[fix] Handle out of range values in scalar quantization

[meiravgri]

Issue description

This PR addresses an issue with out-of-range values during scalar quantization. Previously, when quantizing data, values outside the calibration range could result in incorrect quantization.

Solution

The PR fixes this issue by introducing a clip operation in the quantization process. This operation ensures that quantized values are correctly bounded within the expected range, thus preventing out-of-range values from producing incorrect results.

Example

calibration_set = np.array([[1,20,-3], [4,5,-60]], dtype=np.float32)
dataset = np.array([[-1,15,1]], dtype=np.float32). 
sq_embeddings = quantize_embeddings(
    dataset,
    precision="int8",
    calibration_embeddings=my_np_array,
)
print("quantizing dataset = ", sq_embeddings)

Result:
incorrect quantized values for the first and third entries, respectively, which are outside the calibration range.

quantizing dataset =  [[ -42   42 -112]]

After the PR:
The quantized values are correctly bounded and thus match the expected output.

quantizing dataset =  [[-128   42  127]]

[meiravgri]

Hi @tomaarsen, could you please review my PR? Thanks!