Fix benchmarks CI - pin protobuf
Opened by lhoestq (closed)

fix https://github.com/huggingface/datasets/actions/runs/4156059127/jobs/7189576331

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) | 0.011142 / 0.011353 (-0.000211) | 0.005885 / 0.011008 (-0.005123) | 0.115374 / 0.038508 (0.076866) | 0.041704 / 0.023109 (0.018594) | 0.356996 / 0.275898 (0.081098) | 0.395076 / 0.323480 (0.071596) | 0.008726 / 0.007986 (0.000740) | 0.005528 / 0.004328 (0.001199) | 0.087817 / 0.004250 (0.083566) | 0.049273 / 0.037052 (0.012221) | 0.363778 / 0.258489 (0.105289) | 0.408801 / 0.293841 (0.114960) | 0.045232 / 0.128546 (-0.083314) | 0.013788 / 0.075646 (-0.061859) | 0.395634 / 0.419271 (-0.023637) | 0.056583 / 0.043533 (0.013051) | 0.360779 / 0.255139 (0.105640) | 0.386843 / 0.283200 (0.103643) | 0.116632 / 0.141683 (-0.025051) | 1.830020 / 1.452155 (0.377865) | 1.808720 / 1.492716 (0.316003) |

### 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) | 0.221029 / 0.018006 (0.203023) | 0.489463 / 0.000490 (0.488973) | 0.002104 / 0.000200 (0.001904) | 0.000098 / 0.000054 (0.000043) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.032873 / 0.037411 (-0.004539) | 0.129526 / 0.014526 (0.115000) | 0.141446 / 0.176557 (-0.035111) | 0.189222 / 0.737135 (-0.547913) | 0.149329 / 0.296338 (-0.147010) |

### 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) | 0.471389 / 0.215209 (0.256180) | 4.710174 / 2.077655 (2.632519) | 2.239122 / 1.504120 (0.735002) | 1.977789 / 1.541195 (0.436595) | 2.107336 / 1.468490 (0.638846) | 0.816852 / 4.584777 (-3.767925) | 4.944056 / 3.745712 (1.198344) | 4.637939 / 5.269862 (-0.631922) | 2.355546 / 4.565676 (-2.210131) | 0.099324 / 0.424275 (-0.324951) | 0.014529 / 0.007607 (0.006922) | 0.596322 / 0.226044 (0.370277) | 5.972216 / 2.268929 (3.703287) | 2.697281 / 55.444624 (-52.747344) | 2.293836 / 6.876477 (-4.582641) | 2.380271 / 2.142072 (0.238199) | 1.001307 / 4.805227 (-3.803920) | 0.196981 / 6.500664 (-6.303683) | 0.074390 / 0.075469 (-0.001079) |

### 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) | 1.482915 / 1.841788 (-0.358872) | 18.739511 / 8.074308 (10.665202) | 16.768191 / 10.191392 (6.576799) | 0.203163 / 0.680424 (-0.477261) | 0.037514 / 0.534201 (-0.496687) | 0.529017 / 0.579283 (-0.050266) | 0.577591 / 0.434364 (0.143227) | 0.634057 / 0.540337 (0.093720) | 0.759812 / 1.386936 (-0.627124) |

</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) | 0.008815 / 0.011353 (-0.002537) | 0.005956 / 0.011008 (-0.005052) | 0.087912 / 0.038508 (0.049404) | 0.040291 / 0.023109 (0.017182) | 0.404079 / 0.275898 (0.128181) | 0.447309 / 0.323480 (0.123829) | 0.006515 / 0.007986 (-0.001471) | 0.005917 / 0.004328 (0.001588) | 0.085560 / 0.004250 (0.081310) | 0.057077 / 0.037052 (0.020025) | 0.403349 / 0.258489 (0.144860) | 0.465644 / 0.293841 (0.171803) | 0.043530 / 0.128546 (-0.085016) | 0.014234 / 0.075646 (-0.061412) | 0.102203 / 0.419271 (-0.317068) | 0.058335 / 0.043533 (0.014802) | 0.398488 / 0.255139 (0.143349) | 0.424127 / 0.283200 (0.140927) | 0.119058 / 0.141683 (-0.022625) | 1.748748 / 1.452155 (0.296593) | 1.822190 / 1.492716 (0.329474) |

