[pypy-commit] pypy ufunc-reduce: hg merge default
rlamy
noreply at buildbot.pypy.org
Sat Jul 25 19:22:29 CEST 2015
Author: Ronan Lamy <ronan.lamy at gmail.com>
Branch: ufunc-reduce
Changeset: r78662:dbe051dac229
Date: 2015-07-25 18:14 +0100
http://bitbucket.org/pypy/pypy/changeset/dbe051dac229/
Log: hg merge default
diff --git a/pypy/module/micronumpy/base.py b/pypy/module/micronumpy/base.py
--- a/pypy/module/micronumpy/base.py
+++ b/pypy/module/micronumpy/base.py
@@ -2,6 +2,7 @@
from pypy.interpreter.error import OperationError, oefmt
from rpython.tool.pairtype import extendabletype
from pypy.module.micronumpy import support
+from pypy.module.micronumpy import constants as NPY
def wrap_impl(space, w_cls, w_instance, impl):
if w_cls is None or space.is_w(w_cls, space.gettypefor(W_NDimArray)):
@@ -39,6 +40,13 @@
def from_shape(space, shape, dtype, order='C', w_instance=None, zero=True):
from pypy.module.micronumpy import concrete, descriptor, boxes
from pypy.module.micronumpy.strides import calc_strides
+ if len(shape) > NPY.MAXDIMS:
+ raise oefmt(space.w_ValueError,
+ "sequence too large; must be smaller than %d", NPY.MAXDIMS)
+ try:
+ support.product(shape) * dtype.elsize
+ except OverflowError as e:
+ raise oefmt(space.w_ValueError, "array is too big")
strides, backstrides = calc_strides(shape, dtype.base, order)
impl = concrete.ConcreteArray(shape, dtype.base, order, strides,
backstrides, zero=zero)
@@ -56,13 +64,19 @@
from pypy.module.micronumpy.strides import (calc_strides,
calc_backstrides)
isize = dtype.elsize
+ if len(shape) > NPY.MAXDIMS:
+ raise oefmt(space.w_ValueError,
+ "sequence too large; must be smaller than %d", NPY.MAXDIMS)
+ try:
+ totalsize = support.product(shape) * isize
+ except OverflowError as e:
+ raise oefmt(space.w_ValueError, "array is too big")
if storage_bytes > 0 :
- totalsize = support.product(shape) * isize
if totalsize > storage_bytes:
raise OperationError(space.w_TypeError, space.wrap(
"buffer is too small for requested array"))
else:
- storage_bytes = support.product(shape) * isize
+ storage_bytes = totalsize
if strides is None:
strides, backstrides = calc_strides(shape, dtype, order)
else:
diff --git a/pypy/module/micronumpy/concrete.py b/pypy/module/micronumpy/concrete.py
--- a/pypy/module/micronumpy/concrete.py
+++ b/pypy/module/micronumpy/concrete.py
@@ -400,17 +400,11 @@
class ConcreteArrayNotOwning(BaseConcreteArray):
def __init__(self, shape, dtype, order, strides, backstrides, storage, start=0):
- if len(shape) > NPY.MAXDIMS:
- raise oefmt(dtype.itemtype.space.w_ValueError,
- "sequence too large; must be smaller than %d", NPY.MAXDIMS)
make_sure_not_resized(shape)
make_sure_not_resized(strides)
make_sure_not_resized(backstrides)
self.shape = shape
- try:
- self.size = support.product(shape) * dtype.elsize
- except OverflowError as e:
- raise oefmt(dtype.itemtype.space.w_ValueError, "array is too big")
+ self.size = support.product(shape) * dtype.elsize
self.order = order
self.dtype = dtype
self.strides = strides
@@ -425,6 +419,13 @@
box, 0, self.size, 0, self.gcstruct)
def set_shape(self, space, orig_array, new_shape):
+ if len(new_shape) > NPY.MAXDIMS:
+ raise oefmt(space.w_ValueError,
+ "sequence too large; must be smaller than %d", NPY.MAXDIMS)
+ try:
