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 _update_tileable_and_its_chunk_shapes(self):
need_update_tileable_to_tiled = dict()
for tileable in self._chunk_graph_builder.prev_tileable_graph:
if tileable.key in self._target_tileable_finished:
tiled = self._tileable_key_opid_to_tiled[tileable.key, tileable.op.id][-1]
if ... | def _update_tileable_and_its_chunk_shapes(self):
need_update_tileable_to_tiled = dict()
for tileable in self._chunk_graph_builder.prev_tileable_graph:
if tileable.key in self._target_tileable_finished:
tiled = self._tileable_key_opid_to_tiled[tileable.key, tileable.op.id][-1]
if ... | https://github.com/mars-project/mars/issues/1741 | 2020-12-02 11:19:40,309 mars.scheduler.operands.common 87 ERROR Attempt 1: Unexpected error KeyError occurred in executing operand 5c7a3b06d448300987640036d2f5a34e in 11.238.145.234:49708
Traceback (most recent call last):
File "/home/admin/work/_public-mars-0.5.5.zip/mars/promise.py", line 378, in _wrapped
return f... | KeyError |
def append_graph(self, graph_key, op_info):
super().append_graph(graph_key, op_info)
if not self._is_terminal:
self._is_terminal = op_info.get("is_terminal")
if self.state in OperandState.STORED_STATES:
metas = self.chunk_meta.batch_get_chunk_meta(
self._session_id, self._io_me... | def append_graph(self, graph_key, op_info):
super().append_graph(graph_key, op_info)
if not self._is_terminal:
self._is_terminal = op_info.get("is_terminal")
if self.state not in OperandState.TERMINATED_STATES:
for in_key in self._pred_keys:
self._get_operand_actor(in_key).remo... | https://github.com/mars-project/mars/issues/1741 | 2020-12-02 11:19:40,309 mars.scheduler.operands.common 87 ERROR Attempt 1: Unexpected error KeyError occurred in executing operand 5c7a3b06d448300987640036d2f5a34e in 11.238.145.234:49708
Traceback (most recent call last):
File "/home/admin/work/_public-mars-0.5.5.zip/mars/promise.py", line 378, in _wrapped
return f... | KeyError |
def create_reader(
self,
session_id,
data_key,
source_devices,
packed=False,
packed_compression=None,
_promise=True,
):
"""
Create a data reader from existing data and return in a Promise.
If no readers can be created, will try copying the data into a
readable storage.
:... | def create_reader(
self,
session_id,
data_key,
source_devices,
packed=False,
packed_compression=None,
_promise=True,
):
"""
Create a data reader from existing data and return in a Promise.
If no readers can be created, will try copying the data into a
readable storage.
:... | https://github.com/mars-project/mars/issues/1741 | 2020-12-02 11:19:40,309 mars.scheduler.operands.common 87 ERROR Attempt 1: Unexpected error KeyError occurred in executing operand 5c7a3b06d448300987640036d2f5a34e in 11.238.145.234:49708
Traceback (most recent call last):
File "/home/admin/work/_public-mars-0.5.5.zip/mars/promise.py", line 378, in _wrapped
return f... | KeyError |
def execute(cls, ctx, op):
def _base_concat(chunk, inputs):
# auto generated concat when executing a DataFrame, Series or Index
if chunk.op.output_types[0] == OutputType.dataframe:
return _auto_concat_dataframe_chunks(chunk, inputs)
elif chunk.op.output_types[0] == OutputType.ser... | def execute(cls, ctx, op):
def _base_concat(chunk, inputs):
# auto generated concat when executing a DataFrame, Series or Index
if chunk.op.output_types[0] == OutputType.dataframe:
return _auto_concat_dataframe_chunks(chunk, inputs)
elif chunk.op.output_types[0] == OutputType.ser... | https://github.com/mars-project/mars/issues/1740 | Error
Traceback (most recent call last):
File "/Users/wenjun.swj/Code/mars/mars/scheduler/graph.py", line 410, in _execute_graph
self.prepare_graph(compose=compose)
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line 377, in _wrapped
return func(*args, **kwargs)
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line... | KeyError |
def _auto_concat_dataframe_chunks(chunk, inputs):
xdf = (
pd if isinstance(inputs[0], (pd.DataFrame, pd.Series)) or cudf is None else cudf
)
if chunk.op.axis is not None:
return xdf.concat(inputs, axis=op.axis)
# auto generated concat when executing a DataFrame
if len(inputs) == 1:... | def _auto_concat_dataframe_chunks(chunk, inputs):
xdf = (
pd if isinstance(inputs[0], (pd.DataFrame, pd.Series)) or cudf is None else cudf
)
if chunk.op.axis is not None:
return xdf.concat(inputs, axis=op.axis)
# auto generated concat when executing a DataFrame
if len(inputs) == 1:... | https://github.com/mars-project/mars/issues/1740 | Error