### 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) | 0.255782 / 0.018006 (0.237776) | 0.496665 / 0.000490 (0.496176) | 0.000471 / 0.000200 (0.000271) | 0.000069 / 0.000054 (0.000014) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.034111 / 0.037411 (-0.003301) | 0.131442 / 0.014526 (0.116917) | 0.144660 / 0.176557 (-0.031897) | 0.188156 / 0.737135 (-0.548979) | 0.149875 / 0.296338 (-0.146463) |

### 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) | 0.502218 / 0.215209 (0.287009) | 5.004486 / 2.077655 (2.926832) | 2.420379 / 1.504120 (0.916259) | 2.194671 / 1.541195 (0.653476) | 2.306376 / 1.468490 (0.837886) | 0.856623 / 4.584777 (-3.728154) | 4.963211 / 3.745712 (1.217499) | 2.517965 / 5.269862 (-2.751896) | 1.743880 / 4.565676 (-2.821797) | 0.105270 / 0.424275 (-0.319005) | 0.014725 / 0.007607 (0.007118) | 0.621934 / 0.226044 (0.395890) | 6.183827 / 2.268929 (3.914898) | 2.945868 / 55.444624 (-52.498757) | 2.557676 / 6.876477 (-4.318801) | 2.622282 / 2.142072 (0.480210) | 1.011647 / 4.805227 (-3.793580) | 0.199573 / 6.500664 (-6.301091) | 0.076283 / 0.075469 (0.000814) |

### 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) | 1.518813 / 1.841788 (-0.322975) | 18.833017 / 8.074308 (10.758709) | 16.095249 / 10.191392 (5.903857) | 0.196667 / 0.680424 (-0.483757) | 0.022060 / 0.534201 (-0.512141) | 0.537802 / 0.579283 (-0.041481) | 0.523676 / 0.434364 (0.089312) | 0.629387 / 0.540337 (0.089049) | 0.738042 / 1.386936 (-0.648894) |

</details>
</details>

![](https://cml.dev/watermark.png#813712c3cd133f72f496d279e02344d6ee743fdf "CML watermark")


<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) | 0.008608 / 0.011353 (-0.002745) | 0.004553 / 0.011008 (-0.006455) | 0.100031 / 0.038508 (0.061523) | 0.029498 / 0.023109 (0.006389) | 0.306913 / 0.275898 (0.031015) | 0.367369 / 0.323480 (0.043889) | 0.006883 / 0.007986 (-0.001103) | 0.004768 / 0.004328 (0.000440) | 0.077424 / 0.004250 (0.073173) | 0.034005 / 0.037052 (-0.003047) | 0.317772 / 0.258489 (0.059283) | 0.356859 / 0.293841 (0.063018) | 0.033717 / 0.128546 (-0.094829) | 0.011386 / 0.075646 (-0.064260) | 0.322832 / 0.419271 (-0.096439) | 0.043930 / 0.043533 (0.000397) | 0.308087 / 0.255139 (0.052948) | 0.338349 / 0.283200 (0.055149) | 0.094780 / 0.141683 (-0.046903) | 1.463454 / 1.452155 (0.011300) | 1.495055 / 1.492716 (0.002338) |

### 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) | 0.191039 / 0.018006 (0.173033) | 0.414650 / 0.000490 (0.414160) | 0.002435 / 0.000200 (0.002235) | 0.000075 / 0.000054 (0.000021) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.023871 / 0.037411 (-0.013540) | 0.097140 / 0.014526 (0.082614) | 0.105914 / 0.176557 (-0.070643) | 0.147375 / 0.737135 (-0.589760) | 0.107985 / 0.296338 (-0.188354) |

### 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) | 0.420174 / 0.215209 (0.204965) | 4.208354 / 2.077655 (2.130700) | 1.904568 / 1.504120 (0.400448) | 1.687406 / 1.541195 (0.146212) | 1.723901 / 1.468490 (0.255411) | 0.693554 / 4.584777 (-3.891223) | 3.445474 / 3.745712 (-0.300238) | 1.904919 / 5.269862 (-3.364943) | 1.284378 / 4.565676 (-3.281298) | 0.082539 / 0.424275 (-0.341736) | 0.012490 / 0.007607 (0.004883) | 0.527778 / 0.226044 (0.301733) | 5.300766 / 2.268929 (3.031838) | 2.324666 / 55.444624 (-53.119958) | 1.977166 / 6.876477 (-4.899311) | 2.054396 / 2.142072 (-0.087677) | 0.820966 / 4.805227 (-3.984261) | 0.148584 / 6.500664 (-6.352080) | 0.063618 / 0.075469 (-0.011851) |

