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misc: various Dimension internal fixes #2205
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Codecov Report
@@ Coverage Diff @@
## master #2205 +/- ##
=======================================
Coverage 87.08% 87.08%
=======================================
Files 228 228
Lines 40611 40700 +89
Branches 7429 7454 +25
=======================================
+ Hits 35367 35445 +78
- Misses 4644 4652 +8
- Partials 600 603 +3
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devito/core/autotuning.py
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@@ -209,8 +209,11 @@ def init_time_bounds(stepper, at_args, args): | |||
else: | |||
at_args[dim.max_name] = at_args[dim.min_name] + options['squeezer'] | |||
if dim.size_name in args: | |||
# May need to shrink to avoid OOB accesses | |||
at_args[dim.max_name] = min(at_args[dim.max_name], args[dim.max_name]) | |||
if isinstance(args[dim.size_name], range): |
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if not isinstance(...):
# May need to shrink to avoid OOB accesses
at_args[dim.max_name] = min(at_args[dim.max_name], args[dim.max_name])
devito/operations/interpolators.py
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@@ -380,5 +394,6 @@ def interpolation_coeffs(self): | |||
@property | |||
def _weights(self): | |||
ddim, cdim = self.interpolation_coeffs.dimensions[1:] | |||
return Mul(*[self.interpolation_coeffs.subs({ddim: ri, cdim: rd-rd.symbolic_min}) | |||
return Mul(*[self.interpolation_coeffs.subs({ddim: ri, |
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nitpicking
for better readability, can we introduce mapper = {ddim: ....}
on the line above?
devito/operator/operator.py
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@@ -584,6 +590,9 @@ def _prepare_arguments(self, autotune=None, **kwargs): | |||
if configuration['mpi']: | |||
raise ValueError("Multiple Grids found") | |||
try: | |||
# Take biggest grid, i.e discard grids with subdimensions | |||
grids = {g for g in grids if not any(d.is_Sub for d in g.dimensions)} |
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this needs to be better abstracted in my opinion
I wonder whether we could have a SubGrid object (returned via __new__
) to capture subsampled grids. And dramatically simplify our lives here
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My main though is that this needs to be part of the Function on subdomain
overall, this is a temporary fix for arg processing
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What happens if we drop this line and modify the one above as
discretizations = {g for g in discretizations
if not any(d.is_Sub for d in g.dimensions)}
This should be enough to filter away the Subdomain grids?
Also: can we not at least add a property to Grid such as g.is_subdomain
or g.is_domain
or I don't know what name would be better. I feel having properties as opposed to peeking at the individual dimensions would be neater
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This should be enough to filter away the Subdomain grids?
No this will create issue for example if there is only one "sub-grid" this would end up empty and leads to missing arguments.
But looks like it's a duplicate from above now might be able to remove that one.
@@ -94,7 +94,7 @@ def __init_finalize__(self, *args, function=None, **kwargs): | |||
# a reference to the user-provided buffer | |||
self._initializer = None | |||
if len(initializer) > 0: | |||
self.data_with_halo[:] = initializer | |||
self.data_with_halo[:] = initializer[:] |
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interesting, what's the difference here?
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No difference, just debug leftover, the issue was calling __init_finalize__
before setting newobj.function
above, needed for first touch init. Slightly safer in case of shape differences though for weird (1, n)/(n, 1)
shape where someone might give and (n,)
vector
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just being paranoid here... are we completely sure both the performance and the semantics of this assignment are exactly the same as master, except for that corner case u mention above?
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I worry the new one might be slightly slower
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[:]
is just a view it has no performance impact.
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well the view gets created, so it's not really 0 impact.... but yeah, I agree it's gonna be 0.0000001 in practice 😬
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devito/ir/stree/algorithms.py
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@@ -147,6 +147,12 @@ def preprocess(clusters, options=None, **kwargs): | |||
found = [] | |||
for c1 in list(queue): | |||
distributed_aindices = c1.halo_scheme.distributed_aindices | |||
h_indices = set().union(*[(d, d.root) |
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For homogeneity with the rest of the code below, I would rather write:
distributed_aindices = c1.halo_scheme.distributed_aindices
loc_indices = c1.halo_scheme.loc_indices
all_loc_indices = set().union(*[d._defines for d in ...])
...
Note: I'm using _defines
above
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d_defines ?
devito/operator/operator.py
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@@ -584,6 +590,9 @@ def _prepare_arguments(self, autotune=None, **kwargs): | |||
if configuration['mpi']: | |||
raise ValueError("Multiple Grids found") | |||
try: | |||
# Take biggest grid, i.e discard grids with subdimensions | |||
grids = {g for g in grids if not any(d.is_Sub for d in g.dimensions)} |
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What happens if we drop this line and modify the one above as
discretizations = {g for g in discretizations
if not any(d.is_Sub for d in g.dimensions)}
This should be enough to filter away the Subdomain grids?
