JSON tokenizer memory optimizations

[shrshi]

Description

The full push-down automata that tokenizes the input JSON string, as well as the bracket-brace FST over-estimates the total buffer size required for the translated output and indices. This PR splits the transduce calls for both FSTs into two invocations. The first invocation estimates the size of the translated buffer and the translated indices, and the second call performs the DFA run.

Checklist

• I am familiar with the Contributing Guidelines.
• New or existing tests cover these changes.
• The documentation is up to date with these changes.

[shrshi]

Benchmark used for profiling study: https://github.com/karthikeyann/cudf/blob/enh-profile_memusage_json/wm_benchmark.py

Profiles before and after optimization:

We see that the peak memory usage comes down from 20.8GiB to 10.3GiB and the runtime of get_token_stream also reduces from 1.028s to 825.578ms