Merge pull request #645 from nouiz/on_unused_input

NEWS.txt

@@ -42,6 +42,8 @@ Interface changes
    instance, function([x, y], [y]). You can use the kwarg
    ``on_unused_input={'raise', 'warn', 'ignore'}`` to control this.
    (Pascal L.)
+ * New Theano flag "on_unused_input" that define the default value of the
+   previous point. (Frederic B.)
  * tensor.alloc() now raises an error during graph build time
    when we try to create less dimensions than the number of dimensions
    the provided value have. In the past, the error was at run time.

theano/compile/debugmode.py

@@ -2065,7 +2065,7 @@ class _Maker(FunctionMaker):  # inheritance buys a few helper functions
             accept_inplace = False,
             function_builder = Function,
             profile=None,
-            on_unused_input='raise'):
+            on_unused_input=None):
         """
         :type inputs: a list of SymbolicInput instances
 

theano/compile/function.py

@@ -14,7 +14,7 @@ from numpy import any #for to work in python 2.4
 def function(inputs, outputs=None, mode=None, updates=None, givens=None,
              no_default_updates=False, accept_inplace=False, name=None,
              rebuild_strict=True, allow_input_downcast=None, profile=None,
-             on_unused_input='raise'):
+             on_unused_input=None):
     """
     Return a callable object that will calculate `outputs` from `inputs`.
 
@@ -70,7 +70,7 @@ def function(inputs, outputs=None, mode=None, updates=None, givens=None,
     used.  This profiling object will be available via self.profile.
 
     :param on_unused_input: What to do if a variable in the 'inputs' list is
-    not used in the graph. Possible values are 'raise', 'warn', and 'ignore'.
+    not used in the graph. Possible values are 'raise', 'warn', 'ignore' and None.
 
     :note: Regarding givens: Be careful to make sure that these substitutions are
     independent--behaviour when Var1 of one pair appears in the graph leading to Var2 in

theano/compile/function_module.py

@@ -965,7 +965,7 @@ class FunctionMaker(object):
 
     def __init__(self, inputs, outputs,
             mode = None, accept_inplace = False, function_builder = Function,
-            profile=None, on_unused_input='raise'):
+            profile=None, on_unused_input=None):
         """
         :type inputs: a list of SymbolicInput instances
 
@@ -982,9 +982,10 @@ class FunctionMaker(object):
 
         :param on_unused_input: What to do if a variable in the 'inputs' list
             is not used in the graph. Possible values are:
-                - 'raise' (default): raise an error
+                - 'raise': raise an error
                 - 'warn': log a warning
                 - 'ignore': do not do anything
+                - None: Use the value in the Theano flags on_unused_input
         """
         mode = mode_module.get_mode(mode)
 
@@ -1090,6 +1091,9 @@ class FunctionMaker(object):
                     for i in self.inputs]
 
     def _check_unused_inputs(self, inputs, outputs, on_unused_input):
+        if on_unused_input is None:
+            on_unused_input = theano.config.on_unused_input
+
         if on_unused_input == 'ignore':
             return
 
@@ -1256,7 +1260,7 @@ def register_checker(checker):
 
 
 def orig_function(inputs, outputs, mode=None, accept_inplace=False,
-                  name=None, profile=None, on_unused_input='raise'):
+                  name=None, profile=None, on_unused_input=None):
     """
     Return a Function that will calculate the outputs from the inputs.
 
@@ -1290,7 +1294,8 @@ def orig_function(inputs, outputs, mode=None, accept_inplace=False,
     :param profile: None or ProfileStats instance
 
     :param on_unused_input: What to do if a variable in the 'inputs' list is
-        not used in the graph. Possible values are 'raise', 'warn', and 'ignore'.
+        not used in the graph. Possible values are 'raise', 'warn', 'ignore'
+        and None
     """
 
     # Every element of the input list will be upgraded to an `In` instance if

theano/compile/pfunc.py

@@ -325,7 +325,7 @@ class Param(object):
 def pfunc(params, outputs=None, mode=None, updates=None, givens=None,
         no_default_updates=False, accept_inplace=False, name=None,
         rebuild_strict=True, allow_input_downcast=None,
-        profile=None, on_unused_input='raise'):
+        profile=None, on_unused_input=None):
     """Function-constructor for graphs with shared variables.
 
     :type params: list of either Variable or Param instances.
@@ -375,8 +375,8 @@ def pfunc(params, outputs=None, mode=None, updates=None, givens=None,
 
     :type on_unused_input: str
     :param on_unused_input: What to do if a variable in the 'inputs' list
-        is not used in the graph. Possible values are 'raise', 'warn', and
-        'ignore.
+        is not used in the graph. Possible values are 'raise', 'warn',
+        'ignore' and None.
 
 
     :rtype: theano.compile.Function

theano/configdefaults.py

@@ -159,6 +159,11 @@ AddConfigVar('nocleanup',
         BoolParam(False),
         in_c_key=False)
 
+AddConfigVar('on_unused_input',
+             "What to do if a variable in the 'inputs' list of "
+             " theano.function() is not used in the graph.",
+             EnumStr('raise' 'warn', 'ignore'),
+             in_c_key=False)
 
 # This flag is used when we import Theano to initialize global variables.
 # So changing it after import will not modify these global variables.

theano/tensor/basic.py

@@ -2650,8 +2650,6 @@ def ones_like(model, dtype=None):
     """equivalent of numpy.ones_like"""
     if dtype is None:
         dtype = model.type.dtype
-    if model.ndim == 0 and isinstance(model.type, TensorType):
-        return constant(1.0, dtype=dtype)
     ret = fill(model, constant(1.0, dtype=dtype))
     return ret
 
@@ -2661,8 +2659,6 @@ def zeros_like(model, dtype=None):
     """equivalent of numpy.zeros_like"""
     if dtype is None:
         dtype = model.type.dtype
-    if model.ndim == 0 and isinstance(model.type, TensorType):
-        return constant(0.0, dtype=dtype)
     return fill(model, constant(0.0, dtype=dtype))
 
 

theano/tensor/opt.py

@@ -1078,6 +1078,25 @@ def local_fill_to_alloc(node):
         return rval
 
 
+@gof.local_optimizer([T.fill])
+def local_useless_fill(node):
+    """fill(s,v) -> v
+
+    This optimization is only needed in FAST_COMPILE to make the code
+    more readable. Normally, it is done by the local_fill_to_alloc
+    opt.
+
+    """
+    if node.op == T.fill:
+        r, v = node.inputs
+        if v.type == node.outputs[0].type:
+            # this is a useless fill, erase it.
+            return [v]
+compile.optdb['canonicalize'].register('local_useless_fill',
+                                       in2out(local_useless_fill),
+                                       1.1, 'fast_compile')
+
+
 @register_specialize
 @register_stabilize
 @register_canonicalize