Datasets:
File size: 3,441 Bytes
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---
dataset_info:
- config_name: CHUNK_0
features:
- name: obs
sequence:
sequence:
sequence: uint8
- name: target
sequence: int16
splits:
- name: train
num_bytes: 17589740814
num_examples: 108578647
- name: test
num_bytes: 9883876284
num_examples: 61011582
download_size: 2415896482
dataset_size: 27473617098
- config_name: SHUFFLED_CONCAT
features:
- name: obs
dtype:
array3_d:
shape:
- 2
- 6
- 7
dtype: float32
- name: target
sequence: float32
length: 7
splits:
- name: train
num_bytes: 207168057840.0
num_examples: 488603910
- name: validation
num_bytes: 4603734760.0
num_examples: 10857865
download_size: 8213390894
dataset_size: 211771792600.0
- config_name: SHUFFLED_CONCAT_VALIDATION
features:
- name: obs
dtype:
array3_d:
shape:
- 2
- 6
- 7
dtype: float32
- name: target
sequence: float32
length: 7
splits:
- name: validation
num_bytes: 4603734760.0
num_examples: 10857865
download_size: 178569088
dataset_size: 4603734760.0
- config_name: TRAIN_ONLY
features:
- name: obs
dtype:
array3_d:
shape:
- 2
- 6
- 7
dtype: float32
- name: target
sequence: float32
length: 7
splits:
- name: train
num_bytes: 46037346328
num_examples: 108578647
download_size: 1549311584
dataset_size: 46037346328
- config_name: default
features:
- name: obs
dtype:
array3_d:
shape:
- 2
- 6
- 7
dtype: float32
- name: target
sequence: float32
length: 7
splits:
- name: test
num_bytes: 25868910768
num_examples: 61011582
- name: train
num_bytes: 46037346328
num_examples: 108578647
download_size: 2419867693
dataset_size: 71906257096
configs:
- config_name: CHUNK_0
data_files:
- split: train
path: CHUNK_0/train-*
- split: test
path: CHUNK_0/test-*
- config_name: SHUFFLED_CONCAT
data_files:
- split: train
path: SHUFFLED_CONCAT/train-*
- split: validation
path: SHUFFLED_CONCAT/validation-*
- config_name: SHUFFLED_CONCAT_VALIDATION
data_files:
- split: validation
path: SHUFFLED_CONCAT_VALIDATION/validation-*
- config_name: TRAIN_ONLY
data_files:
- split: train
path: TRAIN_ONLY/train-*
- config_name: default
data_files:
- split: test
path: data/test-*
- split: train
path: data/train-*
license: mit
task_categories:
- reinforcement-learning
size_categories:
- 100M<n<1B
---
Connect 4 Solver Outputs
About 100M + 60M observations and targets generated from selfplay with a solver [https://github.com/PascalPons/connect4] with temperature.
Observations from different depths are roughly uniformly distributed, altough later positions are reached less frequently.
As a consequence early positions are duplicated and there is a small overlap between the train and test split (less than 3%).
Observations are of shape (2,6,7) with binary (0 or 255) data.
The first channel represents the stones placed by the current player while the second channel represent the stones played by the opoonent.
The targets are the scores returned by the solver for placing the next stone in earch column. E.g. 1 / -1 means winning / losing on the last possible move, 2 / -2 means winning / losing one move before etc.
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