fix: Fix memory allocation of ndarray

[xu-song]

Motivation

llama-cpp-python/llama_cpp/llama.py

Line 2052 in 259ee15

self.scores[state.n_tokens :, :] = 0.0

The above part will allocate a large amount of memory.
This commit reduces the memory consumption from more than 10GB to 0GB.

Simle Reproduce

import os
import numpy as np
import psutil

def print_mem():
    mem = psutil.Process(os.getpid()).memory_info().rss / 1024 / 1024 / 1024
    print(f"process_mem: {mem:.2f} GB")

n_ctx = 32768
n_vocab = 150000
scores = np.ndarray((n_ctx, n_vocab), dtype=np.single)
print_mem()   # 0.03 GB;

scores[:1000, :] = 0.5
print_mem()  # 0.59 GB

# zero-ing out the rest
scores[1000:, :] = 0.0     #  ----- large memory allocation
print_mem()  # 18.34 GB

After this pr

zero-ing out the rest will not allocate extra memory if not necessary.

# zero-ing out the rest
rest = scores[1000:, :]
rest[rest > 0] = 0.0
print_mem()  # 0.59 GB

[abetlen]

@xu-song thanks for the contribution. Just added some tests and bug fixes since the recent sampler api changes.