Black formate

src/qibotn/cutn.py

@@ -12,50 +12,50 @@ def eval(qibo_circ, datatype):
 
 
 def eval_tn_MPI(qibo_circ, datatype):
-    
     ncpu_threads = multiprocessing.cpu_count() // 2
     n_samples = 8
-    
+
     root = 0
     comm = MPI.COMM_WORLD
     rank = comm.Get_rank()
     device_id = rank % getDeviceCount()
     cp.cuda.Device(device_id).use()
-    
+
     handle = cutn.create()
     cutn.distributed_reset_configuration(handle, *cutn.get_mpi_comm_pointer(comm))
     network_opts = cutn.NetworkOptions(handle=handle, blocking="auto")
 
     myconvertor = QiboCircuitToEinsum(qibo_circ, dtype=datatype)
     operands_interleave = myconvertor.state_vector_operands()
-    
+
     network = cutn.Network(*operands_interleave, options=network_opts)
-    network.contract_path(optimize={'samples': n_samples, 'threads': ncpu_threads}) # Calculate optimal path, returns path and info
+    network.contract_path(
-    
+        optimize={"samples": n_samples, "threads": ncpu_threads}
+    )  # Calculate optimal path, returns path and info
+
     result = network.contract()
-    
+
     cutn.destroy(handle)
-    
+
     if rank == root:
         return result, rank
 
 
 if __name__ == "__main__":
-    
+    from qibo.models import QFT
-    from qibo.models import QFT 
     import cupy as cp
     import numpy as np
-    
+
-    num_qubits  = 10
+    num_qubits = 10
     swaps = True
     circ_qibo = QFT(num_qubits, swaps)
-    
+
-    dtype="complex128"
+    dtype = "complex128"
     sv_mpi, rank = eval_tn_MPI(circ_qibo, dtype)
-    
+
     if rank == 0:
         sv_reference = eval(circ_qibo, dtype)
         state_vec = np.array(circ_qibo())
         print(f"State vector difference: {abs(sv_mpi-sv_reference).max():0.3e}")
         assert cp.allclose(sv_mpi, sv_reference)
-        assert cp.allclose(sv_mpi.flatten(), state_vec)
+        assert cp.allclose(sv_mpi.flatten(), state_vec)