after_merge stringlengths 28 79.6k | before_merge stringlengths 20 79.6k | url stringlengths 38 71 | full_traceback stringlengths 43 922k | traceback_type stringclasses 555
values |
|---|---|---|---|---|
def get_jinja_env():
from datetime import datetime
from ..utils import readable_size
_jinja_env = jinja2.Environment(
loader=jinja2.FileSystemLoader(
os.path.join(os.path.dirname(__file__), "templates")
),
)
def format_ts(value):
if value is None or np.isnan(val... | def get_jinja_env():
from datetime import datetime
from ..utils import readable_size
_jinja_env = jinja2.Environment(
loader=jinja2.FileSystemLoader(
os.path.join(os.path.dirname(__file__), "templates")
),
)
def format_ts(value):
if value is None:
re... | https://github.com/mars-project/mars/issues/496 | 500 GET /worker?endpoint
Traceback (most recent call last):
File "/opt/conda/lib/python3.6/site-packages/tornado/web.py", line 1592, in _execute
result = yield result
File "/opt/conda/lib/python3.6/site-packages/tornado/gen.py", line 1133, in run
value = future.result()
File "/opt/conda/lib/python3.6/site-packages/torn... | ValueError |
def format_ts(value):
if value is None or np.isnan(value):
return None
return datetime.fromtimestamp(value).strftime("%Y-%m-%d %H:%M:%S")
| def format_ts(value):
if value is None:
return None
return datetime.fromtimestamp(value).strftime("%Y-%m-%d %H:%M:%S")
| https://github.com/mars-project/mars/issues/496 | 500 GET /worker?endpoint
Traceback (most recent call last):
File "/opt/conda/lib/python3.6/site-packages/tornado/web.py", line 1592, in _execute
result = yield result
File "/opt/conda/lib/python3.6/site-packages/tornado/gen.py", line 1133, in run
value = future.result()
File "/opt/conda/lib/python3.6/site-packages/torn... | ValueError |
def start_execution(self, session_id, graph_key, send_addresses=None, callback=None):
"""
Submit graph to the worker and control the execution
:param session_id: session id
:param graph_key: key of the execution graph
:param send_addresses: targets to send results after execution
:param callback... | def start_execution(self, session_id, graph_key, send_addresses=None, callback=None):
"""
Submit graph to the worker and control the execution
:param session_id: session id
:param graph_key: key of the execution graph
:param send_addresses: targets to send results after execution
:param callback... | https://github.com/mars-project/mars/issues/496 | 500 GET /worker?endpoint
Traceback (most recent call last):
File "/opt/conda/lib/python3.6/site-packages/tornado/web.py", line 1592, in _execute
result = yield result
File "/opt/conda/lib/python3.6/site-packages/tornado/gen.py", line 1133, in run
value = future.result()
File "/opt/conda/lib/python3.6/site-packages/torn... | ValueError |
def _handle_success(*_):
self._invoke_finish_callbacks(session_id, graph_key)
| def _handle_success(*_):
self._notify_successors(session_id, graph_key)
self._invoke_finish_callbacks(session_id, graph_key)
| https://github.com/mars-project/mars/issues/496 | 500 GET /worker?endpoint
Traceback (most recent call last):
File "/opt/conda/lib/python3.6/site-packages/tornado/web.py", line 1592, in _execute
result = yield result
File "/opt/conda/lib/python3.6/site-packages/tornado/gen.py", line 1133, in run
value = future.result()
File "/opt/conda/lib/python3.6/site-packages/torn... | ValueError |
def _dump_cache(self, session_id, graph_key, inproc_uid, save_sizes):
"""
Dump calc results into shared cache or spill
:param session_id: session id
:param graph_key: key of the execution graph
:param inproc_uid: uid of the InProcessCacheActor
:param save_sizes: sizes of data
"""
graph_r... | def _dump_cache(self, session_id, graph_key, inproc_uid, save_sizes):
"""
Dump calc results into shared cache or spill
:param session_id: session id
:param graph_key: key of the execution graph
:param inproc_uid: uid of the InProcessCacheActor
:param save_sizes: sizes of data
"""
graph_r... | https://github.com/mars-project/mars/issues/496 | 500 GET /worker?endpoint
Traceback (most recent call last):
File "/opt/conda/lib/python3.6/site-packages/tornado/web.py", line 1592, in _execute
result = yield result
File "/opt/conda/lib/python3.6/site-packages/tornado/gen.py", line 1133, in run
value = future.result()
File "/opt/conda/lib/python3.6/site-packages/torn... | ValueError |
def _cache_result(result_sizes):
save_sizes.update(result_sizes)
self._result_cache[(session_id, graph_key)] = GraphResultRecord(save_sizes)
| def _cache_result(*_):
self._result_cache[(session_id, graph_key)] = GraphResultRecord(save_sizes)
| https://github.com/mars-project/mars/issues/496 | 500 GET /worker?endpoint
Traceback (most recent call last):
File "/opt/conda/lib/python3.6/site-packages/tornado/web.py", line 1592, in _execute
result = yield result
File "/opt/conda/lib/python3.6/site-packages/tornado/gen.py", line 1133, in run
value = future.result()
File "/opt/conda/lib/python3.6/site-packages/torn... | ValueError |
def _get_chunk_index_min_max(cls, df, index_type, axis):
index = getattr(df, index_type)
chunk_index_min_max = []
for i in range(df.chunk_shape[axis]):
chunk_idx = [0, 0]
chunk_idx[axis] = i
chunk = df.cix[tuple(chunk_idx)]
chunk_index = getattr(chunk, index_type)
mi... | def _get_chunk_index_min_max(cls, df, index_type, axis):
index = getattr(df, index_type)
if not index.is_monotonic_increasing_or_decreasing and df.chunk_shape[axis] > 1:
return
chunk_index_min_max = []
for i in range(df.chunk_shape[axis]):
chunk_idx = [0, 0]
chunk_idx[axis] = i
... | https://github.com/mars-project/mars/issues/428 | Traceback (most recent call last):
File "/Users/hetao/mars/mars/tiles.py", line 111, in _dispatch
handler = self._handlers[op_cls]
KeyError: <class 'mars.dataframe.expressions.arithmetic.add.DataFrameAdd'>
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<st... | KeyError |
def _tile_both_dataframes(cls, op):
# if both of the inputs are DataFrames, axis is just ignored
left, right = op.inputs
df = op.outputs[0]
nsplits = [[], []]
splits = _MinMaxSplitInfo()
# first, we decide the chunk size on each axis
# we perform the same logic for both index and columns
... | def _tile_both_dataframes(cls, op):
# if both of the inputs are DataFrames, axis is just ignored
left, right = op.inputs
df = op.outputs[0]
nsplits = [[], []]
splits = _MinMaxSplitInfo()
# first, we decide the chunk size on each axis
# we perform the same logic for both index and columns
... | https://github.com/mars-project/mars/issues/428 | Traceback (most recent call last):
File "/Users/hetao/mars/mars/tiles.py", line 111, in _dispatch
handler = self._handlers[op_cls]
KeyError: <class 'mars.dataframe.expressions.arithmetic.add.DataFrameAdd'>
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<st... | KeyError |
def _calc_properties(cls, x1, x2):
dtypes = columns = index = None
index_shape = column_shape = np.nan
if x1.columns.key == x2.columns.key:
dtypes = x1.dtypes
column_shape = len(dtypes)
columns = copy.copy(x1.columns)
columns.value.should_be_monotonic = True
elif x1.dtyp... | def _calc_properties(cls, x1, x2):
dtypes = columns = index = None
index_shape = column_shape = np.nan
if x1.dtypes is not None and x2.dtypes is not None:
dtypes = infer_dtypes(x1.dtypes, x2.dtypes, cls._operator)
column_shape = len(dtypes)
columns = parse_index(dtypes.index, store_d... | https://github.com/mars-project/mars/issues/428 | Traceback (most recent call last):
File "/Users/hetao/mars/mars/tiles.py", line 111, in _dispatch
handler = self._handlers[op_cls]
KeyError: <class 'mars.dataframe.expressions.arithmetic.add.DataFrameAdd'>
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<st... | KeyError |
def hash_index(index, size):
def func(x, size):
return mmh_hash(bytes(x)) % size
f = functools.partial(func, size=size)
idx_to_grouped = dict(index.groupby(index.map(f)).items())
return [idx_to_grouped.get(i, list()) for i in range(size)]
| def hash_index(index, size):
def func(x, size):
return mmh_hash(bytes(x)) % size
f = functools.partial(func, size=size)
grouped = sorted(index.groupby(index.map(f)).items(), key=operator.itemgetter(0))
return [g[1] for g in grouped]
| https://github.com/mars-project/mars/issues/428 | Traceback (most recent call last):
File "/Users/hetao/mars/mars/tiles.py", line 111, in _dispatch
handler = self._handlers[op_cls]
KeyError: <class 'mars.dataframe.expressions.arithmetic.add.DataFrameAdd'>
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<st... | KeyError |
def prepare_graph(self, compose=True):
"""
Tile and compose tileable graph into chunk graph
:param compose: if True, do compose after tiling
"""
tileable_graph = deserialize_graph(self._serialized_tileable_graph)
self._tileable_graph_cache = tileable_graph
logger.debug(
"Begin prepa... | def prepare_graph(self, compose=True):
"""
Tile and compose tensor graph into chunk graph
:param compose: if True, do compose after tiling
"""
tileable_graph = deserialize_graph(self._serialized_tileable_graph)
self._tileable_graph_cache = tileable_graph
logger.debug(
"Begin prepari... | https://github.com/mars-project/mars/issues/406 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 766, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 88, in mars.actors.pool.gevent_pool.ActorExecutionContext.fire_run
File "mars/actors/pool/gevent_pool.pyx", line 91, in mars.actors.pool.gevent_pool.ActorExecutionCo... | TypeError |
def build_fetch_graph(self, tileable_key):
"""
Convert single tileable node to tiled fetch tileable node and
put into a graph which only contains one tileable node
:param tileable_key: the key of tileable node
"""
tileable = self._get_tileable_by_key(tileable_key)
graph = DAG()
new_tile... | def build_fetch_graph(self, tileable_key):
"""
Convert single tensor to tiled fetch tensor and put into a graph which only contains one tensor
:param tileable_key: the key of tensor
"""
tileable = self._get_tileable_by_key(tileable_key)
graph = DAG()
new_tileable = build_fetch_tileable(tile... | https://github.com/mars-project/mars/issues/406 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 766, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 88, in mars.actors.pool.gevent_pool.ActorExecutionContext.fire_run
File "mars/actors/pool/gevent_pool.pyx", line 91, in mars.actors.pool.gevent_pool.ActorExecutionCo... | TypeError |
def tile_fetch_tileable(self, tileable):
"""
Find the owner of the input tileable node and ask for tiling
"""
tileable_key = tileable.key
graph_ref = self.ctx.actor_ref(
self._session_ref.get_graph_ref_by_tleable_key(tileable_key)
)
fetch_graph = deserialize_graph(graph_ref.build_fet... | def tile_fetch_tileable(self, tileable):
"""
Find the owner of the input tensor and ask for tiling.