Traceback (most recent call last):
File "/Users/wenjun.swj/Code/mars/mars/scheduler/graph.py", line 410, in _execute_graph
self.prepare_graph(compose=compose)
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line 377, in _wrapped
return func(*args, **kwargs)
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line... | KeyError |
def _calc_dataframe_params(cls, chunk_index_to_chunks, chunk_shape):
dtypes = pd.concat(
[
chunk_index_to_chunks[0, i].dtypes
for i in range(chunk_shape[1])
if (0, i) in chunk_index_to_chunks
]
)
columns_value = parse_index(dtypes.index, store_data=True)
... | def _calc_dataframe_params(cls, chunk_index_to_chunks, chunk_shape):
dtypes = pd.concat(
[chunk_index_to_chunks[0, i].dtypes for i in range(chunk_shape[1])]
)
columns_value = parse_index(dtypes.index, store_data=True)
pd_indxes = [
chunk_index_to_chunks[i, 0].index_value.to_pandas()
... | https://github.com/mars-project/mars/issues/1740 | Error
Traceback (most recent call last):
File "/Users/wenjun.swj/Code/mars/mars/scheduler/graph.py", line 410, in _execute_graph
self.prepare_graph(compose=compose)
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line 377, in _wrapped
return func(*args, **kwargs)
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line... | KeyError |
def parse_args(self, parser, argv, environ=None):
args = super().parse_args(parser, argv)
environ = environ or os.environ
args.disable_failover = args.disable_failover or bool(
int(environ.get("MARS_DISABLE_FAILOVER", "0"))
)
options.scheduler.dump_graph_data = bool(
int(environ.get(... | def parse_args(self, parser, argv, environ=None):
args = super().parse_args(parser, argv)
environ = environ or os.environ
args.disable_failover = args.disable_failover or bool(
int(environ.get("MARS_DISABLE_FAILOVER", "0"))
)
return args
| https://github.com/mars-project/mars/issues/1740 | Error
Traceback (most recent call last):
File "/Users/wenjun.swj/Code/mars/mars/scheduler/graph.py", line 410, in _execute_graph
self.prepare_graph(compose=compose)
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line 377, in _wrapped
return func(*args, **kwargs)
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line... | KeyError |
def add_finished_predecessor(
self, op_key, worker, output_sizes=None, output_shapes=None
):
super().add_finished_predecessor(
op_key, worker, output_sizes=output_sizes, output_shapes=output_shapes
)
from ..chunkmeta import WorkerMeta
chunk_key = next(iter(output_sizes.keys()))[0]
self... | def add_finished_predecessor(
self, op_key, worker, output_sizes=None, output_shapes=None
):
super().add_finished_predecessor(
op_key, worker, output_sizes=output_sizes, output_shapes=output_shapes
)
from ..chunkmeta import WorkerMeta
chunk_key = next(iter(output_sizes.keys()))[0]
self... | https://github.com/mars-project/mars/issues/1740 | Error
Traceback (most recent call last):
File "/Users/wenjun.swj/Code/mars/mars/scheduler/graph.py", line 410, in _execute_graph
self.prepare_graph(compose=compose)
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line 377, in _wrapped
return func(*args, **kwargs)
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line... | KeyError |
def all(a, axis=None, out=None, keepdims=None, combine_size=None):
"""
Test whether all array elements along a given axis evaluate to True.
Parameters
----------
a : array_like
Input tensor or object that can be converted to a tensor.
axis : None or int or tuple of ints, optional
... | def all(a, axis=None, out=None, keepdims=None, combine_size=None):
"""
Test whether all array elements along a given axis evaluate to True.
Parameters
----------
a : array_like
Input tensor or object that can be converted to a tensor.
axis : None or int or tuple of ints, optional
... | https://github.com/mars-project/mars/issues/1743 | In [5]: a = mt.tensor(['a', 'b', 'c'], dtype=object)
In [6]: a.max().execute()
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-6-d9ebfaf2dc7b> in <module>
----> 1 a.max().execute()
~/Workspace/mars/m... | AttributeError |
def any(a, axis=None, out=None, keepdims=None, combine_size=None):
"""
Test whether any tensor element along a given axis evaluates to True.
Returns single boolean unless `axis` is not ``None``
Parameters
----------
a : array_like
Input tensor or object that can be converted to an arra... | def any(a, axis=None, out=None, keepdims=None, combine_size=None):
"""
Test whether any tensor element along a given axis evaluates to True.
