The+devil39s+double+2011+bluray+720p+11gb+dual+audio+upd -

The Devil’s Double (2011) is a biographical crime drama starring Dominic Cooper as both Uday Hussein and Latif Yahia. The 11 GB 720p dual audio version would be a high-bitrate encode preserving Blu-ray quality — overkill for 720p, but good for archival.

import numpy as np
# Hypothetical pre-trained word embeddings for simplicity
word_embeddings = 
    "The": np.array([0.1, 0.2]),
    "Devil's": np.array([0.3, 0.4]),
    "Double": np.array([0.5, 0.6]),
    "2011": np.array([0.2, 0.1]),
    "Blu-ray": np.array([0.4, 0.5]),
    "720p": np.array([0.6, 0.7]),
    "11GB": np.array([0.7, 0.6]),
    "Dual": np.array([0.8, 0.9]),
    "Audio": np.array([0.9, 1.0]),
def get_deep_feature(topic):
    tokens = topic.replace("2011", " ").replace("Blu-ray", " ").replace("720p", " ").replace("11GB", " ").replace("Dual", " ").replace("Audio", " ").split()
    vector_sum = np.zeros(2)  # Assuming 2D vectors for simplicity
    count = 0
    for token in tokens:
        if token in word_embeddings:
            vector_sum += word_embeddings[token]
            count += 1
    if count > 0:
        return vector_sum / count
    else:
        return np.zeros(2)
topic = "The Devil's Double 2011 Blu-ray 720p 11GB Dual Audio"
deep_feature = get_deep_feature(topic)
print("Deep Feature:", deep_feature)

Deep features can be generated through various methods, including but not limited to: the+devil39s+double+2011+bluray+720p+11gb+dual+audio+upd

For simplicity and generality, let's focus on generating a textual representation (embedding) for the topic. The Devil’s Double (2011) is a biographical crime