0121 maxsim support

[FarmersWrap]

1. fully random chunking, passage level chunking for training.
2. encode chunks for evaluation.

For training, train

1. --passage_chunk_size 256 # fixed size chunk, will be disable when set 0.
2. --passage_chunk_size_range 32,256 # fixed size chunk within a passage, but a number selected btw 32-256
3. --passage_chunk_size_range 32,256
   --passage_chunk_size_variable # fully random chunks selected btw 32-256
4. --encode_use_pre_chunked # Not fully tested. use dataset with (doc_id, chunks) to train

For evaluation encoding, encode

1. fixed chunk size, 0 means no chunk
   --passage_chunk_size 0
2. pick a random size btw 32-64 tokens to chunk a passage
   --passage_chunk_size_range "32,64" \
3. need a prechunked jsonl
   --dataset_name json
   --dataset_path "${prechunked_corpus_jsonl}"
   --dataset_split train
   --encode_use_pre_chunked

prechunked.jsonl: {"docid": "q-en-0-pos-0", "chunks": ["a", "b", "c"]}