Returns single boolean unless `axis` is not ``None``
Parameters
----------
a : array_like
Input tensor or object that can be converted to an arra... | https://github.com/mars-project/mars/issues/1743 | In [5]: a = mt.tensor(['a', 'b', 'c'], dtype=object)
In [6]: a.max().execute()
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-6-d9ebfaf2dc7b> in <module>
----> 1 a.max().execute()
~/Workspace/mars/m... | AttributeError |
def execute_agg(cls, ctx, op):
(input_chunk,), device_id, xp = as_same_device(
[ctx[c.key] for c in op.inputs], device=op.device, ret_extra=True
)
axis = cls.get_axis(op.axis)
func_name = getattr(cls, "_func_name", None)
reduce_func = getattr(xp, func_name)
out = op.outputs[0]
with d... | def execute_agg(cls, ctx, op):
(input_chunk,), device_id, xp = as_same_device(
[ctx[c.key] for c in op.inputs], device=op.device, ret_extra=True
)
axis = cls.get_axis(op.axis)
func_name = getattr(cls, "_func_name", None)
reduce_func = getattr(xp, func_name)
out = op.outputs[0]
with d... | https://github.com/mars-project/mars/issues/1743 | In [5]: a = mt.tensor(['a', 'b', 'c'], dtype=object)
In [6]: a.max().execute()
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-6-d9ebfaf2dc7b> in <module>
----> 1 a.max().execute()
~/Workspace/mars/m... | AttributeError |
def execute_map(cls, ctx, op):
arg_axis = cls.get_arg_axis(op.axis, op.inputs[0].ndim)
(in_chunk,), device_id, xp = as_same_device(
[ctx[c.key] for c in op.inputs], device=op.device, ret_extra=True
)
func_name = getattr(cls, "_func_name")
agg_func_name = getattr(cls, "_agg_func_name")
a... | def execute_map(cls, ctx, op):
arg_axis = cls.get_arg_axis(op.axis, op.inputs[0].ndim)
(in_chunk,), device_id, xp = as_same_device(
[ctx[c.key] for c in op.inputs], device=op.device, ret_extra=True
)
func_name = getattr(cls, "_func_name")
agg_func_name = getattr(cls, "_agg_func_name")
a... | https://github.com/mars-project/mars/issues/1743 | In [5]: a = mt.tensor(['a', 'b', 'c'], dtype=object)
In [6]: a.max().execute()
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-6-d9ebfaf2dc7b> in <module>
----> 1 a.max().execute()
~/Workspace/mars/m... | AttributeError |
def tile(cls, op):
from ..indexing.slice import TensorSlice
in_tensor = op.inputs[0]
out_tensor = op.outputs[0]
axis = op.axis
if not isinstance(axis, int):
raise ValueError("axis must be a integer")
axis = validate_axis(in_tensor.ndim, axis)
if axis is None:
raise NotImplem... | def tile(cls, op):
from ..indexing.slice import TensorSlice
in_tensor = op.inputs[0]
out_tensor = op.outputs[0]
axis = op.axis
if not isinstance(axis, int):
raise ValueError("axis must be a integer")
axis = validate_axis(in_tensor.ndim, axis)
if axis is None:
raise NotImplem... | https://github.com/mars-project/mars/issues/1743 | In [5]: a = mt.tensor(['a', 'b', 'c'], dtype=object)
In [6]: a.max().execute()
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-6-d9ebfaf2dc7b> in <module>
----> 1 a.max().execute()
~/Workspace/mars/m... | AttributeError |
def sum(a, axis=None, dtype=None, out=None, keepdims=None, combine_size=None):
"""
Sum of tensor elements over a given axis.
Parameters
----------
a : array_like
Elements to sum.
axis : None or int or tuple of ints, optional
Axis or axes along which a sum is performed. The defa... | def sum(a, axis=None, dtype=None, out=None, keepdims=None, combine_size=None):
"""
Sum of tensor elements over a given axis.
Parameters
----------
a : array_like
Elements to sum.
