Fix unused DatasetInfosDict code in push_to_hub



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<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) | 0.008634 / 0.011353 (-0.002719) | 0.005147 / 0.011008 (-0.005861) | 0.102865 / 0.038508 (0.064357) | 0.080245 / 0.023109 (0.057136) | 0.401288 / 0.275898 (0.125390) | 0.419708 / 0.323480 (0.096228) | 0.006342 / 0.007986 (-0.001644) | 0.003998 / 0.004328 (-0.000330) | 0.078880 / 0.004250 (0.074630) | 0.068199 / 0.037052 (0.031147) | 0.389573 / 0.258489 (0.131084) | 0.417292 / 0.293841 (0.123451) | 0.048856 / 0.128546 (-0.079691) | 0.014165 / 0.075646 (-0.061481) | 0.348063 / 0.419271 (-0.071209) | 0.067547 / 0.043533 (0.024014) | 0.402251 / 0.255139 (0.147112) | 0.419478 / 0.283200 (0.136278) | 0.034846 / 0.141683 (-0.106837) | 1.773493 / 1.452155 (0.321338) | 1.930546 / 1.492716 (0.437830) |

### 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) | 0.211835 / 0.018006 (0.193829) | 0.545311 / 0.000490 (0.544821) | 0.006766 / 0.000200 (0.006566) | 0.000104 / 0.000054 (0.000050) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.035406 / 0.037411 (-0.002006) | 0.100769 / 0.014526 (0.086243) | 0.108667 / 0.176557 (-0.067890) | 0.193099 / 0.737135 (-0.544036) | 0.113539 / 0.296338 (-0.182799) |

### 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) | 0.586935 / 0.215209 (0.371726) | 5.895245 / 2.077655 (3.817591) | 2.528375 / 1.504120 (1.024255) | 2.228617 / 1.541195 (0.687423) | 2.295799 / 1.468490 (0.827309) | 0.859272 / 4.584777 (-3.725505) | 5.033434 / 3.745712 (1.287722) | 7.546587 / 5.269862 (2.276726) | 4.457137 / 4.565676 (-0.108539) | 0.099626 / 0.424275 (-0.324649) | 0.009296 / 0.007607 (0.001689) | 0.713498 / 0.226044 (0.487454) | 7.409385 / 2.268929 (5.140456) | 3.361418 / 55.444624 (-52.083206) | 2.681111 / 6.876477 (-4.195366) | 2.849598 / 2.142072 (0.707526) | 1.114863 / 4.805227 (-3.690364) | 0.215494 / 6.500664 (-6.285170) | 0.075807 / 0.075469 (0.000338) |

### 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) | 1.606458 / 1.841788 (-0.235330) | 23.751096 / 8.074308 (15.676788) | 21.279110 / 10.191392 (11.087718) | 0.220785 / 0.680424 (-0.459639) | 0.032688 / 0.534201 (-0.501513) | 0.530948 / 0.579283 (-0.048335) | 0.630056 / 0.434364 (0.195693) | 0.572743 / 0.540337 (0.032405) | 0.771853 / 1.386936 (-0.615083) |

</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) | 0.008693 / 0.011353 (-0.002660) | 0.004750 / 0.011008 (-0.006259) | 0.079764 / 0.038508 (0.041256) | 0.082096 / 0.023109 (0.058987) | 0.467198 / 0.275898 (0.191300) | 0.532361 / 0.323480 (0.208881) | 0.005836 / 0.007986 (-0.002149) | 0.004333 / 0.004328 (0.000005) | 0.080444 / 0.004250 (0.076194) | 0.065883 / 0.037052 (0.028831) | 0.464871 / 0.258489 (0.206382) | 0.575026 / 0.293841 (0.281185) | 0.057807 / 0.128546 (-0.070739) | 0.017462 / 0.075646 (-0.058185) | 0.093667 / 0.419271 (-0.325605) | 0.071466 / 0.043533 (0.027933) | 0.495846 / 0.255139 (0.240707) | 0.526100 / 0.283200 (0.242900) | 0.034852 / 0.141683 (-0.106831) | 1.884152 / 1.452155 (0.431998) | 1.922681 / 1.492716 (0.429965) |

