Author: mattip <[email protected]>
Branch: missing-ndarray-attributes
Changeset: r60307:92d3270bf0ab
Date: 2013-01-21 20:40 +0200
http://bitbucket.org/pypy/pypy/changeset/92d3270bf0ab/
Log: test_zjit thinks cumltative is constant, hack around it
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
@@ -173,32 +173,44 @@
y_iter.next()
return out
-axis_reduce__driver = jit.JitDriver(name='numpy_axis_reduce',
- greens=['shapelen', 'cumultative',
+axis_reduce1__driver = jit.JitDriver(name='numpy_axis_reduce',
+ greens=['shapelen',
'func', 'dtype',
'identity'],
reds=['axis', 'arr', 'out', 'shape',
'out_iter', 'arr_iter',
'temp_iter'])
+axis_reduce2__driver = jit.JitDriver(name='numpy_axis_reduce',
+ greens=['shapelen',
+ 'func', 'dtype',
+ 'identity'],
+ reds=['axis', 'arr', 'out', 'shape',
+ 'out_iter', 'arr_iter',
+ ])
def do_axis_reduce(shape, func, arr, dtype, axis, out, identity, cumultative,
temp):
- out_iter = out.create_axis_iter(arr.get_shape(), axis, cumultative)
if cumultative:
- temp_iter = temp.create_axis_iter(arr.get_shape(), axis, False)
+ return do_cum_axis_reduce(shape, func, arr, dtype, axis, out,
+ identity, temp)
else:
- temp_iter = out_iter # hack
+ return do_nocum_axis_reduce(shape, func, arr, dtype, axis, out,
+ identity, temp)
+
+def do_cum_axis_reduce(shape, func, arr, dtype, axis, out, identity,
+ temp):
+ out_iter = out.create_axis_iter(arr.get_shape(), axis, True)
+ temp_iter = temp.create_axis_iter(arr.get_shape(), axis, False)
arr_iter = arr.create_iter()
if identity is not None:
identity = identity.convert_to(dtype)
shapelen = len(shape)
while not out_iter.done():
- axis_reduce__driver.jit_merge_point(shapelen=shapelen, func=func,
+ axis_reduce1__driver.jit_merge_point(shapelen=shapelen, func=func,
dtype=dtype, identity=identity,
axis=axis, arr=arr, out=out,
shape=shape, out_iter=out_iter,
arr_iter=arr_iter,
- cumultative=cumultative,
temp_iter=temp_iter)
w_val = arr_iter.getitem().convert_to(dtype)
if out_iter.first_line:
@@ -208,9 +220,34 @@
cur = temp_iter.getitem()
w_val = func(dtype, cur, w_val)
out_iter.setitem(w_val)
- if cumultative:
- temp_iter.setitem(w_val)
- temp_iter.next()
+ temp_iter.setitem(w_val)
+ temp_iter.next()
+ arr_iter.next()
+ out_iter.next()
+ return out
+
+def do_nocum_axis_reduce(shape, func, arr, dtype, axis, out, identity,
+ temp):
+ out_iter = out.create_axis_iter(arr.get_shape(), axis, False)
+ arr_iter = arr.create_iter()
+ if identity is not None:
+ identity = identity.convert_to(dtype)
+ shapelen = len(shape)
+ while not out_iter.done():
+ axis_reduce2__driver.jit_merge_point(shapelen=shapelen, func=func,
+ dtype=dtype, identity=identity,
+ axis=axis, arr=arr, out=out,
+ shape=shape, out_iter=out_iter,
+ arr_iter=arr_iter,
+ )
+ w_val = arr_iter.getitem().convert_to(dtype)
+ if out_iter.first_line:
+ if identity is not None:
+ w_val = func(dtype, identity, w_val)
+ else:
+ cur = out_iter.getitem()
+ w_val = func(dtype, cur, w_val)
+ out_iter.setitem(w_val)
arr_iter.next()
out_iter.next()
return out
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