axis : None or int or tuple of ints, optional
Axis or axes along which a sum is performed. The defa... | https://github.com/mars-project/mars/issues/1743 | In [5]: a = mt.tensor(['a', 'b', 'c'], dtype=object)
In [6]: a.max().execute()
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-6-d9ebfaf2dc7b> in <module>
----> 1 a.max().execute()
~/Workspace/mars/m... | AttributeError |
def read_csv(
path,
names=None,
sep=",",
index_col=None,
compression=None,
header="infer",
dtype=None,
usecols=None,
nrows=None,
chunk_bytes="64M",
gpu=None,
head_bytes="100k",
head_lines=None,
incremental_index=False,
use_arrow_dtype=None,
storage_options... | def read_csv(
path,
names=None,
sep=",",
index_col=None,
compression=None,
header="infer",
dtype=None,
usecols=None,
nrows=None,
chunk_bytes="64M",
gpu=None,
head_bytes="100k",
head_lines=None,
incremental_index=False,
use_arrow_dtype=None,
storage_options... | https://github.com/mars-project/mars/issues/1736 | In [20]: d.flag.execute()
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-20-68cd215e82a2> in <module>
----> 1 d.flag.execute()
~/Workspace/mars/mars/core.py in execute(self, session, **kw)
641
642 ... | ValueError |
def __call__(self, series, dtype):
if dtype is None:
inferred_dtype = None
if callable(self._arg):
# arg is a function, try to inspect the signature
sig = inspect.signature(self._arg)
return_type = sig.return_annotation
if return_type is not inspect._e... | def __call__(self, series, dtype):
if dtype is None:
inferred_dtype = None
if callable(self._arg):
# arg is a function, try to inspect the signature
sig = inspect.signature(self._arg)
return_type = sig.return_annotation
if return_type is not inspect._e... | https://github.com/mars-project/mars/issues/1717 | In [4]: import mars.dataframe as md
In [5]: md.Series(['1-1', '2-2']).map(lambda x: x.split('-')[0]).execute()
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-5-90507c117e4f> in <module>
----> 1 md.Se... | ValueError |
def tile(cls, op):
inp = op.input
out = op.outputs[0]
if len(inp.chunks) == 1:
chunk_op = op.copy().reset_key()
chunk_param = out.params
chunk_param["index"] = (0,)
chunk = chunk_op.new_chunk(inp.chunks, kws=[chunk_param])
new_op = op.copy()
param = out.para... | def tile(cls, op):
inp = op.input
out = op.outputs[0]
if len(inp.chunks) == 1:
chunk_op = op.copy().reset_key()
chunk_param = out.params
chunk_param["index"] = (0,)
chunk = chunk_op.new_chunk(inp.chunks, kws=[chunk_param])
new_op = op.copy()
param = out.para... | https://github.com/mars-project/mars/issues/1717 | In [4]: import mars.dataframe as md
In [5]: md.Series(['1-1', '2-2']).map(lambda x: x.split('-')[0]).execute()
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-5-90507c117e4f> in <module>
----> 1 md.Se... | ValueError |
def execute(cls, ctx, op: "DataFrameValueCounts"):
if op.stage != OperandStage.map:
in_data = ctx[op.input.key]
if op.convert_index_to_interval:
result = in_data.value_counts(
normalize=False,
sort=op.sort,
ascending=op.ascending,
... | def execute(cls, ctx, op: "DataFrameValueCounts"):
if op.stage != OperandStage.map:
in_data = ctx[op.input.key]
if op.convert_index_to_interval:
result = in_data.value_counts(
normalize=False,
sort=op.sort,
ascending=op.ascending,
... | https://github.com/mars-project/mars/issues/1717 | In [4]: import mars.dataframe as md
In [5]: md.Series(['1-1', '2-2']).map(lambda x: x.split('-')[0]).execute()
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-5-90507c117e4f> in <module>
----> 1 md.Se... | ValueError |
def build_mock_groupby(self, **kwargs):
in_df = self.inputs[0]
if self.is_dataframe_obj:
empty_df = build_df(in_df, size=1)
obj_dtypes = in_df.dtypes[in_df.dtypes == np.dtype("O")]
empty_df[obj_dtypes.index] = "O"
else:
if in_df.dtype == np.dtype("O"):
empty_df = ... | def build_mock_groupby(self, **kwargs):
in_df = self.inputs[0]
if self.is_dataframe_obj:
empty_df = build_df(in_df, size=2)
obj_dtypes = in_df.dtypes[in_df.dtypes == np.dtype("O")]
empty_df[obj_dtypes.index] = "O"
else:
if in_df.dtype == np.dtype("O"):
empty_df = ... | https://github.com/mars-project/mars/issues/1717 | In [4]: import mars.dataframe as md
In [5]: md.Series(['1-1', '2-2']).map(lambda x: x.split('-')[0]).execute()
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-5-90507c117e4f> in <module>
----> 1 md.Se... | ValueError |
