Match numpy interface for empty reductions#136

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Match numpy interface for empty reductions #136

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c677cc9
Unify pytato reduction handling, support 'initial' arg
inducer Dec 28, 2021
4c06f61
Pass on unrelated TypeErrors in pytato reduction handling
inducer Jan 6, 2022
e23a680
flake8
majosm Jan 6, 2022
1f15ae9
explain _NoValue
majosm Jan 6, 2022
d4271f2
cosmetic changes
majosm Jan 6, 2022
994918a
add empty container support to pyopencl's np.[sum,min,max]
majosm Jan 6, 2022
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95 changes: 61 additions & 34 deletions arraycontext/impl/pyopencl/fake_numpy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -50,6 +50,10 @@

# {{{ fake numpy

class _NoValue:
pass


class PyOpenCLFakeNumpyNamespace(BaseFakeNumpyNamespace):
def _get_fake_numpy_linalg_namespace(self):
return _PyOpenCLFakeNumpyLinalgNamespace(self._array_context)
Expand DownExpand Up@@ -110,58 +114,81 @@ def where_inner(inner_crit, inner_then, inner_else):

return rec_multimap_array_container(where_inner, criterion, then, else_)

def sum(self, a, axis=None, dtype=None):

@staticmethod
def _map_reduce(reduce_func, map_func,
ary, *,
axis, dtype, initial):
if isinstance(axis, int):
axis = axis,

def _rec_sum(ary):
def _reduce_func(partial_results):
if initial is _NoValue:
try:
return reduce(reduce_func, partial_results)
except TypeError as exc:
if "empty sequence" in str(exc):
raise ValueError("zero-size reduction operation "
"without supplied 'initial' value")
else:
raise
else:
return reduce(reduce_func, partial_results, initial)

def _map_func(ary):
if dtype not in [None, ary.dtype]:
raise NotImplementedError
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Sum over '{axis}' axes not supported.")
raise NotImplementedError(
f"Mapping over '{axis}' axes not supported.")
if initial is _NoValue:
return map_func(ary)
else:
return map_func(ary, initial=initial)

return cl_array.sum(ary, dtype=dtype, queue=self._array_context.queue)
return rec_map_reduce_array_container(
_reduce_func,
_map_func,
ary)

result = rec_map_reduce_array_container(sum, _rec_sum, a)
# * appears where positional signature starts diverging from numpy
def sum(self, a, axis=None, dtype=None, *, initial=0):
queue = self._array_context.queue
import operator
result = self._map_reduce(
operator.add,
partial(cl_array.sum, queue=queue),
a,
axis=axis, dtype=dtype, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
return result

def min(self, a, axis=None):
# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def min(self, a, axis=None, *, initial=_NoValue):
queue = self._array_context.queue

if isinstance(axis, int):
axis = axis,

def _rec_min(ary):
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Min. over '{axis}' axes not supported.")
return cl_array.min(ary, queue=queue)

result = rec_map_reduce_array_container(
partial(reduce, partial(cl_array.minimum, queue=queue)),
_rec_min,
a)
result = self._map_reduce(
partial(cl_array.minimum, queue=queue),
partial(cl_array.min, queue=queue),
a,
axis=axis, dtype=None, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
return result

def max(self, a, axis=None):
# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def max(self, a, axis=None, *, initial=_NoValue):
queue = self._array_context.queue

if isinstance(axis, int):
axis = axis,

def _rec_max(ary):
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Max. over '{axis}' axes not supported.")
return cl_array.max(ary, queue=queue)

result = rec_map_reduce_array_container(
partial(reduce, partial(cl_array.maximum, queue=queue)),
_rec_max,
a)
result = self._map_reduce(
partial(cl_array.maximum, queue=queue),
partial(cl_array.max, queue=queue),
a,
axis=axis, dtype=None, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
Expand Down
62 changes: 50 additions & 12 deletions arraycontext/impl/pytato/fake_numpy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -42,6 +42,10 @@ class PytatoFakeNumpyLinalgNamespace(BaseFakeNumpyLinalgNamespace):
pass


class _NoValue:
pass


class PytatoFakeNumpyNamespace(BaseFakeNumpyNamespace):
"""
A :mod:`numpy` mimic for :class:`PytatoPyOpenCLArrayContext`.
Expand DownExpand Up@@ -91,22 +95,56 @@ def minimum(self, x, y):
def where(self, criterion, then, else_):
return rec_multimap_array_container(pt.where, criterion, then, else_)

def sum(self, a, axis=None, dtype=None):
def _pt_sum(ary):
if dtype not in [ary.dtype, None]:
raise NotImplementedError

return pt.sum(ary, axis=axis)
@staticmethod
def _map_reduce(reduce_func, map_func,
ary, *,
axis, dtype, initial):
def _reduce_func(partial_results):
if initial is _NoValue:
try:
return reduce(reduce_func, partial_results)
except TypeError as exc:
if "empty sequence" in str(exc):
raise ValueError("zero-size reduction operation "
"without supplied 'initial' value")
else:
raise
else:
return reduce(reduce_func, partial_results, initial)

return rec_map_reduce_array_container(sum, _pt_sum, a)
def _map_func(ary):
if dtype not in [None, ary.dtype]:
raise NotImplementedError

def min(self, a, axis=None):
return rec_map_reduce_array_container(
partial(reduce, pt.minimum), partial(pt.amin, axis=axis), a)
if initial is _NoValue:
return map_func(ary, axis=axis)
else:
return map_func(ary, axis=axis, initial=initial)

def max(self, a, axis=None):
return rec_map_reduce_array_container(
partial(reduce, pt.maximum), partial(pt.amax, axis=axis), a)
_reduce_func,
_map_func,
ary)

# * appears where positional signature starts diverging from numpy
def sum(self, a, axis=None, dtype=None, *, initial=0):
import operator
return self._map_reduce(operator.add, pt.sum, a,
axis=axis, dtype=dtype, initial=initial)

# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def min(self, a, axis=None, *, initial=_NoValue):
Comment thread
majosm marked this conversation as resolved.
return self._map_reduce(pt.minimum, pt.amin, a,
axis=axis, dtype=None, initial=initial)

# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def max(self, a, axis=None, *, initial=_NoValue):
return self._map_reduce(pt.maximum, pt.amax, a,
axis=axis, dtype=None, initial=initial)

def stack(self, arrays, axis=0):
return rec_multimap_array_container(
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all \u003cpre\u003e\u003ccode\u003e blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks"); } } catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); } })(); (function(){ try { var __m = "github.com"; var __re = new RegExp('^' + "github\\.com" + '
Skip to content

