Remove unused global variables in `audio.py`



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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) | 0.006753 / 0.011353 (-0.004600) | 0.004027 / 0.011008 (-0.006982) | 0.084200 / 0.038508 (0.045692) | 0.072233 / 0.023109 (0.049124) | 0.361535 / 0.275898 (0.085637) | 0.386196 / 0.323480 (0.062716) | 0.004047 / 0.007986 (-0.003939) | 0.003416 / 0.004328 (-0.000912) | 0.064724 / 0.004250 (0.060474) | 0.055740 / 0.037052 (0.018688) | 0.360422 / 0.258489 (0.101933) | 0.399230 / 0.293841 (0.105389) | 0.031537 / 0.128546 (-0.097009) | 0.008630 / 0.075646 (-0.067016) | 0.289652 / 0.419271 (-0.129620) | 0.052881 / 0.043533 (0.009348) | 0.359538 / 0.255139 (0.104399) | 0.379410 / 0.283200 (0.096211) | 0.024539 / 0.141683 (-0.117144) | 1.470891 / 1.452155 (0.018736) | 1.578879 / 1.492716 (0.086163) |

### 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) | 0.239200 / 0.018006 (0.221194) | 0.462100 / 0.000490 (0.461610) | 0.009055 / 0.000200 (0.008856) | 0.000406 / 0.000054 (0.000352) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.028736 / 0.037411 (-0.008675) | 0.088051 / 0.014526 (0.073525) | 0.098101 / 0.176557 (-0.078456) | 0.152399 / 0.737135 (-0.584737) | 0.098776 / 0.296338 (-0.197563) |

### 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) | 0.401761 / 0.215209 (0.186552) | 4.014143 / 2.077655 (1.936488) | 2.033255 / 1.504120 (0.529135) | 1.855347 / 1.541195 (0.314152) | 1.996144 / 1.468490 (0.527654) | 0.488545 / 4.584777 (-4.096232) | 3.712030 / 3.745712 (-0.033682) | 3.439725 / 5.269862 (-1.830137) | 2.119289 / 4.565676 (-2.446388) | 0.057523 / 0.424275 (-0.366752) | 0.007780 / 0.007607 (0.000173) | 0.479522 / 0.226044 (0.253477) | 4.798218 / 2.268929 (2.529290) | 2.543816 / 55.444624 (-52.900809) | 2.180392 / 6.876477 (-4.696085) | 2.427195 / 2.142072 (0.285122) | 0.602071 / 4.805227 (-4.203156) | 0.133450 / 6.500664 (-6.367214) | 0.061975 / 0.075469 (-0.013494) |

### 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) | 1.250040 / 1.841788 (-0.591748) | 19.532327 / 8.074308 (11.458019) | 14.200298 / 10.191392 (4.008906) | 0.165165 / 0.680424 (-0.515259) | 0.018326 / 0.534201 (-0.515875) | 0.389788 / 0.579283 (-0.189495) | 0.419301 / 0.434364 (-0.015063) | 0.452645 / 0.540337 (-0.087693) | 0.643409 / 1.386936 (-0.743527) |

</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) | 0.007040 / 0.011353 (-0.004313) | 0.004157 / 0.011008 (-0.006851) | 0.065439 / 0.038508 (0.026931) | 0.083210 / 0.023109 (0.060101) | 0.406707 / 0.275898 (0.130809) | 0.442759 / 0.323480 (0.119279) | 0.006321 / 0.007986 (-0.001665) | 0.003684 / 0.004328 (-0.000645) | 0.064517 / 0.004250 (0.060266) | 0.060676 / 0.037052 (0.023624) | 0.413395 / 0.258489 (0.154906) | 0.446776 / 0.293841 (0.152935) | 0.032542 / 0.128546 (-0.096004) | 0.008614 / 0.075646 (-0.067033) | 0.071760 / 0.419271 (-0.347511) | 0.049646 / 0.043533 (0.006113) | 0.402409 / 0.255139 (0.147270) | 0.422775 / 0.283200 (0.139575) | 0.024846 / 0.141683 (-0.116836) | 1.522915 / 1.452155 (0.070761) | 1.566518 / 1.492716 (0.073802) |