### 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) | 1.188075 / 1.841788 (-0.653712) | 13.706950 / 8.074308 (5.632642) | 13.725122 / 10.191392 (3.533730) | 0.167379 / 0.680424 (-0.513045) | 0.028729 / 0.534201 (-0.505472) | 0.395373 / 0.579283 (-0.183910) | 0.403604 / 0.434364 (-0.030760) | 0.464290 / 0.540337 (-0.076047) | 0.553792 / 1.386936 (-0.833144) |

</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) | 0.006565 / 0.011353 (-0.004787) | 0.004588 / 0.011008 (-0.006420) | 0.077312 / 0.038508 (0.038804) | 0.027348 / 0.023109 (0.004239) | 0.367753 / 0.275898 (0.091855) | 0.403250 / 0.323480 (0.079770) | 0.005201 / 0.007986 (-0.002785) | 0.004695 / 0.004328 (0.000366) | 0.076203 / 0.004250 (0.071953) | 0.039388 / 0.037052 (0.002336) | 0.374418 / 0.258489 (0.115929) | 0.413623 / 0.293841 (0.119782) | 0.031731 / 0.128546 (-0.096815) | 0.011644 / 0.075646 (-0.064002) | 0.086339 / 0.419271 (-0.332932) | 0.048902 / 0.043533 (0.005369) | 0.352064 / 0.255139 (0.096925) | 0.386637 / 0.283200 (0.103437) | 0.093662 / 0.141683 (-0.048021) | 1.479863 / 1.452155 (0.027709) | 1.562475 / 1.492716 (0.069758) |

### 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) | 0.231874 / 0.018006 (0.213867) | 0.402185 / 0.000490 (0.401695) | 0.005252 / 0.000200 (0.005052) | 0.000086 / 0.000054 (0.000032) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.025402 / 0.037411 (-0.012010) | 0.099896 / 0.014526 (0.085370) | 0.106365 / 0.176557 (-0.070192) | 0.143309 / 0.737135 (-0.593827) | 0.112311 / 0.296338 (-0.184027) |

### 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) | 0.447637 / 0.215209 (0.232428) | 4.469337 / 2.077655 (2.391682) | 2.164332 / 1.504120 (0.660212) | 1.957826 / 1.541195 (0.416631) | 1.984580 / 1.468490 (0.516090) | 0.702909 / 4.584777 (-3.881868) | 3.361725 / 3.745712 (-0.383987) | 2.818102 / 5.269862 (-2.451760) | 1.589815 / 4.565676 (-2.975862) | 0.083647 / 0.424275 (-0.340628) | 0.012502 / 0.007607 (0.004895) | 0.545578 / 0.226044 (0.319534) | 5.480894 / 2.268929 (3.211966) | 2.605599 / 55.444624 (-52.839026) | 2.253444 / 6.876477 (-4.623032) | 2.289818 / 2.142072 (0.147746) | 0.803680 / 4.805227 (-4.001547) | 0.151870 / 6.500664 (-6.348794) | 0.066610 / 0.075469 (-0.008859) |

### 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) | 1.327390 / 1.841788 (-0.514398) | 14.046936 / 8.074308 (5.972628) | 13.643169 / 10.191392 (3.451777) | 0.128223 / 0.680424 (-0.552201) | 0.016941 / 0.534201 (-0.517260) | 0.383887 / 0.579283 (-0.195396) | 0.383891 / 0.434364 (-0.050473) | 0.440191 / 0.540337 (-0.100146) | 0.525357 / 1.386936 (-0.861579) |

</details>
</details>

![](https://cml.dev/watermark.png#1575be339bc14a12229d782e2788746f27aeeb2a "CML watermark")


Yea there must have been an update in another package that unconstrained the protobuf dependency - idk which one though

It is `tensorboard`. I have reported the issue to `tensorflow`:
- https://github.com/tensorflow/tensorflow/issues/59665