Match numpy interface for empty reductions#136

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Draft
inducer wants to merge 6 commits into
base:main
Choose a base branch
from
Draft

Match numpy interface for empty reductions #136

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Commits
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6 commits
Select commit Hold shift + click to select a range
c677cc9
Unify pytato reduction handling, support 'initial' arg
inducer Dec 28, 2021
4c06f61
Pass on unrelated TypeErrors in pytato reduction handling
inducer Jan 6, 2022
e23a680
flake8
majosm Jan 6, 2022
1f15ae9
explain _NoValue
majosm Jan 6, 2022
d4271f2
cosmetic changes
majosm Jan 6, 2022
994918a
add empty container support to pyopencl's np.[sum,min,max]
majosm Jan 6, 2022
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95 changes: 61 additions & 34 deletions arraycontext/impl/pyopencl/fake_numpy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -50,6 +50,10 @@

# {{{ fake numpy

class _NoValue:
pass


class PyOpenCLFakeNumpyNamespace(BaseFakeNumpyNamespace):
def _get_fake_numpy_linalg_namespace(self):
return _PyOpenCLFakeNumpyLinalgNamespace(self._array_context)
Expand DownExpand Up@@ -110,58 +114,81 @@ def where_inner(inner_crit, inner_then, inner_else):

return rec_multimap_array_container(where_inner, criterion, then, else_)

def sum(self, a, axis=None, dtype=None):

@staticmethod
def _map_reduce(reduce_func, map_func,
ary, *,
axis, dtype, initial):
if isinstance(axis, int):
axis = axis,

def _rec_sum(ary):
def _reduce_func(partial_results):
if initial is _NoValue:
try:
return reduce(reduce_func, partial_results)
except TypeError as exc:
if "empty sequence" in str(exc):
raise ValueError("zero-size reduction operation "
"without supplied 'initial' value")
else:
raise
else:
return reduce(reduce_func, partial_results, initial)

def _map_func(ary):
if dtype not in [None, ary.dtype]:
raise NotImplementedError
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Sum over '{axis}' axes not supported.")
raise NotImplementedError(
f"Mapping over '{axis}' axes not supported.")
if initial is _NoValue:
return map_func(ary)
else:
return map_func(ary, initial=initial)

return cl_array.sum(ary, dtype=dtype, queue=self._array_context.queue)
return rec_map_reduce_array_container(
_reduce_func,
_map_func,
ary)

result = rec_map_reduce_array_container(sum, _rec_sum, a)
# * appears where positional signature starts diverging from numpy
def sum(self, a, axis=None, dtype=None, *, initial=0):
queue = self._array_context.queue
import operator
result = self._map_reduce(
operator.add,
partial(cl_array.sum, queue=queue),
a,
axis=axis, dtype=dtype, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
return result

def min(self, a, axis=None):
# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def min(self, a, axis=None, *, initial=_NoValue):
queue = self._array_context.queue

if isinstance(axis, int):
axis = axis,

def _rec_min(ary):
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Min. over '{axis}' axes not supported.")
return cl_array.min(ary, queue=queue)

result = rec_map_reduce_array_container(
partial(reduce, partial(cl_array.minimum, queue=queue)),
_rec_min,
a)
result = self._map_reduce(
partial(cl_array.minimum, queue=queue),
partial(cl_array.min, queue=queue),
a,
axis=axis, dtype=None, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
return result

def max(self, a, axis=None):
# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def max(self, a, axis=None, *, initial=_NoValue):
queue = self._array_context.queue

if isinstance(axis, int):
axis = axis,

def _rec_max(ary):
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Max. over '{axis}' axes not supported.")
return cl_array.max(ary, queue=queue)

result = rec_map_reduce_array_container(
partial(reduce, partial(cl_array.maximum, queue=queue)),
_rec_max,
a)
result = self._map_reduce(
partial(cl_array.maximum, queue=queue),
partial(cl_array.max, queue=queue),
a,
axis=axis, dtype=None, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
Expand Down
62 changes: 50 additions & 12 deletions arraycontext/impl/pytato/fake_numpy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -42,6 +42,10 @@ class PytatoFakeNumpyLinalgNamespace(BaseFakeNumpyLinalgNamespace):
pass


class _NoValue:
pass


class PytatoFakeNumpyNamespace(BaseFakeNumpyNamespace):
"""
A :mod:`numpy` mimic for :class:`PytatoPyOpenCLArrayContext`.
Expand DownExpand Up@@ -91,22 +95,56 @@ def minimum(self, x, y):
def where(self, criterion, then, else_):
return rec_multimap_array_container(pt.where, criterion, then, else_)

def sum(self, a, axis=None, dtype=None):
def _pt_sum(ary):
if dtype not in [ary.dtype, None]:
raise NotImplementedError

return pt.sum(ary, axis=axis)
@staticmethod
def _map_reduce(reduce_func, map_func,
ary, *,
axis, dtype, initial):
def _reduce_func(partial_results):
if initial is _NoValue:
try:
return reduce(reduce_func, partial_results)
except TypeError as exc:
if "empty sequence" in str(exc):
raise ValueError("zero-size reduction operation "
"without supplied 'initial' value")
else:
raise
else:
return reduce(reduce_func, partial_results, initial)

return rec_map_reduce_array_container(sum, _pt_sum, a)
def _map_func(ary):
if dtype not in [None, ary.dtype]:
raise NotImplementedError

def min(self, a, axis=None):
return rec_map_reduce_array_container(
partial(reduce, pt.minimum), partial(pt.amin, axis=axis), a)
if initial is _NoValue:
return map_func(ary, axis=axis)
else:
return map_func(ary, axis=axis, initial=initial)

def max(self, a, axis=None):
return rec_map_reduce_array_container(
partial(reduce, pt.maximum), partial(pt.amax, axis=axis), a)
_reduce_func,
_map_func,
ary)

# * appears where positional signature starts diverging from numpy
def sum(self, a, axis=None, dtype=None, *, initial=0):
import operator
return self._map_reduce(operator.add, pt.sum, a,
axis=axis, dtype=dtype, initial=initial)

# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def min(self, a, axis=None, *, initial=_NoValue):
Comment thread
majosm marked this conversation as resolved.
return self._map_reduce(pt.minimum, pt.amin, a,
axis=axis, dtype=None, initial=initial)

# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def max(self, a, axis=None, *, initial=_NoValue):
return self._map_reduce(pt.maximum, pt.amax, a,
axis=axis, dtype=None, initial=initial)

def stack(self, arrays, axis=0):
return rec_multimap_array_container(
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

