Update GitHub Actions to Node 20
Opened by albertvillanova (closed)

Update GitHub Actions to Node 20.

Fix #6679.

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6682). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

<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) | 0.005292 / 0.011353 (-0.006060) | 0.003354 / 0.011008 (-0.007654) | 0.063150 / 0.038508 (0.024642) | 0.028616 / 0.023109 (0.005507) | 0.242267 / 0.275898 (-0.033631) | 0.267305 / 0.323480 (-0.056175) | 0.003041 / 0.007986 (-0.004944) | 0.003346 / 0.004328 (-0.000982) | 0.048268 / 0.004250 (0.044018) | 0.042070 / 0.037052 (0.005018) | 0.256526 / 0.258489 (-0.001963) | 0.279744 / 0.293841 (-0.014097) | 0.027862 / 0.128546 (-0.100684) | 0.010786 / 0.075646 (-0.064861) | 0.206998 / 0.419271 (-0.212273) | 0.035503 / 0.043533 (-0.008030) | 0.248454 / 0.255139 (-0.006685) | 0.265639 / 0.283200 (-0.017561) | 0.019590 / 0.141683 (-0.122093) | 1.134445 / 1.452155 (-0.317709) | 1.194956 / 1.492716 (-0.297761) |

### 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) | 0.090987 / 0.018006 (0.072981) | 0.301907 / 0.000490 (0.301418) | 0.000213 / 0.000200 (0.000013) | 0.000043 / 0.000054 (-0.000011) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.018324 / 0.037411 (-0.019088) | 0.061492 / 0.014526 (0.046966) | 0.074166 / 0.176557 (-0.102391) | 0.119990 / 0.737135 (-0.617145) | 0.074554 / 0.296338 (-0.221785) |

### 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) | 0.279646 / 0.215209 (0.064437) | 2.773819 / 2.077655 (0.696164) | 1.436460 / 1.504120 (-0.067660) | 1.310303 / 1.541195 (-0.230892) | 1.315328 / 1.468490 (-0.153162) | 0.558328 / 4.584777 (-4.026449) | 2.383819 / 3.745712 (-1.361893) | 2.735034 / 5.269862 (-2.534827) | 1.724413 / 4.565676 (-2.841263) | 0.061476 / 0.424275 (-0.362799) | 0.004899 / 0.007607 (-0.002708) | 0.333195 / 0.226044 (0.107151) | 3.228900 / 2.268929 (0.959971) | 1.787315 / 55.444624 (-53.657309) | 1.526949 / 6.876477 (-5.349527) | 1.539816 / 2.142072 (-0.602257) | 0.636926 / 4.805227 (-4.168302) | 0.117533 / 6.500664 (-6.383131) | 0.041859 / 0.075469 (-0.033610) |

### 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) | 0.964637 / 1.841788 (-0.877151) | 11.296021 / 8.074308 (3.221713) | 9.375436 / 10.191392 (-0.815956) | 0.140330 / 0.680424 (-0.540094) | 0.013638 / 0.534201 (-0.520563) | 0.287046 / 0.579283 (-0.292237) | 0.265054 / 0.434364 (-0.169310) | 0.331548 / 0.540337 (-0.208790) | 0.438418 / 1.386936 (-0.948518) |

</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) | 0.005284 / 0.011353 (-0.006069) | 0.003853 / 0.011008 (-0.007155) | 0.049301 / 0.038508 (0.010793) | 0.030477 / 0.023109 (0.007368) | 0.278507 / 0.275898 (0.002609) | 0.298245 / 0.323480 (-0.025235) | 0.004225 / 0.007986 (-0.003761) | 0.002736 / 0.004328 (-0.001593) | 0.049345 / 0.004250 (0.045094) | 0.045141 / 0.037052 (0.008088) | 0.290992 / 0.258489 (0.032503) | 0.317430 / 0.293841 (0.023589) | 0.029623 / 0.128546 (-0.098924) | 0.010351 / 0.075646 (-0.065295) | 0.058027 / 0.419271 (-0.361244) | 0.051306 / 0.043533 (0.007773) | 0.279947 / 0.255139 (0.024808) | 0.296916 / 0.283200 (0.013717) | 0.018859 / 0.141683 (-0.122823) | 1.153484 / 1.452155 (-0.298670) | 1.189141 / 1.492716 (-0.303575) |

### 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) | 0.091030 / 0.018006 (0.073024) | 0.301305 / 0.000490 (0.300815) | 0.000230 / 0.000200 (0.000030) | 0.000049 / 0.000054 (-0.000005) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.021801 / 0.037411 (-0.015611) | 0.075162 / 0.014526 (0.060636) | 0.086455 / 0.176557 (-0.090102) | 0.125431 / 0.737135 (-0.611705) | 0.087797 / 0.296338 (-0.208542) |

### 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) | 0.295950 / 0.215209 (0.080741) | 2.895839 / 2.077655 (0.818184) | 1.603121 / 1.504120 (0.099001) | 1.482162 / 1.541195 (-0.059033) | 1.474231 / 1.468490 (0.005741) | 0.571370 / 4.584777 (-4.013407) | 2.466864 / 3.745712 (-1.278848) | 2.607279 / 5.269862 (-2.662582) | 1.723106 / 4.565676 (-2.842571) | 0.062068 / 0.424275 (-0.362208) | 0.004958 / 0.007607 (-0.002649) | 0.345213 / 0.226044 (0.119168) | 3.403916 / 2.268929 (1.134987) | 1.935538 / 55.444624 (-53.509086) | 1.658930 / 6.876477 (-5.217547) | 1.767611 / 2.142072 (-0.374461) | 0.645780 / 4.805227 (-4.159447) | 0.116077 / 6.500664 (-6.384587) | 0.040774 / 0.075469 (-0.034695) |

### 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) | 1.025952 / 1.841788 (-0.815836) | 11.935970 / 8.074308 (3.861662) | 9.935799 / 10.191392 (-0.255593) | 0.131081 / 0.680424 (-0.549343) | 0.016010 / 0.534201 (-0.518191) | 0.285476 / 0.579283 (-0.293807) | 0.274928 / 0.434364 (-0.159435) | 0.325788 / 0.540337 (-0.214550) | 0.421666 / 1.386936 (-0.965270) |

</details>
</details>

![](https://cml.dev/watermark.png#7a79064b7a2255c0d6950dc998509ecefb893689 "CML watermark")