Bump version and change default backend to numpy (#236)

* Bump version and swap backend!

* Fixed tests

* Find and replace mistake

* Updated requirements.txt

* Changed default to numpy

* Changed requirements

examples/fft/fft_test.py

@@ -16,7 +16,7 @@ class FftTest(tf.test.TestCase):
 
   def test_fft(self):
     n = 3
-    net = tensornetwork.TensorNetwork()
+    net = tensornetwork.TensorNetwork("tensorflow")
 
     initial_state = [complex(0)] * (1 << n)
     initial_state[1] = 1j

examples/sat/sat_tensornetwork.py

@@ -79,7 +79,7 @@ def sat_tn(clauses: List[Tuple[int, int, int]]
   for clause in clauses:
     if 0 in clause:
       raise ValueError("0's are not allowed in the clauses.")
-  net = tensornetwork.TensorNetwork()
+  net = tensornetwork.TensorNetwork("tensorflow")
   var_set = set()
   for clause in clauses:
     var_set |= {abs(x) for x in clause}

examples/wavefunctions/wavefunctions.py

@@ -59,7 +59,7 @@ def apply_op(psi, op, n1, pbc=False):
     Returns:
       psi_final: The result of applying `op` to `psi`.
   """
-  net = tensornetwork.TensorNetwork()
+  net = tensornetwork.TensorNetwork("tensorflow")
   n_psi = net.add_node(psi)
   site_edges = n_psi.get_all_edges()
 
@@ -101,7 +101,7 @@ def expval(psi, op, n1, pbc=False):
     Returns:
       expval: The expectation value.
   """
-  net = tensornetwork.TensorNetwork()
+  net = tensornetwork.TensorNetwork("tensorflow")
   n_psi = net.add_node(psi)
   site_edges = n_psi.get_all_edges()
 
@@ -245,7 +245,7 @@ def apply_circuit(psi, layers):
   """
   num_sites = len(psi.shape)
 
-  net = tensornetwork.TensorNetwork()
+  net = tensornetwork.TensorNetwork("tensorflow")
   n_psi = net.add_node(psi)
   site_edges = n_psi.get_all_edges()
   nodes = [n_psi]

experiments/MERA/binary_mera_lib.py

@@ -197,7 +197,7 @@ def two_site_ascending_super_operator(operator, isometry, unitary):
         tf.Tensor
     """
 
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
 
     iso_l = net.add_node(isometry)
     iso_r = net.add_node(isometry)
@@ -244,7 +244,7 @@ def two_site_descending_super_operator(rho, isometry, unitary):
         tf.Tensor
     """
 
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
 
     iso_l = net.add_node(isometry)
     iso_r = net.add_node(isometry)
@@ -291,7 +291,7 @@ def left_ascending_super_operator(hamiltonian, isometry, unitary):
         tf.Tensor
     """
 
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
 
     iso_l = net.add_node(isometry)
     iso_c = net.add_node(isometry)
@@ -367,7 +367,7 @@ def right_ascending_super_operator(hamiltonian, isometry, unitary):
         tf.Tensor
     """
 
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
 
     iso_l = net.add_node(isometry)
     iso_c = net.add_node(isometry)
@@ -444,7 +444,7 @@ def left_descending_super_operator(reduced_density, isometry, unitary):
         tf.Tensor
     """
 
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
 
     iso_l = net.add_node(isometry)
     iso_c = net.add_node(isometry)
@@ -523,7 +523,7 @@ def right_descending_super_operator(reduced_density, isometry, unitary):
         tf.Tensor
     """
 
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
 
     iso_l = net.add_node(isometry)
     iso_c = net.add_node(isometry)
@@ -610,7 +610,7 @@ def descending_super_operator(rho, isometry, unitary):
 
 @tf.contrib.eager.defun(autograph=False)
 def get_env_disentangler_1(hamiltonian, reduced_density, isometry, unitary):
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
 
     iso_l = net.add_node(isometry)
     iso_c = net.add_node(isometry)
@@ -677,7 +677,7 @@ def get_env_disentangler_1(hamiltonian, reduced_density, isometry, unitary):
 
 @tf.contrib.eager.defun(autograph=False)
 def get_env_disentangler_2(hamiltonian, reduced_density, isometry, unitary):
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
 
     iso_l = net.add_node(isometry)
     iso_c = net.add_node(isometry)
@@ -743,7 +743,7 @@ def get_env_disentangler_2(hamiltonian, reduced_density, isometry, unitary):
 
 @tf.contrib.eager.defun(autograph=False)
 def get_env_disentangler_3(hamiltonian, reduced_density, isometry, unitary):
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
 
     iso_l = net.add_node(isometry)
     iso_c = net.add_node(isometry)
@@ -809,7 +809,7 @@ def get_env_disentangler_3(hamiltonian, reduced_density, isometry, unitary):
 
