README.md

---
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.