Also: can we not at least add a property to Grid such as g.is_subdomain
or g.is_domain
or I don't know what name would be better. I feel having properties as opposed to peeking at the individual dimensions would be neater
devito/passes/iet/langbase.py
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@@ -336,7 +345,8 @@ def _is_offloadable(self, iet): | |||
functions = FindSymbols().visit(iet) | |||
buffers = [f for f in functions if f.is_Array and f._mem_mapped] | |||
hostfuncs = [f for f in functions if not is_on_device(f, self.gpu_fit)] | |||
return not (buffers and hostfuncs) | |||
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|||
return not (hostfuncs and buffers) |
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leftover change?
devito/passes/iet/parpragma.py
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@@ -377,6 +375,12 @@ def _make_partree(self, candidates, nthreads=None): | |||
ncollapsed=ncollapsed, nthreads=nthreads, | |||
**root.args) | |||
prefix = [] | |||
elif all(i.is_ParallelRelaxed for i in candidates) and nthreads is not None: |
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how about just
elif nthreads is not None:
actually, to mirror what we have in the first if
, I might prefer:
else:
if nthreads is None:
nthreads = self.nthreads_nonaffine
chunk_size = ...
...
else:
body = self.HostIteration(schedule='static', ...)
prefix = []
@@ -94,7 +94,7 @@ def __init_finalize__(self, *args, function=None, **kwargs): | |||
# a reference to the user-provided buffer | |||
self._initializer = None | |||
if len(initializer) > 0: | |||
self.data_with_halo[:] = initializer | |||
self.data_with_halo[:] = initializer[:] |
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just being paranoid here... are we completely sure both the performance and the semantics of this assignment are exactly the same as master, except for that corner case u mention above?
@@ -94,7 +94,7 @@ def __init_finalize__(self, *args, function=None, **kwargs): | |||
# a reference to the user-provided buffer | |||
self._initializer = None | |||
if len(initializer) > 0: | |||
self.data_with_halo[:] = initializer | |||
self.data_with_halo[:] = initializer[:] |
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I worry the new one might be slightly slower
@@ -286,7 +284,7 @@ def test_cache_blocking_structure_optrelax_prec_inject(): | |||
'openmp': True, | |||
'par-collapse-ncores': 1})) | |||
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assert_structure(op, ['t', 't,p_s0_blk0,p_s,rsx,rsy'], | |||
assert_structure(op, ['t,p_s0_blk0,p_s', 't,p_s0_blk0,p_s,rsx,rsy'], |
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mmhh, why?
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CHange of parent hierachy in interp with rx...
always being conditional
devito/types/dimension.py
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@@ -1446,7 +1452,7 @@ def symbolic_max(self): | |||
def _arg_names(self): | |||
return (self.min_name, self.max_name, self.name) + self.parent._arg_names | |||
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def _arg_defaults(self, _min=None, **kwargs): | |||
def _arg_defaults(self, _min=None, size=None, **kwargs): |
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why?
devito/types/dimension.py
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@@ -977,7 +983,7 @@ def symbolic_incr(self): | |||
def bound_symbols(self): | |||
return set(self.parent.bound_symbols) | |||
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def _arg_defaults(self, **kwargs): | |||
def _arg_defaults(self, alias=None, **kwargs): |
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useless change
@@ -1515,7 +1515,7 @@ def test_issue_1927(self, factor): | |||
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op = Operator(Eq(f, 1)) | |||
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assert op.arguments()['time_M'] == 4*(save-1) # == min legal endpoint | |||
assert op.arguments()['time_M'] == 4*save-1 # == min legal endpoint |
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I had a comment here which appearly I forgot to fire up...
anyway: was my old comment (min legal endpoint) wrong? or is the new one to be updated?
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The comment is correct, the value wasn't
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ok
devito/ir/stree/algorithms.py
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h_indices = set().union(*[(d, d.root) | ||
for d in c1.halo_scheme.loc_indices]) | ||
|
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# Skip if the Halo echange would end up outside its need iteration space |
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couple of typos here
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args = kwargs['args'] = args.reduce_all() | ||
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# DiscreteFunctions may be created from CartesianDiscretizations, which in | ||
# turn could be Grids or SubDomains. Both may provide arguments | ||
discretizations = {getattr(kwargs[p.name], 'grid', None) for p in overrides} | ||
discretizations.update({getattr(p, 'grid', None) for p in defaults}) | ||
discretizations.discard(None) | ||
# Remove subgrids if multiple grids | ||
if len(discretizations) > 1: |
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We need to coin a term for any CartesianDiscretization that is not the main Grid
Also, we need to distinguish I think between SubDomain and SubGrid. The latter being a coarser representation of the (main) Grid
I don't exactly what names to use, but I feel an increasing need for a set of CartesianDiscretization attributes -- suitably overridden in the various subclasses -- along the lines of
is_root (is_main? is_domain?)
is_subdomain
is_subgrid
etc
and then here just g.is_domain
for eaxmple
@@ -1515,7 +1515,7 @@ def test_issue_1927(self, factor): | |||
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op = Operator(Eq(f, 1)) | |||
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assert op.arguments()['time_M'] == 4*(save-1) # == min legal endpoint | |||
assert op.arguments()['time_M'] == 4*save-1 # == min legal endpoint |
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ok
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GTG , thanks
Fixes #2204
Fixes #2132
Fixes #2206
Fixes issue with ConditionalDimension range from @ccuetom