"""
tileable_key = tileable.key
graph_ref = self.ctx.actor_ref(
self._session_ref.get_graph_ref_by_tleable_key(tileable_key)
)
fetch_graph = deserialize_graph(graph_ref.build_fetch_gra... | https://github.com/mars-project/mars/issues/406 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 766, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 88, in mars.actors.pool.gevent_pool.ActorExecutionContext.fire_run
File "mars/actors/pool/gevent_pool.pyx", line 91, in mars.actors.pool.gevent_pool.ActorExecutionCo... | TypeError |
def build_fetch_chunk(chunk, input_chunk_keys=None, **kwargs):
from .operands import ShuffleProxy
chunk_op = chunk.op
params = chunk.params.copy()
if isinstance(chunk_op, ShuffleProxy):
# for shuffle nodes, we build FetchShuffle chunks
# to replace ShuffleProxy
to_fetch_keys = ... | def build_fetch_chunk(chunk, input_chunk_keys=None, **kwargs):
from .operands import ShuffleProxy
chunk_op = chunk.op
params = chunk.params.copy()
params.pop("index", None)
if isinstance(chunk_op, ShuffleProxy):
# for shuffle nodes, we build FetchShuffle chunks
# to replace Shuffle... | https://github.com/mars-project/mars/issues/406 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 766, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 88, in mars.actors.pool.gevent_pool.ActorExecutionContext.fire_run
File "mars/actors/pool/gevent_pool.pyx", line 91, in mars.actors.pool.gevent_pool.ActorExecutionCo... | TypeError |
def build_fetch_tileable(tileable, coarse=False):
if coarse or tileable.is_coarse():
chunks = None
else:
chunks = []
for c in tileable.chunks:
fetch_chunk = build_fetch_chunk(c, index=c.index)
chunks.append(fetch_chunk)
tileable_op = tileable.op
params = ... | def build_fetch_tileable(tileable, coarse=False):
if coarse or tileable.is_coarse():
chunks = None
else:
chunks = []
for c in tileable.chunks:
fetch_chunk = build_fetch_chunk(c, index=c.index)
chunks.append(fetch_chunk)
tileable_op = tileable.op
params = ... | https://github.com/mars-project/mars/issues/406 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 766, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 88, in mars.actors.pool.gevent_pool.ActorExecutionContext.fire_run
File "mars/actors/pool/gevent_pool.pyx", line 91, in mars.actors.pool.gevent_pool.ActorExecutionCo... | TypeError |
def mars_serialize_context():
global _serialize_context
if _serialize_context is None:
ctx = pyarrow.default_serialization_context()
ctx.register_type(
SparseNDArray,
"mars.SparseNDArray",
custom_serializer=_serialize_sparse_csr_list,
custom_deseri... | def mars_serialize_context():
global _serialize_context
if _serialize_context is None:
ctx = pyarrow.default_serialization_context()
ctx.register_type(
SparseNDArray,
"mars.SparseNDArray",
custom_serializer=_serialize_sparse_csr_list,
custom_deseri... | https://github.com/mars-project/mars/issues/370 | Traceback (most recent call last):
File "/home/admin/work/_public-mars-0.1.1.zip/mars/scheduler/operand.py", line 461, in _rejecter
six.reraise(*exc)
File "/home/admin/work/_public-mars-0.1.1.zip/mars/lib/six.py", line 702, in reraise
raise value.with_traceback(tb)
File "/home/admin/work/_public-mars-0.1.1.zip/mars/pro... | TypeError |
def create(self, session_id, chunk_key, size):
from pyarrow.lib import PlasmaStoreFull
obj_id = self._new_object_id(session_id, chunk_key)
try:
self._plasma_client.evict(size)
buffer = self._plasma_client.create(obj_id, size)
return buffer
except PlasmaStoreFull:
exc_ty... | def create(self, session_id, chunk_key, size):
from pyarrow.lib import PlasmaStoreFull
obj_id = self._new_object_id(session_id, chunk_key)
try:
buffer = self._plasma_client.create(obj_id, size)
return buffer
except PlasmaStoreFull:
exc_type = PlasmaStoreFull
logger.warn... | https://github.com/mars-project/mars/issues/370 | Traceback (most recent call last):
File "/home/admin/work/_public-mars-0.1.1.zip/mars/scheduler/operand.py", line 461, in _rejecter
six.reraise(*exc)
File "/home/admin/work/_public-mars-0.1.1.zip/mars/lib/six.py", line 702, in reraise
raise value.with_traceback(tb)
File "/home/admin/work/_public-mars-0.1.1.zip/mars/pro... | TypeError |
def seal(self, session_id, chunk_key):
from pyarrow.lib import PlasmaObjectNonexistent
obj_id = self._get_object_id(session_id, chunk_key)
try:
self._plasma_client.seal(obj_id)
except PlasmaObjectNonexistent:
raise KeyError((session_id, chunk_key))
| def seal(self, session_id, chunk_key):
from pyarrow.lib import PlasmaObjectNonexistent
obj_id = self._get_object_id(session_id, chunk_key)
try:
self._plasma_client.seal(obj_id)
except PlasmaObjectNonexistent:
raise KeyError("(%r, %r)" % (session_id, chunk_key))
| https://github.com/mars-project/mars/issues/370 | Traceback (most recent call last):
File "/home/admin/work/_public-mars-0.1.1.zip/mars/scheduler/operand.py", line 461, in _rejecter
six.reraise(*exc)
File "/home/admin/work/_public-mars-0.1.1.zip/mars/lib/six.py", line 702, in reraise
raise value.with_traceback(tb)
File "/home/admin/work/_public-mars-0.1.1.zip/mars/pro... | TypeError |
def get(self, session_id, chunk_key):
"""
Get deserialized Mars object from plasma store
"""
from pyarrow.plasma import ObjectNotAvailable
obj_id = self._get_object_id(session_id, chunk_key)
obj = self._plasma_client.get(
obj_id, serialization_context=self._serialize_context, timeout_ms... | def get(self, session_id, chunk_key):
"""
Get deserialized Mars object from plasma store
"""
from pyarrow.plasma import ObjectNotAvailable
obj_id = self._get_object_id(session_id, chunk_key)
obj = self._plasma_client.get(
obj_id, serialization_context=self._serialize_context, timeout_ms... | https://github.com/mars-project/mars/issues/370 | Traceback (most recent call last):
File "/home/admin/work/_public-mars-0.1.1.zip/mars/scheduler/operand.py", line 461, in _rejecter
six.reraise(*exc)
File "/home/admin/work/_public-mars-0.1.1.zip/mars/lib/six.py", line 702, in reraise
raise value.with_traceback(tb)
File "/home/admin/work/_public-mars-0.1.1.zip/mars/pro... | TypeError |
def get_buffer(self, session_id, chunk_key):
"""
Get raw buffer from plasma store
"""
obj_id = self._get_object_id(session_id, chunk_key)
[buf] = self._plasma_client.get_buffers([obj_id], timeout_ms=10)
if buf is None:
raise KeyError((session_id, chunk_key))
return buf
| def get_buffer(self, session_id, chunk_key):
"""
Get raw buffer from plasma store
"""
obj_id = self._get_object_id(session_id, chunk_key)
[buf] = self._plasma_client.get_buffers([obj_id], timeout_ms=10)
if buf is None:
raise KeyError("(%r, %r)" % (session_id, chunk_key))
return buf
| https://github.com/mars-project/mars/issues/370 | Traceback (most recent call last):
File "/home/admin/work/_public-mars-0.1.1.zip/mars/scheduler/operand.py", line 461, in _rejecter
six.reraise(*exc)
File "/home/admin/work/_public-mars-0.1.1.zip/mars/lib/six.py", line 702, in reraise
raise value.with_traceback(tb)
File "/home/admin/work/_public-mars-0.1.1.zip/mars/pro... | TypeError |
def get_actual_size(self, session_id, chunk_key):
"""
Get actual size of Mars object from plasma store
"""
buf = None
try:
obj_id = self._get_object_id(session_id, chunk_key)
[buf] = self._plasma_client.get_buffers([obj_id], timeout_ms=10)
if buf is None:
raise Ke... | def get_actual_size(self, session_id, chunk_key):
"""
Get actual size of Mars object from plasma store
"""
buf = None
try:
obj_id = self._get_object_id(session_id, chunk_key)
[buf] = self._plasma_client.get_buffers([obj_id], timeout_ms=10)
size = buf.size
finally:
... | https://github.com/mars-project/mars/issues/370 | Traceback (most recent call last):
File "/home/admin/work/_public-mars-0.1.1.zip/mars/scheduler/operand.py", line 461, in _rejecter
six.reraise(*exc)
File "/home/admin/work/_public-mars-0.1.1.zip/mars/lib/six.py", line 702, in reraise
raise value.with_traceback(tb)
File "/home/admin/work/_public-mars-0.1.1.zip/mars/pro... | TypeError |
def put(self, session_id, chunk_key, value):
"""
Put a Mars object into plasma store
:param session_id: session id
:param chunk_key: chunk key
:param value: Mars object to be put
"""
import pyarrow
from pyarrow.lib import PlasmaStoreFull
data_size = calc_data_size(value)
try:
... | def put(self, session_id, chunk_key, value):
"""
Put a Mars object into plasma store
:param session_id: session id
:param chunk_key: chunk key
:param value: Mars object to be put
"""
import pyarrow
from pyarrow.lib import PlasmaStoreFull
from ..serialize.dataserializer import DataTup... | https://github.com/mars-project/mars/issues/370 | Traceback (most recent call last):
File "/home/admin/work/_public-mars-0.1.1.zip/mars/scheduler/operand.py", line 461, in _rejecter
six.reraise(*exc)
File "/home/admin/work/_public-mars-0.1.1.zip/mars/lib/six.py", line 702, in reraise
raise value.with_traceback(tb)
File "/home/admin/work/_public-mars-0.1.1.zip/mars/pro... | TypeError |
def run(self, *tensors, **kw):
from . import tensor as mt
fetch = kw.get("fetch", True)
ret_list = False
if len(tensors) == 1 and isinstance(tensors[0], (tuple, list)):
ret_list = True
tensors = tensors[0]
elif len(tensors) > 1:
ret_list = True
tensors = tuple(mt.tensor... | def run(self, *tensors, **kw):
from . import tensor as mt
fetch = kw.get("fetch", True)
ret_list = False
if len(tensors) == 1 and isinstance(tensors[0], (tuple, list)):
ret_list = True
tensors = tensors[0]
elif len(tensors) > 1:
ret_list = True
tensors = tuple(mt.tensor... | https://github.com/mars-project/mars/issues/334 | In [1]: import mars.tensor as mt
In [2]: a = mt.arange(12)
In [3]: a.totiledb('test_tiledb').execute()
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-3-5174935f197d> in <module>
----> 1 a.totiledb('... | IndexError |
def fetch(self, *tensors, **kw):
ret_list = False
if len(tensors) == 1 and isinstance(tensors[0], (tuple, list)):
ret_list = True
tensors = tensors[0]
elif len(tensors) > 1:
ret_list = True
result = self._sess.fetch(*tensors, **kw)
ret = []
for r, t in zip(result, tenso... | def fetch(self, *tensors, **kw):
ret_list = False
if len(tensors) == 1 and isinstance(tensors[0], (tuple, list)):
ret_list = True
tensors = tensors[0]
elif len(tensors) > 1:
ret_list = True
result = self._sess.fetch(*tensors, **kw)
ret = []
for r, t in zip(result, tenso... | https://github.com/mars-project/mars/issues/334 | In [1]: import mars.tensor as mt
In [2]: a = mt.arange(12)
In [3]: a.totiledb('test_tiledb').execute()
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-3-5174935f197d> in <module>
----> 1 a.totiledb('... | IndexError |
def _store_tiledb(ctx, chunk):
tiledb_ctx = get_tiledb_ctx(chunk.op.tiledb_config)
uri = chunk.op.tiledb_uri
key = chunk.op.tiledb_key
timestamp = chunk.op.tiledb_timestamp
axis_offsets = chunk.op.axis_offsets
if not chunk.issparse():
# dense
to_store = np.ascontiguousarray(ctx[... | def _store_tiledb(ctx, chunk):
