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Huawei HCIP-AI-EI Developer V2.5 Sample Questions:

1. Which of the following statements about the multi-head attention mechanism of the Transformer are true?

A) Each header's query, key, and value undergo a shared linear transformation to obtain them.
B) The concatenated output is fed directly into the multi-headed attention mechanism.
C) The multi-head attention mechanism captures information about different subspaces within a sequence.
D) The dimension for each header is calculated by dividing the original embedded dimension by the number of headers before concatenation.

2. In natural language processing tasks, word vector evaluation is an important aspect for measuring the performance of a word embedding model. Which of the following statements about word vector evaluation are true?

A) Word vector evaluation can be performed through intrinsic evaluation. Common methods include word similarity tasks and word analogy tasks.
B) The word analogy task evaluates the capability of word vectors in capturing semantic relationships between words, for example, by determining whether "king - man + woman = ?" is close to "queen".
C) Extrinsic evaluation is the main method used for evaluating word vectors because it directly reflects the performance of word vectors in real-world application tasks.
D) Word similarity tasks typically employ manually labeled datasets to evaluate word vectors, compute the cosine similarity between word vectors, and compare it with the manual labeling result.

3. Which of the following is not an algorithm for training word vectors?

A) TextCNN
B) Word2Vec
C) BERT
D) FastText

4. The accuracy of object location detection can be evaluated using the intersection over union (IoU) value, which is a ratio. The denominator is the overlapping area between the prediction bounding box and ground truth bounding box, and the numerator is the area of union encompassed by both boxes.

A) TRUE
B) FALSE

5. In 2017, the Google machine translation team proposed the Transformer in their paperAttention is All You Need. The Transformer consists of an encoder and a(n) --------. (Fill in the blank.)

Solutions: