Merge branch 'main_generate' into 'main'

            raw_text = None

            context_count += 1

# We added this function to support the tasks evaluation such as squad

# and drop in the https://github.com/EleutherAI/lm-evaluation-harness 

# codebase. The lm-evaluation-harness code can now call this function

# similar to their current generate function call used for gpt style models.

def generate_samples_eval(model, context, max_gen_length, eos_token_id):

    # Generate samples for lm evaluation

    # NEED TO THINK ABOUT eos token

    args = get_args()

    tokenizer = get_tokenizer()

    raw_text_len = len(context)

    model.eval()

    context_tokens = tokenizer.tokenize(context)

    args.out_seq_length = max_gen_length + len(context_tokens)

    args.eos_id = eos_token_id

    with torch.no_grad():

        token_stream = get_token_stream(model, [context_tokens])

        for counter, decode_tokens in enumerate(token_stream):

            if counter == args.out_seq_length:

                break

    decode_tokens, _ = decode_tokens

    decode_tokens = decode_tokens[0].cpu().numpy().tolist()

    trim_decode_tokens = tokenizer.detokenize(

        decode_tokens)[raw_text_len:]

    return trim_decode_tokens

def generate_samples_interactive(model, print_frequency=24):

    model.eval()

    with torch.no_grad():

        context_length = context_lengths.min().item()

        # added eos_id to support the function generate_samples_eval that passes

        # eos_id as an argument and needs termination when that id id found.

        if hasattr(args, 'eos_id'):

            eos_id = args.eos_id

        else:

            eos_id = tokenizer.eod

        counter = 0