Merge branch 'cuQuantum_cuTensorNet' of https://github.com/qiboteam/qibotn into cuQuantum_cuTensorNet

src/qibotn/__main__.py

@@ -1,11 +1,6 @@
 import argparse
-from timeit import default_timer as timer
 
-from qibotn import quimb as qiboquimb
+import qibotn.quimb
-from QiboCircuitConvertor import QiboCircuitToEinsum
-from cuquantum import contract
-import cupy as cp
-from qibo.models import QFT
 
 
 def parser():
@@ -18,65 +13,8 @@ def parser():
 
 def main(args: argparse.Namespace):
     print("Testing for %d nqubits" % (args.nqubits))
-    qiboquimb.eval(args.nqubits, args.qasm_circ, args.init_state)
+    qibotn.quimb.eval(args.nqubits, args.qasm_circ, args.init_state)
-
-
-def parser_cuquantum():
-    parser = argparse.ArgumentParser()
-
-    parser.add_argument(
-        "--nqubits", default=10, type=int, help="Number of quibits in the circuits."
-    )
-
-    parser.add_argument(
-        "--circuit",
-        default="qft",
-        type=str,
-        help="Type of circuit to use. See README for the list of "
-        "available circuits.",
-    )
-
-    parser.add_argument(
-        "--precision",
-        default="complex128",
-        type=str,
-        help="Numerical precision of the simulation. "
-        "Choose between 'complex128' and 'complex64'.",
-    )
-
-    return parser.parse_args()
-
-
-def run_bench(task, label):
-    start = timer()
-    result = task()
-    end = timer()
-    circuit_eval_time = end - start
-    print(f"Simulation time: {label} = {circuit_eval_time}s")
-
-    return result
-
-
-def main_cuquantum(args: argparse.Namespace):
-    print("Testing for %d nqubits" % (args.nqubits))
-    nqubits = args.nqubits
-    circuit_name = args.circuit
-    datatype = args.precision
-
-    if circuit_name in ("qft", "QFT"):
-        circuit = QFT(nqubits)
-    else:
-        raise NotImplementedError(f"Cannot find circuit {circuit_name}.")
-
-    myconvertor = QiboCircuitToEinsum(circuit, dtype=datatype)
-    operands_expression = myconvertor.state_vector()
-
-    result_qibo = run_bench(circuit, "Qibo")
-    sv_cutn = run_bench(lambda: contract(*operands_expression), "cuQuantum cuTensorNet")
-
-    # print(f"is sv in agreement?", cp.allclose(sv_cutn.flatten(), result_qibo.state(numpy=True)))
-    assert cp.allclose(sv_cutn.flatten(), result_qibo.state(numpy=True))
 
 
 if __name__ == "__main__":
-    main_cuquantum(parser_cuquantum())
+    main(parser())

src/qibotn/cutn.py

@@ -1,10 +1,10 @@
 # from qibotn import quimb as qiboquimb
-from QiboCircuitConvertor import QiboCircuitToEinsum
+from qibotn.QiboCircuitConvertor import QiboCircuitToEinsum
 from cuquantum import contract
 
 
-def eval(qibo_circ,datatype):
+def eval(qibo_circ, datatype):
     myconvertor = QiboCircuitToEinsum(qibo_circ, dtype=datatype)
     operands_expression = myconvertor.state_vector()
     results = contract(*operands_expression)
-    return results.flatten()
+    return results

tests/test_cuquantum_cutensor_backend.py

@@ -1,5 +1,3 @@
-import copy
-import os
 from timeit import default_timer as timer
 
 import config
@@ -22,18 +20,29 @@ def time(func):
     time = end - start
     return time, res
 
+
 @pytest.mark.gpu
 @pytest.mark.parametrize("nqubits", [1, 2, 5, 10])
-def test_eval(nqubits: int):
+def test_eval(nqubits: int, dtype="complex128"):
+    """Evaluate QASM with cuQuantum.
+
+    Args:
+        nqubits (int): Total number of qubits in the system.
+        dtype (str): The data type for precision, 'complex64' for single,
+            'complex128' for double.
+    """
     import qibotn.cutn
 
     # Test qibo
-    qibo.set_backend(backend=config.qibo.backend, platform=config.qibo.platform)
+    qibo.set_backend(backend=config.qibo.backend,
-    qibo_time, (qibo_circ, result_sv) = time(lambda: qibo_qft(nqubits, swaps=True))
+                     platform=config.qibo.platform)
+    qibo_time, (qibo_circ, result_sv) = time(
+        lambda: qibo_qft(nqubits, swaps=True))
 
     # Test Cuquantum
-    data_type = "complex128"
+    cutn_time, result_tn = time(
-    cutn_time, result_tn = time(lambda: qibotn.cutn.eval(qibo_circ,data_type))
+        lambda: qibotn.cutn.eval(qibo_circ, dtype).flatten())
 
     assert 1e-2 * qibo_time < cutn_time < 1e2 * qibo_time
-    assert np.allclose(result_sv, result_tn), "Resulting dense vectors do not match"
+    assert np.allclose(
+        result_sv, result_tn), "Resulting dense vectors do not match"