### 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) | 0.234478 / 0.018006 (0.216472) | 0.461318 / 0.000490 (0.460828) | 0.006304 / 0.000200 (0.006105) | 0.000105 / 0.000054 (0.000051) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.036904 / 0.037411 (-0.000508) | 0.102144 / 0.014526 (0.087619) | 0.108985 / 0.176557 (-0.067572) | 0.162609 / 0.737135 (-0.574526) | 0.110295 / 0.296338 (-0.186044) |

### 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) | 0.438735 / 0.215209 (0.223526) | 4.377602 / 2.077655 (2.299948) | 2.375305 / 1.504120 (0.871185) | 2.215877 / 1.541195 (0.674682) | 2.317468 / 1.468490 (0.848978) | 0.495137 / 4.584777 (-4.089640) | 3.726323 / 3.745712 (-0.019389) | 3.493785 / 5.269862 (-1.776077) | 2.177891 / 4.565676 (-2.387785) | 0.058975 / 0.424275 (-0.365300) | 0.007897 / 0.007607 (0.000290) | 0.514063 / 0.226044 (0.288019) | 5.132714 / 2.268929 (2.863786) | 2.914125 / 55.444624 (-52.530499) | 2.532912 / 6.876477 (-4.343564) | 2.776438 / 2.142072 (0.634365) | 0.624831 / 4.805227 (-4.180396) | 0.135023 / 6.500664 (-6.365641) | 0.062040 / 0.075469 (-0.013429) |

### 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) | 1.359970 / 1.841788 (-0.481818) | 20.816464 / 8.074308 (12.742156) | 16.103544 / 10.191392 (5.912152) | 0.149120 / 0.680424 (-0.531304) | 0.020279 / 0.534201 (-0.513922) | 0.408727 / 0.579283 (-0.170556) | 0.436191 / 0.434364 (0.001827) | 0.485056 / 0.540337 (-0.055281) | 0.737727 / 1.386936 (-0.649209) |

</details>
</details>

![](https://cml.dev/watermark.png#d15280f435b7e27c9350a0cc37a07dbc5e2ea9ca "CML watermark")


CI failures are unrelated

<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) | 0.008102 / 0.011353 (-0.003251) | 0.004886 / 0.011008 (-0.006123) | 0.090482 / 0.038508 (0.051974) | 0.071594 / 0.023109 (0.048485) | 0.428678 / 0.275898 (0.152780) | 0.442179 / 0.323480 (0.118699) | 0.004329 / 0.007986 (-0.003657) | 0.003756 / 0.004328 (-0.000573) | 0.087125 / 0.004250 (0.082874) | 0.055159 / 0.037052 (0.018107) | 0.437646 / 0.258489 (0.179157) | 0.446665 / 0.293841 (0.152824) | 0.046402 / 0.128546 (-0.082145) | 0.014248 / 0.075646 (-0.061398) | 0.331401 / 0.419271 (-0.087871) | 0.062010 / 0.043533 (0.018478) | 0.434774 / 0.255139 (0.179635) | 0.441063 / 0.283200 (0.157863) | 0.037424 / 0.141683 (-0.104258) | 1.720276 / 1.452155 (0.268121) | 1.731491 / 1.492716 (0.238775) |

### 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) | 0.302935 / 0.018006 (0.284929) | 0.590556 / 0.000490 (0.590067) | 0.014473 / 0.000200 (0.014274) | 0.000712 / 0.000054 (0.000658) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.031289 / 0.037411 (-0.006122) | 0.091175 / 0.014526 (0.076649) | 0.112895 / 0.176557 (-0.063661) | 0.199558 / 0.737135 (-0.537577) | 0.113397 / 0.296338 (-0.182942) |

