Merge pull request #192 from Zhaoyilunnn/main

fix: make the parameter shift example compatible with latest tq

examples/param_shift_onchip_training/param_shift.py

@@ -29,7 +29,7 @@
 
 import torchquantum as tq
 import torchquantum.functional as tqf
-from torchquantum.layer import SethLayer0
+from torchquantum.layer.layers import SethLayer0
 
 from torchquantum.dataset import MNIST
 from torch.optim.lr_scheduler import CosineAnnealingLR
@@ -39,7 +39,6 @@ class QFCModel(tq.QuantumModule):
     def __init__(self):
         super().__init__()
         self.n_wires = 4
-        self.q_device = tq.QuantumDevice(n_wires=self.n_wires)
         self.encoder = tq.GeneralEncoder(tq.encoder_op_list_name_dict["4x4_ryzxy"])
 
         self.arch = {"n_wires": self.n_wires, "n_blocks": 2, "n_layers_per_block": 2}
@@ -49,16 +48,17 @@ def __init__(self):
 
     def forward(self, x, use_qiskit=False):
         bsz = x.shape[0]
+        q_device = tq.QuantumDevice(n_wires=self.n_wires, bsz=bsz)
         x = F.avg_pool2d(x, 6).view(bsz, 16)
 
         if use_qiskit:
             x = self.qiskit_processor.process_parameterized(
-                self.q_device, self.encoder, self.q_layer, self.measure, x
+                q_device, self.encoder, self.q_layer, self.measure, x
             )
         else:
-            self.encoder(self.q_device, x)
-            self.q_layer(self.q_device)
-            x = self.measure(self.q_device)
+            self.encoder(q_device, x)
+            self.q_layer(q_device)
+            x = self.measure(q_device)
 
         x = x.reshape(bsz, 4)