title: Pytorch Inferencing form the model is giving me different results every time
body: <p>I have created and trained one very simple network in pytorch as shown below:</p>
  <pre><code>self.task_layers[task][task_layer_key]; TaskLayerManager(
    (taskLayers): ModuleList(
      (0): lc_hidden(
        (dropout_layer): Dropout(p=0.0, inplace=False)
        (layer_norm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
      )
      (1): cnn(
        (cnn_layer): CNN_Text(
          (dropout): Dropout(p=0.1, inplace=False)
          (fc1): Linear(in_features=300, out_features=2, bias=True)
          (convs1): ModuleList(
            (0): Conv2d(1, 300, kernel_size=(5, 768), stride=(1, 1), padding=(4, 0))
          )
        )
      )
    )
  )
  
  Layer descriptions:
  taskLayers.0.linear_weights      torch.Size([13])
  taskLayers.0.layer_norm.weight      torch.Size([768])
  taskLayers.0.layer_norm.bias      torch.Size([768])
  taskLayers.1.cnn_layer.fc1.weight      torch.Size([2, 300])
  taskLayers.1.cnn_layer.fc1.bias      torch.Size([2])
  taskLayers.1.cnn_layer.convs1.0.weight      torch.Size([300, 1, 5, 768])
  taskLayers.1.cnn_layer.convs1.0.bias      torch.Size([300])
  </code></pre>
  <p>It is a binary classification network that take a 3d tensor as input [N,K,768] and gives output [N,2] tensor
  I am not able to figure out &quot;Why at every run it is giving me different results&quot;?
  Please help me with this - I am new to pytorch.
  And let me know if any other information is needed.</p>