fix error of conv_variational

mindspore/nn/probability/bnn_layers/conv_variational.py

@@ -61,10 +61,10 @@ class _ConvVariational(_Conv):
             raise ValueError('Attr \'pad_mode\' of \'Conv2d\' Op passed '
                              + str(pad_mode) + ', should be one of values in \'valid\', \'same\', \'pad\'.')
 
-        if not isinstance(stride, (int, tuple)):
+        if isinstance(stride, bool) or not isinstance(stride, (int, tuple)):
             raise TypeError('The type of `stride` should be `int` of `tuple`')
 
-        if not isinstance(dilation, (int, tuple)):
+        if isinstance(dilation, bool) or not isinstance(dilation, (int, tuple)):
             raise TypeError('The type of `dilation` should be `int` of `tuple`')
 
         # convolution args
@@ -136,8 +136,8 @@ class _ConvVariational(_Conv):
         return outputs
 
     def extend_repr(self):
-        str_info = 'in_channels={}, out_channels={}, kernel_size={}, weight_mean={}, stride={},  pad_mode={}, ' \
-                    'padding={}, dilation={}, group={}, weight_std={}, has_bias={}'\
+        str_info = 'in_channels={}, out_channels={}, kernel_size={}, stride={},  pad_mode={}, ' \
+                    'padding={}, dilation={}, group={}, weight_mean={}, weight_std={}, has_bias={}'\
             .format(self.in_channels, self.out_channels, self.kernel_size, self.stride, self.pad_mode, self.padding,
                     self.dilation, self.group, self.weight_posterior.mean, self.weight_posterior.untransformed_std,
                     self.has_bias)

tests/st/probability/test_bnn_layer.py

@@ -137,7 +137,7 @@ if __name__ == "__main__":
     epoch = 100
 
     for i in range(epoch):
-        train_loss, train_acc = train_model(train_bnn_network, network, test_set)
+        train_loss, train_acc = train_model(train_bnn_network, network, train_set)
 
         valid_acc = validate_model(network, test_set)
 

tests/st/probability/test_transform_bnn_layer.py

@@ -142,7 +142,7 @@ if __name__ == "__main__":
     epoch = 100
 
     for i in range(epoch):
-        train_loss, train_acc = train_model(train_bnn_network, network, test_set)
+        train_loss, train_acc = train_model(train_bnn_network, network, train_set)
 
         valid_acc = validate_model(network, test_set)
 

tests/st/probability/test_transform_bnn_model.py

@@ -141,7 +141,7 @@ if __name__ == "__main__":
     epoch = 500
 
     for i in range(epoch):
-        train_loss, train_acc = train_model(train_bnn_network, network, test_set)
+        train_loss, train_acc = train_model(train_bnn_network, network, train_set)
 
         valid_acc = validate_model(network, test_set)