tiledb_ctx = get_tiledb_ctx(chunk.op.tiledb_config)
uri = chunk.op.tiledb_uri
key = chunk.op.tiledb_key
timestamp = chunk.op.tiledb_timestamp
axis_offsets = chunk.op.axis_offsets
if not chunk.issparse():
# dense
to_store = np.ascontiguousarray(ctx[... | https://github.com/mars-project/mars/issues/334 | In [1]: import mars.tensor as mt
In [2]: a = mt.arange(12)
In [3]: a.totiledb('test_tiledb').execute()
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-3-5174935f197d> in <module>
----> 1 a.totiledb('... | IndexError |
def scalar(data, dtype=None, gpu=False):
try:
arr = np.array(data, dtype=dtype)
op = Scalar(arr.item(), dtype=arr.dtype, gpu=gpu)
shape = ()
return op(shape)
except ValueError:
raise TypeError("Expect scalar, got: {0}".format(data))
| def scalar(data, dtype=None, gpu=False):
try:
arr = np.array(data, dtype=dtype)
op = Scalar(np.asscalar(arr), dtype=arr.dtype, gpu=gpu)
shape = ()
return op(shape)
except ValueError:
raise TypeError("Expect scalar, got: {0}".format(data))
| https://github.com/mars-project/mars/issues/334 | In [1]: import mars.tensor as mt
In [2]: a = mt.arange(12)
In [3]: a.totiledb('test_tiledb').execute()
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-3-5174935f197d> in <module>
----> 1 a.totiledb('... | IndexError |
def _partial_reduction(
cls, agg_op_type, tensor, axis, dtype, keepdims, combine_size, kw=None
):
from ..merge.concatenate import TensorConcatenate
kw = kw or {}
axes = sorted(combine_size.keys())
combine_blocks = [
cls._combine_split(i, combine_size, tensor.chunk_shape)
for i in r... | def _partial_reduction(
cls, agg_op_type, tensor, axis, dtype, keepdims, combine_size, kw=None
):
from ..merge.concatenate import TensorConcatenate
kw = kw or {}
axes = sorted(combine_size.keys())
combine_blocks = [
cls._combine_split(i, combine_size, tensor.chunk_shape)
for i in r... | https://github.com/mars-project/mars/issues/334 | In [1]: import mars.tensor as mt
In [2]: a = mt.arange(12)
In [3]: a.totiledb('test_tiledb').execute()
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-3-5174935f197d> in <module>
----> 1 a.totiledb('... | IndexError |
def decide_chunk_sizes(shape, chunk_size, itemsize):
"""
Decide how a given tensor can be split into chunk.
:param shape: tensor's shape
:param chunk_size: if dict provided, it's dimension id to chunk size;
if provided, it's the chunk size for each dimension.
:param itemsize:... | def decide_chunk_sizes(shape, chunk_size, itemsize):
"""
Decide how a given tensor can be split into chunk.
:param shape: tensor's shape
:param chunk_size: if dict provided, it's dimension id to chunk size;
if provided, it's the chunk size for each dimension.
:param itemsize:... | https://github.com/mars-project/mars/issues/334 | In [1]: import mars.tensor as mt
In [2]: a = mt.arange(12)
In [3]: a.totiledb('test_tiledb').execute()
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-3-5174935f197d> in <module>
----> 1 a.totiledb('... | IndexError |
def __init__(self, *args, **kwargs):
super(BaseWithKey, self).__init__(*args, **kwargs)
if self._init_update_key_ and (not hasattr(self, "_key") or not self._key):
self._update_key()
if not hasattr(self, "_id") or not self._id:
self._id = str(id(self))
| def __init__(self, *args, **kwargs):
super(BaseWithKey, self).__init__(*args, **kwargs)
if self._init_update_key_ and (not hasattr(self, "_key") or not self._key):
self.update_key()
if not hasattr(self, "_id") or not self._id:
self._id = str(id(self))
| https://github.com/mars-project/mars/issues/297 | In [1]: from mars.deploy.local import new_cluster
In [2]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=3, shared_memory='100M')
/Users/travis/build/wesm/crossbow/arrow/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 0.104858GB of memory.
/Users/travis/build/wesm/crossbow/arrow/cpp/... | IndexError |
def build_graph(
self, graph=None, cls=DAG, tiled=False, compose=True, executed_keys=None
):
from .tensor.expressions.utils import convert_to_fetch
executed_keys = executed_keys or []
if tiled and self.is_coarse():
self.tiles()
graph = graph if graph is not None else cls()
keys = None
... | def build_graph(
self, graph=None, cls=DAG, tiled=False, compose=True, executed_keys=None
):
from .tensor.expressions.utils import convert_to_fetch
executed_keys = executed_keys or []
if tiled and self.is_coarse():
self.tiles()
graph = graph if graph is not None else cls()
keys = None
... | https://github.com/mars-project/mars/issues/297 | In [1]: from mars.deploy.local import new_cluster
In [2]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=3, shared_memory='100M')
/Users/travis/build/wesm/crossbow/arrow/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 0.104858GB of memory.
/Users/travis/build/wesm/crossbow/arrow/cpp/... | IndexError |
def _new_chunks(self, inputs, shape, index=None, output_limit=None, kws=None, **kw):
output_limit = (
getattr(self, "output_limit") if output_limit is None else output_limit
)
self.check_inputs(inputs)
getattr(self, "_set_inputs")(inputs)
if getattr(self, "_key", None) is None:
geta... | def _new_chunks(self, inputs, shape, index=None, output_limit=None, kws=None, **kw):
output_limit = (
getattr(self, "output_limit") if output_limit is None else output_limit
)
self.check_inputs(inputs)
getattr(self, "_set_inputs")(inputs)
if getattr(self, "_key", None) is None:
geta... | https://github.com/mars-project/mars/issues/297 | In [1]: from mars.deploy.local import new_cluster
In [2]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=3, shared_memory='100M')
/Users/travis/build/wesm/crossbow/arrow/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 0.104858GB of memory.
/Users/travis/build/wesm/crossbow/arrow/cpp/... | IndexError |
def _new_entities(
self, inputs, shape, chunks=None, nsplits=None, output_limit=None, kws=None, **kw
):
output_limit = (
getattr(self, "output_limit") if output_limit is None else output_limit
)
self.check_inputs(inputs)
getattr(self, "_set_inputs")(inputs)
if getattr(self, "_key", None... | def _new_entities(
self, inputs, shape, chunks=None, nsplits=None, output_limit=None, kws=None, **kw
):
output_limit = (
getattr(self, "output_limit") if output_limit is None else output_limit
)
self.check_inputs(inputs)
getattr(self, "_set_inputs")(inputs)
if getattr(self, "_key", None... | https://github.com/mars-project/mars/issues/297 | In [1]: from mars.deploy.local import new_cluster
In [2]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=3, shared_memory='100M')
/Users/travis/build/wesm/crossbow/arrow/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 0.104858GB of memory.
/Users/travis/build/wesm/crossbow/arrow/cpp/... | IndexError |
def _build_elementwise(op):
def _handle(ctx, chunk):
inputs, device_id, xp = as_same_device(
[ctx[c.key] for c in chunk.inputs], device=chunk.device, ret_extra=True
)
if isinstance(op, six.string_types):
func = getattr(xp, op)
else:
func = op
... | def _build_elementwise(op):
def _handle(ctx, chunk):
inputs, device_id, xp = as_same_device(
[ctx[c.key] for c in chunk.inputs], device=chunk.device, ret_extra=True
)
if isinstance(op, six.string_types):
func = getattr(xp, op)
else:
func = op
... | https://github.com/mars-project/mars/issues/282 | In [1]: import numpy as np
In [2]: import mars.tensor as mt
In [3]: a = np.array([[0, -2, -1], [-3, 0, 0]])
In [4]: mt.absolute(a, where=a > -2).execute()
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-i... | ValueError |
def _handle(ctx, chunk):
inputs, device_id, xp = as_same_device(
[ctx[c.key] for c in chunk.inputs], device=chunk.device, ret_extra=True
)
if isinstance(op, six.string_types):
func = getattr(xp, op)
else:
func = op
with device(device_id):
kw = {"casting": chunk.op.c... | def _handle(ctx, chunk):
inputs, device_id, xp = as_same_device(
[ctx[c.key] for c in chunk.inputs], device=chunk.device, ret_extra=True
)
if isinstance(op, six.string_types):
func = getattr(xp, op)
else:
func = op
with device(device_id):
kw = {"casting": chunk.op.c... | https://github.com/mars-project/mars/issues/282 | In [1]: import numpy as np
In [2]: import mars.tensor as mt
In [3]: a = np.array([[0, -2, -1], [-3, 0, 0]])
In [4]: mt.absolute(a, where=a > -2).execute()
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-i... | ValueError |
def _call(self, x1, x2, out=None, where=None):
# if x1 or x2 is scalar, and out is none, to constant
if (np.isscalar(x1) or np.isscalar(x2)) and not out and not where:
return self.to_constant(x1, x2)
x1, x2, out, where = self._process_inputs(x1, x2, out, where)
# check broadcast
shape = bro... | def _call(self, x1, x2, out=None, where=None):
# if x1 or x2 is scalar, and out is none, to constant
if (np.isscalar(x1) or np.isscalar(x2)) and not out:
return self.to_constant(x1, x2)
x1, x2, out, where = self._process_inputs(x1, x2, out, where)
# check broadcast
shape = broadcast_shape(x... | https://github.com/mars-project/mars/issues/282 | In [1]: import numpy as np
In [2]: import mars.tensor as mt
In [3]: a = np.array([[0, -2, -1], [-3, 0, 0]])
In [4]: mt.absolute(a, where=a > -2).execute()
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-i... | ValueError |
def _collect_operand_io_meta(graph, chunks):
# collect operand i/o information
predecessor_keys = set()
successor_keys = set()
input_chunk_keys = set()
shared_input_chunk_keys = set()
chunk_keys = set()
for c in chunks:
# handling predecessor args
for pn in graph.iter_predec... | def _collect_operand_io_meta(graph, chunks):
# collect operand i/o information
predecessor_keys = set()
successor_keys = set()
input_chunk_keys = set()
shared_input_chunk_keys = set()
chunk_keys = set()
for c in chunks:
# handling predecessor args
for pn in graph.iter_predec... | https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def create_operand_actors(self, _clean_io_meta=True, _start=True):
"""
Create operand actors for all operands
"""
logger.debug("Creating operand actors for graph %s", self._graph_key)
chunk_graph = self.get_chunk_graph()
operand_infos = self._operand_infos
op_refs = dict()
initial_keys... | def create_operand_actors(self, _clean_io_meta=True, _start=True):
"""
Create operand actors for all operands
"""
logger.debug("Creating operand actors for graph %s", self._graph_key)
chunk_graph = self.get_chunk_graph()
operand_infos = self._operand_infos
op_refs = dict()
initial_keys... | https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def get_operand_states(self, op_keys):
return [
self._operand_infos[k]["state"] for k in op_keys if k in self._operand_infos
]
| def get_operand_states(self, op_keys):
return [self._operand_infos[k]["state"] for k in op_keys]
| https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def check_operand_can_be_freed(self, succ_op_keys):
"""
Check if the data of an operand can be freed.
