sigmoidMatrix function

Tensor<Matrix> sigmoidMatrix(Tensor<Matrix> m)

Implementation

Tensor<Matrix> sigmoidMatrix(Tensor<Matrix> m) {
  int numRows = m.value.length;
  int numCols = m.value[0].length;
  Matrix outValue = [];
  for (int i = 0; i < numRows; i++) {
    Vector row = [];
    for (int j = 0; j < numCols; j++) {
      row.add(1.0 / (1.0 + exp(-m.value[i][j])));
    }
    outValue.add(row);
  }
  Tensor<Matrix> out = Tensor<Matrix>(outValue);
  out.creator = Node(
    [m],
    () {
      for (int i = 0; i < numRows; i++) {
        for (int j = 0; j < numCols; j++) {
          // BUG FIX: The original gradient calculation was incorrect.
          // It should use m.grad, not out.grad on the left side.
          m.grad[i][j] +=
              out.grad[i][j] * (out.value[i][j] * (1 - out.value[i][j]));
        }
      }
    },
    opName: 'sigmoid_matrix', // <-- Renamed for clarity
    cost: numRows * numCols,
  );
  return out;
}