+ support.product(new_shape) * self.dtype.elsize
+ except OverflowError as e:
+ raise oefmt(space.w_ValueError, "array is too big")
strides, backstrides = calc_strides(new_shape, self.dtype,
self.order)
return SliceArray(self.start, strides, backstrides, new_shape, self,
@@ -451,14 +452,9 @@
storage=lltype.nullptr(RAW_STORAGE), zero=True):
gcstruct = V_OBJECTSTORE
flags = NPY.ARRAY_ALIGNED | NPY.ARRAY_WRITEABLE
- if len(shape) > NPY.MAXDIMS:
- raise oefmt(dtype.itemtype.space.w_ValueError,
- "sequence too large; must be smaller than %d", NPY.MAXDIMS)
+ length = support.product(shape)
+ self.size = length * dtype.elsize
if storage == lltype.nullptr(RAW_STORAGE):
- try:
- length = support.product(shape)
- except OverflowError as e:
- raise oefmt(dtype.itemtype.space.w_ValueError, "array is too big")
if dtype.num == NPY.OBJECT:
storage = dtype.itemtype.malloc(length * dtype.elsize, zero=True)
gcstruct = _create_objectstore(storage, length, dtype.elsize)
@@ -559,6 +555,13 @@
loop.fill(self, box.convert_to(space, self.dtype))
def set_shape(self, space, orig_array, new_shape):
+ if len(new_shape) > NPY.MAXDIMS:
+ raise oefmt(space.w_ValueError,
+ "sequence too large; must be smaller than %d", NPY.MAXDIMS)
+ try:
+ support.product(new_shape) * self.dtype.elsize
+ except OverflowError as e:
+ raise oefmt(space.w_ValueError, "array is too big")
if len(self.get_shape()) < 2 or self.size == 0:
# TODO: this code could be refactored into calc_strides
# but then calc_strides would have to accept a stepping factor
diff --git a/pypy/module/micronumpy/converters.py b/pypy/module/micronumpy/converters.py
--- a/pypy/module/micronumpy/converters.py
+++ b/pypy/module/micronumpy/converters.py
@@ -113,3 +113,12 @@
shape.append(space.int_w(w_item))
shape += dtype.shape
return shape[:]
+
+def out_converter(space, w_out):
+ from .ndarray import W_NDimArray
+ if space.is_none(w_out):
+ return None
+ elif not isinstance(w_out, W_NDimArray):
+ raise oefmt(space.w_TypeError, 'output must be an array')
+ else:
+ return w_out
diff --git a/pypy/module/micronumpy/ndarray.py b/pypy/module/micronumpy/ndarray.py
--- a/pypy/module/micronumpy/ndarray.py
+++ b/pypy/module/micronumpy/ndarray.py
@@ -15,8 +15,9 @@
from pypy.module.micronumpy.base import W_NDimArray, convert_to_array, \
ArrayArgumentException, wrap_impl
from pypy.module.micronumpy.concrete import BaseConcreteArray
-from pypy.module.micronumpy.converters import multi_axis_converter, \
- order_converter, shape_converter, searchside_converter
+from pypy.module.micronumpy.converters import (
+ multi_axis_converter, order_converter, shape_converter,
+ searchside_converter, out_converter)
from pypy.module.micronumpy.flagsobj import W_FlagsObject
from pypy.module.micronumpy.strides import (
get_shape_from_iterable, shape_agreement, shape_agreement_multiple,
@@ -1090,12 +1091,7 @@
def descr_dot(self, space, w_other, w_out=None):
from .casting import find_result_type
- if space.is_none(w_out):
- out = None
- elif not isinstance(w_out, W_NDimArray):
- raise oefmt(space.w_TypeError, 'output must be an array')
- else:
- out = w_out
+ out = out_converter(space, w_out)
other = convert_to_array(space, w_other)
if other.is_scalar():
#Note: w_out is not modified, this is numpy compliant.