def __call__(self, df):
if self.col_names is not None:
# if col_names is a list, return a DataFrame, else return a Series
if isinstance(self._col_names, list):
dtypes = df.dtypes[self._col_names]
columns = parse_index(pd.Index(self._col_names), store_data=True)
re... | def __call__(self, df):
if self.col_names is not None:
# if col_names is a list, return a DataFrame, else return a Series
if isinstance(self._col_names, list):
dtypes = df.dtypes[self._col_names]
columns = parse_index(pd.Index(self._col_names), store_data=True)
re... | https://github.com/mars-project/mars/issues/1717 | In [4]: import mars.dataframe as md
In [5]: md.Series(['1-1', '2-2']).map(lambda x: x.split('-')[0]).execute()
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-5-90507c117e4f> in <module>
----> 1 md.Se... | ValueError |
def set_index(df, keys, drop=True, append=False, inplace=False, verify_integrity=False):
op = DataFrameSetIndex(
keys=keys,
drop=drop,
append=append,
verify_integrity=verify_integrity,
output_types=[OutputType.dataframe],
)
result = op(df)
if not inplace:
... | def set_index(df, keys, drop=True, append=False, verify_integrity=False, **kw):
op = DataFrameSetIndex(
keys=keys,
drop=drop,
append=append,
verify_integrity=verify_integrity,
output_types=[OutputType.dataframe],
**kw,
)
return op(df)
| https://github.com/mars-project/mars/issues/1717 | In [4]: import mars.dataframe as md
In [5]: md.Series(['1-1', '2-2']).map(lambda x: x.split('-')[0]).execute()
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-5-90507c117e4f> in <module>
----> 1 md.Se... | ValueError |
def parse_index(index_value, *args, store_data=False, key=None):
from .core import IndexValue
def _extract_property(index, tp, ret_data):
kw = {
"_min_val": _get_index_min(index),
"_max_val": _get_index_max(index),
"_min_val_close": True,
"_max_val_close"... | def parse_index(index_value, *args, store_data=False, key=None):
from .core import IndexValue
def _extract_property(index, tp, ret_data):
kw = {
"_min_val": _get_index_min(index),
"_max_val": _get_index_max(index),
"_min_val_close": True,
"_max_val_close"... | https://github.com/mars-project/mars/issues/1717 | In [4]: import mars.dataframe as md
In [5]: md.Series(['1-1', '2-2']).map(lambda x: x.split('-')[0]).execute()
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-5-90507c117e4f> in <module>
----> 1 md.Se... | ValueError |
def _serialize_index(index):
tp = getattr(IndexValue, type(index).__name__)
properties = _extract_property(index, tp, store_data)
properties["_name"] = index.name
return tp(**properties)
| def _serialize_index(index):
tp = getattr(IndexValue, type(index).__name__)
properties = _extract_property(index, tp, store_data)
return tp(**properties)
| https://github.com/mars-project/mars/issues/1717 | In [4]: import mars.dataframe as md
In [5]: md.Series(['1-1', '2-2']).map(lambda x: x.split('-')[0]).execute()
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-5-90507c117e4f> in <module>
----> 1 md.Se... | ValueError |
def _install():
from ..core import DATAFRAME_TYPE, SERIES_TYPE, INDEX_TYPE
from .standardize_range_index import ChunkStandardizeRangeIndex
from .string_ import _string_method_to_handlers
from .datetimes import _datetime_method_to_handlers
from .accessor import StringAccessor, DatetimeAccessor, Cache... | def _install():
from ..core import DATAFRAME_TYPE, SERIES_TYPE, INDEX_TYPE
from .standardize_range_index import ChunkStandardizeRangeIndex
from .string_ import _string_method_to_handlers
from .datetimes import _datetime_method_to_handlers
from .accessor import StringAccessor, DatetimeAccessor, Cache... | https://github.com/mars-project/mars/issues/1704 | In [4]: df.sort_values(by='col1').execute()
Out[4]: ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
~/miniconda3/lib/python3.7/site-packages/IPython/core/formatters.py in __call__(self, obj)
700 type_... | AttributeError |
def load(file):
header = read_file_header(file)
file = open_decompression_file(file, header.compress)
try:
buf = file.read()
finally:
if header.compress != CompressType.NONE:
file.close()
if header.type == SerialType.ARROW:
return deserialize(memoryview(buf))
... | def load(file):
header = read_file_header(file)
file = open_decompression_file(file, header.compress)
try:
buf = file.read()
finally:
if header.compress != CompressType.NONE:
