Issue: Export to_iterable_dataset to document
State: closed
Author: npuichigo

Fix the export of a missing method of `Dataset`

Comments:
_The documentation is not available anymore as the PR was closed or merged._

<details>
<summary>Show benchmarks</summary>

PyArrow==8.0.0

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.006076 / 0.011353 (-0.005277) | 0.003730 / 0.011008 (-0.007279) | 0.080778 / 0.038508 (0.042270) | 0.062970 / 0.023109 (0.039860) | 0.395864 / 0.275898 (0.119966) | 0.430024 / 0.323480 (0.106544) | 0.004823 / 0.007986 (-0.003162) | 0.002949 / 0.004328 (-0.001379) | 0.062423 / 0.004250 (0.058172) | 0.047343 / 0.037052 (0.010291) | 0.403153 / 0.258489 (0.144664) | 0.443666 / 0.293841 (0.149825) | 0.027798 / 0.128546 (-0.100748) | 0.008056 / 0.075646 (-0.067590) | 0.262260 / 0.419271 (-0.157011) | 0.045958 / 0.043533 (0.002425) | 0.391349 / 0.255139 (0.136210) | 0.421831 / 0.283200 (0.138632) | 0.021837 / 0.141683 (-0.119846) | 1.485509 / 1.452155 (0.033355) | 1.542940 / 1.492716 (0.050224) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.196831 / 0.018006 (0.178825) | 0.435774 / 0.000490 (0.435285) | 0.003647 / 0.000200 (0.003447) | 0.000065 / 0.000054 (0.000011) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.023756 / 0.037411 (-0.013655) | 0.075737 / 0.014526 (0.061211) | 0.303703 / 0.176557 (0.127146) | 0.164862 / 0.737135 (-0.572273) | 0.198483 / 0.296338 (-0.097855) |

### Benchmark: benchmark_iterating.json

| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.405220 / 0.215209 (0.190011) | 4.065983 / 2.077655 (1.988328) | 2.043001 / 1.504120 (0.538881) | 1.853318 / 1.541195 (0.312123) | 1.977452 / 1.468490 (0.508962) | 0.500897 / 4.584777 (-4.083880) | 3.065756 / 3.745712 (-0.679956) | 2.924096 / 5.269862 (-2.345765) | 1.876194 / 4.565676 (-2.689482) | 0.057774 / 0.424275 (-0.366501) | 0.006809 / 0.007607 (-0.000798) | 0.470979 / 0.226044 (0.244934) | 4.719546 / 2.268929 (2.450618) | 2.449651 / 55.444624 (-52.994973) | 2.211817 / 6.876477 (-4.664660) | 2.398760 / 2.142072 (0.256687) | 0.590608 / 4.805227 (-4.214619) | 0.125836 / 6.500664 (-6.374829) | 0.060759 / 0.075469 (-0.014710) |

### Benchmark: benchmark_map_filter.json

| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 1.243609 / 1.841788 (-0.598179) | 18.836193 / 8.074308 (10.761885) | 13.835053 / 10.191392 (3.643661) | 0.129708 / 0.680424 (-0.550716) | 0.016708 / 0.534201 (-0.517493) | 0.337219 / 0.579283 (-0.242065) | 0.359045 / 0.434364 (-0.075319) | 0.383329 / 0.540337 (-0.157009) | 0.539629 / 1.386936 (-0.847307) |

</details>
PyArrow==latest

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.006073 / 0.011353 (-0.005280) | 0.003713 / 0.011008 (-0.007295) | 0.062642 / 0.038508 (0.024134) | 0.062618 / 0.023109 (0.039508) | 0.362029 / 0.275898 (0.086130) | 0.401924 / 0.323480 (0.078445) | 0.004689 / 0.007986 (-0.003297) | 0.002945 / 0.004328 (-0.001384) | 0.062720 / 0.004250 (0.058470) | 0.048901 / 0.037052 (0.011848) | 0.363780 / 0.258489 (0.105291) | 0.405111 / 0.293841 (0.111270) | 0.027738 / 0.128546 (-0.100808) | 0.008046 / 0.075646 (-0.067600) | 0.067752 / 0.419271 (-0.351519) | 0.041955 / 0.043533 (-0.001577) | 0.361615 / 0.255139 (0.106476) | 0.388762 / 0.283200 (0.105562) | 0.021302 / 0.141683 (-0.120380) | 1.473527 / 1.452155 (0.021372) | 1.529753 / 1.492716 (0.037037) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.300446 / 0.018006 (0.282440) | 0.425844 / 0.000490 (0.425354) | 0.054507 / 0.000200 (0.054307) | 0.000282 / 0.000054 (0.000228) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.025478 / 0.037411 (-0.011933) | 0.078298 / 0.014526 (0.063772) | 0.087647 / 0.176557 (-0.088909) | 0.138978 / 0.737135 (-0.598157) | 0.088396 / 0.296338 (-0.207942) |

### Benchmark: benchmark_iterating.json

| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.421345 / 0.215209 (0.206136) | 4.209188 / 2.077655 (2.131533) | 2.260731 / 1.504120 (0.756611) | 2.072329 / 1.541195 (0.531134) | 2.086778 / 1.468490 (0.618288) | 0.495425 / 4.584777 (-4.089352) | 2.987519 / 3.745712 (-0.758194) | 2.895106 / 5.269862 (-2.374756) | 1.874637 / 4.565676 (-2.691039) | 0.057080 / 0.424275 (-0.367195) | 0.006402 / 0.007607 (-0.001205) | 0.498233 / 0.226044 (0.272188) | 4.974385 / 2.268929 (2.705457) | 2.671755 / 55.444624 (-52.772870) | 2.356120 / 6.876477 (-4.520357) | 2.531374 / 2.142072 (0.389301) | 0.581955 / 4.805227 (-4.223272) | 0.125491 / 6.500664 (-6.375173) | 0.062267 / 0.075469 (-0.013202) |

### Benchmark: benchmark_map_filter.json

| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 1.307233 / 1.841788 (-0.534555) | 18.929740 / 8.074308 (10.855431) | 14.029693 / 10.191392 (3.838301) | 0.161992 / 0.680424 (-0.518431) | 0.017127 / 0.534201 (-0.517074) | 0.336644 / 0.579283 (-0.242639) | 0.336550 / 0.434364 (-0.097814) | 0.400554 / 0.540337 (-0.139783) | 0.560725 / 1.386936 (-0.826211) |

</details>
</details>

![](https://cml.dev/watermark.png#cb8c5de5145c7e7eee65391cb7f4d92f0d565d62 "CML watermark")