### 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) | 0.571586 / 0.215209 (0.356377) | 5.706894 / 2.077655 (3.629240) | 2.512701 / 1.504120 (1.008581) | 2.151705 / 1.541195 (0.610510) | 2.252738 / 1.468490 (0.784248) | 0.857524 / 4.584777 (-3.727253) | 5.189027 / 3.745712 (1.443315) | 4.464979 / 5.269862 (-0.804882) | 2.787486 / 4.565676 (-1.778190) | 0.090161 / 0.424275 (-0.334115) | 0.008649 / 0.007607 (0.001042) | 0.703367 / 0.226044 (0.477322) | 7.128971 / 2.268929 (4.860043) | 3.437475 / 55.444624 (-52.007149) | 2.562291 / 6.876477 (-4.314186) | 2.753419 / 2.142072 (0.611346) | 0.981964 / 4.805227 (-3.823263) | 0.194533 / 6.500664 (-6.306131) | 0.069659 / 0.075469 (-0.005810) |

### 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) | 1.510356 / 1.841788 (-0.331431) | 22.414117 / 8.074308 (14.339809) | 20.325418 / 10.191392 (10.134025) | 0.226823 / 0.680424 (-0.453601) | 0.029123 / 0.534201 (-0.505078) | 0.454656 / 0.579283 (-0.124627) | 0.559588 / 0.434364 (0.125224) | 0.547386 / 0.540337 (0.007048) | 0.770169 / 1.386936 (-0.616767) |

</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) | 0.010167 / 0.011353 (-0.001186) | 0.005164 / 0.011008 (-0.005844) | 0.094897 / 0.038508 (0.056388) | 0.078027 / 0.023109 (0.054918) | 0.474442 / 0.275898 (0.198544) | 0.503362 / 0.323480 (0.179882) | 0.006988 / 0.007986 (-0.000998) | 0.005369 / 0.004328 (0.001041) | 0.079547 / 0.004250 (0.075297) | 0.059382 / 0.037052 (0.022329) | 0.468759 / 0.258489 (0.210270) | 0.566780 / 0.293841 (0.272939) | 0.050791 / 0.128546 (-0.077755) | 0.013191 / 0.075646 (-0.062455) | 0.086086 / 0.419271 (-0.333186) | 0.060399 / 0.043533 (0.016866) | 0.492985 / 0.255139 (0.237846) | 0.509139 / 0.283200 (0.225940) | 0.034537 / 0.141683 (-0.107146) | 1.699166 / 1.452155 (0.247011) | 1.789781 / 1.492716 (0.297065) |

### 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) | 0.278776 / 0.018006 (0.260769) | 0.615877 / 0.000490 (0.615387) | 0.009062 / 0.000200 (0.008862) | 0.000112 / 0.000054 (0.000057) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.032931 / 0.037411 (-0.004481) | 0.094796 / 0.014526 (0.080270) | 0.126697 / 0.176557 (-0.049859) | 0.168172 / 0.737135 (-0.568963) | 0.113906 / 0.296338 (-0.182433) |

### 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) | 0.602378 / 0.215209 (0.387169) | 5.987708 / 2.077655 (3.910054) | 2.800339 / 1.504120 (1.296219) | 2.474127 / 1.541195 (0.932932) | 2.502387 / 1.468490 (1.033897) | 0.808147 / 4.584777 (-3.776630) | 5.212691 / 3.745712 (1.466979) | 4.479452 / 5.269862 (-0.790409) | 2.831960 / 4.565676 (-1.733717) | 0.086777 / 0.424275 (-0.337498) | 0.009492 / 0.007607 (0.001885) | 0.716848 / 0.226044 (0.490803) | 7.099904 / 2.268929 (4.830975) | 3.794708 / 55.444624 (-51.649916) | 2.859826 / 6.876477 (-4.016650) | 3.109673 / 2.142072 (0.967600) | 0.936776 / 4.805227 (-3.868451) | 0.195152 / 6.500664 (-6.305512) | 0.074184 / 0.075469 (-0.001285) |

### 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) | 1.585419 / 1.841788 (-0.256369) | 22.420377 / 8.074308 (14.346068) | 20.761533 / 10.191392 (10.570141) | 0.228480 / 0.680424 (-0.451943) | 0.030944 / 0.534201 (-0.503257) | 0.444717 / 0.579283 (-0.134566) | 0.579632 / 0.434364 (0.145268) | 0.521669 / 0.540337 (-0.018669) | 0.748274 / 1.386936 (-0.638662) |

</details>
</details>

![](https://cml.dev/watermark.png#94e07965a400e6901f12e6f0f25c7090656c828c "CML watermark")