 @tf.contrib.eager.defun(autograph=False)
 def get_env_disentangler_4(hamiltonian, reduced_density, isometry, unitary):
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
 
     iso_l = net.add_node(isometry)
     iso_c = net.add_node(isometry)
@@ -897,7 +897,7 @@ def get_env_disentangler(ham, rho, isometry, unitary):
 @tf.contrib.eager.defun(autograph=False)
 def get_env_isometry_1(hamiltonian, reduced_density, isometry, unitary):
 
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
 
     iso_c = net.add_node(isometry)
     iso_r = net.add_node(isometry)
@@ -964,7 +964,7 @@ def get_env_isometry_1(hamiltonian, reduced_density, isometry, unitary):
 @tf.contrib.eager.defun(autograph=False)
 def get_env_isometry_2(hamiltonian, reduced_density, isometry, unitary):
 
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
 
     iso_c = net.add_node(isometry)
     iso_r = net.add_node(isometry)
@@ -1033,7 +1033,7 @@ def get_env_isometry_2(hamiltonian, reduced_density, isometry, unitary):
 @tf.contrib.eager.defun(autograph=False)
 def get_env_isometry_3(hamiltonian, reduced_density, isometry, unitary):
 
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
 
     iso_l = net.add_node(isometry)
     iso_r = net.add_node(isometry)
@@ -1099,7 +1099,7 @@ def get_env_isometry_3(hamiltonian, reduced_density, isometry, unitary):
 @tf.contrib.eager.defun(autograph=False)
 def get_env_isometry_4(hamiltonian, reduced_density, isometry, unitary):
 
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
 
     iso_l = net.add_node(isometry)
     iso_r = net.add_node(isometry)
@@ -1167,7 +1167,7 @@ def get_env_isometry_4(hamiltonian, reduced_density, isometry, unitary):
 @tf.contrib.eager.defun(autograph=False)
 def get_env_isometry_5(hamiltonian, reduced_density, isometry, unitary):
 
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
 
     iso_l = net.add_node(isometry)
     iso_c = net.add_node(isometry)
@@ -1236,7 +1236,7 @@ def get_env_isometry_5(hamiltonian, reduced_density, isometry, unitary):
 @tf.contrib.eager.defun(autograph=False)
 def get_env_isometry_6(hamiltonian, reduced_density, isometry, unitary):
 
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
 
     iso_l = net.add_node(isometry)
     iso_c = net.add_node(isometry)
@@ -1561,23 +1561,23 @@ def initialize_TFI_hams(dtype=tf.float64):
     sZ = np.array([[1, 0], [0, -1]]).astype(dtype.as_numpy_dtype)
     eye = np.eye(2).astype(dtype.as_numpy_dtype)
 
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
     X1 = net.add_node(sX)
     X2 = net.add_node(sX)
     I3 = net.add_node(eye)
     out_order = [X1[0], X2[0], I3[0], X1[1], X2[1], I3[1]]
     t1 = net.outer_product(net.outer_product(X1, X2), I3)
     t1 = t1.reorder_edges(out_order).get_tensor()
 
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
     Z1 = net.add_node(sZ)
     I2 = net.add_node(eye)
     I3 = net.add_node(eye)
     out_order = [Z1[0], I2[0], I3[0], Z1[1], I2[1], I3[1]]
     t2 = net.outer_product(net.outer_product(Z1, I2), I3)
     t2 = t2.reorder_edges(out_order).get_tensor() / 2
 
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
     I1 = net.add_node(eye)
     Z2 = net.add_node(sZ)
     I3 = net.add_node(eye)
@@ -1676,7 +1676,7 @@ def optimize_binary_mera(ham_0,
         if verbose > 0:
             if np.mod(k, 10) == 1:
                 Z = misc_mera.trace(rho[0])
-                net = tn.TensorNetwork()
+                net = tn.TensorNetwork("tensorflow")
                 r = net.add_node(rho[0])
                 h = net.add_node(ham[0])
                 edges = [net.connect(r[n], h[n]) for n in range(6)]

experiments/MERA/binary_mera_test.py

@@ -22,6 +22,7 @@
 import experiments.MERA.misc_mera as misc_mera
 import pytest
 import copy
+tn.set_default_backend("tensorflow")
 tf.enable_v2_behavior()
 
 @pytest.mark.parametrize("chi", [4, 6])

experiments/MERA/misc_mera.py

@@ -27,7 +27,7 @@ def trace(rho):
     compute the trace of `rho`
     """
     dim = len(rho.shape) // 2
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
     r = net.add_node(rho)
 
     edges = [net.connect(r[n], r[n + dim]) for n in range(dim)]
@@ -63,7 +63,7 @@ def scalar_product(bottom, top):
         tf.Tensor:  the inner product
     """
 