Match numpy interface for empty reductions#136

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Draft
inducer wants to merge 6 commits into
base:main
Choose a base branch
from
Draft

Match numpy interface for empty reductions #136

Show file tree
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Changes from all commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
c677cc9
Unify pytato reduction handling, support 'initial' arg
inducer Dec 28, 2021
4c06f61
Pass on unrelated TypeErrors in pytato reduction handling
inducer Jan 6, 2022
e23a680
flake8
majosm Jan 6, 2022
1f15ae9
explain _NoValue
majosm Jan 6, 2022
d4271f2
cosmetic changes
majosm Jan 6, 2022
994918a
add empty container support to pyopencl's np.[sum,min,max]
majosm Jan 6, 2022
File filter

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95 changes: 61 additions & 34 deletions arraycontext/impl/pyopencl/fake_numpy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -50,6 +50,10 @@

# {{{ fake numpy

class _NoValue:
pass


class PyOpenCLFakeNumpyNamespace(BaseFakeNumpyNamespace):
def _get_fake_numpy_linalg_namespace(self):
return _PyOpenCLFakeNumpyLinalgNamespace(self._array_context)
Expand DownExpand Up@@ -110,58 +114,81 @@ def where_inner(inner_crit, inner_then, inner_else):

return rec_multimap_array_container(where_inner, criterion, then, else_)

def sum(self, a, axis=None, dtype=None):

@staticmethod
def _map_reduce(reduce_func, map_func,
ary, *,
axis, dtype, initial):
if isinstance(axis, int):
axis = axis,

def _rec_sum(ary):
def _reduce_func(partial_results):
if initial is _NoValue:
try:
return reduce(reduce_func, partial_results)
except TypeError as exc:
if "empty sequence" in str(exc):
raise ValueError("zero-size reduction operation "
"without supplied 'initial' value")
else:
raise
else:
return reduce(reduce_func, partial_results, initial)

def _map_func(ary):
if dtype not in [None, ary.dtype]:
raise NotImplementedError
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Sum over '{axis}' axes not supported.")
raise NotImplementedError(
f"Mapping over '{axis}' axes not supported.")
if initial is _NoValue:
return map_func(ary)
else:
return map_func(ary, initial=initial)

return cl_array.sum(ary, dtype=dtype, queue=self._array_context.queue)
return rec_map_reduce_array_container(
_reduce_func,
_map_func,
ary)

result = rec_map_reduce_array_container(sum, _rec_sum, a)
# * appears where positional signature starts diverging from numpy
def sum(self, a, axis=None, dtype=None, *, initial=0):
queue = self._array_context.queue
import operator
result = self._map_reduce(
operator.add,
partial(cl_array.sum, queue=queue),
a,
axis=axis, dtype=dtype, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
return result

def min(self, a, axis=None):
# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def min(self, a, axis=None, *, initial=_NoValue):
queue = self._array_context.queue

if isinstance(axis, int):
axis = axis,

def _rec_min(ary):
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Min. over '{axis}' axes not supported.")
return cl_array.min(ary, queue=queue)

result = rec_map_reduce_array_container(
partial(reduce, partial(cl_array.minimum, queue=queue)),
_rec_min,
a)
result = self._map_reduce(
partial(cl_array.minimum, queue=queue),
partial(cl_array.min, queue=queue),
a,
axis=axis, dtype=None, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
return result

def max(self, a, axis=None):
# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def max(self, a, axis=None, *, initial=_NoValue):
queue = self._array_context.queue

if isinstance(axis, int):
axis = axis,

def _rec_max(ary):
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Max. over '{axis}' axes not supported.")
return cl_array.max(ary, queue=queue)

result = rec_map_reduce_array_container(
partial(reduce, partial(cl_array.maximum, queue=queue)),
_rec_max,
a)
result = self._map_reduce(
partial(cl_array.maximum, queue=queue),
partial(cl_array.max, queue=queue),
a,
axis=axis, dtype=None, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
Expand Down
62 changes: 50 additions & 12 deletions arraycontext/impl/pytato/fake_numpy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -42,6 +42,10 @@ class PytatoFakeNumpyLinalgNamespace(BaseFakeNumpyLinalgNamespace):
pass


class _NoValue:
pass


class PytatoFakeNumpyNamespace(BaseFakeNumpyNamespace):
"""
A :mod:`numpy` mimic for :class:`PytatoPyOpenCLArrayContext`.
Expand DownExpand Up@@ -91,22 +95,56 @@ def minimum(self, x, y):
def where(self, criterion, then, else_):
return rec_multimap_array_container(pt.where, criterion, then, else_)

def sum(self, a, axis=None, dtype=None):
def _pt_sum(ary):
if dtype not in [ary.dtype, None]:
raise NotImplementedError

return pt.sum(ary, axis=axis)
@staticmethod
def _map_reduce(reduce_func, map_func,
ary, *,
axis, dtype, initial):
def _reduce_func(partial_results):
if initial is _NoValue:
try:
return reduce(reduce_func, partial_results)
except TypeError as exc:
if "empty sequence" in str(exc):
raise ValueError("zero-size reduction operation "
"without supplied 'initial' value")
else:
raise
else:
return reduce(reduce_func, partial_results, initial)

return rec_map_reduce_array_container(sum, _pt_sum, a)
def _map_func(ary):
if dtype not in [None, ary.dtype]:
raise NotImplementedError

def min(self, a, axis=None):
return rec_map_reduce_array_container(
partial(reduce, pt.minimum), partial(pt.amin, axis=axis), a)
if initial is _NoValue:
return map_func(ary, axis=axis)
else:
return map_func(ary, axis=axis, initial=initial)

def max(self, a, axis=None):
return rec_map_reduce_array_container(
partial(reduce, pt.maximum), partial(pt.amax, axis=axis), a)
_reduce_func,
_map_func,
ary)

# * appears where positional signature starts diverging from numpy
def sum(self, a, axis=None, dtype=None, *, initial=0):
import operator
return self._map_reduce(operator.add, pt.sum, a,
axis=axis, dtype=dtype, initial=initial)

# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def min(self, a, axis=None, *, initial=_NoValue):
Comment thread
majosm marked this conversation as resolved.
return self._map_reduce(pt.minimum, pt.amin, a,
axis=axis, dtype=None, initial=initial)

# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def max(self, a, axis=None, *, initial=_NoValue):
return self._map_reduce(pt.maximum, pt.amax, a,
axis=axis, dtype=None, initial=initial)

def stack(self, arrays, axis=0):
return rec_multimap_array_container(
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length \u003e 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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Match numpy interface for empty reductions#136