### 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) | 0.250969 / 0.018006 (0.232963) | 0.504979 / 0.000490 (0.504489) | 0.000466 / 0.000200 (0.000266) | 0.000083 / 0.000054 (0.000028) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.032411 / 0.037411 (-0.005000) | 0.093184 / 0.014526 (0.078658) | 0.110798 / 0.176557 (-0.065759) | 0.165741 / 0.737135 (-0.571394) | 0.111022 / 0.296338 (-0.185317) |

### 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) | 0.661284 / 0.215209 (0.446075) | 6.622388 / 2.077655 (4.544733) | 3.095705 / 1.504120 (1.591585) | 2.745698 / 1.541195 (1.204503) | 2.694103 / 1.468490 (1.225612) | 0.862154 / 4.584777 (-3.722623) | 5.109985 / 3.745712 (1.364273) | 5.040362 / 5.269862 (-0.229499) | 3.072837 / 4.565676 (-1.492840) | 0.110421 / 0.424275 (-0.313854) | 0.008476 / 0.007607 (0.000869) | 0.910020 / 0.226044 (0.683975) | 8.123626 / 2.268929 (5.854698) | 3.813811 / 55.444624 (-51.630813) | 3.017244 / 6.876477 (-3.859232) | 3.061222 / 2.142072 (0.919150) | 1.073548 / 4.805227 (-3.731680) | 0.216327 / 6.500664 (-6.284338) | 0.072977 / 0.075469 (-0.002492) |

### 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) | 1.722482 / 1.841788 (-0.119305) | 23.706716 / 8.074308 (15.632407) | 23.192134 / 10.191392 (13.000742) | 0.276733 / 0.680424 (-0.403691) | 0.033538 / 0.534201 (-0.500663) | 0.602083 / 0.579283 (0.022799) | 0.578718 / 0.434364 (0.144354) | 0.558311 / 0.540337 (0.017974) | 0.740341 / 1.386936 (-0.646595) |

</details>
</details>

![](https://cml.dev/watermark.png#7ac575b8ed57dac60d7ba33a616894f38601f84a "CML watermark")


<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) | 0.006862 / 0.011353 (-0.004491) | 0.004223 / 0.011008 (-0.006786) | 0.085931 / 0.038508 (0.047423) | 0.081437 / 0.023109 (0.058328) | 0.349542 / 0.275898 (0.073644) | 0.379881 / 0.323480 (0.056401) | 0.005651 / 0.007986 (-0.002334) | 0.003662 / 0.004328 (-0.000666) | 0.065251 / 0.004250 (0.061001) | 0.061599 / 0.037052 (0.024547) | 0.359681 / 0.258489 (0.101192) | 0.392502 / 0.293841 (0.098661) | 0.031300 / 0.128546 (-0.097246) | 0.008591 / 0.075646 (-0.067055) | 0.288577 / 0.419271 (-0.130694) | 0.062920 / 0.043533 (0.019388) | 0.348989 / 0.255139 (0.093850) | 0.362769 / 0.283200 (0.079569) | 0.030087 / 0.141683 (-0.111596) | 1.480748 / 1.452155 (0.028594) | 1.580413 / 1.492716 (0.087697) |

### 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) | 0.205804 / 0.018006 (0.187798) | 0.455386 / 0.000490 (0.454897) | 0.003134 / 0.000200 (0.002934) | 0.000077 / 0.000054 (0.000023) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.030252 / 0.037411 (-0.007159) | 0.087566 / 0.014526 (0.073041) | 0.098209 / 0.176557 (-0.078347) | 0.155816 / 0.737135 (-0.581319) | 0.098938 / 0.296338 (-0.197401) |

### 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) | 0.386688 / 0.215209 (0.171479) | 3.852777 / 2.077655 (1.775123) | 1.938688 / 1.504120 (0.434568) | 1.779234 / 1.541195 (0.238039) | 1.864262 / 1.468490 (0.395772) | 0.482472 / 4.584777 (-4.102305) | 3.658060 / 3.745712 (-0.087652) | 5.206489 / 5.269862 (-0.063373) | 3.262498 / 4.565676 (-1.303179) | 0.057523 / 0.424275 (-0.366752) | 0.007365 / 0.007607 (-0.000242) | 0.466886 / 0.226044 (0.240841) | 4.671026 / 2.268929 (2.402097) | 2.380357 / 55.444624 (-53.064268) | 2.096590 / 6.876477 (-4.779887) | 2.274415 / 2.142072 (0.132342) | 0.579705 / 4.805227 (-4.225522) | 0.134522 / 6.500664 (-6.366142) | 0.062232 / 0.075469 (-0.013237) |

