Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Implements mars.tensor.stats.ks_2samp #2324

Merged
merged 4 commits into from
Aug 11, 2021
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions docs/source/reference/tensor/statistics.rst
Original file line number Diff line number Diff line change
Expand Up @@ -62,6 +62,7 @@ Statistical tests
:nosignatures:

mars.tensor.stats.chisquare
mars.tensor.stats.ks_2samp
mars.tensor.stats.power_divergence
mars.tensor.stats.ttest_1samp
mars.tensor.stats.ttest_ind
Expand Down
14 changes: 6 additions & 8 deletions mars/_utils.pyx
Original file line number Diff line number Diff line change
Expand Up @@ -14,8 +14,8 @@

import importlib
import os
import pkgutil
import pickle
import pkgutil
import types
import uuid
from collections import deque
Expand All @@ -27,23 +27,21 @@ import numpy as np
import pandas as pd
import cloudpickle
cimport cython

from .lib.mmh3 import hash as mmh_hash, hash_bytes as mmh_hash_bytes, \
hash_from_buffer as mmh3_hash_from_buffer

try:
from pandas.tseries.offsets import Tick as PDTick
except ImportError:
PDTick = None

try:
from sqlalchemy.sql import Selectable as SASelectable
from sqlalchemy.sql.sqltypes import TypeEngine as SATypeEngine
except ImportError:
SASelectable, SATypeEngine = None, None

cdef bint _has_cupy = pkgutil.find_loader('cupy')
cdef bint _has_cudf = pkgutil.find_loader('cudf')
from .lib.mmh3 import hash as mmh_hash, hash_bytes as mmh_hash_bytes, \
hash_from_buffer as mmh3_hash_from_buffer

cdef bint _has_cupy = bool(pkgutil.find_loader('cupy'))
cdef bint _has_cudf = bool(pkgutil.find_loader('cudf'))


cpdef str to_str(s, encoding='utf-8'):
Expand Down
1 change: 1 addition & 0 deletions mars/config.yml
Original file line number Diff line number Diff line change
@@ -0,0 +1 @@
"@inherits": "@mars/deploy/oscar/base_config.yml"
13 changes: 13 additions & 0 deletions mars/core/entity/tests/__init__.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,13 @@
# Copyright 1999-2021 Alibaba Group Holding Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
46 changes: 46 additions & 0 deletions mars/core/entity/tests/test_utils.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,46 @@
# Copyright 1999-2021 Alibaba Group Holding Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from mars import tensor as mt
from mars.core import recursive_tile
from mars.tensor.operands import TensorOperand, TensorOperandMixin
from mars.utils import has_unknown_shape


class _TestOperand(TensorOperand, TensorOperandMixin):

@classmethod
def tile(cls, op: "_TestOperand"):
data1, data2 = op.inputs

data1 = mt.sort(data1)
data2 = mt.sort(data2)
data_all = mt.concatenate([data1, data2])
s1 = mt.searchsorted(data1, data_all)
s2 = mt.searchsorted(data2, data_all)
result = yield from recursive_tile(mt.concatenate([s1, s2]))
# data1 will be yield by s1
assert not has_unknown_shape(data1)
assert not has_unknown_shape(data2)
assert not has_unknown_shape(data_all)
return result


def test_recursive_tile(setup):
d1 = mt.random.rand(10, chunk_size=5)
d2 = mt.random.rand(10, chunk_size=5)
op = _TestOperand()
t = op.new_tensor([d1, d2], dtype=d1.dtype,
shape=(20,), order=d1.order)
t.execute()
14 changes: 13 additions & 1 deletion mars/core/entity/utils.py
Original file line number Diff line number Diff line change
Expand Up @@ -64,6 +64,7 @@ def recursive_tile(tileable: TileableType, *tileables: TileableType) -> \
tileable = raw[0]
tileables = raw[1:]

