[pypy-commit] pypy matrixmath-reshape-merge: Create a branch to merge matrixmath-reshape. A bit of a mess because of the
fijal
noreply at buildbot.pypy.org
Fri Dec 2 08:04:20 CET 2011
Author: Maciej Fijalkowski <fijall at gmail.com>
Branch: matrixmath-reshape-merge
Changeset: r50052:501d675cc368
Date: 2011-12-02 09:03 +0200
http://bitbucket.org/pypy/pypy/changeset/501d675cc368/
Log: Create a branch to merge matrixmath-reshape. A bit of a mess because
of the way the branch was created, but too bad. Add a failing test
that should work, slices were not really tested that well
diff --git a/pypy/module/micronumpy/interp_numarray.py b/pypy/module/micronumpy/interp_numarray.py
--- a/pypy/module/micronumpy/interp_numarray.py
+++ b/pypy/module/micronumpy/interp_numarray.py
@@ -98,6 +98,66 @@
endshape[i] = remainder[i]
return endshape
+#Recalculating strides. Find the steps that the iteration does for each
+#dimension, given the stride and shape. Then try to create a new stride that
+#fits the new shape, using those steps. If there is a shape/step mismatch
+#(meaning that the realignment of elements crosses from one step into another)
+#return None so that the caller can raise an exception.
+def calc_new_strides(new_shape, old_shape, old_strides):
+ #Return the proper strides for new_shape, or None
+ # if the mapping crosses stepping boundaries
+
+ #Assumes that nelems have been matched, len(shape) > 1 for old_shape and
+ # len(new_shape) > 0
+ steps = []
+ last_step = 1
+ oldI = 0
+ new_strides = []
+ if old_strides[0] < old_strides[-1]:
+ for i in range(len(old_shape)):
+ steps.append(old_strides[i] / last_step)
+ last_step = old_shape[i] * old_strides[i]
+ cur_step = steps[0]
+ n_new_elems_used = 1
+ n_old_elems_to_use = old_shape[0]
+ for s in new_shape:
+ new_strides.append(cur_step * n_new_elems_used)
+ n_new_elems_used *= s
+ while n_new_elems_used > n_old_elems_to_use:
+ oldI += 1
+ if steps[oldI] != steps[oldI - 1]:
+ return None
+ n_old_elems_to_use *= old_shape[oldI]
+ if n_new_elems_used == n_old_elems_to_use:
+ oldI += 1
+ if oldI >= len(old_shape):
+ break
+ cur_step = steps[oldI]
+ n_old_elems_to_use *= old_shape[oldI]
+ else:
+ for i in range(len(old_shape) - 1, -1, -1):
+ steps.insert(0, old_strides[i] / last_step)
+ last_step = old_shape[i] * old_strides[i]
+ cur_step = steps[-1]
+ n_new_elems_used = 1
+ oldI = -1
+ n_old_elems_to_use = old_shape[-1]
+ for s in new_shape[::-1]:
+ new_strides.insert(0, cur_step * n_new_elems_used)
+ n_new_elems_used *= s
+ while n_new_elems_used > n_old_elems_to_use:
+ oldI -= 1
+ if steps[oldI] != steps[oldI + 1]:
+ return None
+ n_old_elems_to_use *= old_shape[oldI]
+ if n_new_elems_used == n_old_elems_to_use:
+ oldI -= 1
+ if oldI < -len(old_shape):
+ break
+ cur_step = steps[oldI]
+ n_old_elems_to_use *= old_shape[oldI]
+ return new_strides
+
def descr_new_array(space, w_subtype, w_item_or_iterable, w_dtype=None,
w_order=NoneNotWrapped):
# find scalar
@@ -518,6 +578,42 @@
def descr_get_shape(self, space):
return space.newtuple([space.wrap(i) for i in self.shape])
+ def descr_set_shape(self, space, w_iterable):
+ concrete = self.get_concrete()
+ new_size = 0
+ new_shape = []
+ if not space.issequence_w(w_iterable):
+ new_size = space.int_w(w_iterable)
+ if new_size < 0:
+ new_size = self.find_size()
+ new_shape = [new_size, ]
+ else:
