Create a weight matrix with He (Kaiming) normal initialisation: draw each entry from N(0,2/fan_in) using np.random.default_rng(seed).normal(0, sqrt(2/fan_in), (fan_in, fan_out)).
Implement solve(fan_in,fan_out,seed=0).
Returns. Return a float NumPy array of shape (fan_in, fan_out).
Example 1
Input:
solve(2, 3, 0)
Output:
[[0.12573, -0.132105, 0.640423], [0.1049, -0.535669, 0.361595]]
Example 2
Input:
solve(4, 1, 3)
Output:
[[1.443148], [-1.807128], [0.295641], [-0.401474]]
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