file.close()
if header.type == SerialType.ARROW:
return pyarrow.deserialize(memoryview(... | https://github.com/mars-project/mars/issues/1704 | In [4]: df.sort_values(by='col1').execute()
Out[4]: ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
~/miniconda3/lib/python3.7/site-packages/IPython/core/formatters.py in __call__(self, obj)
700 type_... | AttributeError |
def loads(buf):
mv = memoryview(buf)
header = read_file_header(mv)
compress = header.compress
if compress == CompressType.NONE:
data = buf[HEADER_LENGTH:]
else:
data = decompressors[compress](mv[HEADER_LENGTH:])
if header.type == SerialType.ARROW:
try:
retur... | def loads(buf):
mv = memoryview(buf)
header = read_file_header(mv)
compress = header.compress
if compress == CompressType.NONE:
data = buf[HEADER_LENGTH:]
else:
data = decompressors[compress](mv[HEADER_LENGTH:])
if header.type == SerialType.ARROW:
try:
retur... | https://github.com/mars-project/mars/issues/1704 | In [4]: df.sort_values(by='col1').execute()
Out[4]: ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
~/miniconda3/lib/python3.7/site-packages/IPython/core/formatters.py in __call__(self, obj)
700 type_... | AttributeError |
def __init__(self, meta_store=None):
self.meta_store = meta_store or RemoteMetaStore.remote()
| def __init__(self):
self._store = dict()
| https://github.com/mars-project/mars/issues/1711 | 2020-11-17 16:48:29,349 WARNING worker.py:1157 -- Traceback (most recent call last):
File "/home/admin/.local/lib/python3.6/site-packages/ray/function_manager.py", line 445, in _load_actor_class_from_local
actor_class = getattr(module, class_name)
AttributeError: module 'mars.ray.core' has no attribute 'RemoteMetaStore... | AttributeError |
def __init__(self, pure_depends=None, axis=None, output_types=None, **kwargs):
super().__init__(
_pure_depends=pure_depends, _axis=axis, _output_types=output_types, **kwargs
)
| def __init__(self, prepare_inputs=None, axis=None, output_types=None, **kwargs):
super().__init__(
_prepare_inputs=prepare_inputs, _axis=axis, _output_types=output_types, **kwargs
)
| https://github.com/mars-project/mars/issues/1672 | 2020-11-02 16:51:59,275 mars.scheduler.operands.common 143 ERROR Attempt 1: Unexpected error ValueError occurred in executing operand 05f71b4ed53f21cea47398b40c0ec61d in 33.19.117.174:21137
Traceback (most recent call last):
File "/home/admin/work/turing_dev-pymars-0.6.0a3.zip/mars/promise.py", line 378, in _wrapped... | ValueError |
def standardize_range_index(chunks, axis=0):
from .base.standardize_range_index import ChunkStandardizeRangeIndex
row_chunks = dict(
(k, next(v)) for k, v in itertools.groupby(chunks, key=lambda x: x.index[axis])
)
row_chunks = [row_chunks[i] for i in range(len(row_chunks))]
out_chunks = [... | def standardize_range_index(chunks, axis=0):
from .base.standardize_range_index import ChunkStandardizeRangeIndex
row_chunks = dict(
(k, next(v)) for k, v in itertools.groupby(chunks, key=lambda x: x.index[axis])
)
row_chunks = [row_chunks[i] for i in range(len(row_chunks))]
out_chunks = [... | https://github.com/mars-project/mars/issues/1672 | 2020-11-02 16:51:59,275 mars.scheduler.operands.common 143 ERROR Attempt 1: Unexpected error ValueError occurred in executing operand 05f71b4ed53f21cea47398b40c0ec61d in 33.19.117.174:21137
Traceback (most recent call last):
File "/home/admin/work/turing_dev-pymars-0.6.0a3.zip/mars/promise.py", line 378, in _wrapped... | ValueError |
def estimate_size(cls, ctx, op):
exec_size = 0
outputs = op.outputs
pure_dep_keys = set(
inp.key for inp, is_dep in zip(op.inputs or (), op.pure_depends or ()) if is_dep
)
if all(
not c.is_sparse() and hasattr(c, "nbytes") and not np.isnan(c.nbytes)
for c in outputs
):
... | def estimate_size(cls, ctx, op):
exec_size = 0
outputs = op.outputs
if all(
not c.is_sparse() and hasattr(c, "nbytes") and not np.isnan(c.nbytes)
for c in outputs
):
for out in outputs:
ctx[out.key] = (out.nbytes, out.nbytes)
all_overhead = 0
for inp in op.in... | https://github.com/mars-project/mars/issues/1672 | 2020-11-02 16:51:59,275 mars.scheduler.operands.common 143 ERROR Attempt 1: Unexpected error ValueError occurred in executing operand 05f71b4ed53f21cea47398b40c0ec61d in 33.19.117.174:21137
Traceback (most recent call last):
File "/home/admin/work/turing_dev-pymars-0.6.0a3.zip/mars/promise.py", line 378, in _wrapped... | ValueError |
