Merge pull request #1188 from goodfeli/doc

Document DBM stuff
lisa-lab · Oct 21, 2014 · 3be2a6d · 3be2a6d
2 parents da31911 + 34dae86
commit 3be2a6d
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Showing 5 changed files with 599 additions and 446 deletions.
diff --git a/pylearn2/devtools/nan_guard.py b/pylearn2/devtools/nan_guard.py
@@ -105,4 +105,4 @@ def nan_check(i, node, fn):
                 do_check_on(x, node, fn, False)
 
         wrap_linker = theano.gof.WrapLinkerMany([theano.gof.OpWiseCLinker()], [nan_check])
-        super(NanGuardMode, self).__init__(wrap_linker, optimizer='fast_run')
+        super(NanGuardMode, self).__init__(wrap_linker, optimizer=theano.config.optimizer)
diff --git a/pylearn2/devtools/tests/test_format.py b/pylearn2/devtools/tests/test_format.py
@@ -24,7 +24,6 @@
     "models/dbm/layer.py",
     "models/dbm/__init__.py",
     "models/dbm/ising.py",
-    "models/dbm/inference_procedure.py",
     "models/differentiable_sparse_coding.py",
     "models/local_coordinate_coding.py",
     "models/mnd.py",
@@ -319,7 +318,6 @@
     'models/dbm/__init__.py',
     'models/dbm/dbm.py',
     'models/dbm/ising.py',
-    'models/dbm/inference_procedure.py',
     'models/differentiable_sparse_coding.py',
     'models/local_coordinate_coding.py',
     'models/maxout.py',

diff --git a/pylearn2/expr/nnet.py b/pylearn2/expr/nnet.py
@@ -75,9 +75,9 @@ def inverse_sigmoid_numpy(x):
 
 def arg_of_softmax(Y_hat):
     """
-    .. todo::
-
-        WRITEME properly
+    Given the output of a call to theano.tensor.nnet.softmax,
+    returns the argument to the softmax (by tracing the Theano
+    graph).
 
     Parameters
     ----------
@@ -138,7 +138,7 @@ def kl(Y, Y_hat, batch_axis):
     ave : Variable
         average kl divergence between Y and Y_hat.
     """
-    
+
     assert hasattr(Y_hat, 'owner')
     assert batch_axis is not None
 
@@ -150,12 +150,12 @@ def kl(Y, Y_hat, batch_axis):
         raise ValueError("Expected Y_hat to be generated by an Elemwise "
                          "op, got "+str(op)+" of type "+str(type(op)))
     assert isinstance(op.scalar_op, T.nnet.sigm.ScalarSigmoid)
-    
+
     for Yv in get_debug_values(Y):
         if not (Yv.min() >= 0.0 and Yv.max() <= 1.0):
             raise ValueError("Expected Y to be between 0 and 1. Either Y"
                              + "< 0 or Y > 1 was found in the input.")
-    
+
     z, = owner.inputs
 
     term_1 = Y * T.nnet.softplus(-z)
@@ -207,12 +207,12 @@ def elemwise_kl(Y, Y_hat):
         raise ValueError("Expected Y_hat to be generated by an Elemwise "
                          "op, got "+str(op)+" of type "+str(type(op)))
     assert isinstance(op.scalar_op, T.nnet.sigm.ScalarSigmoid)
-    
+
     for Yv in get_debug_values(Y):
         if not (Yv.min() >= 0.0 and Yv.max() <= 1.0):
             raise ValueError("Expected Y to be between 0 and 1. Either Y"
                              + "< 0 or Y > 1 was found in the input.")
-    
+
     z, = owner.inputs
 
     term_1 = Y * T.nnet.softplus(-z)