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Match numpy interface for empty reductions #136

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c677cc9
Unify pytato reduction handling, support 'initial' arg
inducer Dec 28, 2021
4c06f61
Pass on unrelated TypeErrors in pytato reduction handling
inducer Jan 6, 2022
e23a680
flake8
majosm Jan 6, 2022
1f15ae9
explain _NoValue
majosm Jan 6, 2022
d4271f2
cosmetic changes
majosm Jan 6, 2022
994918a
add empty container support to pyopencl's np.[sum,min,max]
majosm Jan 6, 2022
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95 changes: 61 additions & 34 deletions arraycontext/impl/pyopencl/fake_numpy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -50,6 +50,10 @@

# {{{ fake numpy

class _NoValue:
pass


class PyOpenCLFakeNumpyNamespace(BaseFakeNumpyNamespace):
def _get_fake_numpy_linalg_namespace(self):
return _PyOpenCLFakeNumpyLinalgNamespace(self._array_context)
Expand DownExpand Up@@ -110,58 +114,81 @@ def where_inner(inner_crit, inner_then, inner_else):

return rec_multimap_array_container(where_inner, criterion, then, else_)

def sum(self, a, axis=None, dtype=None):

@staticmethod
def _map_reduce(reduce_func, map_func,
ary, *,
axis, dtype, initial):
if isinstance(axis, int):
axis = axis,

def _rec_sum(ary):
def _reduce_func(partial_results):
if initial is _NoValue:
try:
return reduce(reduce_func, partial_results)
except TypeError as exc:
if "empty sequence" in str(exc):
raise ValueError("zero-size reduction operation "
"without supplied 'initial' value")
else:
raise
else:
return reduce(reduce_func, partial_results, initial)

def _map_func(ary):
if dtype not in [None, ary.dtype]:
raise NotImplementedError
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Sum over '{axis}' axes not supported.")
raise NotImplementedError(
f"Mapping over '{axis}' axes not supported.")
if initial is _NoValue:
return map_func(ary)
else:
return map_func(ary, initial=initial)

return cl_array.sum(ary, dtype=dtype, queue=self._array_context.queue)
return rec_map_reduce_array_container(
_reduce_func,
_map_func,
ary)

result = rec_map_reduce_array_container(sum, _rec_sum, a)
# * appears where positional signature starts diverging from numpy
def sum(self, a, axis=None, dtype=None, *, initial=0):
queue = self._array_context.queue
import operator
result = self._map_reduce(
operator.add,
partial(cl_array.sum, queue=queue),
a,
axis=axis, dtype=dtype, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
return result

def min(self, a, axis=None):
# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def min(self, a, axis=None, *, initial=_NoValue):
queue = self._array_context.queue

if isinstance(axis, int):
axis = axis,

def _rec_min(ary):
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Min. over '{axis}' axes not supported.")
return cl_array.min(ary, queue=queue)

result = rec_map_reduce_array_container(
partial(reduce, partial(cl_array.minimum, queue=queue)),
_rec_min,
a)
result = self._map_reduce(
partial(cl_array.minimum, queue=queue),
partial(cl_array.min, queue=queue),
a,
axis=axis, dtype=None, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
return result

def max(self, a, axis=None):
# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def max(self, a, axis=None, *, initial=_NoValue):
queue = self._array_context.queue

if isinstance(axis, int):
axis = axis,

def _rec_max(ary):
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Max. over '{axis}' axes not supported.")
return cl_array.max(ary, queue=queue)

result = rec_map_reduce_array_container(
partial(reduce, partial(cl_array.maximum, queue=queue)),
_rec_max,
a)
result = self._map_reduce(
partial(cl_array.maximum, queue=queue),
partial(cl_array.max, queue=queue),
a,
axis=axis, dtype=None, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
Expand Down
62 changes: 50 additions & 12 deletions arraycontext/impl/pytato/fake_numpy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -42,6 +42,10 @@ class PytatoFakeNumpyLinalgNamespace(BaseFakeNumpyLinalgNamespace):
pass


class _NoValue:
pass


class PytatoFakeNumpyNamespace(BaseFakeNumpyNamespace):
"""
A :mod:`numpy` mimic for :class:`PytatoPyOpenCLArrayContext`.
Expand DownExpand Up@@ -91,22 +95,56 @@ def minimum(self, x, y):
def where(self, criterion, then, else_):
return rec_multimap_array_container(pt.where, criterion, then, else_)

def sum(self, a, axis=None, dtype=None):
def _pt_sum(ary):
if dtype not in [ary.dtype, None]:
raise NotImplementedError

return pt.sum(ary, axis=axis)
@staticmethod
def _map_reduce(reduce_func, map_func,
ary, *,
axis, dtype, initial):
def _reduce_func(partial_results):
if initial is _NoValue:
try:
return reduce(reduce_func, partial_results)
except TypeError as exc:
if "empty sequence" in str(exc):
raise ValueError("zero-size reduction operation "
"without supplied 'initial' value")
else:
raise
else:
return reduce(reduce_func, partial_results, initial)

return rec_map_reduce_array_container(sum, _pt_sum, a)
def _map_func(ary):
if dtype not in [None, ary.dtype]:
raise NotImplementedError

def min(self, a, axis=None):
return rec_map_reduce_array_container(
partial(reduce, pt.minimum), partial(pt.amin, axis=axis), a)
if initial is _NoValue:
return map_func(ary, axis=axis)
else:
return map_func(ary, axis=axis, initial=initial)

def max(self, a, axis=None):
return rec_map_reduce_array_container(
partial(reduce, pt.maximum), partial(pt.amax, axis=axis), a)
_reduce_func,
_map_func,
ary)

# * appears where positional signature starts diverging from numpy
def sum(self, a, axis=None, dtype=None, *, initial=0):
import operator
return self._map_reduce(operator.add, pt.sum, a,
axis=axis, dtype=dtype, initial=initial)

# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def min(self, a, axis=None, *, initial=_NoValue):
Comment thread
majosm marked this conversation as resolved.
return self._map_reduce(pt.minimum, pt.amin, a,
axis=axis, dtype=None, initial=initial)

# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def max(self, a, axis=None, *, initial=_NoValue):
return self._map_reduce(pt.maximum, pt.amax, a,
axis=axis, dtype=None, initial=initial)

def stack(self, arrays, axis=0):
return rec_multimap_array_container(
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
Skip to content

Match numpy interface for empty reductions#136

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Draft
inducer wants to merge 6 commits into
base:main
Choose a base branch
from
Draft