:param succ_op_keys: keys of successor operands
:return: True if can be freed, False if cannot. None when the result
is not determinant and we need to test later.
"""
operand_infos... | def check_operand_can_be_freed(self, succ_op_keys):
"""
Check if the data of an operand can be freed.
:param succ_op_keys: keys of successor operands
:return: True if can be freed, False if cannot. None when the result
is not determinant and we need to test later.
"""
operand_infos... | https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def __init__(self, session_id, graph_id, op_key, op_info, worker=None, position=None):
super(BaseOperandActor, self).__init__()
self._session_id = session_id
self._graph_ids = [graph_id]
self._info = copy.deepcopy(op_info)
self._op_key = op_key
self._op_path = "/sessions/%s/operands/%s" % (self.... | def __init__(self, session_id, graph_id, op_key, op_info, worker=None, position=None):
super(BaseOperandActor, self).__init__()
self._session_id = session_id
self._graph_id = graph_id
self._info = copy.deepcopy(op_info)
self._op_key = op_key
self._op_path = "/sessions/%s/operands/%s" % (self._se... | https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def post_create(self):
from ..graph import GraphActor
from ..assigner import AssignerActor
from ..chunkmeta import ChunkMetaActor
from ..kvstore import KVStoreActor
from ..resource import ResourceActor
self.set_cluster_info_ref()
self._assigner_ref = self.ctx.actor_ref(AssignerActor.default... | def post_create(self):
from ..graph import GraphActor
from ..assigner import AssignerActor
from ..chunkmeta import ChunkMetaActor
from ..kvstore import KVStoreActor
from ..resource import ResourceActor
self.set_cluster_info_ref()
self._assigner_ref = self.ctx.actor_ref(AssignerActor.default... | https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def state(self, value):
self._last_state = self._state
if value != self._last_state:
logger.debug(
"Operand %s(%s) state from %s to %s.",
self._op_key,
self._op_name,
self._last_state,
value,
)
self._state = value
self._info["st... | def state(self, value):
self._last_state = self._state
if value != self._last_state:
logger.debug(
"Operand %s(%s) state from %s to %s.",
self._op_key,
self._op_name,
self._last_state,
value,
)
self._state = value
self._info["st... | https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def worker(self, value):
futures = []
for graph_ref in self._graph_refs:
futures.append(
graph_ref.set_operand_worker(self._op_key, value, _tell=True, _wait=False)
)
if self._kv_store_ref is not None:
if value:
futures.append(
self._kv_store_re... | def worker(self, value):
futures = [
self._graph_ref.set_operand_worker(self._op_key, value, _tell=True, _wait=False)
]
if self._kv_store_ref is not None:
if value:
futures.append(
self._kv_store_ref.write(
"%s/worker" % self._op_path, value, _... | https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def add_running_predecessor(self, op_key, worker):
self._running_preds.add(op_key)
self._pred_workers.add(worker)
if len(self._pred_workers) > 1:
# we do not push when multiple workers in input
self._pred_workers = set()
self._running_preds = set()
return
if self.state !... | def add_running_predecessor(self, op_key, worker):
self._running_preds.add(op_key)
self._pred_workers.add(worker)
if len(self._pred_workers) > 1:
# we do not push when multiple workers in input
self._pred_workers = set()
self._running_preds = set()
return
if self.state !... | https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def add_finished_successor(self, op_key):
super(OperandActor, self).add_finished_successor(op_key)
if self._position != OperandPosition.TERMINAL and all(
k in self._finish_succs for k in self._succ_keys
):
# make sure that all prior states are terminated (in case of failover)
states ... | def add_finished_successor(self, op_key):
super(OperandActor, self).add_finished_successor(op_key)
if self._position != OperandPosition.TERMINAL and all(
k in self._finish_succs for k in self._succ_keys
):
# make sure that all prior states are terminated (in case of failover)
states ... | https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def move_failover_state(self, from_states, state, new_target, dead_workers):
"""
Move the operand into new state when executing fail-over step
:param from_states: the source states the operand should be in, when not match, we stopped.
:param state: the target state to move
:param new_target: new tar... | def move_failover_state(self, from_states, state, new_target, dead_workers):
"""
Move the operand into new state when executing fail-over step
:param from_states: the source states the operand should be in, when not match, we stopped.
:param state: the target state to move
:param new_target: new tar... | https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def free_data(self, state=OperandState.FREED):
"""
Free output data of current operand
:param state: target state
"""
if self.state == OperandState.FREED:
return
if state == OperandState.CANCELLED:
can_be_freed = True
else:
can_be_freed_states = [
graph_re... | def free_data(self, state=OperandState.FREED):
"""
Free output data of current operand
:param state: target state
"""
if self.state == OperandState.FREED:
return
if state == OperandState.CANCELLED:
can_be_freed = True
else:
can_be_freed = self._graph_ref.check_operand... | https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def _handle_worker_accept(self, worker):
def _dequeue_worker(endpoint, wait=True):
try:
with rewrite_worker_errors():
return self._get_execution_ref(address=endpoint).dequeue_graph(
self._session_id, self._op_key, _tell=True, _wait=wait
)
... | def _handle_worker_accept(self, worker):
def _dequeue_worker(endpoint, wait=True):
try:
with rewrite_worker_errors():
return self._get_execution_ref(address=endpoint).dequeue_graph(
self._session_id, self._op_key, _tell=True, _wait=wait
)
... | https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def _on_ready(self):
self.worker = None
self._execution_ref = None
# if under retry, give application a delay
delay = options.scheduler.retry_delay if self.retries else 0
# Send resource application. Submit job when worker assigned
try:
new_assignment = self._assigner_ref.get_worker_ass... | def _on_ready(self):
self.worker = None
self._execution_ref = None
# if under retry, give application a delay
delay = options.scheduler.retry_delay if self.retries else 0
# Send resource application. Submit job when worker assigned
try:
new_assignment = self._assigner_ref.get_worker_ass... | https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def _on_finished(self):
if self._last_state == OperandState.CANCELLING:
self.start_operand(OperandState.CANCELLING)
return
futures = []
# update pred & succ finish records to trigger further actions
# record if successors can be executed
for out_key in self._succ_keys:
futur... | def _on_finished(self):
if self._last_state == OperandState.CANCELLING:
self.start_operand(OperandState.CANCELLING)
return
futures = []
# update pred & succ finish records to trigger further actions
# record if successors can be executed
for out_key in self._succ_keys:
futur... | https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def _on_fatal(self):
if self._last_state == OperandState.FATAL:
return
futures = []
if self._position == OperandPosition.TERMINAL:
# update records in GraphActor to help decide if the whole graph finished execution
futures.extend(self._add_finished_terminal(final_state=GraphState.FA... | def _on_fatal(self):
if self._last_state == OperandState.FATAL:
return
futures = []
if self._position == OperandPosition.TERMINAL:
# update records in GraphActor to help decide if the whole graph finished execution
futures.append(
self._graph_ref.add_finished_terminal(
... | https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def _on_cancelled(self):
futures = []
if self._position == OperandPosition.TERMINAL:
futures.extend(self._add_finished_terminal(final_state=GraphState.CANCELLED))
for k in self._succ_keys:
futures.append(
self._get_operand_actor(k).stop_operand(
OperandState.CANCE... | def _on_cancelled(self):
futures = []
if self._position == OperandPosition.TERMINAL:
futures.append(
self._graph_ref.add_finished_terminal(
self._op_key, final_state=GraphState.CANCELLED, _tell=True, _wait=False
)
)
for k in self._succ_keys:
fu... | https://github.com/mars-project/mars/issues/179 | In [1]: from mars.deploy.local import new_cluster
In [2]: import mars.tensor as mt
In [3]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=2)
/Users/travis/miniconda3/conda-bld/arrow-cpp_1540410566532/work/cpp/src/plasma/store.cc:971: Allowing the Plasma store to use up to 3.43597GB of memory.
/Users/tr... | SystemError |
def fetch_tensors(self, tensors, **kw):
from .tensor.expressions.fetch import TensorFetch
results = []
to_concat_tensors = OrderedDict()
for i, tensor in enumerate(tensors):
if tensor.key not in self.stored_tensors:
# check if the tensor is executed before
raise ValueEr... | def fetch_tensors(self, tensors, **kw):
from .tensor.expressions.fetch import TensorFetch
results = []
to_concat_tensors = OrderedDict()
for i, tensor in enumerate(tensors):
if tensor.key not in self.stored_tensors:
# check if the tensor is executed before
raise ValueEr... | https://github.com/mars-project/mars/issues/276 | In [1]: from mars.deploy.local import new_cluster
In [2]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=3, shared_memory='20M',)
In [3]: import mars.tensor as mt
In [4]: import scipy.sparse as sps
In [5]: a = sps.csr_matrix((10000, 10000))
In [6]: b = sps.csr_matrix((10000, 1))
In [7]: t1 = mt.ten... | mars.error |
def default_size_estimator(ctx, chunk, multiplier=1):
exec_size = int(sum(ctx[inp.key][0] for inp in chunk.inputs or ()) * multiplier)
total_out_size = 0
chunk_sizes = dict()
outputs = chunk.op.outputs
for out in outputs:
try:
chunk_size = out.nbytes if not out.is_sparse() else ... | def default_size_estimator(ctx, chunk, multiplier=1):
exec_size = int(sum(ctx[inp.key][0] for inp in chunk.inputs or ()) * multiplier)
total_out_size = 0
chunk_sizes = dict()
outputs = chunk.op.outputs
for out in outputs:
try:
chunk_size = out.nbytes if not out.is_sparse() else ... | https://github.com/mars-project/mars/issues/276 | In [1]: from mars.deploy.local import new_cluster
In [2]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=3, shared_memory='20M',)
In [3]: import mars.tensor as mt
In [4]: import scipy.sparse as sps
In [5]: a = sps.csr_matrix((10000, 10000))
In [6]: b = sps.csr_matrix((10000, 1))
In [7]: t1 = mt.ten... | mars.error |
def get_executable_operand_dag(self, op_key, serialize=True):
"""
Make an operand into a worker-executable dag
:param op_key: operand key
:param serialize: whether to return serialized dag
"""
graph = DAG()
inputs_to_copied = dict()
for c in self._op_key_to_chunk[op_key]:
for in... | def get_executable_operand_dag(self, op_key, serialize=True):
"""
Make an operand into a worker-executable dag
:param op_key: operand key
:param serialize: whether to return serialized dag
"""
graph = DAG()
inputs_to_copied = dict()
for c in self._op_key_to_chunk[op_key]:
for in... | https://github.com/mars-project/mars/issues/276 | In [1]: from mars.deploy.local import new_cluster
In [2]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=3, shared_memory='20M',)
In [3]: import mars.tensor as mt
In [4]: import scipy.sparse as sps
In [5]: a = sps.csr_matrix((10000, 10000))
In [6]: b = sps.csr_matrix((10000, 1))
In [7]: t1 = mt.ten... | mars.error |
def build_tensor_merge_graph(self, tensor_key):
from ..tensor.expressions.merge.concatenate import TensorConcatenate
tiled_tensor = self._get_tensor_by_key(tensor_key)
graph = DAG()
if len(tiled_tensor.chunks) == 1:
# only one chunk, just trigger fetch
c = tiled_tensor.chunks[0]
... | def build_tensor_merge_graph(self, tensor_key):
from ..tensor.expressions.merge.concatenate import TensorConcatenate
tiled_tensor = self._get_tensor_by_key(tensor_key)
graph = DAG()
if len(tiled_tensor.chunks) == 1:
# only one chunk, just trigger fetch
c = tiled_tensor.chunks[0]
... | https://github.com/mars-project/mars/issues/276 | In [1]: from mars.deploy.local import new_cluster
In [2]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=3, shared_memory='20M',)
In [3]: import mars.tensor as mt
In [4]: import scipy.sparse as sps
In [5]: a = sps.csr_matrix((10000, 10000))
In [6]: b = sps.csr_matrix((10000, 1))
In [7]: t1 = mt.ten... | mars.error |
def build_fetch_graph(self, tensor_key):
"""
Convert single tensor to tiled fetch tensor and put into a graph which only contains one tensor
:param tensor_key: the key of tensor
"""
tiled_tensor = self._get_tensor_by_key(tensor_key)
graph = DAG()
chunks = []
for c in tiled_tensor.chunks... | def build_fetch_graph(self, tensor_key):
"""
Convert single tensor to tiled fetch tensor and put into a graph which only contains one tensor
:param tensor_key: the key of tensor
"""
tiled_tensor = self._get_tensor_by_key(tensor_key)
graph = DAG()
chunks = []
for c in tiled_tensor.chunks... | https://github.com/mars-project/mars/issues/276 | In [1]: from mars.deploy.local import new_cluster
In [2]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=3, shared_memory='20M',)
In [3]: import mars.tensor as mt
In [4]: import scipy.sparse as sps
In [5]: a = sps.csr_matrix((10000, 10000))
In [6]: b = sps.csr_matrix((10000, 1))
In [7]: t1 = mt.ten... | mars.error |
def __init__(self, dtype=None, to_fetch_key=None, sparse=False, **kw):
super(TensorFetch, self).__init__(
_dtype=dtype, _to_fetch_key=to_fetch_key, _sparse=sparse, **kw
)
| def __init__(self, dtype=None, to_fetch_key=None, **kw):
super(TensorFetch, self).__init__(_dtype=dtype, _to_fetch_key=to_fetch_key, **kw)
| https://github.com/mars-project/mars/issues/276 | In [1]: from mars.deploy.local import new_cluster
In [2]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=3, shared_memory='20M',)
In [3]: import mars.tensor as mt
In [4]: import scipy.sparse as sps
In [5]: a = sps.csr_matrix((10000, 10000))
In [6]: b = sps.csr_matrix((10000, 1))
In [7]: t1 = mt.ten... | mars.error |
def convert_to_fetch(entity):
from ..core import CHUNK_TYPE, TENSOR_TYPE
from .fetch import TensorFetch
if isinstance(entity, CHUNK_TYPE):
new_op = TensorFetch(dtype=entity.dtype, sparse=entity.op.sparse)
return new_op.new_chunk(
None, entity.shape, index=entity.index, _key=enti... | def convert_to_fetch(entity):
from ..core import CHUNK_TYPE, TENSOR_TYPE
from .fetch import TensorFetch
if isinstance(entity, CHUNK_TYPE):
new_op = TensorFetch(dtype=entity.dtype)
return new_op.new_chunk(
None, entity.shape, index=entity.index, _key=entity.key, _id=entity.id
... | https://github.com/mars-project/mars/issues/276 | In [1]: from mars.deploy.local import new_cluster
In [2]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=3, shared_memory='20M',)
In [3]: import mars.tensor as mt
In [4]: import scipy.sparse as sps
In [5]: a = sps.csr_matrix((10000, 10000))
In [6]: b = sps.csr_matrix((10000, 1))
In [7]: t1 = mt.ten... | mars.error |
def merge_tensor_chunks(input_tensor, ctx):
from .executor import Executor
from .tensor.expressions.fetch import TensorFetch
if len(input_tensor.chunks) == 1:
return ctx[input_tensor.chunks[0].key]
chunks = []
for c in input_tensor.chunks:
op = TensorFetch(dtype=c.dtype, sparse=c.o... | def merge_tensor_chunks(input_tensor, ctx):
from .executor import Executor
from .tensor.expressions.fetch import TensorFetch
if len(input_tensor.chunks) == 1:
return ctx[input_tensor.chunks[0].key]
chunks = []
for c in input_tensor.chunks:
op = TensorFetch(dtype=c.dtype)
ch... | https://github.com/mars-project/mars/issues/276 | In [1]: from mars.deploy.local import new_cluster
In [2]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=3, shared_memory='20M',)
In [3]: import mars.tensor as mt
In [4]: import scipy.sparse as sps
In [5]: a = sps.csr_matrix((10000, 10000))
In [6]: b = sps.csr_matrix((10000, 1))
In [7]: t1 = mt.ten... | mars.error |
def kernel_mode(func):
"""
A decorator for kernel functions.
When eager mode is on, expressions will be executed after `new_entities`, however
`new_entities` is also called in `Executor` and `OperandTilesHandler`, this decorator
provides an options context for kernel functions to avoid execution.
... | def kernel_mode(func):
"""
A decorator for kernel functions.
When eager mode is on, expressions will be executed after `new_entities`, however
`new_entities` is also called in `Executor` and `OperandTilesHandler`, this decorator
provides an options context for kernel functions to avoid execution.
... | https://github.com/mars-project/mars/issues/268 | In [1]: import mars.tensor as mt
In [2]: from mars.config import options
In [3]: a = mt.array(
...: [[0.1, 0.2, 0.3],
...: [0.3, 0.4, 0.2]]
...: )
In [4]: (a[:, mt.newaxis, :] - a[mt.newaxis, ...]).execute()
Out[4]:
array([[[ 0. , 0. , 0. ],
[-0.2, -0.2, 0.1]],
[[ 0.2, 0.2, -0.1],
[ 0. , 0. , 0. ... | KeyError |
def _wrapped(*args, **kwargs):
try:
_kernel_mode.eager = False
return func(*args, **kwargs)
finally:
_kernel_mode.eager = None
| def _wrapped(*args, **kwargs):
_kernel_mode.eager = False
return_value = func(*args, **kwargs)
_kernel_mode.eager = None
return return_value
| https://github.com/mars-project/mars/issues/268 | In [1]: import mars.tensor as mt
In [2]: from mars.config import options
In [3]: a = mt.array(
...: [[0.1, 0.2, 0.3],
...: [0.3, 0.4, 0.2]]
...: )
In [4]: (a[:, mt.newaxis, :] - a[mt.newaxis, ...]).execute()
Out[4]:
array([[[ 0. , 0. , 0. ],
[-0.2, -0.2, 0.1]],
[[ 0.2, 0.2, -0.1],
[ 0. , 0. , 0. ... | KeyError |
def tile(cls, op):
"""
Use LU decomposition to compute inverse of matrix.
Given a square matrix A:
P, L, U = lu(A)
b_eye is an identity matrix with the same shape as matrix A, then,
(P * L * U) * A_inv = b_eye
L * (U * A_inv) = P.T * b_eye
use `solve_triangular` twice to compute the inve... | def tile(cls, op):
"""
Use LU decomposition to compute inverse of matrix.
Given a square matrix A:
P, L, U = lu(A)
b_eye is an identity matrix with the same shape as matrix A, then,
(P * L * U) * A_inv = b_eye
L * (U * A_inv) = P.T * b_eye
use `solve_triangular` twice to compute the inve... | https://github.com/mars-project/mars/issues/250 | In [32]: a = mt.tensor(sps.csr_matrix([[0, 0], [1, 0]]))
In [33]: b = mt.linalg.inv(a)
In [34]: b.execute()
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
~/Workspace/mars/mars/tiles.py in _dispatch(self, op)
110 ... | KeyError |
def _execute_operand(self, op):
results = self._chunk_results
ref_counts = self._chunk_key_ref_counts
op_keys = self._executed_op_keys
executed_chunk_keys = set()
deleted_chunk_keys = set()
try:
ops = list(self._op_key_to_ops[op.key])
if not self._mock:
# do real exec... | def _execute_operand(self, op):
results = self._chunk_results
ref_counts = self._chunk_key_ref_counts
op_keys = self._executed_op_keys
try:
ops = list(self._op_key_to_ops[op.key])
if not self._mock:
# do real execution
# note that currently execution is the chunk-... | https://github.com/mars-project/mars/issues/248 | In [1]: import mars.tensor as mt
In [2]: a = mt.ones((10, 5), chunk_size=5)
In [3]: s = mt.linalg.svd(a)[1]
In [4]: s.execute()
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-4-4a5966ced510> in <mo... | KeyError |
def inv(a):
"""
Compute the (multiplicative) inverse of a matrix.
