Title: Update actions/checkout in CD Conda release
Author: albertvillanova (MEMBER)
State: closed
Created: 2023-01-18T06:53:15Z

This PR updates the "checkout" GitHub Action to its latest version, as previous ones are deprecated: https://github.blog/changelog/2022-09-22-github-actions-all-actions-will-begin-running-on-node16-instead-of-node12/

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

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

PyArrow==6.0.0

<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) | 0.008470 / 0.011353 (-0.002883) | 0.004721 / 0.011008 (-0.006287) | 0.099024 / 0.038508 (0.060516) | 0.029831 / 0.023109 (0.006722) | 0.325887 / 0.275898 (0.049989) | 0.380753 / 0.323480 (0.057273) | 0.007101 / 0.007986 (-0.000885) | 0.004734 / 0.004328 (0.000406) | 0.077576 / 0.004250 (0.073326) | 0.037207 / 0.037052 (0.000154) | 0.320463 / 0.258489 (0.061974) | 0.369284 / 0.293841 (0.075443) | 0.033411 / 0.128546 (-0.095135) | 0.011610 / 0.075646 (-0.064037) | 0.321460 / 0.419271 (-0.097811) | 0.041315 / 0.043533 (-0.002217) | 0.349186 / 0.255139 (0.094047) | 0.384546 / 0.283200 (0.101347) | 0.088045 / 0.141683 (-0.053637) | 1.536341 / 1.452155 (0.084186) | 1.527806 / 1.492716 (0.035089) |

### 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) | 0.193435 / 0.018006 (0.175429) | 0.451732 / 0.000490 (0.451243) | 0.003165 / 0.000200 (0.002965) | 0.000082 / 0.000054 (0.000027) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.023203 / 0.037411 (-0.014208) | 0.096211 / 0.014526 (0.081685) | 0.105665 / 0.176557 (-0.070891) | 0.141074 / 0.737135 (-0.596061) | 0.108584 / 0.296338 (-0.187755) |

### 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) | 0.419041 / 0.215209 (0.203832) | 4.187915 / 2.077655 (2.110261) | 1.855336 / 1.504120 (0.351216) | 1.660046 / 1.541195 (0.118851) | 1.674646 / 1.468490 (0.206156) | 0.692257 / 4.584777 (-3.892520) | 3.466853 / 3.745712 (-0.278860) | 1.900925 / 5.269862 (-3.368936) | 1.294696 / 4.565676 (-3.270980) | 0.082792 / 0.424275 (-0.341483) | 0.012808 / 0.007607 (0.005201) | 0.529622 / 0.226044 (0.303578) | 5.337025 / 2.268929 (3.068096) | 2.326558 / 55.444624 (-53.118066) | 1.956256 / 6.876477 (-4.920221) | 2.035911 / 2.142072 (-0.106161) | 0.815824 / 4.805227 (-3.989403) | 0.148720 / 6.500664 (-6.351944) | 0.064226 / 0.075469 (-0.011243) |

### 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) | 1.231347 / 1.841788 (-0.610440) | 13.724596 / 8.074308 (5.650288) | 13.933878 / 10.191392 (3.742486) | 0.150913 / 0.680424 (-0.529511) | 0.028460 / 0.534201 (-0.505741) | 0.393564 / 0.579283 (-0.185719) | 0.407185 / 0.434364 (-0.027179) | 0.458250 / 0.540337 (-0.082087) | 0.547993 / 1.386936 (-0.838943) |

</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) | 0.006653 / 0.011353 (-0.004699) | 0.004615 / 0.011008 (-0.006393) | 0.098062 / 0.038508 (0.059554) | 0.027849 / 0.023109 (0.004740) | 0.409116 / 0.275898 (0.133218) | 0.448770 / 0.323480 (0.125290) | 0.004856 / 0.007986 (-0.003130) | 0.003427 / 0.004328 (-0.000901) | 0.075748 / 0.004250 (0.071498) | 0.037942 / 0.037052 (0.000889) | 0.410232 / 0.258489 (0.151743) | 0.457394 / 0.293841 (0.163553) | 0.031927 / 0.128546 (-0.096620) | 0.011618 / 0.075646 (-0.064028) | 0.321231 / 0.419271 (-0.098040) | 0.041416 / 0.043533 (-0.002117) | 0.413535 / 0.255139 (0.158396) | 0.438196 / 0.283200 (0.154997) | 0.089551 / 0.141683 (-0.052132) | 1.459298 / 1.452155 (0.007143) | 1.552594 / 1.492716 (0.059878) |

### 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) | 0.228186 / 0.018006 (0.210180) | 0.404393 / 0.000490 (0.403904) | 0.006944 / 0.000200 (0.006744) | 0.000081 / 0.000054 (0.000026) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.025167 / 0.037411 (-0.012244) | 0.101282 / 0.014526 (0.086756) | 0.107282 / 0.176557 (-0.069275) | 0.139797 / 0.737135 (-0.597339) | 0.110477 / 0.296338 (-0.185861) |

### 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) | 0.479121 / 0.215209 (0.263912) | 4.778210 / 2.077655 (2.700555) | 2.464687 / 1.504120 (0.960567) | 2.255312 / 1.541195 (0.714118) | 2.287348 / 1.468490 (0.818858) | 0.694769 / 4.584777 (-3.890008) | 3.460860 / 3.745712 (-0.284852) | 3.078881 / 5.269862 (-2.190980) | 1.297726 / 4.565676 (-3.267950) | 0.082699 / 0.424275 (-0.341576) | 0.012652 / 0.007607 (0.005045) | 0.583308 / 0.226044 (0.357263) | 5.839199 / 2.268929 (3.570271) | 2.893724 / 55.444624 (-52.550900) | 2.546503 / 6.876477 (-4.329974) | 2.559570 / 2.142072 (0.417498) | 0.802357 / 4.805227 (-4.002870) | 0.151890 / 6.500664 (-6.348774) | 0.068593 / 0.075469 (-0.006876) |

### 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) | 1.262421 / 1.841788 (-0.579367) | 13.771848 / 8.074308 (5.697540) | 14.046017 / 10.191392 (3.854625) | 0.140950 / 0.680424 (-0.539474) | 0.016839 / 0.534201 (-0.517362) | 0.378870 / 0.579283 (-0.200413) | 0.385908 / 0.434364 (-0.048456) | 0.438539 / 0.540337 (-0.101799) | 0.522761 / 1.386936 (-0.864175) |

</details>
</details>

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