I dropped a neural net

Oh no! I dropped an extremely valuable trading model and it fell apart into linear layers! I need to rebuild it before anyone notices, but I can't remember how these pieces go together, or how it was trained.

All I have left are the pieces of the model and some historical data. Can you help me figure out how to put it back together?

Luckily I still have the source code of the layers that the neural network is made of. They look like this:

class Block(nn.Module):
    def __init__(self, in_dim: int, hidden_dim: int):
        super().__init__()
        self.inp = nn.Linear(in_dim, hidden_dim)
        self.activation = nn.ReLU()
        self.out = nn.Linear(hidden_dim, in_dim)

    def forward(self, x):
        residual = x
        x = self.inp(x)
        x = self.activation(x)
        x = self.out(x)
        return residual + x

class LastLayer(nn.Module):
    def __init__(self, in_dim: int, out_dim: int):
        super().__init__()
        self.layer = nn.Linear(in_dim, out_dim)

    def forward(self, x):
        return self.layer(x)

The solution to this puzzle is a permutation. For each index from 0 to 96 (inclusive), give the index of the piece that is applied in that position.

Download the pieces and data