64'), 'evaluationEpisodes': Value('int64')}}, 'evaluation': {'successRateMin': Value('float64'), 'fallRateMax': Value('float64'), 'medianCloseSecondsMax': Value('float64'), 'p95LidSpeedMax': Value('float64'), 'p95ImpactForceMax': Value('float64')}, 'promotion': {'smoke': {'minimumCompletedSeeds': Value('int64'), 'minimumPassingSeeds': Value('int64')}, 'pilot': {'minimumCompletedSeeds': Value('int64'), 'minimumPassingSeeds': Value('int64'), 'maxSuccessRateStdDev': Value('float64')}, 'full': {'minimumCompletedSeeds': Value('int64'), 'minimumPassingSeeds': Value('int64'), 'maxSuccessRateStdDev': Value('float64')}}}
              because column names don't match

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NottyDuck training ledger

Run manifests and evaluation summaries for NottyDuck motor policies. This is the public evidence layer: promoted policies should identify their source run, task, source commit, simulator settings, randomized evaluation seeds, physical cue, and observed failure modes.

Raw source tarballs and checkpoints remain private. This repository must not contain access tokens, private social messages, provider payloads, or personal conversation data.

The canonical schema is in schema.json. The dataset begins empty because no NottyDuck policy has completed evaluation yet.

Source: https://github.com/reachjalil/nottyduck
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