Added infer_shape to choose function and deleted the out input.

theano/tensor/basic.py

@@ -5095,7 +5095,8 @@ def swapaxes(y, axis1, axis2):
 
 
 def choose(a, choices, out=None, mode='raise'):
-    return Choose(mode)(a, choices, out)
+    assert out is None
+    return Choose(mode)(a, choices)
 
 class Choose(Op):
 
@@ -5111,29 +5112,20 @@ class Choose(Op):
     def props(self):
         return self.mode
 
-    def make_node(self, a, choices, out):
+    def infer_shape(self, nodes, shapes):
+        return [(shapes[0])]
+
+    def make_node(self, a, choices):
         a = as_tensor_variable(a)
         choices = as_tensor_variable(choices)
-        out = theano.gof.Constant(theano.gof.generic, out)
 
-        return Apply(self, [a, choices, out], [a.type()])
+        return Apply(self, [a, choices], [a.type()])
 
     def perform(self, node, inputs, (z, )):
         a = inputs[0]
         choices = inputs[1]
-        out = inputs[2]
-        z[0] = numpy.choose(a, choices, out, self.mode)
+
+        z[0] = numpy.choose(a, choices, mode=self.mode)
 
     def __str__(self):
         return self.__class__.__name__
-
-"""
-import theano
-from theano import tensor as T
-from theano import function
-from theano.tensor import basic
-x = T.vector(dtype='int64')
-y = T.matrix(dtype='int64')
-z = basic.choose(x,y)
-f = function([x, y], z)
-"""
\ No newline at end of file

theano/tensor/tests/test_basic.py

@@ -7029,7 +7029,6 @@ class T_Choose():
             n_c = numpy.choose(A, B, mode=m)
             assert numpy.allclose(t_c, n_c)
 
-
     def wrong_choice_array(self):
 
         a = tensor.matrix(dtype='int64')