Given a square matrix `a`, return the matrix `ainv` satisfying
``dot(a, ainv) = dot(ainv, a) = eye(a.shape[0])``.
Parameters
----------
a : (..., M, M) array_like
Matrix to be inverted.
Returns
-------
ainv... | def inv(a):
"""
Compute the (multiplicative) inverse of a matrix.
Given a square matrix `a`, return the matrix `ainv` satisfying
``dot(a, ainv) = dot(ainv, a) = eye(a.shape[0])``.
Parameters
----------
a : (..., M, M) array_like
Matrix to be inverted.
Returns
-------
ainv... | https://github.com/mars-project/mars/issues/230 | In [1]: import mars.tensor as mt
In [2]: a = mt.random.randint(1, 10, (6, 6), chunk_size=3)
In [3]: b = a.dot(a)
In [4]: r = mt.linalg.inv(b)
Traceback (most recent call last):
File "/Users/hekaisheng/Documents/mars_dev/mars/mars/utils.py", line 65, in __getattr__
return self[item]
KeyError: 'raw_chunk_size'
During... | KeyError |
def tile(cls, op):
a, b = op.inputs
tensor = op.outputs[0]
# the axes to align on
a_axes = lrange(a.ndim - 2)[::-1] + [tensor.ndim - 2, tensor.ndim - 1]
b_axes = lrange(b.ndim - 2)[::-1] + [tensor.ndim - 1, tensor.ndim]
a, b = unify_chunks((a, a_axes), (b, b_axes))
get_nsplit = lambda i: a.... | def tile(cls, op):
a, b = op.inputs
tensor = op.outputs[0]
# the axes to align on
a_axes = lrange(a.ndim - 2)[::-1] + [tensor.ndim - 2, tensor.ndim - 1]
b_axes = lrange(b.ndim - 2)[::-1] + [tensor.ndim - 1, tensor.ndim]
a, b = unify_chunks((a, a_axes), (b, b_axes))
get_nsplit = lambda i: a.... | https://github.com/mars-project/mars/issues/230 | In [1]: import mars.tensor as mt
In [2]: a = mt.random.randint(1, 10, (6, 6), chunk_size=3)
In [3]: b = a.dot(a)
In [4]: r = mt.linalg.inv(b)
Traceback (most recent call last):
File "/Users/hekaisheng/Documents/mars_dev/mars/mars/utils.py", line 65, in __getattr__
return self[item]
KeyError: 'raw_chunk_size'
During... | KeyError |
def tile(cls, op):
a, b, a_axes, b_axes = op.a, op.b, op.a_axes, op.b_axes
c = itertools.count(max(a.ndim, b.ndim))
a_ax = tuple(a_axes.index(i) if i in a_axes else next(c) for i in range(a.ndim))
b_ax = tuple(b_axes.index(i) if i in b_axes else next(c) for i in range(b.ndim))
a, b = unify_chunks((... | def tile(cls, op):
a, b, a_axes, b_axes = op.a, op.b, op.a_axes, op.b_axes
c = itertools.count(max(a.ndim, b.ndim))
a_ax = tuple(a_axes.index(i) if i in a_axes else next(c) for i in range(a.ndim))
b_ax = tuple(b_axes.index(i) if i in b_axes else next(c) for i in range(b.ndim))
a, b = unify_chunks((... | https://github.com/mars-project/mars/issues/230 | In [1]: import mars.tensor as mt
In [2]: a = mt.random.randint(1, 10, (6, 6), chunk_size=3)
In [3]: b = a.dot(a)
In [4]: r = mt.linalg.inv(b)
Traceback (most recent call last):
File "/Users/hekaisheng/Documents/mars_dev/mars/mars/utils.py", line 65, in __getattr__
return self[item]
KeyError: 'raw_chunk_size'
During... | KeyError |
def _execute_operand(self, op):
results = self._chunk_results
ref_counts = self._chunk_key_ref_counts
op_keys = self._executed_op_keys
try:
ops = list(self._op_key_to_ops[op.key])
if not self._mock:
# do real execution
# note that currently execution is the chunk-... | def _execute_operand(self, op):
results = self._chunk_results
ref_counts = self._chunk_key_ref_counts
op_keys = self._executed_op_keys
try:
ops = list(self._op_key_to_ops[op.key])
if not self._mock:
# do real execution
# note that currently execution is the chunk-... | https://github.com/mars-project/mars/issues/220 | In [1]: import mars.tensor as mt
In [2]: a = mt.random.randint(1, 10, (5, 5))
...: arrs = mt.linalg.qr(a)
...: arrs[0].execute()
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
~/Documents/mars_dev/mars/mars/graph.p... | KeyError |
def _main(self, argv=None):
parser = argparse.ArgumentParser(description=self.service_description)
parser.add_argument("-a", "--advertise", help="advertise ip")
parser.add_argument(
"-k",
"--kv-store",
help="address of kv store service, for instance, etcd://localhost:4001",
)
... | def _main(self, argv=None):
parser = argparse.ArgumentParser(description=self.service_description)
parser.add_argument("-a", "--advertise", help="advertise ip")
parser.add_argument(
"-k",
"--kv-store",
help="address of kv store service, for instance, etcd://localhost:4001",
)
... | https://github.com/mars-project/mars/issues/201 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 766, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 444, in mars.actors.pool.gevent_pool.ActorRemoteHelper._send_remote
File "mars/actors/pool/gevent_pool.pyx", line 448, in mars.actors.pool.gevent_pool.ActorRemoteHel... | ValueError |
def main_loop(self):
try:
with self.pool:
try:
self.start()
self._running = True
while True:
self.pool.join(1)
stopped = []
for idx, proc in enumerate(self.pool.processes):
... | def main_loop(self):
if self.args.profile == -1:
profile_file = None
else:
profile_file = self.args.profile or (
"mars_" + self.__class__.__name__ + ".prof"
)
try:
if profile_file:
import yappi
yappi.set_clock_type("wall")
yapp... | https://github.com/mars-project/mars/issues/201 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 766, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 444, in mars.actors.pool.gevent_pool.ActorRemoteHelper._send_remote
File "mars/actors/pool/gevent_pool.pyx", line 448, in mars.actors.pool.gevent_pool.ActorRemoteHel... | ValueError |
def _get_schedulers(self):
schedulers = [
s.key.rsplit("/", 1)[1] for s in self._client.read(SCHEDULER_PATH).children
]
logger.debug("Schedulers obtained. Results: %r", schedulers)
return [to_str(s) for s in schedulers]
| def _get_schedulers(self):
schedulers = [
s.key.rsplit("/", 1)[1] for s in self._client.read(SCHEDULER_PATH).children
]
logger.debug("Schedulers obtained. Results: %r", schedulers)
return schedulers
| https://github.com/mars-project/mars/issues/201 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 766, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 444, in mars.actors.pool.gevent_pool.ActorRemoteHelper._send_remote
File "mars/actors/pool/gevent_pool.pyx", line 448, in mars.actors.pool.gevent_pool.ActorRemoteHel... | ValueError |
def watch(self):
for new_schedulers in self._client.eternal_watch(SCHEDULER_PATH):
self._cluster_info_ref.set_schedulers([to_str(s) for s in new_schedulers])
| def watch(self):
for new_schedulers in self._client.eternal_watch(SCHEDULER_PATH):
self._cluster_info_ref.set_schedulers(new_schedulers)
| https://github.com/mars-project/mars/issues/201 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 766, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 444, in mars.actors.pool.gevent_pool.ActorRemoteHelper._send_remote
File "mars/actors/pool/gevent_pool.pyx", line 448, in mars.actors.pool.gevent_pool.ActorRemoteHel... | ValueError |
def _values_(self):
return [
getattr(self, k, None) for k in self._keys_ if k not in self._no_copy_attrs_
]
| def _values_(self):
return [
getattr(self, k, None) for k in self.__slots__ if k not in self._no_copy_attrs_
]
| https://github.com/mars-project/mars/issues/201 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 766, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 444, in mars.actors.pool.gevent_pool.ActorRemoteHelper._send_remote
File "mars/actors/pool/gevent_pool.pyx", line 448, in mars.actors.pool.gevent_pool.ActorRemoteHel... | ValueError |
def update_key(self):
object.__setattr__(
self,
"_key",
tokenize(
type(self), *(getattr(self, k, None) for k in self._keys_ if k != "_index")
),
)
| def update_key(self):
object.__setattr__(
self,
"_key",
tokenize(
type(self),
*(getattr(self, k, None) for k in self.__slots__ if k != "_index"),
),
)
| https://github.com/mars-project/mars/issues/201 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 766, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 444, in mars.actors.pool.gevent_pool.ActorRemoteHelper._send_remote
File "mars/actors/pool/gevent_pool.pyx", line 448, in mars.actors.pool.gevent_pool.ActorRemoteHel... | ValueError |
def update_key(self):
args = tuple(getattr(self, k, None) for k in self._keys_)
if self.state is None:
args += (np.random.random(),)
self._key = tokenize(type(self), *args)
| def update_key(self):
args = tuple(getattr(self, k, None) for k in self.__slots__)
if self.state is None:
args += (np.random.random(),)
self._key = tokenize(type(self), *args)
| https://github.com/mars-project/mars/issues/201 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 766, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 444, in mars.actors.pool.gevent_pool.ActorRemoteHelper._send_remote
File "mars/actors/pool/gevent_pool.pyx", line 448, in mars.actors.pool.gevent_pool.ActorRemoteHel... | ValueError |
def start(self, endpoint, schedulers, pool):
"""
there are two way to start a scheduler
1) if options.kv_store is specified as an etcd address, the endpoint will be written
into kv-storage to indicate that this scheduler is one the schedulers,
and the etcd is used as a service discover.
2) if op... | def start(self, endpoint, schedulers, pool):
"""
there are two way to start a scheduler
1) if options.kv_store is specified as an etcd address, the endpoint will be written
into kv-storage to indicate that this scheduler is one the schedulers,
and the etcd is used as a service discover.