-    net = tn.TensorNetwork()
+    net = tn.TensorNetwork("tensorflow")
     b = net.add_node(tf.conj(bottom))
     t = net.add_node(top)
     edges = [net.connect(b[n], t[n]) for n in range(len(bottom.shape))]

experiments/MPS/misc_mps.py

@@ -23,7 +23,9 @@
 import functools as fct
 import tensornetwork as tn
 from scipy.sparse.linalg import LinearOperator, lgmres, eigs
-ncon_defuned = tf.contrib.eager.defun(ncon_tn, autograph=False)
+import functools
+tf_ncon = functools.partial(ncon_tn, backend="tensorflow")
+ncon_defuned = tf.contrib.eager.defun(tf_ncon, autograph=False)
 
 
 def transfer_op(As, Bs, direction, x):
@@ -420,7 +422,7 @@ def prepare_tensor_SVD(tensor, direction, D=None, thresh=1E-32, normalize=False)
     assert (direction != 0), 'do NOT use direction=0!'
     [l1, l2, d] = tensor.shape
     if direction in (1, 'l', 'left'):
-        net = tn.TensorNetwork()
+        net = tn.TensorNetwork("tensorflow")
         node = net.add_node(tensor)
         u_node, s_node, v_node, _ = net.split_node_full_svd(node, [node[0], node[1]], [node[2]], max_singular_values=D, max_truncation_err=thresh)
         Z = tf.linalg.norm(s_node.tensor)
@@ -429,7 +431,7 @@ def prepare_tensor_SVD(tensor, direction, D=None, thresh=1E-32, normalize=False)
         return u_node.tensor, s_node.tensor, v_node.tensor, Z
 
     if direction in (-1, 'r', 'right'):
-        net = tn.TensorNetwork()
+        net = tn.TensorNetwork("tensorflow")
         node = net.add_node(tensor)
         u_node, s_node, v_node, _ = net.split_node_full_svd(node, [node[0]], [node[1], node[2]], max_singular_values=D, max_truncation_err=thresh)
         Z = tf.linalg.norm(s_node.tensor)
@@ -471,7 +473,7 @@ def apply_2site_schmidt_canonical(op,
   L0_i = tf.matrix_inverse(L0)
   L2_i = tf.matrix_inverse(L2)
 
-  net = tn.TensorNetwork()
+  net = tn.TensorNetwork("tensorflow")
   nL0_i = net.add_node(L0_i, axis_names=["L", "R"])
   nL0 = net.add_node(L0, axis_names=["L", "R"])
   nG1 = net.add_node(G1, axis_names=["L", "p", "R"])
@@ -545,7 +547,7 @@ def apply_2site_generic(op, A1, A2, max_bond_dim=None, auto_trunc_max_err=0.0):
         op_shp[3],
         message="Operator dimensions do not match MPS physical dimensions.")
 
-  net = tn.TensorNetwork()
+  net = tn.TensorNetwork("tensorflow")
   nA1 = net.add_node(A1, axis_names=["L", "p", "R"])
   nA2 = net.add_node(A2, axis_names=["L", "p", "R"])
   nop = net.add_node(op, axis_names=["p_out_1", "p_out_2", "p_in_1", "p_in_2"])

experiments/MPS_classifier/classifier.py

@@ -112,7 +112,7 @@ def create_network(self, data: tf.Tensor, data0: tf.Tensor
       var_nodes: List of the two MPS nodes.
       data_nodes: Tuple of the two data nodes.
     """
-    net = batchtensornetwork.BatchTensorNetwork()
+    net = batchtensornetwork.BatchTensorNetwork("tensorflow")
 
     # Connect the bond edges of the MPS tensors
     var_nodes = [net.add_node(self.vector), net.add_node(self.matrices)]

requirements.txt

@@ -1,5 +1,4 @@
 numpy>=1.16
-tensorflow>=1.13
 graphviz>=0.11.1
 opt_einsum>=2.3.0
-h5py>=2.9.0
+h5py>=2.9.0

requirements_travis.txt

@@ -1,5 +1,6 @@
-jax>=0.1.0
-jaxlib>=0.1.27
+tensorflow>=1.13
 pytype>=2019.06.21
 pytest
 torch>=1.1
+jax>=0.1.0
+jaxlib>=0.1.27

tensornetwork/config.py

@@ -12,5 +12,5 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-default_backend = "tensorflow"
+default_backend = "numpy"
 default_dtype = None

tensornetwork/version.py

@@ -12,4 +12,4 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-__version__ = '0.0.7'
+__version__ = '0.1.0'