Speed up opt. Now constant folding is done in the eq, no need to traverse the…

theano/tensor/basic.py

@@ -3344,7 +3344,7 @@ pprint.assign(pow, printing.OperatorPrinter('**', 1, 'right'))
 ##########################
 
 
-def extract_constant(x, elemwise=True):
+def extract_constant(x, elemwise=True, only_process_constants=False):
     """
     This function is basically a call to tensor.get_scalar_constant_value.
 
@@ -3356,7 +3356,9 @@ def extract_constant(x, elemwise=True):
 
     """
     try:
-        x = get_scalar_constant_value(x, elemwise=elemwise)
+        x = get_scalar_constant_value(x,
+                                      elemwise,
+                                      only_process_constants)
     except NotScalarConstantError:
         pass
     if ((isinstance(x, scal.ScalarVariable) or

theano/tensor/opt.py

@@ -4665,23 +4665,23 @@ def local_useless_elemwise_comparison(node):
     if isinstance(node.op.scalar_op, scalar.LT) and \
        node.inputs[0].owner and \
        isinstance(node.inputs[0].owner.op, Shape_i) and \
-       T.extract_constant(node.inputs[1]) == 0:
+       T.extract_constant(node.inputs[1], only_process_constants=True) == 0:
         return [T.zeros_like(node.inputs[0], dtype=node.outputs[0].dtype)]
     # Elemwise[GE](X.shape[i], 0) -> Elemwise[ones](X)
     if isinstance(node.op.scalar_op, scalar.GE) and \
        node.inputs[0].owner and \
        isinstance(node.inputs[0].owner.op, Shape_i) and \
-       T.extract_constant(node.inputs[1]) == 0:
+       T.extract_constant(node.inputs[1], only_process_constants=True) == 0:
         return [T.ones_like(node.inputs[0], dtype=node.outputs[0].dtype)]
     # Elemwise[maximum](X.shape[i], 0) -> X.shape[i]
     if isinstance(node.op.scalar_op, scalar.Maximum) and \
        node.inputs[0].owner and \
        isinstance(node.inputs[0].owner.op, Shape_i) and \
-       T.extract_constant(node.inputs[1]) == 0:
+       T.extract_constant(node.inputs[1], only_process_constants=True) == 0:
         return [node.inputs[0]]
     # Elemwise[maximum](0, X.shape[i]) -> X.shape[i]
     if isinstance(node.op.scalar_op, scalar.Maximum) and \
-       T.extract_constant(node.inputs[0]) == 0 and \
+       T.extract_constant(node.inputs[0], only_process_constants=True) == 0 and \
        node.inputs[1].owner and \
        isinstance(node.inputs[1].owner.op, Shape_i):
         return [node.inputs[1]]
@@ -4689,11 +4689,11 @@ def local_useless_elemwise_comparison(node):
     if isinstance(node.op.scalar_op, scalar.Minimum) and \
        node.inputs[0].owner and \
        isinstance(node.inputs[0].owner.op, Shape_i) and \
-       T.extract_constant(node.inputs[1]) == 0:
+       T.extract_constant(node.inputs[1], only_process_constants=True) == 0:
         return [T.zeros_like(node.inputs[0], dtype=node.outputs[0].dtype)]
     # Elemwise[minimum](0, X.shape[i]) -> 0
     if isinstance(node.op.scalar_op, scalar.Minimum) and \
-       T.extract_constant(node.inputs[0]) == 0 and \
+       T.extract_constant(node.inputs[0], only_process_constants=True) == 0 and \
        node.inputs[1].owner and \
        isinstance(node.inputs[1].owner.op, Shape_i):
         return [T.zeros_like(node.inputs[1], dtype=node.outputs[0].dtype)]
@@ -4705,7 +4705,7 @@ def local_useless_elemwise_comparison(node):
        isinstance(node.inputs[0].owner.op.scalar_op, scalar.Add) and \
        all([isinstance(var.owner and var.owner.op, Shape_i)
             for var in node.inputs[0].owner.inputs]) and \
-       T.extract_constant(node.inputs[1]) == 0:
+       T.extract_constant(node.inputs[1], only_process_constants=True) == 0:
 
         return [T.zeros_like(node.inputs[0], dtype=node.outputs[0].dtype)]
     # Elemwise[GE](add([anything that is shapes]), 0) -> Elemwise[ones](X)
@@ -4715,7 +4715,7 @@ def local_useless_elemwise_comparison(node):
        isinstance(node.inputs[0].owner.op.scalar_op, scalar.Add) and \
        all([isinstance(var.owner and var.owner.op, Shape_i)
             for var in node.inputs[0].owner.inputs]) and \
-       T.extract_constant(node.inputs[1]) == 0:
+       T.extract_constant(node.inputs[1], only_process_constants=True) == 0:
         return [T.ones_like(node.inputs[0], dtype=node.outputs[0].dtype)]
 
     return