Match numpy interface for empty reductions #136

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Commits
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6 commits
Select commit Hold shift + click to select a range
c677cc9
Unify pytato reduction handling, support 'initial' arg
inducer Dec 28, 2021
4c06f61
Pass on unrelated TypeErrors in pytato reduction handling
inducer Jan 6, 2022
e23a680
flake8
majosm Jan 6, 2022
1f15ae9
explain _NoValue
majosm Jan 6, 2022
d4271f2
cosmetic changes
majosm Jan 6, 2022
994918a
add empty container support to pyopencl's np.[sum,min,max]
majosm Jan 6, 2022
File filter

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95 changes: 61 additions & 34 deletions arraycontext/impl/pyopencl/fake_numpy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -50,6 +50,10 @@

# {{{ fake numpy

class _NoValue:
pass


class PyOpenCLFakeNumpyNamespace(BaseFakeNumpyNamespace):
def _get_fake_numpy_linalg_namespace(self):
return _PyOpenCLFakeNumpyLinalgNamespace(self._array_context)
Expand DownExpand Up@@ -110,58 +114,81 @@ def where_inner(inner_crit, inner_then, inner_else):

return rec_multimap_array_container(where_inner, criterion, then, else_)

def sum(self, a, axis=None, dtype=None):

@staticmethod
def _map_reduce(reduce_func, map_func,
ary, *,
axis, dtype, initial):
if isinstance(axis, int):
axis = axis,

def _rec_sum(ary):
def _reduce_func(partial_results):
if initial is _NoValue:
try:
return reduce(reduce_func, partial_results)
except TypeError as exc:
if "empty sequence" in str(exc):
raise ValueError("zero-size reduction operation "
"without supplied 'initial' value")
else:
raise
else:
return reduce(reduce_func, partial_results, initial)

def _map_func(ary):
if dtype not in [None, ary.dtype]:
raise NotImplementedError
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Sum over '{axis}' axes not supported.")
raise NotImplementedError(
f"Mapping over '{axis}' axes not supported.")
if initial is _NoValue:
return map_func(ary)
else:
return map_func(ary, initial=initial)

return cl_array.sum(ary, dtype=dtype, queue=self._array_context.queue)
return rec_map_reduce_array_container(
_reduce_func,
_map_func,
ary)

result = rec_map_reduce_array_container(sum, _rec_sum, a)
# * appears where positional signature starts diverging from numpy
def sum(self, a, axis=None, dtype=None, *, initial=0):
queue = self._array_context.queue
import operator
result = self._map_reduce(
operator.add,
partial(cl_array.sum, queue=queue),
a,
axis=axis, dtype=dtype, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
return result

def min(self, a, axis=None):
# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def min(self, a, axis=None, *, initial=_NoValue):
queue = self._array_context.queue

if isinstance(axis, int):
axis = axis,

def _rec_min(ary):
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Min. over '{axis}' axes not supported.")
return cl_array.min(ary, queue=queue)

result = rec_map_reduce_array_container(
partial(reduce, partial(cl_array.minimum, queue=queue)),
_rec_min,
a)
result = self._map_reduce(
partial(cl_array.minimum, queue=queue),
partial(cl_array.min, queue=queue),
a,
axis=axis, dtype=None, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
return result

def max(self, a, axis=None):
# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def max(self, a, axis=None, *, initial=_NoValue):
queue = self._array_context.queue

if isinstance(axis, int):
axis = axis,

def _rec_max(ary):
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Max. over '{axis}' axes not supported.")
return cl_array.max(ary, queue=queue)

result = rec_map_reduce_array_container(
partial(reduce, partial(cl_array.maximum, queue=queue)),
_rec_max,
a)
result = self._map_reduce(
partial(cl_array.maximum, queue=queue),
partial(cl_array.max, queue=queue),
a,
axis=axis, dtype=None, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
Expand Down
62 changes: 50 additions & 12 deletions arraycontext/impl/pytato/fake_numpy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -42,6 +42,10 @@ class PytatoFakeNumpyLinalgNamespace(BaseFakeNumpyLinalgNamespace):
pass


class _NoValue:
pass


class PytatoFakeNumpyNamespace(BaseFakeNumpyNamespace):
"""
A :mod:`numpy` mimic for :class:`PytatoPyOpenCLArrayContext`.
Expand DownExpand Up@@ -91,22 +95,56 @@ def minimum(self, x, y):
def where(self, criterion, then, else_):
return rec_multimap_array_container(pt.where, criterion, then, else_)

def sum(self, a, axis=None, dtype=None):
def _pt_sum(ary):
if dtype not in [ary.dtype, None]:
raise NotImplementedError

return pt.sum(ary, axis=axis)
@staticmethod
def _map_reduce(reduce_func, map_func,
ary, *,
axis, dtype, initial):
def _reduce_func(partial_results):
if initial is _NoValue:
try:
return reduce(reduce_func, partial_results)
except TypeError as exc:
if "empty sequence" in str(exc):
raise ValueError("zero-size reduction operation "
"without supplied 'initial' value")
else:
raise
else:
return reduce(reduce_func, partial_results, initial)

return rec_map_reduce_array_container(sum, _pt_sum, a)
def _map_func(ary):
if dtype not in [None, ary.dtype]:
raise NotImplementedError

def min(self, a, axis=None):
return rec_map_reduce_array_container(
partial(reduce, pt.minimum), partial(pt.amin, axis=axis), a)
if initial is _NoValue:
return map_func(ary, axis=axis)
else:
return map_func(ary, axis=axis, initial=initial)

def max(self, a, axis=None):
return rec_map_reduce_array_container(
partial(reduce, pt.maximum), partial(pt.amax, axis=axis), a)
_reduce_func,
_map_func,
ary)

# * appears where positional signature starts diverging from numpy
def sum(self, a, axis=None, dtype=None, *, initial=0):
import operator
return self._map_reduce(operator.add, pt.sum, a,
axis=axis, dtype=dtype, initial=initial)

# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def min(self, a, axis=None, *, initial=_NoValue):
Comment thread
majosm marked this conversation as resolved.
return self._map_reduce(pt.minimum, pt.amin, a,
axis=axis, dtype=None, initial=initial)

# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def max(self, a, axis=None, *, initial=_NoValue):
return self._map_reduce(pt.maximum, pt.amax, a,
axis=axis, dtype=None, initial=initial)

def stack(self, arrays, axis=0):
return rec_multimap_array_container(
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

Match numpy interface for empty reductions#136

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Draft
inducer wants to merge 6 commits into
base:main
Choose a base branch
from
Draft