def _allocate_resource(
self, session_id, op_key, op_info, target_worker=None, reject_workers=None
):
"""
Allocate resource for single operand
:param session_id: session id
:param op_key: operand key
:param op_info: operand info dict
:param target_worker: worker to allocate, can be None
... | def _allocate_resource(
self, session_id, op_key, op_info, target_worker=None, reject_workers=None
):
"""
Allocate resource for single operand
:param session_id: session id
:param op_key: operand key
:param op_info: operand info dict
:param target_worker: worker to allocate, can be None
... | https://github.com/mars-project/mars/issues/1672 | 2020-11-02 16:51:59,275 mars.scheduler.operands.common 143 ERROR Attempt 1: Unexpected error ValueError occurred in executing operand 05f71b4ed53f21cea47398b40c0ec61d in 33.19.117.174:21137
Traceback (most recent call last):
File "/home/admin/work/turing_dev-pymars-0.6.0a3.zip/mars/promise.py", line 378, in _wrapped... | 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()
pure_dep_chunk_keys = set()
no_prepare_chunk_keys = set()
chunk_keys = set()
shuffle_keys = dict()
... | 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()
no_prepare_chunk_keys = set()
chunk_keys = set()
shuffle_keys = dict()
predecessors_to_successors = ... | https://github.com/mars-project/mars/issues/1672 | 2020-11-02 16:51:59,275 mars.scheduler.operands.common 143 ERROR Attempt 1: Unexpected error ValueError occurred in executing operand 05f71b4ed53f21cea47398b40c0ec61d in 33.19.117.174:21137
Traceback (most recent call last):
File "/home/admin/work/turing_dev-pymars-0.6.0a3.zip/mars/promise.py", line 378, in _wrapped... | ValueError |
def _get_keys_to_fetch(graph):
from ..operands import Fetch, FetchShuffle
fetch_keys = set()
exclude_fetch_keys = set()
for chunk in graph:
if isinstance(chunk.op, Fetch):
fetch_keys.add(chunk.op.to_fetch_key or chunk.key)
elif isinstance(chunk.op, FetchShuffle):
... | def _get_keys_to_fetch(graph):
from ..operands import Fetch, FetchShuffle
fetch_keys = set()
exclude_fetch_keys = set()
for chunk in graph:
if isinstance(chunk.op, Fetch):
fetch_keys.add(chunk.op.to_fetch_key or chunk.key)
elif isinstance(chunk.op, FetchShuffle):
... | https://github.com/mars-project/mars/issues/1672 | 2020-11-02 16:51:59,275 mars.scheduler.operands.common 143 ERROR Attempt 1: Unexpected error ValueError occurred in executing operand 05f71b4ed53f21cea47398b40c0ec61d in 33.19.117.174:21137
Traceback (most recent call last):
File "/home/admin/work/turing_dev-pymars-0.6.0a3.zip/mars/promise.py", line 378, in _wrapped... | ValueError |
def _calc_results(self, session_id, graph_key, graph, context_dict, chunk_targets):
_, op_name = concat_operand_keys(graph, "_")
logger.debug("Start calculating operand %s in %s.", graph_key, self.uid)
start_time = time.time()
for chunk in graph:
for inp, prepare_inp, is_dep in zip(
... | def _calc_results(self, session_id, graph_key, graph, context_dict, chunk_targets):
_, op_name = concat_operand_keys(graph, "_")
logger.debug("Start calculating operand %s in %s.", graph_key, self.uid)
start_time = time.time()
for chunk in graph:
for inp, prepare_inp in zip(chunk.inputs, chunk... | https://github.com/mars-project/mars/issues/1672 | 2020-11-02 16:51:59,275 mars.scheduler.operands.common 143 ERROR Attempt 1: Unexpected error ValueError occurred in executing operand 05f71b4ed53f21cea47398b40c0ec61d in 33.19.117.174:21137
Traceback (most recent call last):
File "/home/admin/work/turing_dev-pymars-0.6.0a3.zip/mars/promise.py", line 378, in _wrapped... | ValueError |
def __init__(
self,
graph_serialized,
state,
chunk_targets=None,
data_targets=None,
io_meta=None,
data_metas=None,
mem_request=None,
shared_input_chunks=None,
pinned_keys=None,
mem_overhead_keys=None,
est_finish_time=None,
calc_actor_uid=None,
send_addresses=None,... | def __init__(
self,
graph_serialized,
state,
chunk_targets=None,
data_targets=None,
io_meta=None,
data_metas=None,
mem_request=None,
shared_input_chunks=None,
pinned_keys=None,
mem_overhead_keys=None,
est_finish_time=None,
calc_actor_uid=None,
send_addresses=None,... | https://github.com/mars-project/mars/issues/1672 | 2020-11-02 16:51:59,275 mars.scheduler.operands.common 143 ERROR Attempt 1: Unexpected error ValueError occurred in executing operand 05f71b4ed53f21cea47398b40c0ec61d in 33.19.117.174:21137
