Issue: Fix CI benchmarks by temporarily pinning Docker image version
State: closed
Author: albertvillanova

This PR fixes CI benchmarks, by temporarily pinning Docker image version, instead of "latest" tag.

It also updates deprecated `cml-send-comment` command and using `cml comment create` instead.

Fix #5431.

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) | 0.008519 / 0.011353 (-0.002834) | 0.004451 / 0.011008 (-0.006558) | 0.102401 / 0.038508 (0.063893) | 0.029779 / 0.023109 (0.006669) | 0.302654 / 0.275898 (0.026756) | 0.366002 / 0.323480 (0.042522) | 0.007044 / 0.007986 (-0.000942) | 0.003350 / 0.004328 (-0.000978) | 0.078213 / 0.004250 (0.073963) | 0.035208 / 0.037052 (-0.001844) | 0.312980 / 0.258489 (0.054491) | 0.344217 / 0.293841 (0.050376) | 0.033089 / 0.128546 (-0.095457) | 0.011443 / 0.075646 (-0.064203) | 0.353143 / 0.419271 (-0.066128) | 0.040851 / 0.043533 (-0.002682) | 0.304501 / 0.255139 (0.049362) | 0.329118 / 0.283200 (0.045918) | 0.087399 / 0.141683 (-0.054284) | 1.500200 / 1.452155 (0.048046) | 1.536176 / 1.492716 (0.043459) |

### 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) | 0.209626 / 0.018006 (0.191619) | 0.425551 / 0.000490 (0.425061) | 0.001168 / 0.000200 (0.000968) | 0.000069 / 0.000054 (0.000014) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.023664 / 0.037411 (-0.013748) | 0.096792 / 0.014526 (0.082266) | 0.105652 / 0.176557 (-0.070905) | 0.140796 / 0.737135 (-0.596340) | 0.109319 / 0.296338 (-0.187019) |

### 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) | 0.414802 / 0.215209 (0.199593) | 4.152619 / 2.077655 (2.074964) | 1.814403 / 1.504120 (0.310283) | 1.611392 / 1.541195 (0.070198) | 1.667350 / 1.468490 (0.198860) | 0.691855 / 4.584777 (-3.892922) | 3.406584 / 3.745712 (-0.339128) | 1.940332 / 5.269862 (-3.329530) | 1.279061 / 4.565676 (-3.286615) | 0.082938 / 0.424275 (-0.341337) | 0.012388 / 0.007607 (0.004781) | 0.521738 / 0.226044 (0.295693) | 5.233764 / 2.268929 (2.964835) | 2.306573 / 55.444624 (-53.138051) | 1.954631 / 6.876477 (-4.921845) | 2.048315 / 2.142072 (-0.093757) | 0.816921 / 4.805227 (-3.988306) | 0.150983 / 6.500664 (-6.349681) | 0.066628 / 0.075469 (-0.008842) |

### 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) | 1.235939 / 1.841788 (-0.605849) | 14.047114 / 8.074308 (5.972806) | 14.149842 / 10.191392 (3.958450) | 0.152836 / 0.680424 (-0.527588) | 0.028837 / 0.534201 (-0.505364) | 0.396232 / 0.579283 (-0.183051) | 0.409950 / 0.434364 (-0.024414) | 0.460296 / 0.540337 (-0.080041) | 0.556787 / 1.386936 (-0.830149) |

</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) | 0.006582 / 0.011353 (-0.004771) | 0.004491 / 0.011008 (-0.006518) | 0.100093 / 0.038508 (0.061585) | 0.026826 / 0.023109 (0.003717) | 0.413971 / 0.275898 (0.138073) | 0.445625 / 0.323480 (0.122145) | 0.004892 / 0.007986 (-0.003094) | 0.003295 / 0.004328 (-0.001034) | 0.077879 / 0.004250 (0.073628) | 0.039177 / 0.037052 (0.002125) | 0.353299 / 0.258489 (0.094810) | 0.406566 / 0.293841 (0.112725) | 0.031633 / 0.128546 (-0.096913) | 0.011517 / 0.075646 (-0.064130) | 0.320939 / 0.419271 (-0.098332) | 0.041487 / 0.043533 (-0.002046) | 0.353735 / 0.255139 (0.098596) | 0.434786 / 0.283200 (0.151586) | 0.087722 / 0.141683 (-0.053961) | 1.515134 / 1.452155 (0.062979) | 1.588908 / 1.492716 (0.096191) |

### 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) | 0.225312 / 0.018006 (0.207305) | 0.398324 / 0.000490 (0.397834) | 0.000453 / 0.000200 (0.000253) | 0.000064 / 0.000054 (0.000009) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.024645 / 0.037411 (-0.012766) | 0.099399 / 0.014526 (0.084873) | 0.107006 / 0.176557 (-0.069550) | 0.145090 / 0.737135 (-0.592045) | 0.110046 / 0.296338 (-0.186292) |

### 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) | 0.450573 / 0.215209 (0.235364) | 4.498030 / 2.077655 (2.420375) | 2.193164 / 1.504120 (0.689044) | 1.940103 / 1.541195 (0.398908) | 1.957137 / 1.468490 (0.488647) | 0.697599 / 4.584777 (-3.887178) | 3.465146 / 3.745712 (-0.280566) | 1.918209 / 5.269862 (-3.351653) | 1.183921 / 4.565676 (-3.381756) | 0.082540 / 0.424275 (-0.341735) | 0.012495 / 0.007607 (0.004888) | 0.549702 / 0.226044 (0.323658) | 5.526841 / 2.268929 (3.257912) | 2.658611 / 55.444624 (-52.786014) | 2.259542 / 6.876477 (-4.616935) | 2.310139 / 2.142072 (0.168066) | 0.810550 / 4.805227 (-3.994677) | 0.152369 / 6.500664 (-6.348295) | 0.066295 / 0.075469 (-0.009174) |

### 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) | 1.289240 / 1.841788 (-0.552547) | 14.032143 / 8.074308 (5.957834) | 13.973492 / 10.191392 (3.782100) | 0.140082 / 0.680424 (-0.540342) | 0.017113 / 0.534201 (-0.517088) | 0.386534 / 0.579283 (-0.192749) | 0.393723 / 0.434364 (-0.040641) | 0.448891 / 0.540337 (-0.091446) | 0.533085 / 1.386936 (-0.853851) |

</details>
</details>

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