Match numpy interface for empty reductions #136

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
c677cc9
Unify pytato reduction handling, support 'initial' arg
inducer Dec 28, 2021
4c06f61
Pass on unrelated TypeErrors in pytato reduction handling
inducer Jan 6, 2022
e23a680
flake8
majosm Jan 6, 2022
1f15ae9
explain _NoValue
majosm Jan 6, 2022
d4271f2
cosmetic changes
majosm Jan 6, 2022
994918a
add empty container support to pyopencl's np.[sum,min,max]
majosm Jan 6, 2022
File filter

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Conversations
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Failed to load files.
Loading
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Diff view
95 changes: 61 additions & 34 deletions arraycontext/impl/pyopencl/fake_numpy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -50,6 +50,10 @@

# {{{ fake numpy

class _NoValue:
pass


class PyOpenCLFakeNumpyNamespace(BaseFakeNumpyNamespace):
def _get_fake_numpy_linalg_namespace(self):
return _PyOpenCLFakeNumpyLinalgNamespace(self._array_context)
Expand DownExpand Up@@ -110,58 +114,81 @@ def where_inner(inner_crit, inner_then, inner_else):

return rec_multimap_array_container(where_inner, criterion, then, else_)

def sum(self, a, axis=None, dtype=None):

@staticmethod
def _map_reduce(reduce_func, map_func,
ary, *,
axis, dtype, initial):
if isinstance(axis, int):
axis = axis,

def _rec_sum(ary):
def _reduce_func(partial_results):
if initial is _NoValue:
try:
return reduce(reduce_func, partial_results)
except TypeError as exc:
if "empty sequence" in str(exc):
raise ValueError("zero-size reduction operation "
"without supplied 'initial' value")
else:
raise
else:
return reduce(reduce_func, partial_results, initial)

def _map_func(ary):
if dtype not in [None, ary.dtype]:
raise NotImplementedError
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Sum over '{axis}' axes not supported.")
raise NotImplementedError(
f"Mapping over '{axis}' axes not supported.")
if initial is _NoValue:
return map_func(ary)
else:
return map_func(ary, initial=initial)

return cl_array.sum(ary, dtype=dtype, queue=self._array_context.queue)
return rec_map_reduce_array_container(
_reduce_func,
_map_func,
ary)

result = rec_map_reduce_array_container(sum, _rec_sum, a)
# * appears where positional signature starts diverging from numpy
def sum(self, a, axis=None, dtype=None, *, initial=0):
queue = self._array_context.queue
import operator
result = self._map_reduce(
operator.add,
partial(cl_array.sum, queue=queue),
a,
axis=axis, dtype=dtype, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
return result

def min(self, a, axis=None):
# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def min(self, a, axis=None, *, initial=_NoValue):
queue = self._array_context.queue

if isinstance(axis, int):
axis = axis,

def _rec_min(ary):
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Min. over '{axis}' axes not supported.")
return cl_array.min(ary, queue=queue)

result = rec_map_reduce_array_container(
partial(reduce, partial(cl_array.minimum, queue=queue)),
_rec_min,
a)
result = self._map_reduce(
partial(cl_array.minimum, queue=queue),
partial(cl_array.min, queue=queue),
a,
axis=axis, dtype=None, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
return result

def max(self, a, axis=None):
# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def max(self, a, axis=None, *, initial=_NoValue):
queue = self._array_context.queue

if isinstance(axis, int):
axis = axis,

def _rec_max(ary):
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Max. over '{axis}' axes not supported.")
return cl_array.max(ary, queue=queue)

result = rec_map_reduce_array_container(
partial(reduce, partial(cl_array.maximum, queue=queue)),
_rec_max,
a)
result = self._map_reduce(
partial(cl_array.maximum, queue=queue),
partial(cl_array.max, queue=queue),
a,
axis=axis, dtype=None, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
Expand Down
62 changes: 50 additions & 12 deletions arraycontext/impl/pytato/fake_numpy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -42,6 +42,10 @@ class PytatoFakeNumpyLinalgNamespace(BaseFakeNumpyLinalgNamespace):
pass


class _NoValue:
pass


class PytatoFakeNumpyNamespace(BaseFakeNumpyNamespace):
"""
A :mod:`numpy` mimic for :class:`PytatoPyOpenCLArrayContext`.
Expand DownExpand Up@@ -91,22 +95,56 @@ def minimum(self, x, y):
def where(self, criterion, then, else_):
return rec_multimap_array_container(pt.where, criterion, then, else_)

def sum(self, a, axis=None, dtype=None):
def _pt_sum(ary):
if dtype not in [ary.dtype, None]:
raise NotImplementedError

return pt.sum(ary, axis=axis)
@staticmethod
def _map_reduce(reduce_func, map_func,
ary, *,
axis, dtype, initial):
def _reduce_func(partial_results):
if initial is _NoValue:
try:
return reduce(reduce_func, partial_results)
except TypeError as exc:
if "empty sequence" in str(exc):
raise ValueError("zero-size reduction operation "
"without supplied 'initial' value")
else:
raise
else:
return reduce(reduce_func, partial_results, initial)

return rec_map_reduce_array_container(sum, _pt_sum, a)
def _map_func(ary):
if dtype not in [None, ary.dtype]:
raise NotImplementedError

def min(self, a, axis=None):
return rec_map_reduce_array_container(
partial(reduce, pt.minimum), partial(pt.amin, axis=axis), a)
if initial is _NoValue:
return map_func(ary, axis=axis)
else:
return map_func(ary, axis=axis, initial=initial)

def max(self, a, axis=None):
return rec_map_reduce_array_container(
partial(reduce, pt.maximum), partial(pt.amax, axis=axis), a)
_reduce_func,
_map_func,
ary)

# * appears where positional signature starts diverging from numpy
def sum(self, a, axis=None, dtype=None, *, initial=0):
import operator
return self._map_reduce(operator.add, pt.sum, a,
axis=axis, dtype=dtype, initial=initial)

# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def min(self, a, axis=None, *, initial=_NoValue):
Comment thread
majosm marked this conversation as resolved.
return self._map_reduce(pt.minimum, pt.amin, a,
axis=axis, dtype=None, initial=initial)

# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def max(self, a, axis=None, *, initial=_NoValue):
return self._map_reduce(pt.maximum, pt.amax, a,
axis=axis, dtype=None, initial=initial)

def stack(self, arrays, axis=0):
return rec_multimap_array_container(
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

Match numpy interface for empty reductions#136

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Draft
inducer wants to merge 6 commits into
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Match numpy interface for empty reductions #136

