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

1. 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.)

2. The basic operations of morphological processing include dilation and erosion. These operations can be combined to achieve practical algorithms such as opening and closing operations.

A) TRUE
B) FALSE

3. In 2017, the Google machine translation team proposed the Transformer in their paperAttention is All You Need. In a Transformer model, there is customized LSTM with CNN layers.

A) TRUE
B) FALSE

4. Which of the following statements about the functions of layer normalization and residual connection in the Transformer is true?

A) In shallow networks, residual connections are beneficial, but they aggravate the vanishing gradient problem in deep networks.
B) Residual connections primarily add depth to the model but do not aid in gradient propagation.
C) Layer normalization accelerates model convergence and does not affect model stability.
D) Residual connections and layer normalization help prevent vanishing gradients and exploding gradients in deep networks.

5. Which of the following statements are true about the differences between using convolutional neural networks (CNNs) in text tasks and image tasks?

A) When the CNN is used for text tasks, the kernel size must be the same as the number of word vector dimensions. This constraint, however, does not apply to image tasks.
B) Color image input is multi-channel, whereas text input is single-channel.
C) For CNN, there is no difference in handling text or image tasks.
D) CNNs are suitable for image tasks, but they perform poorly in text tasks.

Solutions: