From b50249339cfde1279c5c98afbbe376a8c9df3408 Mon Sep 17 00:00:00 2001
From: jdsteve2 <jdsteve2@illinois.edu>
Date: Tue, 20 Feb 2018 03:35:37 -0600
Subject: [PATCH] made docstring indentation more consistent
---
loopy/statistics.py | 133 ++++++++++++++++++++++----------------------
1 file changed, 67 insertions(+), 66 deletions(-)
diff --git a/loopy/statistics.py b/loopy/statistics.py
index d9bbd4b24..a63ee41ad 100755
--- a/loopy/statistics.py
+++ b/loopy/statistics.py
@@ -208,13 +208,13 @@ class ToCountMap(object):
def filter_by(self, **kwargs):
"""Remove items without specified key fields.
- :arg kwargs: Keyword arguments matching fields in the keys of
- the :class:`ToCountMap`, each given a list of
- allowable values for that key field.
+ :arg kwargs: Keyword arguments matching fields in the keys of the
+ :class:`ToCountMap`, each given a list of allowable values for that
+ key field.
:return: A :class:`ToCountMap` containing the subset of the items in
- the original :class:`ToCountMap` that match the field values
- passed.
+ the original :class:`ToCountMap` that match the field values
+ passed.
Example usage::
@@ -256,11 +256,11 @@ class ToCountMap(object):
def filter_by_func(self, func):
"""Keep items that pass a test.
- :arg func: A function that takes a map key a parameter and
- returns a :class:`bool`.
+ :arg func: A function that takes a map key a parameter and returns a
+ :class:`bool`.
- :arg: A :class:`ToCountMap` containing the subset of the items in
- the original :class:`ToCountMap` for which func(key) is true.
+ :arg: A :class:`ToCountMap` containing the subset of the items in the
+ original :class:`ToCountMap` for which func(key) is true.
Example usage::
@@ -289,13 +289,13 @@ class ToCountMap(object):
def group_by(self, *args):
"""Group map items together, distinguishing by only the key fields
- passed in args.
+ passed in args.
:arg args: Zero or more :class:`str` fields of map keys.
- :return: A :class:`ToCountMap` containing the same total counts
- grouped together by new keys that only contain the fields
- specified in the arguments passed.
+ :return: A :class:`ToCountMap` containing the same total counts grouped
+ together by new keys that only contain the fields specified in the
+ arguments passed.
Example usage::
@@ -363,8 +363,8 @@ class ToCountMap(object):
"""Convert counts to bytes using data type in map key.
:return: A :class:`ToCountMap` mapping each original key to a
- :class:`islpy.PwQPolynomial` with counts in bytes rather than
- instances.
+ :class:`islpy.PwQPolynomial` with counts in bytes rather than
+ instances.
Example usage::
@@ -404,8 +404,8 @@ class ToCountMap(object):
def sum(self):
"""Add all counts in ToCountMap.
- :return: A :class:`islpy.PwQPolynomial` or :class:`int` containing the sum of
- counts.
+ :return: A :class:`islpy.PwQPolynomial` or :class:`int` containing the
+ sum of counts.
"""
@@ -431,7 +431,7 @@ class ToCountMap(object):
parameter dict.
:return: An :class:`int` containing the sum of all counts in the
- :class:`ToCountMap` evaluated with the parameters provided.
+ :class:`ToCountMap` evaluated with the parameters provided.
Example usage::
@@ -502,11 +502,12 @@ class Op(Record):
A :class:`str` that specifies whether this operation should be counted
once per *work-item*, *sub-group*, or *group*. A work-item is a single
- instance of computation executing on a single processor (think 'thread'),
- a collection of which may be grouped together into a work-group. Each
- work-group executes on a single compute unit with all work-items within
- the group sharing local memory. A sub-group is an implementation-dependent
- grouping of work-items within a work-group, analagous to an NVIDIA CUDA warp.
+ instance of computation executing on a single processor (think
+ 'thread'), a collection of which may be grouped together into a
+ work-group. Each work-group executes on a single compute unit with all
+ work-items within the group sharing local memory. A sub-group is an
+ implementation-dependent grouping of work-items within a work-group,
+ analagous to an NVIDIA CUDA warp.
"""
@@ -555,8 +556,8 @@ class MemAccess(Record):
.. attribute:: stride
- An :class:`int` that specifies stride of the memory access. A stride of 0
- indicates a uniform access (i.e. all work-items access the same item).
+ An :class:`int` that specifies stride of the memory access. A stride of
+ 0 indicates a uniform access (i.e. all work-items access the same item).
.. attribute:: direction
@@ -1229,15 +1230,15 @@ def get_op_map(knl, numpy_types=True, count_redundant_work=False,
:arg knl: A :class:`loopy.LoopKernel` whose operations are to be counted.
- :arg numpy_types: A :class:`bool` specifying whether the types
- in the returned mapping should be numpy types
- instead of :class:`loopy.LoopyType`.
+ :arg numpy_types: A :class:`bool` specifying whether the types in the
+ returned mapping should be numpy types instead of
+ :class:`loopy.LoopyType`.
:arg count_redundant_work: Based on usage of hardware axes or other
specifics, a kernel may perform work redundantly. This :class:`bool`
flag indicates whether this work should be included in the count.
- (Likely desirable for performance modeling, but undesirable for
- code optimization.)
+ (Likely desirable for performance modeling, but undesirable for code
+ optimization.)
:return: A :class:`ToCountMap` of **{** :class:`Op` **:**
:class:`islpy.PwQPolynomial` **}**.