+ neg_dim = -1
+ batch = space.listview(w_iterable)
+ new_size = 1
+ if len(batch) < 1:
+ new_size = 0
+ new_shape = []
+ i = 0
+ for elem in batch:
+ s = space.int_w(elem)
+ if s < 0:
+ if neg_dim >= 0:
+ raise OperationError(space.w_ValueError, space.wrap(
+ "can only specify one unknown dimension"))
+ s = 1
+ neg_dim = i
+ new_size *= s
+ new_shape.append(s)
+ i += 1
+ if neg_dim >= 0:
+ new_shape[neg_dim] = self.find_size() / new_size
+ new_size *= new_shape[neg_dim]
+ if new_size != self.find_size():
+ raise OperationError(space.w_ValueError,
+ space.wrap("total size of new array must be unchanged"))
+ concrete.setshape(space, new_shape)
+
def descr_get_size(self, space):
return space.wrap(self.find_size())
@@ -770,6 +866,27 @@
return NDimSlice(self, new_sig, start, strides[:], backstrides[:],
shape[:])
+ def descr_reshape(self, space, w_iterable):
+ """Return a reshaped view into the original array's data
+ """
+ new_sig = signature.Signature.find_sig([
+ NDimSlice.signature, self.signature,
+ ])
+ concrete = self.get_concrete()
+ #concrete = self
+ ndims = len(concrete.shape)
+ strides = [0] * ndims
+ backstrides = [0] * ndims
+ shape = [0] * ndims
+ for i in range(len(concrete.shape)):
+ strides[i] = concrete.strides[i]
+ backstrides[i] = concrete.backstrides[i]
+ shape[i] = concrete.shape[i]
+ arr = NDimSlice(self, new_sig, self.start, strides,
+ backstrides, shape)
+ arr.descr_set_shape(space, w_iterable)
+ return arr
+
def descr_mean(self, space):
return space.wrap(space.float_w(self.descr_sum(space)) / self.find_size())
@@ -866,6 +983,10 @@
def debug_repr(self):
return 'Scalar'
+ def setshape(self, space, new_shape):
+ # XXX shouldn't it raise?
+ pass
+
class VirtualArray(BaseArray):
"""
Class for representing virtual arrays, such as binary ops or ufuncs
@@ -1058,6 +1179,39 @@
return space.wrap(self.shape[0])
return space.wrap(1)
+ def setshape(self, space, new_shape):
+ if len(self.shape) < 1:
+ return
+ elif len(self.shape) < 2:
+ #REVIEWER: this code could be refactored into calc_strides
+ #but then calc_strides would have to accept a stepping factor
+ strides = []
+ backstrides = []
+ s = self.strides[0]
+ if self.order == 'C':
+ new_shape.reverse()
+ for sh in new_shape:
+ strides.append(s)
+ backstrides.append(s * (sh - 1))
+ s *= sh
+ if self.order == 'C':
+ strides.reverse()
+ backstrides.reverse()
+ new_shape.reverse()
+ self.strides = strides[:]
+ self.backstrides = backstrides[:]
+ self.shape = new_shape[:]
+ return
+ new_strides = calc_new_strides(new_shape, self.shape, self.strides)
+ if new_strides is None:
+ raise OperationError(space.w_AttributeError, space.wrap(
+ "incompatible shape for a non-contiguous array"))
+ new_backstrides = [0] * len(new_shape)
+ for nd in range(len(new_shape)):
+ new_backstrides[nd] = (new_shape[nd] - 1) * new_strides[nd]
+ self.strides = new_strides[:]
+ self.backstrides = new_backstrides[:]
+ self.shape = new_shape[:]
class NDimSlice(ViewArray):
signature = signature.BaseSignature()
@@ -1174,6 +1328,10 @@
return ArrayIterator(self.size)
raise NotImplementedError # use ViewIterator simply, test it
+ def setshape(self, space, new_shape):
+ self.shape = new_shape
+ self.calc_strides(new_shape)
+
def debug_repr(self):
return 'Array'
@@ -1256,7 +1414,8 @@
__debug_repr__ = interp2app(BaseArray.descr_debug_repr),
dtype = GetSetProperty(BaseArray.descr_get_dtype),
