Left-Indexing With Result of DML Function Changes Matrix Size

I've found a bug in which assigning the result of a DML function to a portion of a matrix with left-indexing results in the left-hand matrix being reduced in size dimensionally. This bug was encountered while working on the deep learning DML library, and the following simplified example aims to provide a simple, reproducible example.

Given the following code,

N = 3
M = 5
forward = function(matrix[double] X) return (matrix[double] out) {
  out = 1 / (1 + exp(-X))
}

X = rand(rows=N, cols=M)
X[,1:2] = forward(X[,1:2])
print("X1: " + nrow(X) + "x" + ncol(X))

if(1==1){}

X = rand(rows=N, cols=M)
temp = forward(X[,1:2])
X[,1:2] = temp
print("X2: " + nrow(X) + "x" + ncol(X))

if(1==1){}
print("")

, notice that X should always be a 3x5 matrix, as both cases are equivalent. However, in the first case, X is truncated to a 3x2 matrix:

X1: 3x2
X2: 3x5

Note: The if(1==1) statements are included because otherwise the print statements are executed out of order.