help me regarding simulation of ldpc codes

Hi @Chandrasekhar_K, According to my knowledge LDPC (Low Density Parity Check) contains mostly 0’s and a low density of 1’s which is considered as a sparse matrix in tensorflow. To find the parity equation we need to find the indices of the 1’s in the sparse matrix. For example:

```
st1 = tf.sparse.SparseTensor(indices=[[0, 3], [2, 4]],
values=[1 , 1],
dense_shape=[3, 10])
```

The above code will create a sparse matrix with shape (3,10), where [0,3],[2,4] indices will have only values 1.

To find the indices which contain values

```
def pprint_sparse_tensor(st):
s = "<SparseTensor shape=%s \n values={" % (st.dense_shape.numpy().tolist(),)
for (index, value) in zip(st.indices, st.values):
s += f"\n %s: %s" % (index.numpy().tolist(), value.numpy().tolist())
return s + "}>"
```

```
print(pprint_sparse_tensor(st1))
#output
<SparseTensor shape=[3, 10]
values={
[0, 3]: 1
[2, 4]: 1}>
```

I hope this helps. Thank You.