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c677cc9
Unify pytato reduction handling, support 'initial' arg
inducer Dec 28, 2021
4c06f61
Pass on unrelated TypeErrors in pytato reduction handling
inducer Jan 6, 2022
e23a680
flake8
majosm Jan 6, 2022
1f15ae9
explain _NoValue
majosm Jan 6, 2022
d4271f2
cosmetic changes
majosm Jan 6, 2022
994918a
add empty container support to pyopencl's np.[sum,min,max]
majosm Jan 6, 2022
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95 changes: 61 additions & 34 deletions arraycontext/impl/pyopencl/fake_numpy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -50,6 +50,10 @@

# {{{ fake numpy

class _NoValue:
pass


class PyOpenCLFakeNumpyNamespace(BaseFakeNumpyNamespace):
def _get_fake_numpy_linalg_namespace(self):
return _PyOpenCLFakeNumpyLinalgNamespace(self._array_context)
Expand DownExpand Up@@ -110,58 +114,81 @@ def where_inner(inner_crit, inner_then, inner_else):

return rec_multimap_array_container(where_inner, criterion, then, else_)

def sum(self, a, axis=None, dtype=None):

@staticmethod
def _map_reduce(reduce_func, map_func,
ary, *,
axis, dtype, initial):
if isinstance(axis, int):
axis = axis,

def _rec_sum(ary):
def _reduce_func(partial_results):
if initial is _NoValue:
try:
return reduce(reduce_func, partial_results)
except TypeError as exc:
if "empty sequence" in str(exc):
raise ValueError("zero-size reduction operation "
"without supplied 'initial' value")
else:
raise
else:
return reduce(reduce_func, partial_results, initial)

def _map_func(ary):
if dtype not in [None, ary.dtype]:
raise NotImplementedError
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Sum over '{axis}' axes not supported.")
raise NotImplementedError(
f"Mapping over '{axis}' axes not supported.")
if initial is _NoValue:
return map_func(ary)
else:
return map_func(ary, initial=initial)

return cl_array.sum(ary, dtype=dtype, queue=self._array_context.queue)
return rec_map_reduce_array_container(
_reduce_func,
_map_func,
ary)

result = rec_map_reduce_array_container(sum, _rec_sum, a)
# * appears where positional signature starts diverging from numpy
def sum(self, a, axis=None, dtype=None, *, initial=0):
queue = self._array_context.queue
import operator
result = self._map_reduce(
operator.add,
partial(cl_array.sum, queue=queue),
a,
axis=axis, dtype=dtype, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
return result

def min(self, a, axis=None):
# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def min(self, a, axis=None, *, initial=_NoValue):
queue = self._array_context.queue

if isinstance(axis, int):
axis = axis,

def _rec_min(ary):
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Min. over '{axis}' axes not supported.")
return cl_array.min(ary, queue=queue)

result = rec_map_reduce_array_container(
partial(reduce, partial(cl_array.minimum, queue=queue)),
_rec_min,
a)
result = self._map_reduce(
partial(cl_array.minimum, queue=queue),
partial(cl_array.min, queue=queue),
a,
axis=axis, dtype=None, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
return result

def max(self, a, axis=None):
# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def max(self, a, axis=None, *, initial=_NoValue):
queue = self._array_context.queue

if isinstance(axis, int):
axis = axis,

def _rec_max(ary):
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Max. over '{axis}' axes not supported.")
return cl_array.max(ary, queue=queue)

result = rec_map_reduce_array_container(
partial(reduce, partial(cl_array.maximum, queue=queue)),
_rec_max,
a)
result = self._map_reduce(
partial(cl_array.maximum, queue=queue),
partial(cl_array.max, queue=queue),
a,
axis=axis, dtype=None, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
Expand Down
62 changes: 50 additions & 12 deletions arraycontext/impl/pytato/fake_numpy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -42,6 +42,10 @@ class PytatoFakeNumpyLinalgNamespace(BaseFakeNumpyLinalgNamespace):
pass


class _NoValue:
pass


class PytatoFakeNumpyNamespace(BaseFakeNumpyNamespace):
"""
A :mod:`numpy` mimic for :class:`PytatoPyOpenCLArrayContext`.
Expand DownExpand Up@@ -91,22 +95,56 @@ def minimum(self, x, y):
def where(self, criterion, then, else_):
return rec_multimap_array_container(pt.where, criterion, then, else_)

def sum(self, a, axis=None, dtype=None):
def _pt_sum(ary):
if dtype not in [ary.dtype, None]:
raise NotImplementedError

return pt.sum(ary, axis=axis)
@staticmethod
def _map_reduce(reduce_func, map_func,
ary, *,
axis, dtype, initial):
def _reduce_func(partial_results):
if initial is _NoValue:
try:
return reduce(reduce_func, partial_results)
except TypeError as exc:
if "empty sequence" in str(exc):
raise ValueError("zero-size reduction operation "
"without supplied 'initial' value")
else:
raise
else:
return reduce(reduce_func, partial_results, initial)

return rec_map_reduce_array_container(sum, _pt_sum, a)
def _map_func(ary):
if dtype not in [None, ary.dtype]:
raise NotImplementedError

def min(self, a, axis=None):
return rec_map_reduce_array_container(
partial(reduce, pt.minimum), partial(pt.amin, axis=axis), a)
if initial is _NoValue:
return map_func(ary, axis=axis)
else:
return map_func(ary, axis=axis, initial=initial)

def max(self, a, axis=None):
return rec_map_reduce_array_container(
partial(reduce, pt.maximum), partial(pt.amax, axis=axis), a)
_reduce_func,
_map_func,
ary)

# * appears where positional signature starts diverging from numpy
def sum(self, a, axis=None, dtype=None, *, initial=0):
import operator
return self._map_reduce(operator.add, pt.sum, a,
axis=axis, dtype=dtype, initial=initial)

# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def min(self, a, axis=None, *, initial=_NoValue):
Comment thread
majosm marked this conversation as resolved.
return self._map_reduce(pt.minimum, pt.amin, a,
axis=axis, dtype=None, initial=initial)

# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def max(self, a, axis=None, *, initial=_NoValue):
return self._map_reduce(pt.maximum, pt.amax, a,
axis=axis, dtype=None, initial=initial)

def stack(self, arrays, axis=0):
return rec_multimap_array_container(
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode"); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
Skip to content

Match numpy interface for empty reductions#136

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Draft
inducer wants to merge 6 commits into
base:main
Choose a base branch
from
Draft

