change error type

tests/ut/python/nn/test_dynamic_lr.py

@@ -32,7 +32,7 @@ power = 0.5
 class TestInputs:
     def test_milestone1(self):        
         milestone1 = 1
-        with pytest.raises(ValueError):
+        with pytest.raises(TypeError):
             dr.piecewise_constant_lr(milestone1, learning_rates)
 
     def test_milestone2(self):
@@ -46,12 +46,12 @@ class TestInputs:
 
     def test_learning_rates1(self):
         lr = True
-        with pytest.raises(ValueError):
+        with pytest.raises(TypeError):
             dr.piecewise_constant_lr(milestone, lr)
 
     def test_learning_rates2(self):
         lr = [1, 2, 1]
-        with pytest.raises(ValueError):
+        with pytest.raises(TypeError):
             dr.piecewise_constant_lr(milestone, lr)
 
     def test_learning_rate_type(self):
@@ -158,7 +158,7 @@ class TestInputs:
 
     def test_is_stair(self):
         is_stair = 1
-        with pytest.raises(ValueError):
+        with pytest.raises(TypeError):
             dr.exponential_decay_lr(learning_rate, decay_rate, total_step, step_per_epoch, decay_epoch, is_stair)
 
     def test_min_lr_type(self):
@@ -183,12 +183,12 @@ class TestInputs:
 
     def test_power(self):
         power1 = True
-        with pytest.raises(ValueError):
+        with pytest.raises(TypeError):
             dr.polynomial_decay_lr(learning_rate, end_learning_rate, total_step, step_per_epoch, decay_epoch, power1)
 
     def test_update_decay_epoch(self):
         update_decay_epoch = 1
-        with pytest.raises(ValueError):
+        with pytest.raises(TypeError):
             dr.polynomial_decay_lr(learning_rate, end_learning_rate, total_step, step_per_epoch, decay_epoch,
                                    power, update_decay_epoch)
 

tests/ut/python/nn/test_psnr.py

@@ -52,7 +52,7 @@ def test_psnr_max_val_negative():
 
 def test_psnr_max_val_bool():
     max_val = True
-    with pytest.raises(ValueError):
+    with pytest.raises(TypeError):
         net = PSNRNet(max_val)
 
 def test_psnr_max_val_zero():

tests/ut/python/nn/test_ssim.py

@@ -51,7 +51,7 @@ def test_ssim_max_val_negative():
 
 def test_ssim_max_val_bool():
     max_val = True
-    with pytest.raises(ValueError):
+    with pytest.raises(TypeError):
         net = SSIMNet(max_val)
 
 def test_ssim_max_val_zero():

tests/ut/python/ops/test_nn_ops.py

@@ -528,7 +528,7 @@ test_cases_for_verify_exception = [
         'desc_inputs': [0],
     }),
     ('MaxPoolWithArgmax_ValueError_2', {
-        'block': (lambda _: P.MaxPoolWithArgmax(ksize='1'), {'exception': ValueError}),
+        'block': (lambda _: P.MaxPoolWithArgmax(ksize='1'), {'exception': TypeError}),
         'desc_inputs': [0],
     }),
     ('MaxPoolWithArgmax_ValueError_3', {
@@ -560,31 +560,31 @@ test_cases_for_verify_exception = [
         'desc_inputs': [0],
     }),
     ('Softmax_ValueError_1', {
-        'block': (lambda _: P.Softmax("1"), {'exception': ValueError}),
+        'block': (lambda _: P.Softmax("1"), {'exception': TypeError}),
         'desc_inputs': [0],
     }),
     ('Softmax_ValueError_2', {
-        'block': (lambda _: P.Softmax(1.1), {'exception': ValueError}),
+        'block': (lambda _: P.Softmax(1.1), {'exception': TypeError}),
         'desc_inputs': [0],
     }),
     ('Softmax_ValueError_3', {
-        'block': (lambda _: P.Softmax(axis="1"), {'exception': ValueError}),
+        'block': (lambda _: P.Softmax(axis="1"), {'exception': TypeError}),
         'desc_inputs': [0],
     }),
     ('DropoutGenMask_ValueError_1', {
-        'block': (lambda _: P.DropoutGenMask(Seed0="seed0"), {'exception': ValueError}),
+        'block': (lambda _: P.DropoutGenMask(Seed0="seed0"), {'exception': TypeError}),
         'desc_inputs': [0],
     }),
     ('DropoutGenMask_ValueError_2', {
-        'block': (lambda _: P.DropoutGenMask(Seed0=1.0), {'exception': ValueError}),
+        'block': (lambda _: P.DropoutGenMask(Seed0=1.0), {'exception': TypeError}),
         'desc_inputs': [0],
     }),
     ('DropoutGenMask_ValueError_3', {
-        'block': (lambda _: P.DropoutGenMask(Seed1="seed1"), {'exception': ValueError}),
+        'block': (lambda _: P.DropoutGenMask(Seed1="seed1"), {'exception': TypeError}),
         'desc_inputs': [0],
     }),
     ('DropoutGenMask_ValueError_4', {
-        'block': (lambda _: P.DropoutGenMask(Seed1=2.0), {'exception': ValueError}),
+        'block': (lambda _: P.DropoutGenMask(Seed1=2.0), {'exception': TypeError}),
         'desc_inputs': [0],
     }),
     ('MaxPool2d_ValueError_1', {
@@ -594,14 +594,14 @@ test_cases_for_verify_exception = [
     ('MaxPool2d_ValueError_2', {
         'block': (
             lambda _: nn.MaxPool2d(kernel_size=120, stride=True, pad_mode="valid"),
-            {'exception': ValueError},
+            {'exception': TypeError},
         ),
         'desc_inputs': [Tensor(np.random.randn(32, 3, 112, 112).astype(np.float32).transpose(0, 3, 1, 2))],
     }),
     ('MaxPool2d_ValueError_3', {
         'block': (
             lambda _: nn.MaxPool2d(kernel_size=3, stride=True, pad_mode="valid"),
-            {'exception': ValueError},
+            {'exception': TypeError},
         ),
         'desc_inputs': [Tensor(np.random.randn(32, 3, 112, 112).astype(np.float32).transpose(0, 3, 1, 2))],
     }),