Merge pull request #133 from tqchen/master

[MODEL] Allow extra params

python/mxnet/model.py

@@ -420,15 +420,32 @@ class FeedForward(BASE_ESTIMATOR):
     aux_params : dict of str to NDArray, optional
         Model parameter, dict of name to NDArray of net's auxiliary states.
 
+    allow_extra_params : boolean, optional
+        Whether allow extra parameters that are not needed by symbol
+        to be passed by aux_params and arg_params.
+        If this is True, no error will be thrown when aux_params and arg_params
+        contain extra parameters than needed.
+
     **kwargs : dict
         The additional keyword arguments passed to optimizer.
     """
     def __init__(self, symbol, ctx=None,
                  num_round=None, optimizer='sgd', initializer=Xavier(),
                  arg_params=None, aux_params=None,
+                 allow_extra_params=False,
                  **kwargs):
         # check if symbol contain duplicated names.
         _check_arguments(symbol)
+        # rematch parameters to delete useless ones
+        if allow_extra_params:
+            if arg_params:
+                arg_names = set(symbol.list_arguments())
+                arg_params = {k : v for k, v in arg_params.items()
+                              if k in arg_names}
+            if aux_params:
+                aux_names = set(symbol.list_auxiliary_states())
+                aux_params = {k : v for k, v in aux_params.items()
+                              if k in aux_names}
         # basic configuration
         self.symbol = symbol
         if ctx is None:

python/mxnet/symbol.py

@@ -154,6 +154,16 @@ def _compose(self, *args, **kwargs):
             self.handle, name, num_args, keys, args))
 
     def __getitem__(self, index):
+        if isinstance(index, string_types):
+            idx = None
+            for i, name in enumerate(self.list_outputs()):
+                if name == index:
+                    if idx is not None:
+                        raise ValueError('There are multiple outputs with name \"%s\"' % index)
+                    idx = i
+            if idx is None:
+                raise ValueError('Cannot find output that matches name \"%s\"' % index)
+            index = idx
         if not isinstance(index, int):
             raise TypeError('Symbol only support integer index to fetch i-th output')
         handle = SymbolHandle()

tests/python/train/test_mlp.py

@@ -67,6 +67,15 @@ def test_mlp():
     logging.info('final accuracy = %f', acc1)
     assert(acc1 > 0.95)
 
+    # predict internal featuremaps
+    internals = softmax.get_internals()
+    fc2 = internals['fc2_output']
+    mfeat = mx.model.FeedForward(symbol=fc2,
+                                 arg_params=model.arg_params,
+                                 aux_params=model.aux_params,
+                                 allow_extra_params=True)
+    feat = mfeat.predict(val_dataiter)
+    assert feat.shape == (10000, 64)
     # pickle the model
     smodel = pickle.dumps(model)
     model2 = pickle.loads(smodel)
@@ -79,9 +88,6 @@ def test_mlp():
     assert np.sum(np.abs(prob - prob3)) == 0
 
     # save model explicitly
-
-
-
     model.save(prefix, 128)
     model4 = mx.model.FeedForward.load(prefix, 128)
     prob4 = model4.predict(val_dataiter)

tests/python/unittest/test_symbol.py

@@ -39,8 +39,8 @@ def test_symbol_internal():
                               'fc1_weight', 'fc1_bias',
                               'fc2_weight', 'fc2_bias']
     internal =  net1.get_internals()
-    nmap = {x: i for i, x in enumerate(internal.list_outputs())}
-    fc1 = internal[nmap['fc1_output']]
+    print internal.list_outputs()
+    fc1 = internal['fc1_output']
     assert fc1.list_arguments() == oldfc.list_arguments()