Fix symmetric svd decomp (#944)

* modify decompositions.svd to allow truncating all singular values

* modify decompositions.svd to allow truncating all singular values

* updated test_max_truncation_error

* remove unusedvariable

Author: mganahl

tensornetwork/backends/symmetric/decompositions.py

@@ -84,10 +84,6 @@ def svd(
     #sort singular values
     inds = np.argsort(extended_flat_singvals, kind='stable')
     discarded_inds = np.zeros(0, dtype=SIZE_T)
-    if inds.shape[0] > 0:
-      maxind = inds[-1]
-    else:
-      maxind = 0
     if max_truncation_error is not None:
       if relative and (len(singvals) > 0):
         max_truncation_error = max_truncation_error * np.max(
@@ -114,9 +110,7 @@ def svd(
 
     if len(inds) == 0:
       #special case of truncation to 0 dimension;
-      warnings.warn("svd_decomposition truncated to 0 dimensions. "
-                    "Adjusting to `max_singular_values = 1`")
-      inds = np.asarray([maxind])
+      warnings.warn("svd_decomposition truncated to 0 dimensions.")
 
     if extended_singvals.shape[1] > 0:
       #pylint: disable=no-member

tensornetwork/backends/symmetric/decompositions_test.py

@@ -87,8 +87,9 @@ def test_max_singular_values(dtype, R, R1, num_charges):
 
 @pytest.mark.parametrize("dtype", np_dtypes)
 @pytest.mark.parametrize("num_charges", [1, 2, 3])
-def test_max_truncation_error(dtype, num_charges):
-  np.random.seed(10)
+@pytest.mark.parametrize("seed", np.arange(20))
+def test_max_truncation_error(dtype, num_charges, seed):
+  np.random.seed(seed)
   R = 2
   D = 30
   charges = [