[pypy-commit] pypy vecopt-merge: added missing vectorize=True for the jit drivers in loop.py

[plan_rich]

Author: Richard Plangger <rich at pasra.at>
Branch: vecopt-merge
Changeset: r78881:4dcddb2caee3
Date: 2015-08-11 11:59 +0200
http://bitbucket.org/pypy/pypy/changeset/4dcddb2caee3/

Log:	added missing vectorize=True for the jit drivers in loop.py

diff --git a/pypy/module/micronumpy/compile.py b/pypy/module/micronumpy/compile.py
--- a/pypy/module/micronumpy/compile.py
+++ b/pypy/module/micronumpy/compile.py
@@ -15,7 +15,7 @@
 from pypy.module.micronumpy.descriptor import get_dtype_cache
 from pypy.interpreter.miscutils import ThreadLocals, make_weak_value_dictionary
 from pypy.interpreter.executioncontext import (ExecutionContext, ActionFlag,
-    UserDelAction, CodeUniqueIds)
+    UserDelAction)
 from pypy.interpreter.pyframe import PyFrame
 
 
@@ -93,7 +93,6 @@
         self.config = config
 
         self.interned_strings = make_weak_value_dictionary(self, str, W_Root)
-        self.code_unique_ids = CodeUniqueIds()
         self.builtin = DictObject({})
         self.FrameClass = PyFrame
         self.threadlocals = ThreadLocals()
@@ -165,6 +164,10 @@
                 lgt = (stop - start - 1) / step + 1
             return (start, stop, step, lgt)
 
+    def unicode_from_object(self, w_item):
+        # XXX
+        return StringObject("")
+
     @specialize.argtype(1)
     def wrap(self, obj):
         if isinstance(obj, float):
@@ -281,6 +284,12 @@
             return w_obj.v
         raise NotImplementedError
 
+    def unicode_w(self, w_obj):
+        # XXX
+        if isinstance(w_obj, StringObject):
+            return unicode(w_obj.v)
+        raise NotImplementedError
+
     def int(self, w_obj):
         if isinstance(w_obj, IntObject):
             return w_obj
diff --git a/pypy/module/micronumpy/flatiter.py b/pypy/module/micronumpy/flatiter.py
--- a/pypy/module/micronumpy/flatiter.py
+++ b/pypy/module/micronumpy/flatiter.py
@@ -97,7 +97,7 @@
         finally:
             self.iter.reset(self.state, mutate=True)
 
-    def descr___array_wrap__(self, space, obj):
+    def descr___array_wrap__(self, space, obj, w_context=None):
         return obj
 
 W_FlatIterator.typedef = TypeDef("numpy.flatiter",
diff --git a/pypy/module/micronumpy/loop.py b/pypy/module/micronumpy/loop.py
--- a/pypy/module/micronumpy/loop.py
+++ b/pypy/module/micronumpy/loop.py
@@ -9,7 +9,7 @@
 from pypy.module.micronumpy import support, constants as NPY
 from pypy.module.micronumpy.base import W_NDimArray, convert_to_array
 from pypy.module.micronumpy.iterators import PureShapeIter, AxisIter, \
-    AllButAxisIter
+    AllButAxisIter, ArrayIter
 from pypy.interpreter.argument import Arguments
 
 
@@ -202,29 +202,28 @@
 
 reduce_flat_driver = jit.JitDriver(
     name='numpy_reduce_flat',
-    greens = ['shapelen', 'func', 'done_func', 'calc_dtype'], reds = 'auto')
+    greens = ['shapelen', 'func', 'done_func', 'calc_dtype'], reds = 'auto',
+    vectorize = True)
 
-def compute_reduce(space, obj, calc_dtype, func, done_func, identity):
-    obj_iter, obj_state = obj.create_iter()
+def reduce_flat(space, func, w_arr, calc_dtype, done_func, identity):
+    obj_iter, obj_state = w_arr.create_iter()
     if identity is None:
         cur_value = obj_iter.getitem(obj_state).convert_to(space, calc_dtype)
         obj_state = obj_iter.next(obj_state)
     else:
         cur_value = identity.convert_to(space, calc_dtype)
-    shapelen = len(obj.get_shape())
+    shapelen = len(w_arr.get_shape())
     while not obj_iter.done(obj_state):
-        reduce_driver.jit_merge_point(shapelen=shapelen, func=func,
-                                      done_func=done_func,
-                                      calc_dtype=calc_dtype)
+        reduce_flat_driver.jit_merge_point(
+            shapelen=shapelen, func=func,
+            done_func=done_func, calc_dtype=calc_dtype)
         rval = obj_iter.getitem(obj_state).convert_to(space, calc_dtype)
         if done_func is not None and done_func(calc_dtype, rval):
             return rval
         cur_value = func(calc_dtype, cur_value, rval)
         obj_state = obj_iter.next(obj_state)
-        rval = None
     return cur_value
 
-
 reduce_driver = jit.JitDriver(
     name='numpy_reduce',
     greens=['shapelen', 'func', 'dtype'], reds='auto',
@@ -316,7 +315,8 @@
 
 accumulate_driver = jit.JitDriver(
     name='numpy_accumulate',
-    greens=['shapelen', 'func', 'calc_dtype'], reds='auto',
+    greens=['shapelen', 'func', 'calc_dtype'],
+    reds='auto',
     vectorize=True)
 
 
@@ -367,7 +367,8 @@
 
 where_driver = jit.JitDriver(name='numpy_where',
                              greens = ['shapelen', 'dtype', 'arr_dtype'],
-                             reds = 'auto', vectorize=True)
+                             reds = 'auto',
+                             vectorize=True)
 
 def where(space, out, shape, arr, x, y, dtype):
     out_iter, out_state = out.create_iter(shape)
diff --git a/pypy/module/micronumpy/strides.py b/pypy/module/micronumpy/strides.py
--- a/pypy/module/micronumpy/strides.py
+++ b/pypy/module/micronumpy/strides.py
@@ -7,6 +7,7 @@
 # structures to describe slicing
 
 class BaseChunk(object):
+    _attrs_ = ['step']
     pass
 
 
diff --git a/pypy/module/micronumpy/ufuncs.py b/pypy/module/micronumpy/ufuncs.py
--- a/pypy/module/micronumpy/ufuncs.py
+++ b/pypy/module/micronumpy/ufuncs.py
@@ -276,7 +276,7 @@
                 loop.accumulate_flat(
                     space, self.func, obj, dtype, out, self.identity)
             if call__array_wrap__:
-                out = space.call_method(obj, '__array_wrap__', out)
+                out = space.call_method(obj, '__array_wrap__', out, None)
             return out
 
         axis_flags = [False] * shapelen
@@ -313,7 +313,7 @@
                 out.implementation.setitem(0, res)
                 res = out
             if call__array_wrap__:
-                res = space.call_method(obj, '__array_wrap__', res)
+                res = space.call_method(obj, '__array_wrap__', res, None)
             return res
 
         else:
@@ -360,7 +360,7 @@
             loop.reduce(
                 space, self.func, obj, axis_flags, dtype, out, self.identity)
             if call__array_wrap__:
-                out = space.call_method(obj, '__array_wrap__', out)
+                out = space.call_method(obj, '__array_wrap__', out, None)
             return out
 
     def descr_outer(self, space, __args__):