Fix verification_mode when ignore_verifications is passed
State: closed | Author: albertvillanova (MEMBER)

This PR fixes the values assigned to `verification_mode` when passing `ignore_verifications` to `load_dataset`.

Related to:
- #5303

Fix #5682.

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

<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) | 0.006935 / 0.011353 (-0.004418) | 0.004711 / 0.011008 (-0.006297) | 0.098461 / 0.038508 (0.059953) | 0.028889 / 0.023109 (0.005780) | 0.332167 / 0.275898 (0.056269) | 0.363309 / 0.323480 (0.039829) | 0.005179 / 0.007986 (-0.002807) | 0.004783 / 0.004328 (0.000455) | 0.074293 / 0.004250 (0.070043) | 0.038778 / 0.037052 (0.001726) | 0.318871 / 0.258489 (0.060382) | 0.362975 / 0.293841 (0.069134) | 0.032897 / 0.128546 (-0.095649) | 0.011685 / 0.075646 (-0.063961) | 0.322824 / 0.419271 (-0.096447) | 0.043842 / 0.043533 (0.000309) | 0.334789 / 0.255139 (0.079650) | 0.352922 / 0.283200 (0.069723) | 0.089692 / 0.141683 (-0.051991) | 1.490110 / 1.452155 (0.037955) | 1.601530 / 1.492716 (0.108813) |

### 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) | 0.201882 / 0.018006 (0.183875) | 0.410875 / 0.000490 (0.410385) | 0.002472 / 0.000200 (0.002272) | 0.000073 / 0.000054 (0.000018) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.023636 / 0.037411 (-0.013775) | 0.102168 / 0.014526 (0.087642) | 0.107247 / 0.176557 (-0.069310) | 0.171858 / 0.737135 (-0.565278) | 0.110619 / 0.296338 (-0.185720) |

### 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) | 0.433740 / 0.215209 (0.218531) | 4.332121 / 2.077655 (2.254466) | 2.075398 / 1.504120 (0.571278) | 1.941074 / 1.541195 (0.399879) | 2.033331 / 1.468490 (0.564841) | 0.697134 / 4.584777 (-3.887643) | 3.463855 / 3.745712 (-0.281857) | 3.080446 / 5.269862 (-2.189416) | 1.575020 / 4.565676 (-2.990656) | 0.083054 / 0.424275 (-0.341221) | 0.012454 / 0.007607 (0.004847) | 0.537996 / 0.226044 (0.311951) | 5.366765 / 2.268929 (3.097836) | 2.464398 / 55.444624 (-52.980227) | 2.143912 / 6.876477 (-4.732564) | 2.245706 / 2.142072 (0.103634) | 0.801397 / 4.805227 (-4.003831) | 0.150954 / 6.500664 (-6.349710) | 0.066758 / 0.075469 (-0.008711) |

### 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) | 1.216412 / 1.841788 (-0.625376) | 13.679322 / 8.074308 (5.605014) | 14.055286 / 10.191392 (3.863894) | 0.130264 / 0.680424 (-0.550160) | 0.016566 / 0.534201 (-0.517635) | 0.379126 / 0.579283 (-0.200157) | 0.390815 / 0.434364 (-0.043549) | 0.437586 / 0.540337 (-0.102751) | 0.526822 / 1.386936 (-0.860114) |

</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) | 0.006898 / 0.011353 (-0.004455) | 0.004705 / 0.011008 (-0.006304) | 0.078592 / 0.038508 (0.040084) | 0.028635 / 0.023109 (0.005525) | 0.340143 / 0.275898 (0.064245) | 0.377526 / 0.323480 (0.054047) | 0.005645 / 0.007986 (-0.002340) | 0.003533 / 0.004328 (-0.000796) | 0.078441 / 0.004250 (0.074191) | 0.039408 / 0.037052 (0.002356) | 0.342303 / 0.258489 (0.083814) | 0.386837 / 0.293841 (0.092996) | 0.032427 / 0.128546 (-0.096119) | 0.011763 / 0.075646 (-0.063883) | 0.087984 / 0.419271 (-0.331287) | 0.042126 / 0.043533 (-0.001406) | 0.339951 / 0.255139 (0.084812) | 0.366165 / 0.283200 (0.082966) | 0.091414 / 0.141683 (-0.050269) | 1.502034 / 1.452155 (0.049880) | 1.597901 / 1.492716 (0.105184) |

### 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) | 0.232122 / 0.018006 (0.214115) | 0.410205 / 0.000490 (0.409715) | 0.000418 / 0.000200 (0.000218) | 0.000063 / 0.000054 (0.000009) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.026013 / 0.037411 (-0.011399) | 0.105520 / 0.014526 (0.090995) | 0.108649 / 0.176557 (-0.067908) | 0.159324 / 0.737135 (-0.577811) | 0.114033 / 0.296338 (-0.182306) |

### 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) | 0.455634 / 0.215209 (0.240425) | 4.508544 / 2.077655 (2.430889) | 2.087065 / 1.504120 (0.582945) | 1.872622 / 1.541195 (0.331427) | 1.935617 / 1.468490 (0.467127) | 0.696909 / 4.584777 (-3.887868) | 3.449365 / 3.745712 (-0.296348) | 3.008399 / 5.269862 (-2.261462) | 1.459245 / 4.565676 (-3.106431) | 0.083637 / 0.424275 (-0.340638) | 0.012358 / 0.007607 (0.004750) | 0.547232 / 0.226044 (0.321187) | 5.522395 / 2.268929 (3.253466) | 2.691019 / 55.444624 (-52.753605) | 2.408083 / 6.876477 (-4.468394) | 2.369239 / 2.142072 (0.227166) | 0.807148 / 4.805227 (-3.998080) | 0.152030 / 6.500664 (-6.348634) | 0.067883 / 0.075469 (-0.007586) |

### 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) | 1.336956 / 1.841788 (-0.504832) | 14.403730 / 8.074308 (6.329422) | 14.854084 / 10.191392 (4.662692) | 0.146530 / 0.680424 (-0.533894) | 0.016611 / 0.534201 (-0.517590) | 0.398557 / 0.579283 (-0.180726) | 0.393194 / 0.434364 (-0.041170) | 0.486824 / 0.540337 (-0.053513) | 0.572844 / 1.386936 (-0.814092) |

</details>
</details>

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