@@ -1152,12 +1148,7 @@
def _reduce_ufunc_impl(ufunc_name, name, variant=ufuncs.REDUCE, bool_result=False):
@unwrap_spec(keepdims=bool)
def impl(self, space, w_axis=None, w_dtype=None, w_out=None, keepdims=False):
- if space.is_none(w_out):
- out = None
- elif not isinstance(w_out, W_NDimArray):
- raise oefmt(space.w_TypeError, 'output must be an array')
- else:
- out = w_out
+ out = out_converter(space, w_out)
if bool_result:
w_dtype = descriptor.get_dtype_cache(space).w_booldtype
return getattr(ufuncs.get(space), ufunc_name).reduce(
@@ -1336,7 +1327,9 @@
dtype = space.interp_w(descriptor.W_Dtype, space.call_function(
space.gettypefor(descriptor.W_Dtype), w_dtype))
shape = shape_converter(space, w_shape, dtype)
-
+ if len(shape) > NPY.MAXDIMS:
+ raise oefmt(space.w_ValueError,
+ "sequence too large; must be smaller than %d", NPY.MAXDIMS)
if not space.is_none(w_buffer):
if (not space.is_none(w_strides)):
strides = [space.int_w(w_i) for w_i in
@@ -1373,6 +1366,10 @@
if space.is_w(w_subtype, space.gettypefor(W_NDimArray)):
return W_NDimArray.from_shape(space, shape, dtype, order)
strides, backstrides = calc_strides(shape, dtype.base, order)
+ try:
+ totalsize = support.product(shape) * dtype.base.elsize
+ except OverflowError as e:
+ raise oefmt(space.w_ValueError, "array is too big")
impl = ConcreteArray(shape, dtype.base, order, strides, backstrides)
w_ret = space.allocate_instance(W_NDimArray, w_subtype)
W_NDimArray.__init__(w_ret, impl)
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
@@ -20,6 +20,7 @@
from pypy.module.micronumpy.strides import shape_agreement
from pypy.module.micronumpy.support import (_parse_signature, product,
get_storage_as_int, is_rhs_priority_higher)
+from .converters import out_converter
from .casting import (
can_cast_type, can_cast_array, can_cast_to,
find_result_type, promote_types)
@@ -127,10 +128,7 @@
args_w, kwds_w = __args__.unpack()
# sig, extobj are used in generic ufuncs
w_subok, w_out, sig, w_casting, extobj = self.parse_kwargs(space, kwds_w)
- if space.is_w(w_out, space.w_None):
- out = None
- else:
- out = w_out
+ out = out_converter(space, w_out)
if (w_subok is not None and space.is_true(w_subok)):
raise oefmt(space.w_NotImplementedError, "parameter subok unsupported")
if kwds_w:
@@ -152,9 +150,6 @@
out = args_w[-1]
else:
args_w = args_w + [out]
- if out is not None and not isinstance(out, W_NDimArray):
- raise OperationError(space.w_TypeError, space.wrap(
- 'output must be an array'))
if w_casting is None:
casting = 'unsafe'
else:
@@ -166,13 +161,7 @@
def descr_accumulate(self, space, w_obj, w_axis=None, w_dtype=None, w_out=None):
if space.is_none(w_axis):
w_axis = space.wrap(0)
- if space.is_none(w_out):
- out = None
- elif not isinstance(w_out, W_NDimArray):
- raise OperationError(space.w_TypeError, space.wrap(
- 'output must be an array'))
- else:
- out = w_out
+ out = out_converter(space, w_out)
return self.reduce(space, w_obj, w_axis, True, #keepdims must be true
out, w_dtype, variant=ACCUMULATE)
@@ -234,13 +223,7 @@
from pypy.module.micronumpy.ndarray import W_NDimArray
if w_axis is None:
w_axis = space.wrap(0)
- if space.is_none(w_out):
- out = None
- elif not isinstance(w_out, W_NDimArray):
- raise OperationError(space.w_TypeError, space.wrap(
- 'output must be an array'))
- else:
- out = w_out
+ out = out_converter(space, w_out)
