Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator
Paper • 2607.10960 • Published
Dataset Preview
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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1531, in _prepare_split_single
for key, record in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 127, in _generate_examples
for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
for filename, f in tar_iterator:
^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/track.py", line 49, in __iter__
for x in self.generator(*self.args):
~~~~~~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1405, in _iter_from_urlpath
with xopen(urlpath, "rb", download_config=download_config, block_size=0) as f:
~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 982, in xopen
file_obj = fs.open(paths[0], mode)
File "<string>", line 3, in open
File "/usr/local/lib/python3.14/unittest/mock.py", line 1176, in __call__
return self._mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1180, in _mock_call
return self._execute_mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1247, in _execute_mock_call
result = effect(*args, **kwargs)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 786, in wrapped
tracker.files[urlpath] = {"read": 0, "size": int(f.size)}
~~~^^^^^^^^
TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1393, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1571, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
log unknown | __key__ string | __url__ string |
|---|---|---|
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... | dqn_train | hf://datasets/egpivo/rl-execution-training-logs@6a12dbe1441d84b51cbd2154dba1b549812a5253/dqn_train_logs.tar.gz |
[
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... | dqn_train_completion_aware | hf://datasets/egpivo/rl-execution-training-logs@6a12dbe1441d84b51cbd2154dba1b549812a5253/dqn_train_logs.tar.gz |
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... | dqn_train_constant_duopoly | hf://datasets/egpivo/rl-execution-training-logs@6a12dbe1441d84b51cbd2154dba1b549812a5253/dqn_train_logs.tar.gz |
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... | dqn_train_dynamic_monopoly | hf://datasets/egpivo/rl-execution-training-logs@6a12dbe1441d84b51cbd2154dba1b549812a5253/dqn_train_logs.tar.gz |
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... | dqn_train_order_after | hf://datasets/egpivo/rl-execution-training-logs@6a12dbe1441d84b51cbd2154dba1b549812a5253/dqn_train_logs.tar.gz |
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... | dqn_train_order_random | hf://datasets/egpivo/rl-execution-training-logs@6a12dbe1441d84b51cbd2154dba1b549812a5253/dqn_train_logs.tar.gz |
RL Execution Training Logs
Per-checkpoint DQN training logs for arXiv:2607.10960 — Reinforcement Learning for Execution under Dynamic Fees in a Closed-Loop DEX Simulator.
Primary artifacts (model checkpoints, result CSVs, code) live in the public
repo github.com/egpivo/amm-lab
(data/rl_equilibrium/), commit 656ae56. These training logs are
supplementary reproducibility evidence — validation implementation-shortfall
(IS) curves per episode, with the selected ("best") checkpoint marked — kept
separately since they were briefly excluded by an overly broad .gitignore
rule.
Contents
dqn_train_logs.tar.gz — 6 logs, one per DQN variant:
dqn_train.log(dynamic duopoly, the base variant)dqn_train_completion_aware.logdqn_train_constant_duopoly.logdqn_train_dynamic_monopoly.logdqn_train_order_after.logdqn_train_order_random.log
Each line: ep <episode> eps <exploration rate> val IS <bps> (<elapsed s>),
with <- best marking the checkpoint that was selected and shipped.
Note on reproducibility
The paper's reproducibility claim rests on the shipped .pt checkpoints
being exactly re-evaluable (content-hashed in
data/rl_equilibrium/m3r_run_manifest.json), not on these training curves.
These logs are included for transparency, not as a correctness dependency.
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