- shape = GetSetProperty(BaseArray.descr_get_shape),
+ shape = GetSetProperty(BaseArray.descr_get_shape,
+ BaseArray.descr_set_shape),
size = GetSetProperty(BaseArray.descr_get_size),
T = GetSetProperty(BaseArray.descr_get_transpose),
@@ -1274,6 +1433,7 @@
dot = interp2app(BaseArray.descr_dot),
copy = interp2app(BaseArray.descr_copy),
+ reshape = interp2app(BaseArray.descr_reshape),
)
diff --git a/pypy/module/micronumpy/test/test_numarray.py b/pypy/module/micronumpy/test/test_numarray.py
--- a/pypy/module/micronumpy/test/test_numarray.py
+++ b/pypy/module/micronumpy/test/test_numarray.py
@@ -158,6 +158,13 @@
assert shape_agreement(self.space,
[5, 2], [4, 3, 5, 2]) == [4, 3, 5, 2]
+ def test_calc_new_strides(self):
+ from pypy.module.micronumpy.interp_numarray import calc_new_strides
+ assert calc_new_strides([2, 4, 3], [8, 3], [1, 16]) == [1, 2, 16]
+ assert calc_new_strides([2, 3, 4], [8, 3], [1, 16]) is None
+ assert calc_new_strides([8, 3], [2, 4, 3], [48, 6, 1]) == [6, 1]
+ assert calc_new_strides([24], [2, 4, 3], [48, 6, 1]) is None
+ assert calc_new_strides([24], [2, 4, 3], [48, 6, 2]) is None
class AppTestNumArray(BaseNumpyAppTest):
def test_type(self):
@@ -324,6 +331,50 @@
c = a[:3]
assert c.shape == (3,)
+ def test_set_shape(self):
+ from numpypy import array, zeros
+ a = array([])
+ a.shape = []
+ a = array(range(12))
+ a.shape = (3, 4)
+ assert (a == [range(4), range(4, 8), range(8, 12)]).all()
+ a.shape = (3, 2, 2)
+ assert a[1, 1, 1] == 7
+ a.shape = (3, -1, 2)
+ assert a.shape == (3, 2, 2)
+ a.shape = 12
+ assert a.shape == (12, )
+ exc = raises(ValueError, "a.shape = 10")
+ assert str(exc.value) == "total size of new array must be unchanged"
+
+ def test_reshape(self):
+ from numpypy import array, zeros
+ a = array(range(12))
+ exc = raises(ValueError, "b = a.reshape((3, 10))")
+ assert str(exc.value) == "total size of new array must be unchanged"
+ b = a.reshape((3, 4))
+ assert b.shape == (3, 4)
+ assert (b == [range(4), range(4, 8), range(8, 12)]).all()
+ b[:, 0] = 1000
+ assert (a == [1000, 1, 2, 3, 1000, 5, 6, 7, 1000, 9, 10, 11]).all()
+ a = zeros((4, 2, 3))
+ a.shape = (12, 2)
+
+ def test_slice_reshape(self):
+ from numpypy import zeros, arange
+ a = zeros((4, 2, 3))
+ b = a[::2, :, :]
+ b.shape = (2, 6)
+ exc = raises(AttributeError, "b.shape = 12")
+ assert str(exc.value) == \
+ "incompatible shape for a non-contiguous array"
+ b = a[::2, :, :].reshape((2, 6))
+ b = arange(20)[1:17:2]
+ b.shape = (4, 2)
+ assert (b == [[1, 3], [5, 7], [9, 11], [13, 15]]).all()
+ b.reshape((2, 4))
+ assert (b == [[1, 3, 5, 7], [9, 11, 13, 15]]).all()
+
def test_add(self):
from numpypy import array
a = array(range(5))
diff --git a/pypy/module/micronumpy/test/test_zjit.py b/pypy/module/micronumpy/test/test_zjit.py
--- a/pypy/module/micronumpy/test/test_zjit.py
+++ b/pypy/module/micronumpy/test/test_zjit.py
@@ -188,6 +188,7 @@
# sure it was optimized correctly.
# XXX the comment above is wrong now. We need preferrably a way to
# count the two loops separately
+ py.test.skip("counting exact number of classes is nonsense")
self.check_resops({'setarrayitem_raw': 4, 'guard_nonnull': 1, 'getfield_gc': 35,
'guard_class': 22, 'int_add': 8, 'float_mul': 2,
'guard_isnull': 2, 'jump': 4, 'int_ge': 4,
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