2) if op... | https://github.com/mars-project/mars/issues/201 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 766, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 444, in mars.actors.pool.gevent_pool.ActorRemoteHelper._send_remote
File "mars/actors/pool/gevent_pool.pyx", line 448, in mars.actors.pool.gevent_pool.ActorRemoteHel... | ValueError |
def _prepare_graph_inputs(self, session_id, graph_key):
"""
Load input data from spilled storage and other workers
:param session_id: session id
:param graph_key: key of the execution graph
"""
graph_record = self._graph_records[(session_id, graph_key)]
if graph_record.stop_requested:
... | def _prepare_graph_inputs(self, session_id, graph_key):
"""
Load input data from spilled storage and other workers
:param session_id: session id
:param graph_key: key of the execution graph
"""
graph_record = self._graph_records[(session_id, graph_key)]
if graph_record.stop_requested:
... | https://github.com/mars-project/mars/issues/201 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 766, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 444, in mars.actors.pool.gevent_pool.ActorRemoteHelper._send_remote
File "mars/actors/pool/gevent_pool.pyx", line 448, in mars.actors.pool.gevent_pool.ActorRemoteHel... | ValueError |
def start(
self, endpoint, pool, distributed=True, schedulers=None, process_start_index=0
):
if schedulers:
if isinstance(schedulers, six.string_types):
schedulers = schedulers.split(",")
service_discover_addr = None
else:
schedulers = None
service_discover_addr =... | def start(
self, endpoint, pool, distributed=True, schedulers=None, process_start_index=0
):
if schedulers:
if isinstance(schedulers, six.string_types):
schedulers = [schedulers]
service_discover_addr = None
else:
schedulers = None
service_discover_addr = options.... | https://github.com/mars-project/mars/issues/201 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 766, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 444, in mars.actors.pool.gevent_pool.ActorRemoteHelper._send_remote
File "mars/actors/pool/gevent_pool.pyx", line 448, in mars.actors.pool.gevent_pool.ActorRemoteHel... | ValueError |
def execute_graph(
self,
session_id,
graph_key,
graph_ser,
io_meta,
data_sizes,
send_targets=None,
callback=None,
):
"""
Submit graph to the worker and control the execution
:param session_id: session id
:param graph_key: graph key
:param graph_ser: serialized executa... | def execute_graph(
self,
session_id,
graph_key,
graph_ser,
io_meta,
data_sizes,
send_targets=None,
callback=None,
):
"""
Submit graph to the worker and control the execution
:param session_id: session id
:param graph_key: graph key
:param graph_ser: serialized executa... | https://github.com/mars-project/mars/issues/129 | Unexpected error occurred in executing bd974beb010abfa6964bdee22c5d2080
Traceback (most recent call last):
File "/home/admin/work/_public-mars-0.1.0b1.zip/mars/worker/execution.py", line 457, in _handle_rejection
six.reraise(*exc)
File "/home/admin/work/_public-mars-0.1.0b1.zip/mars/lib/six.py", line 703, in reraise
ra... | AttributeError |
def _prepare_inputs(*_):
if graph_key in self._stop_requests:
raise ExecutionInterrupted
logger.debug("Start preparing input data for graph %s", graph_key)
self._update_stage_info(session_id, graph_key, graph_ops, "prepare_inputs")
prepare_promises = []
handled_keys = set()
for chunk i... | def _prepare_inputs(*_):
if graph_key in self._stop_requests:
raise ExecutionInterrupted
logger.debug("Start preparing input data for graph %s", graph_key)
self._update_stage_info(session_id, graph_key, graph_ops, "prepare_inputs")
prepare_promises = []
handled_keys = set()
for chunk i... | https://github.com/mars-project/mars/issues/129 | Unexpected error occurred in executing bd974beb010abfa6964bdee22c5d2080
Traceback (most recent call last):
File "/home/admin/work/_public-mars-0.1.0b1.zip/mars/worker/execution.py", line 457, in _handle_rejection
six.reraise(*exc)
File "/home/admin/work/_public-mars-0.1.0b1.zip/mars/lib/six.py", line 703, in reraise
ra... | AttributeError |
def __init__(
self,
session_id,
graph_key,
serialized_tensor_graph,
target_tensors=None,
serialized_chunk_graph=None,
state=GraphState.UNSCHEDULED,
final_state=None,
):
super(GraphActor, self).__init__()
self._graph_key = graph_key
self._session_id = session_id
self._seri... | def __init__(
self,
session_id,
graph_key,
serialized_tensor_graph,
target_tensors=None,
serialized_chunk_graph=None,
state=GraphState.UNSCHEDULED,
final_state=None,
):
super(GraphActor, self).__init__()
self._graph_key = graph_key
self._session_id = session_id
self._seri... | https://github.com/mars-project/mars/issues/99 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 716, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 88, in mars.actors.pool.gevent_pool.ActorExecutionContext.fire_run
File "mars/actors/pool/gevent_pool.pyx", line 91, in mars.actors.pool.gevent_pool.ActorExecutionCo... | IndexError |
def execute_graph(self):
"""
Start graph execution
"""
def _detect_cancel(callback=None):
if self.reload_state() == GraphState.CANCELLING:
logger.info("Cancel detected, stopping")
if callback:
callback()
else:
self._end_time = ... | def execute_graph(self):
"""
Start graph execution
"""
def _detect_cancel(callback=None):
if self.reload_state() == GraphState.CANCELLING:
logger.info("Cancel detected, stopping")
if callback:
callback()
else:
self._end_time = ... | https://github.com/mars-project/mars/issues/99 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 716, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 88, in mars.actors.pool.gevent_pool.ActorExecutionContext.fire_run
File "mars/actors/pool/gevent_pool.pyx", line 91, in mars.actors.pool.gevent_pool.ActorExecutionCo... | IndexError |
def stop_graph(self):
"""
Stop graph execution
"""
from .operand import OperandActor
if self.state == GraphState.CANCELLED:
return
self.state = GraphState.CANCELLING
try:
chunk_graph = self.get_chunk_graph()
except (KeyError, GraphNotExists):
self.state = GraphS... | def stop_graph(self):
"""
Stop graph execution
"""
from .operand import OperandActor
if self.state == GraphState.CANCELLED:
return
self.state = GraphState.CANCELLING
try:
chunk_graph = self.get_chunk_graph()
except (KeyError, GraphNotExists):
self.state = GraphS... | https://github.com/mars-project/mars/issues/99 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 716, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 88, in mars.actors.pool.gevent_pool.ActorExecutionContext.fire_run
File "mars/actors/pool/gevent_pool.pyx", line 91, in mars.actors.pool.gevent_pool.ActorExecutionCo... | IndexError |
def prepare_graph(self, compose=True):
"""
Tile and compose tensor graph into chunk graph
:param compose: if True, do compose after tiling
"""
tensor_graph = deserialize_graph(self._serialized_tensor_graph)
self._tensor_graph_cache = tensor_graph
logger.debug(
"Begin preparing graph... | def prepare_graph(self, compose=True):
"""
Tile and compose tensor graph into chunk graph
:param compose: if True, do compose after tiling
"""
tensor_graph = deserialize_graph(self._serialized_tensor_graph)
self._tensor_graph_cache = tensor_graph
logger.debug(
"Begin preparing graph... | https://github.com/mars-project/mars/issues/99 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 716, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 88, in mars.actors.pool.gevent_pool.ActorExecutionContext.fire_run
File "mars/actors/pool/gevent_pool.pyx", line 91, in mars.actors.pool.gevent_pool.ActorExecutionCo... | IndexError |
def free_tensor_data(self, tensor_key):
from .operand import OperandActor
tiled_tensor = self._get_tensor_by_key(tensor_key)
for chunk in tiled_tensor.chunks:
op_uid = OperandActor.gen_uid(self._session_id, chunk.op.key)
scheduler_addr = self.get_scheduler(op_uid)
op_ref = self.ctx.... | def free_tensor_data(self, tensor_key):
from .operand import OperandActor
tiled_tensor = self._tensor_to_tiled[tensor_key][-1]
for chunk in tiled_tensor.chunks:
op_uid = OperandActor.gen_uid(self._session_id, chunk.op.key)
scheduler_addr = self.get_scheduler(op_uid)
op_ref = self.ct... | https://github.com/mars-project/mars/issues/99 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 716, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 88, in mars.actors.pool.gevent_pool.ActorExecutionContext.fire_run
File "mars/actors/pool/gevent_pool.pyx", line 91, in mars.actors.pool.gevent_pool.ActorExecutionCo... | IndexError |
def build_tensor_merge_graph(self, tensor_key):
from ..tensor.expressions.merge.concatenate import TensorConcatenate
from ..tensor.expressions.datasource import TensorFetchChunk
tiled_tensor = self._get_tensor_by_key(tensor_key)
graph = DAG()
if len(tiled_tensor.chunks) == 1:
# only one chu... | def build_tensor_merge_graph(self, tensor_key):
from ..tensor.expressions.merge.concatenate import TensorConcatenate
from ..tensor.expressions.datasource import TensorFetchChunk
tiled_tensor = self._tensor_to_tiled[tensor_key][-1]
graph = DAG()
if len(tiled_tensor.chunks) == 1:
# only one c... | https://github.com/mars-project/mars/issues/99 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 716, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 88, in mars.actors.pool.gevent_pool.ActorExecutionContext.fire_run
File "mars/actors/pool/gevent_pool.pyx", line 91, in mars.actors.pool.gevent_pool.ActorExecutionCo... | IndexError |
def fetch_tensor_result(self, tensor_key):
from ..worker.transfer import ResultSenderActor
# TODO for test
tiled_tensor = self._get_tensor_by_key(tensor_key)
if tensor_key not in self._terminated_tensors:
return None
ctx = dict()
for chunk_key in [c.key for c in tiled_tensor.chunks]:
... | def fetch_tensor_result(self, tensor_key):
from ..worker.transfer import ResultSenderActor
# TODO for test
tiled_tensor = self._tensor_to_tiled[tensor_key][-1]
if tensor_key not in self._terminated_tensors:
return None
ctx = dict()
for chunk_key in [c.key for c in tiled_tensor.chunks]:... | https://github.com/mars-project/mars/issues/99 | Traceback (most recent call last):
File "src/gevent/greenlet.py", line 716, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 88, in mars.actors.pool.gevent_pool.ActorExecutionContext.fire_run
