diff --git a/colossalai/nn/layer/parallel_1d/layers.py b/colossalai/nn/layer/parallel_1d/layers.py
index edfe07697..141d988f6 100644
--- a/colossalai/nn/layer/parallel_1d/layers.py
+++ b/colossalai/nn/layer/parallel_1d/layers.py
@@ -139,6 +139,7 @@ class Classifier1D(ParallelLayer):
         set_parallel_input(False)
         env.vocab_parallel = False
 
+
     def reset_parameters(self, weight_initializer, bias_initializer) -> None:
         fan_in, fan_out = self.in_features, self.num_classes
         if self.has_weight:
@@ -155,8 +156,14 @@ class Classifier1D(ParallelLayer):
     def forward(self, input_: Tensor) -> Tensor:
         # Set up backprop all-reduce.
         if self.parallel_input:
+            assert input_.shape[-1] == self.weight.shape[-1], \
+            'Invalid shapes in Classifier1D forward: input={}, weight={}. Expected last dim of input {}.'.format(
+                input_.shape, self.weight.shape, self.weight.shape[-1])
             input_ = input_
         else:
+            assert divide(input_.shape[-1], gpc.tensor_parallel_size) == self.weight.shape[-1], \
+            'Invalid shapes in Classifier1D forward: input={}, weight={}. Expected last dim of input {}.'.format(
+                input_.shape, self.weight.shape, self.weight.shape[-1] * gpc.tensor_parallel_size)
             input_ = split_forward_gather_backward(input_, ParallelMode.PARALLEL_1D, dim=-1)
 
         output_parallel = F.linear(input_, self.weight)
@@ -235,6 +242,9 @@ class VocabParallelClassifier1D(ParallelLayer):
             set_tensor_parallel_attribute_by_partition(self.bias, num_partition)
 
     def forward(self, input_: Tensor) -> Tensor:
+        assert input_.shape[-1] == self.weight.shape[-1], \
+            'Invalid shapes in VocabParallelClassifier1D forward: input={}, weight={}. Expected last dim of input {}.'.format(
+                input_.shape, self.weight.shape, self.weight.shape[-1])
         # Set up backprop all-reduce.
         input_parallel = reduce_grad(input_, ParallelMode.PARALLEL_1D)
         # Matrix multiply.
@@ -305,6 +315,7 @@ class Linear1D_Col(ParallelLayer):
         is_parallel_output = not self.gather_output
         set_parallel_input(is_parallel_output)
 
+
     def reset_parameters(self, weight_initializer, bias_initializer) -> None:
         fan_in, fan_out = self.in_features, self.out_features
         weight_initializer(self.weight, fan_in=fan_in, fan_out=fan_out)
@@ -318,6 +329,9 @@ class Linear1D_Col(ParallelLayer):
             set_tensor_parallel_attribute_by_partition(self.bias, num_partition)
 
     def forward(self, input_: Tensor) -> Tuple[Tensor, Tensor]:
+        assert input_.shape[-1] == self.weight.shape[-1], \
+            'Invalid shapes in Linear1D_Col forward: input={}, weight={}. Expected last dim of input {}.'.format(
+                input_.shape, self.weight.shape, self.weight.shape[-1])
         # Set up backprop all-reduce.
         input_parallel = reduce_grad(input_, ParallelMode.PARALLEL_1D)
         # Matrix multiply.
@@ -329,6 +343,7 @@ class Linear1D_Col(ParallelLayer):
             output = gather_forward_split_backward(output_parallel, ParallelMode.PARALLEL_1D, dim=-1)
         else:
             output = output_parallel
+
         if self.skip_bias_add:
             return output, self.bias
         else:
@@ -393,6 +408,7 @@ class Linear1D_Row(ParallelLayer):
         self._set_tensor_parallel_attributes()
         set_parallel_input(False)
 
+
     def reset_parameters(self, weight_initializer, bias_initializer) -> None:
         fan_in, fan_out = self.in_features, self.out_features
         weight_initializer(self.weight, fan_in=fan_in, fan_out=fan_out)
@@ -407,8 +423,14 @@ class Linear1D_Row(ParallelLayer):
     def forward(self, input_: Tensor) -> Tensor:
         # Set up backprop all-reduce.
         if self.parallel_input:
+            assert input_.shape[-1] == self.weight.shape[-1], \
+            'Invalid shapes in Linear1D_Row forward: input={}, weight={}. Expected last dim of input {}.'.format(
+                input_.shape, self.weight.shape, self.weight.shape[-1])
             input_ = input_
         else:
+            assert divide(input_.shape[-1], gpc.tensor_parallel_size) == self.weight.shape[-1], \
+            'Invalid shapes in Linear1D_Row forward: input={}, weight={}. Expected last dim of input {}.'.format(
+                input_.shape, self.weight.shape, self.weight.shape[-1] * gpc.tensor_parallel_size)
             input_ = split_forward_gather_backward(input_, ParallelMode.PARALLEL_1D, dim=-1)
 
         output_parallel = F.linear(input_, self.weight)