Implement Dropout

Implement the Dropout regularization technique.

During training, randomly zero out elements with probability $p$ and scale the remaining elements by $\frac{1}{1-p}$:

$$y_i = \frac{x_i \cdot m_i}{1 - p}$$

where $m_i \sim \text{Bernoulli}(1 - p)$ is a binary mask.

For this problem, you are given the binary mask directly.

Input:

• x: input tensor of any shape
• mask: binary tensor of the same shape (1 = keep, 0 = drop)
• p: dropout probability (fraction of elements to drop)

Output: Tensor with dropout applied and properly scaled