You are given a matrix 'MATRIX' of dimension 'N' x 'M'. Your task is to make all the elements of row 'i' and column 'j' equal to 0 if any element in the ith row or jth column of the matrix is 0.

#### Note:

```
1) The number of rows should be at least 1.
2) The number of columns should be at least 1.
3) For example, refer to the below matrix illustration:
```

```
The first line of the input contains an integer 'T' denoting the number of test cases.
The first line of each test case contains two space-separated integers, 'N' and 'M', as described in the problem statement.
The next 'N' lines of each test case contain 'M' integers separated by spaces describing rows of the matrix.
```

```
For each test case, return 'N' rows consisting of 'M' integers representing the matrix.
```

##### Note:

```
You don't need to print anything, it has already been taken care of. Just implement the given function.
```

##### Constraints:

```
1 <= T <= 50
1 <= N <= 100
1 <= M <= 100
-10^9 <= MATRIX[i][j] <= 10^9
Where 'MATRIX[i][j]' denotes the matrix element.
```

#### Follow Up:

```
Can you solve it with the space complexity of O(1)?
Time limit: 1 sec
```

##### Sample Input 1:

```
2
2 3
2 4 3
1 0 0
2 2
0 1
2 3
```

##### Sample Output 1:

```
2 0 0
0 0 0
0 0
0 3
```

##### Explanation for Sample Output 1:

```
In test case 1, 2nd row, 2nd column, and 3rd column of the input matrix A contain 0. So, we have to make the entire 2nd row, 2nd column, and 3rd column of matrix A to 0. Aso explained in the above example with the matrix.
In test case 2, element at (0,0) has value 0 and so the entire row 1 and column 1 will be zero.
```

##### Sample Input 2:

```
2
1 1
5
3 3
0 5 0
7 0 9
2 4 2
```

##### Sample Output 2:

```
5
0 0 0
0 0 0
0 0 0
```

##### Explanation for Sample Output 2:

```
In test case 1, the only element in the given matirx is 5 and so no 0's are involved.
In test case 2, 'MATRIX[0][0]', 'MATRIX[1][1]', and 'MATRIX[0][2]' are 0 (0-based indexing are used). So, we have to make the entire 1st column, 2nd column, and 3rd column of matrix A to 0.
```