### 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) | 1.245965 / 1.841788 (-0.595823) | 20.115180 / 8.074308 (12.040872) | 14.602983 / 10.191392 (4.411591) | 0.146890 / 0.680424 (-0.533533) | 0.018424 / 0.534201 (-0.515777) | 0.393941 / 0.579283 (-0.185342) | 0.413785 / 0.434364 (-0.020579) | 0.453344 / 0.540337 (-0.086993) | 0.655446 / 1.386936 (-0.731490) |

</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) | 0.006807 / 0.011353 (-0.004546) | 0.004083 / 0.011008 (-0.006925) | 0.065389 / 0.038508 (0.026881) | 0.081056 / 0.023109 (0.057947) | 0.362823 / 0.275898 (0.086925) | 0.401928 / 0.323480 (0.078448) | 0.005452 / 0.007986 (-0.002533) | 0.003413 / 0.004328 (-0.000915) | 0.065238 / 0.004250 (0.060987) | 0.057264 / 0.037052 (0.020211) | 0.375713 / 0.258489 (0.117224) | 0.407858 / 0.293841 (0.114017) | 0.031580 / 0.128546 (-0.096966) | 0.008643 / 0.075646 (-0.067003) | 0.071693 / 0.419271 (-0.347578) | 0.049392 / 0.043533 (0.005859) | 0.370194 / 0.255139 (0.115055) | 0.384647 / 0.283200 (0.101447) | 0.024805 / 0.141683 (-0.116877) | 1.509511 / 1.452155 (0.057356) | 1.560193 / 1.492716 (0.067477) |

### 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) | 0.234442 / 0.018006 (0.216436) | 0.458818 / 0.000490 (0.458329) | 0.000407 / 0.000200 (0.000207) | 0.000060 / 0.000054 (0.000006) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.031661 / 0.037411 (-0.005750) | 0.093143 / 0.014526 (0.078618) | 0.102205 / 0.176557 (-0.074352) | 0.155850 / 0.737135 (-0.581286) | 0.104345 / 0.296338 (-0.191994) |

### 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) | 0.419641 / 0.215209 (0.204432) | 4.200808 / 2.077655 (2.123153) | 2.218227 / 1.504120 (0.714107) | 2.052604 / 1.541195 (0.511409) | 2.150611 / 1.468490 (0.682121) | 0.482665 / 4.584777 (-4.102112) | 3.606541 / 3.745712 (-0.139172) | 3.310637 / 5.269862 (-1.959224) | 2.070200 / 4.565676 (-2.495476) | 0.056586 / 0.424275 (-0.367689) | 0.007826 / 0.007607 (0.000218) | 0.491037 / 0.226044 (0.264992) | 4.901538 / 2.268929 (2.632610) | 2.676402 / 55.444624 (-52.768223) | 2.363935 / 6.876477 (-4.512542) | 2.587813 / 2.142072 (0.445741) | 0.579302 / 4.805227 (-4.225926) | 0.132792 / 6.500664 (-6.367873) | 0.061865 / 0.075469 (-0.013604) |

### 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) | 1.354315 / 1.841788 (-0.487473) | 20.874516 / 8.074308 (12.800208) | 14.863559 / 10.191392 (4.672167) | 0.183635 / 0.680424 (-0.496789) | 0.018636 / 0.534201 (-0.515565) | 0.395317 / 0.579283 (-0.183966) | 0.410598 / 0.434364 (-0.023766) | 0.476485 / 0.540337 (-0.063853) | 0.643246 / 1.386936 (-0.743690) |

</details>
</details>

![](https://cml.dev/watermark.png#4472a8795c603a95eef7c8f15cb04f1290cc8d11 "CML watermark")