[test] Fixed shapes to match new `quant_param.json`

test_quant_conv2d.py

@@ -18,9 +18,9 @@ quant_params = {
     'weight_zp': torch.randint(-255, 0, (out_ch,)),
     'weight_zp_shape': (out_ch,1,1,1),
     'input_scale': torch.rand((1,)),
-    'input_scale_shape': (1,),
+    'input_scale_shape': tuple(),
     'input_zp': torch.zeros((1,)),
-    'input_zp_shape': (1,),
+    'input_zp_shape': tuple(),
 }
 
 print(quant_params)

test_quant_linear.py

@@ -9,15 +9,15 @@ in_ch = 64
 
 quant_params = {
     'smoothquant_mul': torch.rand((in_ch,)),
-    'smoothquant_mul_shape': (in_ch,),
+    'smoothquant_mul_shape': (1,in_ch),
     'weight_scale': torch.rand((out_ch,)),
     'weight_scale_shape': (out_ch,1),
     'weight_zp': torch.randint(-255, 0, (out_ch,)),
     'weight_zp_shape': (out_ch,1),
     'input_scale': torch.rand((1,)),
-    'input_scale_shape': (1,),
+    'input_scale_shape': tuple(),
     'input_zp': torch.zeros((1,)),
-    'input_zp_shape': (1,),
+    'input_zp_shape': tuple(),
 }
 
 print(quant_params)