update speed up doc (#4281)

docs/en_US/Compression/ModelSpeedup.rst

@@ -198,3 +198,11 @@ The latency is measured on one V100 GPU and the input tensor is  ``torch.randn(1
 
 
 .. image:: ../../img/SA_latency_accuracy.png
+
+
+User configuration for ModelSpeedup
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+**PyTorch**
+
+..  autoclass:: nni.compression.pytorch.ModelSpeedup

nni/compression/pytorch/speedup/compressor.py

@@ -23,11 +23,7 @@ _logger.setLevel(logging.INFO)
 class ModelSpeedup:
     """
     This class is to speedup the model with provided weight mask.
-    """
 
-    def __init__(self, model, dummy_input, masks_file, map_location=None,
-                 batch_dim=0, confidence=8):
-        """
     Parameters
     ----------
     model : pytorch model
@@ -45,6 +41,9 @@ class ModelSpeedup:
     confidence: the confidence coefficient of the sparsity inference. This value is
         actually used as the batchsize of the dummy_input.
     """
+
+    def __init__(self, model, dummy_input, masks_file, map_location=None,
+                 batch_dim=0, confidence=8):
         assert confidence > 1
         # The auto inference will change the values of the parameters in the model
         # so we need make a copy before the mask inference