added scalar-creating functions

_test_tensor_opt.py

@@ -48,6 +48,15 @@ class _test_inplace_opt(unittest.TestCase):
         inplace_optimizer.optimize(g)
         assert str(g) == "[Broadcast{Add}(x, y), Broadcast{Mul}{0: 0}(x, y)]"
 
+    def test_inplace_on_second_argument(self):
+        x, y, z = inputs()
+        e0 = x + y
+        e1 = tensor.mul_inplace(x, z)
+        g = Env([x, y], [e0, e1])
+        assert str(g) == "[Broadcast{Add}(x, y), Broadcast{Mul}{0: 0}(x, z)]"
+        inplace_optimizer.optimize(g)
+        assert str(g) == "[Broadcast{Add}{0: 1}(x, y), Broadcast{Mul}{0: 0}(x, z)]"
+
 
 class _test_dimshuffle_lift(unittest.TestCase):
 

compile.py

@@ -133,8 +133,8 @@ class Function:
             self.fn  = linker.make_function(inplace=True,
                                             unpack_single=unpack_single,
                                             profiler=profiler)
-        self.inputs = inputs
-        self.outputs = outputs
+        self.inputs = env.inputs
+        self.outputs = env.outputs
         self.features = features
         self.optimizer = optimizer
         self.linker_cls = linker_cls
@@ -189,3 +189,100 @@ def eval_outputs(outputs,
     return rval
 
 
+
+
+# StateFunction([x, y], [e], (w, w + lr * bla()))
+
+
+
+
+# class _Function:
+
+#     def __init__(self,
+#                  inputs,
+#                  outputs,
+#                  optimizer,
+#                  linker_type = 'py',
+#                  unpack_single = True,
+#                  except_unreachable_input = True,
+#                  disposable_inputs = [],
+#                  borrow_outputs = []):
+
+
+
+
+#         _mark_indestructible(outputs)
+
+#         if len(inputs) != len(set(inputs)):
+#             raise Exception('duplicate inputs')
+#         if len(outputs) != len(set(outputs)):
+#             raise Exception('duplicate outputs')
+
+#         orphans = list(gof.graph.results_and_orphans(inputs, outputs,
+#             except_unreachable_input=except_unreachable_input)[1])
+#         orphan_data = eval_outputs(orphans, unpack_single=False)
+
+#         env = gof.env.Env(inputs, outputs, features + [gof.EquivTool], consistency_check = True)
+
+#         env = env.clone(clone_inputs=True)
+
+#         for d, o in zip(orphan_data, [env.equiv(orphan) for orphan in orphans]):
+#             o.data = d
+
+#         # optimize and link the cloned env
+#         if None is not optimizer:
+#             optimizer(env)
+
+#         linker = linker_cls(env)
+
+#         if keep_locals:# useful flag for debugging!
+#             self.__dict__.update(locals())
+
+#         if profiler is None:
+#             self.fn  = linker.make_function(inplace=True,
+#                                             unpack_single=unpack_single)
+#         else:
+#             self.fn  = linker.make_function(inplace=True,
+#                                             unpack_single=unpack_single,
+#                                             profiler=profiler)
+#         self.inputs = env.inputs
+#         self.outputs = env.outputs
+#         self.features = features
+#         self.optimizer = optimizer
+#         self.linker_cls = linker_cls
+#         self.profiler = profiler
+#         self.unpack_single = unpack_single
+#         self.except_unreachable_input = except_unreachable_input
+#         self.keep_locals = keep_locals
+
+#     def __call__(self, *args):
+#         return self.fn(*args)
+
+#     def __copy__(self):
+#         return Function(self.inputs, self.outputs,
+#                         features = self.features,
+#                         optimizer = self.optimizer,
+#                         linker_cls = self.linker_cls,
+#                         profiler = self.profiler,
+#                         unpack_single = self.unpack_single,
+#                         except_unreachable_input = self.except_unreachable_input,
+#                         keep_locals = self.keep_locals)
+
+
+
+
+
+
+
+
+
+
+
+
+# class StateFunction:
+
+#     def __init__(self, inputs, outputs, *states):
+#         in_states, out_states = zip(*states)
+#         env = 
+
+    

gof/cc.py

@@ -356,7 +356,7 @@ class CLinker(Linker):
         try: self.op_order = env.toposort()
         except AttributeError: self.op_order = [env]
         