File "mars/actors/pool/gevent_pool.pyx", line 91, in mars.actors.pool.gevent_pool.ActorExecutionCo... | IndexError |
def run(self, *tensors, **kw):
from . import tensor as mt
ret_list = False
if len(tensors) == 1 and isinstance(tensors[0], (tuple, list)):
ret_list = True
tensors = tensors[0]
elif len(tensors) > 1:
ret_list = True
tensors = tuple(mt.tensor(t) for t in tensors)
run_tens... | def run(self, *tensors, **kw):
from . import tensor as mt
ret_list = False
if len(tensors) == 1 and isinstance(tensors[0], (tuple, list)):
ret_list = True
tensors = tensors[0]
elif len(tensors) > 1:
ret_list = True
tensors = tuple(mt.tensor(t) for t in tensors)
result =... | https://github.com/mars-project/mars/issues/17 | Creating operand actors for graph 93ba7372-e748-40ab-af14-6c250f845ba4
Traceback (most recent call last):
File "src/gevent/greenlet.py", line 716, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 88, in mars.actors.pool.gevent_pool.ActorExecutionContext.fire_run
File "mars/actors/pool/geve... | mars.actors.errors.ActorAlreadyExist |
def decref(self, *keys):
self._executed_keys = self._executed_keys.difference(keys)
if hasattr(self._sess, "decref"):
self._sess.decref(*keys)
| def decref(self, *keys):
if hasattr(self._sess, "decref"):
self._sess.decref(*keys)
| https://github.com/mars-project/mars/issues/17 | Creating operand actors for graph 93ba7372-e748-40ab-af14-6c250f845ba4
Traceback (most recent call last):
File "src/gevent/greenlet.py", line 716, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 88, in mars.actors.pool.gevent_pool.ActorExecutionContext.fire_run
File "mars/actors/pool/geve... | mars.actors.errors.ActorAlreadyExist |
def __exit__(self, *_):
self.close()
| def __exit__(self, exc_type, exc_val, exc_tb):
self.close()
| https://github.com/mars-project/mars/issues/17 | Creating operand actors for graph 93ba7372-e748-40ab-af14-6c250f845ba4
Traceback (most recent call last):
File "src/gevent/greenlet.py", line 716, in gevent._greenlet.Greenlet.run
File "mars/actors/pool/gevent_pool.pyx", line 88, in mars.actors.pool.gevent_pool.ActorExecutionContext.fire_run
File "mars/actors/pool/geve... | mars.actors.errors.ActorAlreadyExist |
def prepare_graph(self, compose=True):
"""
Tile and compose tensor graph into chunk graph
:param compose: if True, do compose after tiling
"""
tensor_graph = deserialize_graph(self._serialized_tensor_graph)
self._tensor_graph_cache = tensor_graph
logger.debug(
"Begin preparing graph... | def prepare_graph(self, compose=True):
"""
Tile and compose tensor graph into chunk graph
:param compose: if True, do compose after tiling
"""
tensor_graph = deserialize_graph(self._serialized_tensor_graph)
self._tensor_graph_cache = tensor_graph
logger.debug(
"Begin preparing graph... | https://github.com/mars-project/mars/issues/56 | In [16]: a = mt.random.rand(20, 10, chunk_size=10)
In [19]: _, s, _ = mt.linalg.svd(a)
In [20]: s.build_graph(tiled=False)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-20-77797d4ed4a0> in <module>... | AttributeError |
def execute_chunk(
chunk,
executor=None,
ref_counts=None,
chunk_result=None,
finishes=None,
visited=None,
q=None,
lock=None,
semaphore=None,
has_error=None,
preds=None,
succs=None,
mock=False,
sparse_mock_percent=1.0,
):
try:
with lock:
if ... | def execute_chunk(
chunk,
executor=None,
ref_counts=None,
chunk_result=None,
finishes=None,
visited=None,
q=None,
lock=None,
semaphore=None,
has_error=None,
preds=None,
succs=None,
mock=False,
sparse_mock_percent=1.0,
):
try:
with lock:
if ... | https://github.com/mars-project/mars/issues/56 | In [16]: a = mt.random.rand(20, 10, chunk_size=10)
In [19]: _, s, _ = mt.linalg.svd(a)
In [20]: s.build_graph(tiled=False)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-20-77797d4ed4a0> in <module>... | AttributeError |
def new_tensors(
self,
inputs,
shape,
dtype=None,
chunks=None,
nsplits=None,
output_limit=None,
kws=None,
**kw,
):
tensor_cls = SparseTensor if getattr(self, "issparse")() else Tensor
output_limit = (
getattr(self, "output_limit") if output_limit is None else output_l... | def new_tensors(
self,
inputs,
shape,
dtype=None,
chunks=None,
nsplits=None,
output_limit=None,
kws=None,
**kw,
):
tensor_cls = SparseTensor if getattr(self, "issparse")() else Tensor
output_limit = (
getattr(self, "output_limit") if output_limit is None else output_l... | https://github.com/mars-project/mars/issues/56 | In [16]: a = mt.random.rand(20, 10, chunk_size=10)
In [19]: _, s, _ = mt.linalg.svd(a)
In [20]: s.build_graph(tiled=False)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-20-77797d4ed4a0> in <module>... | AttributeError |
def tile(cls, op):
raise NotSupportTile(
"TensorFuseChunk is a chunk operand which does not support tile"
)
| def tile(cls, op):
raise NotSupportTile("FetchChunk is a chunk operand which does not support tile")
| https://github.com/mars-project/mars/issues/56 | In [16]: a = mt.random.rand(20, 10, chunk_size=10)
In [19]: _, s, _ = mt.linalg.svd(a)
In [20]: s.build_graph(tiled=False)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-20-77797d4ed4a0> in <module>... | AttributeError |
def tile(cls, op):
from ..merge.concatenate import TensorConcatenate
from ..indexing.slice import TensorSlice
from .dot import TensorDot
from .qr import TensorQR
from .svd import TensorSVD
calc_svd = cls._is_svd()
a = op.input
tinyq, tinyr = np.linalg.qr(np.ones((1, 1), dtype=a.dtype)... | def tile(cls, op):
from ..merge.concatenate import TensorConcatenate
from ..indexing.slice import TensorSlice
from .dot import TensorDot
from .qr import TensorQR
from .svd import TensorSVD
calc_svd = cls._is_svd()
get_obj_attr = cls._get_obj_attr
a = op.input
tinyq, tinyr = np.lin... | https://github.com/mars-project/mars/issues/56 | In [16]: a = mt.random.rand(20, 10, chunk_size=10)
In [19]: _, s, _ = mt.linalg.svd(a)
In [20]: s.build_graph(tiled=False)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-20-77797d4ed4a0> in <module>... | AttributeError |
def tile(cls, op):
q, r = op.outputs
q_dtype, r_dtype = q.dtype, r.dtype
q_shape, r_shape = q.shape, r.shape
in_tensor = op.input
if in_tensor.chunk_shape == (1, 1):
in_chunk = in_tensor.chunks[0]
chunk_op = op.copy().reset_key()
qr_chunks = chunk_op.new_chunks(
[... | def tile(cls, op):
q, r = op.outputs
q_dtype, r_dtype = cls._get_obj_attr(q, "dtype"), cls._get_obj_attr(r, "dtype")
q_shape, r_shape = cls._get_obj_attr(q, "shape"), cls._get_obj_attr(r, "shape")
in_tensor = op.input
if in_tensor.chunk_shape == (1, 1):
in_chunk = in_tensor.chunks[0]
... | https://github.com/mars-project/mars/issues/56 | In [16]: a = mt.random.rand(20, 10, chunk_size=10)
In [19]: _, s, _ = mt.linalg.svd(a)
In [20]: s.build_graph(tiled=False)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-20-77797d4ed4a0> in <module>... | AttributeError |
def tile(cls, op):
U, s, V = op.outputs
U_dtype, s_dtype, V_dtype = U.dtype, s.dtype, V.dtype
U_shape, s_shape, V_shape = U.shape, s.shape, V.shape
in_tensor = op.input
if in_tensor.chunk_shape == (1, 1):
in_chunk = in_tensor.chunks[0]
chunk_op = op.copy().reset_key()
svd_chu... | def tile(cls, op):
get_obj_attr = cls._get_obj_attr
U, s, V = op.outputs
U_dtype, s_dtype, V_dtype = (
get_obj_attr(U, "dtype"),
get_obj_attr(s, "dtype"),
get_obj_attr(V, "dtype"),
)
U_shape, s_shape, V_shape = (
get_obj_attr(U, "shape"),
get_obj_attr(s, "shap... | https://github.com/mars-project/mars/issues/56 | In [16]: a = mt.random.rand(20, 10, chunk_size=10)
In [19]: _, s, _ = mt.linalg.svd(a)
In [20]: s.build_graph(tiled=False)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-20-77797d4ed4a0> in <module>... | AttributeError |
def _index_set_value(ctx, chunk):
indexes = [
ctx[index.key] if hasattr(index, "key") else index for index in chunk.op.indexes
]
input = ctx[chunk.inputs[0].key].copy()
value = (
ctx[chunk.op.value.key] if hasattr(chunk.op.value, "key") else chunk.op.value
)
if hasattr(input, "fl... | def _index_set_value(ctx, chunk):
indexes = [
ctx[index.key] if hasattr(index, "key") else index for index in chunk.op.indexes
]
input = ctx[chunk.inputs[0].key]
value = (
ctx[chunk.op.value.key] if hasattr(chunk.op.value, "key") else chunk.op.value
)
if hasattr(input, "flags") a... | https://github.com/mars-project/mars/issues/64 | In [1]: from mars.deploy.local import new_cluster
In [2]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=3, web=True)
In [3]: import mars.tensor as mt
In [4]: t = mt.random.rand(10, 10)
In [5]: mt.split(t, 5).execute()
Traceback (most recent call last):
File "src/gevent/greenlet.py", line 716, in gev... | ValueError |
def new_tensors(self, inputs, shape, **kw):
indexes = kw.pop("indexes", None)
with self._handle_params(inputs, indexes) as mix_inputs:
return super(TensorIndex, self).new_tensors(mix_inputs, shape, **kw)
| def new_tensors(self, inputs, shape, **kw):
tensor, indexes = inputs
self._indexes = indexes
inputs = self._handle_inputs(inputs)
return super(TensorIndex, self).new_tensors(inputs, shape, **kw)
| https://github.com/mars-project/mars/issues/64 | In [1]: from mars.deploy.local import new_cluster
In [2]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=3, web=True)
In [3]: import mars.tensor as mt
In [4]: t = mt.random.rand(10, 10)
In [5]: mt.split(t, 5).execute()
Traceback (most recent call last):
File "src/gevent/greenlet.py", line 716, in gev... | ValueError |
def new_chunks(self, inputs, shape, **kw):
indexes = kw.pop("indexes", None)
with self._handle_params(inputs, indexes) as mix_inputs:
return super(TensorIndex, self).new_chunks(mix_inputs, shape, **kw)
| def new_chunks(self, inputs, shape, **kw):
chunk, indexes = inputs
self._indexes = indexes
inputs = self._handle_inputs(inputs)
return super(TensorIndex, self).new_chunks(inputs, shape, **kw)
| https://github.com/mars-project/mars/issues/64 | In [1]: from mars.deploy.local import new_cluster
In [2]: cluster = new_cluster(scheduler_n_process=2, worker_n_process=3, web=True)
In [3]: import mars.tensor as mt
In [4]: t = mt.random.rand(10, 10)
In [5]: mt.split(t, 5).execute()
Traceback (most recent call last):
File "src/gevent/greenlet.py", line 716, in gev... | ValueError |
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