@@ -1315,9 +1316,9 @@ def get_mem_access_map(knl, numpy_types=True, count_redundant_work=False,
:arg knl: A :class:`loopy.LoopKernel` whose memory accesses are to be
counted.
- :arg numpy_types: A :class:`bool` specifying whether the types
- in the returned mapping should be numpy types
- instead of :class:`loopy.LoopyType`.
+ :arg numpy_types: A :class:`bool` specifying whether the types in the
+ returned mapping should be numpy types instead of
+ :class:`loopy.LoopyType`.
:arg count_redundant_work: Based on usage of hardware axes or other
specifics, a kernel may perform work redundantly. This :class:`bool`
@@ -1325,25 +1326,26 @@ def get_mem_access_map(knl, numpy_types=True, count_redundant_work=False,
(Likely desirable for performance modeling, but undesirable for
code optimization.)
- :arg subgroup_size: A :class:`int` that specifies the sub-group size. An OpenCL
- sub-group is an implementation-dependent grouping of work-items within a
- work-group, analagous to an NVIDIA CUDA warp. subgroup_size is used, e.g.,
- when counting a :class:`MemAccess` whose count_granularity specifies that it
- should only be counted once per sub-group. If set to None an attempt to find
- the sub-group size using the device will be made. A :class:`string` 'guess'
- may also be passed as the subgroup_size, in which case get_mem_access_map
- will attempt to find the sub-group sizeusing the device and, if
- unsuccessful, will make a wild guess.
+ :arg subgroup_size: A :class:`int` that specifies the sub-group size. An
+ OpenCL sub-group is an implementation-dependent grouping of work-items
+ within a work-group, analagous to an NVIDIA CUDA warp. subgroup_size is
+ used, e.g., when counting a :class:`MemAccess` whose count_granularity
+ specifies that it should only be counted once per sub-group. If set to
+ None an attempt to find the sub-group size using the device will be
+ made. A :class:`string` 'guess' may also be passed as the
+ subgroup_size, in which case get_mem_access_map will attempt to find
+ the sub-group sizeusing the device and, if unsuccessful, will make a
+ wild guess.
:return: A :class:`ToCountMap` of **{** :class:`MemAccess` **:**
:class:`islpy.PwQPolynomial` **}**.
- - The :class:`MemAccess` specifies the characteristics of the
- memory access.
+ - The :class:`MemAccess` specifies the characteristics of the memory
+ access.
- - The :class:`islpy.PwQPolynomial` holds the number of memory
- accesses with the characteristics specified in the key (in terms
- of the :class:`loopy.LoopKernel` *inames*).
+ - The :class:`islpy.PwQPolynomial` holds the number of memory accesses
+ with the characteristics specified in the key (in terms of the
+ :class:`loopy.LoopKernel` *inames*).
Example usage::
@@ -1547,17 +1549,16 @@ def get_mem_access_map(knl, numpy_types=True, count_redundant_work=False,
def get_synchronization_map(knl, subgroup_size=None):
- """Count the number of synchronization events each work-item encounters in a
- loopy kernel.
+ """Count the number of synchronization events each work-item encounters in
+ a loopy kernel.
:arg knl: A :class:`loopy.LoopKernel` whose barriers are to be counted.
:return: A dictionary mapping each type of synchronization event to a
- :class:`islpy.PwQPolynomial` holding the number of events per
- work-item.
+ :class:`islpy.PwQPolynomial` holding the number of events per work-item.
- Possible keys include ``barrier_local``, ``barrier_global``
- (if supported by the target) and ``kernel_launch``.
+ Possible keys include ``barrier_local``, ``barrier_global``
+ (if supported by the target) and ``kernel_launch``.
Example usage::
@@ -1626,14 +1627,14 @@ def get_synchronization_map(knl, subgroup_size=None):
# {{{ gather_access_footprints
def gather_access_footprints(kernel, ignore_uncountable=False):
- """Return a dictionary mapping ``(var_name, direction)``
- to :class:`islpy.Set` instances capturing which indices
- of each the array *var_name* are read/written (where
- *direction* is either ``read`` or ``write``.
-
- :arg ignore_uncountable: If *False*, an error will be raised for
- accesses on which the footprint cannot be determined (e.g.
- data-dependent or nonlinear indices)
+ """Return a dictionary mapping ``(var_name, direction)`` to
+ :class:`islpy.Set` instances capturing which indices of each the array
+ *var_name* are read/written (where *direction* is either ``read`` or
+ ``write``.
+
+ :arg ignore_uncountable: If *False*, an error will be raised for accesses
+ on which the footprint cannot be determined (e.g. data-dependent or
+ nonlinear indices)
"""
from loopy.preprocess import preprocess_kernel, infer_unknown_types
@@ -1685,9 +1686,9 @@ def gather_access_footprint_bytes(kernel, ignore_uncountable=False):
read/written (where *direction* is either ``read`` or ``write`` on array
*var_name*
- :arg ignore_uncountable: If *True*, an error will be raised for
- accesses on which the footprint cannot be determined (e.g.
- data-dependent or nonlinear indices)
+ :arg ignore_uncountable: If *True*, an error will be raised for accesses on
+ which the footprint cannot be determined (e.g. data-dependent or
+ nonlinear indices)
"""
from loopy.preprocess import preprocess_kernel, infer_unknown_types
@@ -1763,8 +1764,8 @@ def get_gmem_access_poly(knl):
def get_synchronization_poly(knl):
- """Count the number of synchronization events each work-item encounters in a
- loopy kernel.
+ """Count the number of synchronization events each work-item encounters in
+ a loopy kernel.
get_synchronization_poly is deprecated. Use get_synchronization_map instead.
--
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