inputs_set = set(tileable.op.inputs)
to_tile = [tileable] + list(tileables)
q = [t for t in to_tile if t.is_coarse()]
while q:
Expand All @@ -72,7 +73,18 @@ def recursive_tile(tileable: TileableType, *tileables: TileableType) -> \
if cs:
q.extend(cs)
continue
yield from handler.tile(t.op.outputs)
for obj in handler.tile(t.op.outputs):
to_update_inputs = []
chunks = []
for inp in t.op.inputs:
if has_unknown_shape(inp):
to_update_inputs.append(inp)
if inp not in inputs_set:
chunks.extend(inp.chunks)
if obj is None:
yield chunks + to_update_inputs
else:
yield obj + to_update_inputs
q.pop()

if not return_list:
Expand Down
8 changes: 3 additions & 5 deletions mars/core/graph/builder/chunk.py
Original file line number Diff line number Diff line change
Expand Up @@ -92,17 +92,15 @@ def _tile(self,
visited: Set[EntityType]):
try:
need_process = next(tile_handler)
if need_process is None:
chunks = []
else:
chunks = []
chunks = []
if need_process is not None:
for t in need_process:
if isinstance(t, CHUNK_TYPE):
chunks.append(self._get_data(t))
elif isinstance(t, TILEABLE_TYPE):
to_update_tileables.append(self._get_data(t))
# not finished yet
self._add_nodes(chunk_graph, chunks, visited)
self._add_nodes(chunk_graph, chunks.copy(), visited)
next_tileable_handlers.append((tileable, tile_handler))
# add intermediate chunks into result chunks
# to prevent them being pruned
Expand Down
4 changes: 3 additions & 1 deletion mars/deploy/oscar/session.py
Original file line number Diff line number Diff line change
Expand Up @@ -1129,9 +1129,11 @@ def __exit__(self, *_):
self.progress_bar.__exit__(*_)

def update(self, progress: float):
progress = min(progress, 100)
last_progress = self.last_progress
if self.progress_bar:
self.progress_bar.update(progress - last_progress)
incr = max(progress - last_progress, 0)
self.progress_bar.update(incr)
self.last_progress = max(last_progress, progress)


Expand Down
7 changes: 0 additions & 7 deletions mars/opcodes.py
Original file line number Diff line number Diff line change
Expand Up @@ -386,13 +386,6 @@

FUSE = 801

# control
ENTER = 901
LEAVE = 902
FIX_LATEST = 903
IF_ELSE = 904
NEXT_ITER = 905

# table like input for tensor
TABLE_COO = 1003
# store tensor as coo format
Expand Down
3 changes: 2 additions & 1 deletion mars/services/task/analyzer/analyzer.py
Original file line number Diff line number Diff line change
Expand Up @@ -182,7 +182,8 @@ def _build_fuse_subtask_chunk_graph(self,
# the last chunk
result_chunks.append(copied_fuse_chunk)
fuse_to_copied[fuse_chunk] = copied_fuse_chunk
self._chunk_to_copied[chunk] = fuse_to_copied[chunk.chunk]
self._chunk_to_copied[chunk.chunk] = self._chunk_to_copied[chunk] = \
fuse_to_copied[chunk.chunk]
return subtask_chunk_graph

def _gen_subtask(self,
Expand Down
4 changes: 2 additions & 2 deletions mars/services/task/supervisor/processor.py
Original file line number Diff line number Diff line change
Expand Up @@ -254,8 +254,8 @@ async def get_next_stage_processor(self) \

# gen subtask graph
available_bands = await self._get_available_band_slots()
subtask_graph = self._preprocessor.analyze(
chunk_graph, available_bands)
subtask_graph = await asyncio.to_thread(
self._preprocessor.analyze, chunk_graph, available_bands)
stage_processor = TaskStageProcessor(
new_task_id(), self._task, chunk_graph, subtask_graph,
list(available_bands), self._get_chunk_optimization_records(),
Expand Down
Loading