update arg name to align with default.tensor

pennylane_lightning/lightning_tensor/_tensornet.py

@@ -51,7 +51,7 @@ def __init__(
         self,
         num_wires,
         method: str = "mps",
-        dtype=np.complex128,
+        c_dtype=np.complex128,
         max_bond_dim: int = 128,
         cutoff: float = 0,
         cutoff_mode: str = "abs",
@@ -62,7 +62,7 @@ def __init__(
         self._method = method
         self._cutoff = cutoff
         self._cutoff_mode = cutoff_mode
-        self._dtype = dtype
+        self._c_dtype = c_dtype
 
         if device_name != "lightning.tensor":
             raise DeviceError(f'The device name "{device_name}" is not a valid option.')
@@ -73,7 +73,7 @@ def __init__(
     @property
     def dtype(self):
         """Returns the tensor network data type."""
-        return self._dtype
+        return self._c_dtype
 
     @property
     def device_name(self):

pennylane_lightning/lightning_tensor/lightning_tensor.py

@@ -192,7 +192,7 @@ class LightningTensor(Device):
             Defaults to ``None`` if not specified.
         method (str): Supported method. Currently, only ``mps`` is supported.
         c_dtype: Datatypes for the tensor representation. Must be one of
-            ``np.complex64`` or ``np.complex128``. Default is ``np.complex128``.
+            ``numpy.complex64`` or ``numpy.complex128``. Default is ``numpy.complex128``.
     Keyword Args:
         max_bond_dim (int): The maximum bond dimension to be used in the MPS simulation. Default is 128.
             The accuracy of the wavefunction representation comes with a memory tradeoff which can be

tests/lightning_tensor/test_measurements_class.py

@@ -40,7 +40,7 @@
 )
 def lightning_tn(request):
     """Fixture for creating a LightningTensorNet object."""
-    return LightningTensorNet(num_wires=5, max_bond_dim=128, dtype=request.param)
+    return LightningTensorNet(num_wires=5, max_bond_dim=128, c_dtype=request.param)
 
 
 class TestMeasurementFunction:

tests/lightning_tensor/test_tensornet_class.py

@@ -39,7 +39,7 @@
 @pytest.mark.parametrize("device_name", ["lightning.tensor"])
 def test_device_name_and_init(num_wires, bondDims, dtype, device_name):
     """Test the class initialization and returned properties."""
-    tensornet = LightningTensorNet(num_wires, bondDims, dtype=dtype, device_name=device_name)
+    tensornet = LightningTensorNet(num_wires, bondDims, c_dtype=dtype, device_name=device_name)
     assert tensornet.dtype == dtype
     assert tensornet.device_name == device_name
     assert tensornet.num_wires == num_wires