-    def code_gen(self, reuse_storage = True):
+    def code_gen(self, do_not_reuse = []): # reuse_storage = True):
         """
         Generates code for a struct that does the computation of the env and
         stores it in the struct_code field of the instance.
@@ -370,7 +370,7 @@ class CLinker(Linker):
         This method caches its computations.
         """
 
-        if getattr(self, 'struct_code', False) and self.reuse_storage == reuse_storage:
+        if getattr(self, 'struct_code', False) and self.do_not_reuse == do_not_reuse:
             return self.struct_code
 
         env = self.env
@@ -424,7 +424,7 @@ class CLinker(Linker):
             elif result in self.temps:
                 # temps don't need to be extracted from Python, so we call c_init rather than c_extract
                 # they do not need to be relayed to Python, so we don't sync
-                if result.c_is_simple() or not reuse_storage:
+                if result.c_is_simple() or result in do_not_reuse:
                     policy = [[get_nothing, get_nothing, get_nothing],
                               [get_c_declare, get_c_init, get_c_cleanup]]
                 else:
@@ -433,7 +433,7 @@ class CLinker(Linker):
                               [get_nothing, get_nothing, get_nothing]]
             elif result in self.outputs:
                 # outputs don't need to be extracted from Python, so we call c_init rather than c_extract
-                if result.c_is_simple() or not reuse_storage:
+                if result.c_is_simple() or result in do_not_reuse:
                     
                     policy = [[get_nothing, get_nothing, get_nothing],
                               [get_c_declare, get_c_init, (get_c_sync, get_c_cleanup)]]
@@ -513,7 +513,7 @@ class CLinker(Linker):
         struct_code %= dict(name = struct_name)
 
         self.struct_code = struct_code
-        self.reuse_storage = reuse_storage
+        self.do_not_reuse = do_not_reuse
         self.struct_name = struct_name
         self.hash = hash
         self.args = args

gof/opt.py

@@ -460,9 +460,7 @@ class PatternDescOptimizer(LocalOptimizer):
 
 class ConstantFinder(Optimizer):
     """
-    Sets as constant every orphan that is not destroyed
-    and sets as indestructible every input that is not
-    destroyed.
+    Sets as constant every orphan that is not destroyed.
     """
     
     def apply(self, env):
@@ -471,15 +469,15 @@ class ConstantFinder(Optimizer):
                 if not env.destroyers(r):
                     r.indestructible = True
                     r.constant = True
-            for r in env.inputs:
-                if not env.destroyers(r):
-                    r.indestructible = True
+#             for r in env.inputs:
+#                 if not env.destroyers(r):
+#                     r.indestructible = True
         else:
             for r in env.orphans():
                 r.indestructible = True
                 r.constant = True
-            for r in env.inputs:
-                r.indestructible = True
+#             for r in env.inputs:
+#                 r.indestructible = True
 
 import graph
 class MergeOptimizer(Optimizer):

scalar.py

@@ -3,7 +3,8 @@ import numpy
 import math
 
 from copy import copy
-import inspect
+
+from functools import partial
 
 import gof
 from gof import Result, GuardedOp, Env, utils
@@ -184,6 +185,28 @@ class Scalar(Result):
     def __rpow__(self,other): return pow(other,self)
 
 
+# Easy constructors
+
+def _multi(*fns):
+    def f2(f, names):
+        if len(names) == 1:
+            return f(names)
+        else:
+            return [f(name) for name in names]
+    if len(fns) == 1:
+        return partial(f2, fns)
+    else:
+        return [partial(f2, f) for f in fns]
+
+def intr(name):
+    return Scalar(name = name, dtype = 'int64')
+ints = _multi(intr)
+
+def floatr(name):
+    return Scalar(name = name, dtype = 'float64')
+floats = _multi(floatr)
+
+
 
 def upcast(dtype, *dtypes):
     z = numpy.zeros((), dtype = dtype)