return self.reduce(space, w_obj, w_axis, keepdims, out, w_dtype)
@specialize.arg(7)
@@ -497,11 +480,7 @@
w_obj = args_w[0]
out = None
if len(args_w) > 1:
- out = args_w[1]
- if space.is_w(out, space.w_None):
- out = None
- elif out is not None and not isinstance(out, W_NDimArray):
- raise oefmt(space.w_TypeError, 'output must be an array')
+ out = out_converter(space, args_w[1])
w_obj = numpify(space, w_obj)
dtype = w_obj.get_dtype(space)
calc_dtype, dt_out, func = self.find_specialization(space, dtype, out, casting)
@@ -599,10 +578,7 @@
def call(self, space, args_w, sig, casting, extobj):
if len(args_w) > 2:
[w_lhs, w_rhs, out] = args_w
- if space.is_none(out):
- out = None
- elif not isinstance(out, W_NDimArray):
- raise oefmt(space.w_TypeError, 'output must be an array')
+ out = out_converter(space, out)
else:
[w_lhs, w_rhs] = args_w
out = None
@@ -750,7 +726,8 @@
if use_min_scalar:
w_arg1 = convert_to_array(space, w_arg1)
w_arg2 = convert_to_array(space, w_arg2)
- elif in_casting == 'safe' and l_dtype.num == 7 and r_dtype.num == 7:
+ elif (in_casting == 'safe' and l_dtype.num == 7 and r_dtype.num == 7 and
+ out is None and not self.promote_to_float):
# while long (7) can be cast to int32 (5) on 32 bit, don't do it
return l_dtype, l_dtype
for dt_in, dt_out in self.dtypes:
diff --git a/pypy/module/operator/test/test_operator.py b/pypy/module/operator/test/test_operator.py
--- a/pypy/module/operator/test/test_operator.py
+++ b/pypy/module/operator/test/test_operator.py
@@ -10,13 +10,16 @@
class A(object):
getx = operator.attrgetter('x')
get3 = operator.itemgetter(3)
+ callx = operator.methodcaller("append", "x")
a = A()
a.x = 5
assert a.getx(a) == 5
assert a.get3("foobar") == "b"
assert a.getx(*(a,)) == 5
assert a.get3(obj="foobar") == "b"
-
+ l = []
+ a.callx(l)
+ assert l == ["x"]
def test_getter_multiple_gest(self):
import operator
diff --git a/pypy/module/pypyjit/test_pypy_c/test_micronumpy.py b/pypy/module/pypyjit/test_pypy_c/test_micronumpy.py
--- a/pypy/module/pypyjit/test_pypy_c/test_micronumpy.py
+++ b/pypy/module/pypyjit/test_pypy_c/test_micronumpy.py
@@ -29,7 +29,7 @@
guard_true(i15, descr=...)
guard_not_invalidated(descr=...)
i17 = cast_float_to_int(f16)
- i19 = int_and(i17, 255)
+ i19 = int_is_true(i17)
guard_true(i19, descr=...)
i20 = getfield_gc_pure(p2, descr=<FieldU pypy.module.micronumpy.boxes.W_BoolBox.inst_value \d+>)
i21 = int_is_true(i20)
diff --git a/pypy/objspace/test/test_descroperation.py b/pypy/objspace/test/test_descroperation.py
--- a/pypy/objspace/test/test_descroperation.py
+++ b/pypy/objspace/test/test_descroperation.py
@@ -639,10 +639,10 @@
pass
a = A()
b = B()
- assert isinstance(a, A)
+ assert isinstance(a, A) # "shortcut" does not go through metaclass
assert not isinstance(a, B)
assert isinstance(b, A)
- assert not isinstance(b, B)
+ assert isinstance(b, B) # "shortcut" does not go through metaclass
assert isinstance(4, A)
assert not issubclass(A, A)
assert not issubclass(B, A)
diff --git a/rpython/rlib/buffer.py b/rpython/rlib/buffer.py
--- a/rpython/rlib/buffer.py
+++ b/rpython/rlib/buffer.py
@@ -74,6 +74,8 @@
return ""
if step == 1:
assert 0 <= start <= stop
+ if start == 0 and stop == len(self.value):
+ return self.value
return self.value[start:stop]
return Buffer.getslice(self, start, stop, step, size)
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