Match numpy interface for empty reductions #136

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Hide file tree
Changes from all commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
c677cc9
Unify pytato reduction handling, support 'initial' arg
inducer Dec 28, 2021
4c06f61
Pass on unrelated TypeErrors in pytato reduction handling
inducer Jan 6, 2022
e23a680
flake8
majosm Jan 6, 2022
1f15ae9
explain _NoValue
majosm Jan 6, 2022
d4271f2
cosmetic changes
majosm Jan 6, 2022
994918a
add empty container support to pyopencl's np.[sum,min,max]
majosm Jan 6, 2022
File filter

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95 changes: 61 additions & 34 deletions arraycontext/impl/pyopencl/fake_numpy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -50,6 +50,10 @@

# {{{ fake numpy

class _NoValue:
pass


class PyOpenCLFakeNumpyNamespace(BaseFakeNumpyNamespace):
def _get_fake_numpy_linalg_namespace(self):
return _PyOpenCLFakeNumpyLinalgNamespace(self._array_context)
Expand DownExpand Up@@ -110,58 +114,81 @@ def where_inner(inner_crit, inner_then, inner_else):

return rec_multimap_array_container(where_inner, criterion, then, else_)

def sum(self, a, axis=None, dtype=None):

@staticmethod
def _map_reduce(reduce_func, map_func,
ary, *,
axis, dtype, initial):
if isinstance(axis, int):
axis = axis,

def _rec_sum(ary):
def _reduce_func(partial_results):
if initial is _NoValue:
try:
return reduce(reduce_func, partial_results)
except TypeError as exc:
if "empty sequence" in str(exc):
raise ValueError("zero-size reduction operation "
"without supplied 'initial' value")
else:
raise
else:
return reduce(reduce_func, partial_results, initial)

def _map_func(ary):
if dtype not in [None, ary.dtype]:
raise NotImplementedError
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Sum over '{axis}' axes not supported.")
raise NotImplementedError(
f"Mapping over '{axis}' axes not supported.")
if initial is _NoValue:
return map_func(ary)
else:
return map_func(ary, initial=initial)

return cl_array.sum(ary, dtype=dtype, queue=self._array_context.queue)
return rec_map_reduce_array_container(
_reduce_func,
_map_func,
ary)

result = rec_map_reduce_array_container(sum, _rec_sum, a)
# * appears where positional signature starts diverging from numpy
def sum(self, a, axis=None, dtype=None, *, initial=0):
queue = self._array_context.queue
import operator
result = self._map_reduce(
operator.add,
partial(cl_array.sum, queue=queue),
a,
axis=axis, dtype=dtype, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
return result

def min(self, a, axis=None):
# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def min(self, a, axis=None, *, initial=_NoValue):
queue = self._array_context.queue

if isinstance(axis, int):
axis = axis,

def _rec_min(ary):
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Min. over '{axis}' axes not supported.")
return cl_array.min(ary, queue=queue)

result = rec_map_reduce_array_container(
partial(reduce, partial(cl_array.minimum, queue=queue)),
_rec_min,
a)
result = self._map_reduce(
partial(cl_array.minimum, queue=queue),
partial(cl_array.min, queue=queue),
a,
axis=axis, dtype=None, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
return result

def max(self, a, axis=None):
# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def max(self, a, axis=None, *, initial=_NoValue):
queue = self._array_context.queue

if isinstance(axis, int):
axis = axis,

def _rec_max(ary):
if axis not in [None, tuple(range(ary.ndim))]:
raise NotImplementedError(f"Max. over '{axis}' axes not supported.")
return cl_array.max(ary, queue=queue)

result = rec_map_reduce_array_container(
partial(reduce, partial(cl_array.maximum, queue=queue)),
_rec_max,
a)
result = self._map_reduce(
partial(cl_array.maximum, queue=queue),
partial(cl_array.max, queue=queue),
a,
axis=axis, dtype=None, initial=initial)

if not self._array_context._force_device_scalars:
result = result.get()[()]
Expand Down
62 changes: 50 additions & 12 deletions arraycontext/impl/pytato/fake_numpy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -42,6 +42,10 @@ class PytatoFakeNumpyLinalgNamespace(BaseFakeNumpyLinalgNamespace):
pass


class _NoValue:
pass


class PytatoFakeNumpyNamespace(BaseFakeNumpyNamespace):
"""
A :mod:`numpy` mimic for :class:`PytatoPyOpenCLArrayContext`.
Expand DownExpand Up@@ -91,22 +95,56 @@ def minimum(self, x, y):
def where(self, criterion, then, else_):
return rec_multimap_array_container(pt.where, criterion, then, else_)

def sum(self, a, axis=None, dtype=None):
def _pt_sum(ary):
if dtype not in [ary.dtype, None]:
raise NotImplementedError

return pt.sum(ary, axis=axis)
@staticmethod
def _map_reduce(reduce_func, map_func,
ary, *,
axis, dtype, initial):
def _reduce_func(partial_results):
if initial is _NoValue:
try:
return reduce(reduce_func, partial_results)
except TypeError as exc:
if "empty sequence" in str(exc):
raise ValueError("zero-size reduction operation "
"without supplied 'initial' value")
else:
raise
else:
return reduce(reduce_func, partial_results, initial)

return rec_map_reduce_array_container(sum, _pt_sum, a)
def _map_func(ary):
if dtype not in [None, ary.dtype]:
raise NotImplementedError

def min(self, a, axis=None):
return rec_map_reduce_array_container(
partial(reduce, pt.minimum), partial(pt.amin, axis=axis), a)
if initial is _NoValue:
return map_func(ary, axis=axis)
else:
return map_func(ary, axis=axis, initial=initial)

def max(self, a, axis=None):
return rec_map_reduce_array_container(
partial(reduce, pt.maximum), partial(pt.amax, axis=axis), a)
_reduce_func,
_map_func,
ary)

# * appears where positional signature starts diverging from numpy
def sum(self, a, axis=None, dtype=None, *, initial=0):
import operator
return self._map_reduce(operator.add, pt.sum, a,
axis=axis, dtype=dtype, initial=initial)

# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def min(self, a, axis=None, *, initial=_NoValue):
Comment thread
majosm marked this conversation as resolved.
return self._map_reduce(pt.minimum, pt.amin, a,
axis=axis, dtype=None, initial=initial)

# * appears where positional signature starts diverging from numpy
# Use _NoValue to indicate a lack of neutral element so that the caller can
# use None as a neutral element
def max(self, a, axis=None, *, initial=_NoValue):
return self._map_reduce(pt.maximum, pt.amax, a,
axis=axis, dtype=None, initial=initial)

def stack(self, arrays, axis=0):
return rec_multimap_array_container(
Expand Down