merge

compile.py

@@ -45,6 +45,7 @@ def experimental_linker(env, target = None):
     else:
         raise NotImplementedError("Cannot write thunk representation to a file.")
 
+
 # def experimental_linker(env, target = None):
 #     def fetch(op):
 #         try:

core.py

@@ -884,6 +884,19 @@ class exp(elemwise):
         return "z_i = exp(x_i);"
 
 
+## Logarithm ##
+
+class log(elemwise):
+    impl = numpy.log
+    def c_foreach((x_i, ), (z_i, )):
+        return "z_i = log(x_i);"
+
+class log2(elemwise):
+    impl = numpy.log2
+    def c_foreach((x_i, ), (z_i, )):
+        return "z_i = log(x_i);"
+    
+
 ## Element-wise division ##
 
 class div_elemwise(elemwise):
@@ -1109,6 +1122,7 @@ class dot(omega_op):
         return dot(gz, transpose(y)), dot(transpose(x), gz)
     def specs(x, y):
         # todo: handle all tensors!
+        assert x[2][1] == y[2][0]
         shape = (x[2][0], y[2][1])
         return (numpy.ndarray, upcast(x[1], y[1]), shape)
     def c_headers(self):

gof/lib.py

@@ -220,8 +220,8 @@ class PythonOp(Op):
     def _perform(self):
         results = self._impl()
         if self.nout == 1:
-            #self.out.set_value(results)
-            self.outputs[0].data = results
+            self.out.set_value(results)
+#            self.outputs[0].data = results
         else:
             assert self.nout == len(results)
             for result, output in zip(results, self.outputs):

gof/link.py

 
 
 def perform_linker(env, target = None):
+    order = env.toposort()
+    thunks = [op.perform for op in order]
+    def ret():
+        for thunk in thunks:
+            thunk()
+    if not target:
+        return ret
+    else:
+        raise NotImplementedError("Cannot write thunk representation to a file.")
+
+
+def perform_linker_nochecks(env, target = None):
     order = env.toposort()
     thunks = [op._perform for op in order]
     def ret():