Traceback (most recent call last):
File "/home/admin/work/turing_dev-pymars-0.6.0a3.zip/mars/promise.py", line 378, in _wrapped... | ValueError |
def _prepare_quota_request(self, session_id, graph_key):
"""
Calculate quota request for an execution graph
:param session_id: session id
:param graph_key: key of the execution graph
:return: allocation dict
"""
try:
graph_record = self._graph_records[(session_id, graph_key)]
exc... | def _prepare_quota_request(self, session_id, graph_key):
"""
Calculate quota request for an execution graph
:param session_id: session id
:param graph_key: key of the execution graph
:return: allocation dict
"""
try:
graph_record = self._graph_records[(session_id, graph_key)]
exc... | https://github.com/mars-project/mars/issues/1672 | 2020-11-02 16:51:59,275 mars.scheduler.operands.common 143 ERROR Attempt 1: Unexpected error ValueError occurred in executing operand 05f71b4ed53f21cea47398b40c0ec61d in 33.19.117.174:21137
Traceback (most recent call last):
File "/home/admin/work/turing_dev-pymars-0.6.0a3.zip/mars/promise.py", line 378, in _wrapped... | ValueError |
def execute_graph(
self,
session_id,
graph_key,
graph_ser,
io_meta,
data_metas,
calc_device=None,
send_addresses=None,
callback=None,
):
"""
Submit graph to the worker and control the execution
:param session_id: session id
:param graph_key: graph key
:param graph... | def execute_graph(
self,
session_id,
graph_key,
graph_ser,
io_meta,
data_metas,
calc_device=None,
send_addresses=None,
callback=None,
):
"""
Submit graph to the worker and control the execution
:param session_id: session id
:param graph_key: graph key
:param graph... | https://github.com/mars-project/mars/issues/1672 | 2020-11-02 16:51:59,275 mars.scheduler.operands.common 143 ERROR Attempt 1: Unexpected error ValueError occurred in executing operand 05f71b4ed53f21cea47398b40c0ec61d in 33.19.117.174:21137
Traceback (most recent call last):
File "/home/admin/work/turing_dev-pymars-0.6.0a3.zip/mars/promise.py", line 378, in _wrapped... | 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
"""
storage_client = self.storage_client
graph_record = self._graph_records[(session_id, graph_key)]
... | 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
"""
storage_client = self.storage_client
graph_record = self._graph_records[(session_id, graph_key)]
... | https://github.com/mars-project/mars/issues/1672 | 2020-11-02 16:51:59,275 mars.scheduler.operands.common 143 ERROR Attempt 1: Unexpected error ValueError occurred in executing operand 05f71b4ed53f21cea47398b40c0ec61d in 33.19.117.174:21137
Traceback (most recent call last):
File "/home/admin/work/turing_dev-pymars-0.6.0a3.zip/mars/promise.py", line 378, in _wrapped... | ValueError |
def collect_status(self):
"""
Collect worker status and write to kvstore
"""
meta_dict = dict()
try:
if not self._upload_status:
return
cpu_percent = resource.cpu_percent()
disk_io = resource.disk_io_usage()
net_io = resource.net_io_usage()
if cpu... | def collect_status(self):
"""
Collect worker status and write to kvstore
"""
meta_dict = dict()
try:
if not self._upload_status:
return
cpu_percent = resource.cpu_percent()
disk_io = resource.disk_io_usage()
net_io = resource.net_io_usage()
if cpu... | https://github.com/mars-project/mars/issues/1672 | 2020-11-02 16:51:59,275 mars.scheduler.operands.common 143 ERROR Attempt 1: Unexpected error ValueError occurred in executing operand 05f71b4ed53f21cea47398b40c0ec61d in 33.19.117.174:21137
Traceback (most recent call last):
File "/home/admin/work/turing_dev-pymars-0.6.0a3.zip/mars/promise.py", line 378, in _wrapped... | ValueError |
def put_objects_by_keys(self, session_id, data_keys, shapes=None, pin_token=None):
sizes = []
for data_key in data_keys:
buf = None
try:
buf = self._shared_store.get_buffer(session_id, data_key)
size = len(buf)
self._internal_put_object(session_id, data_key, b... | def put_objects_by_keys(self, session_id, data_keys, shapes=None, pin_token=None):
sizes = []
for data_key in data_keys:
buf = None
try:
buf = self._shared_store.get_buffer(session_id, data_key)
size = len(buf)
self._internal_put_object(session_id, data_key, b... | https://github.com/mars-project/mars/issues/1672 | 2020-11-02 16:51:59,275 mars.scheduler.operands.common 143 ERROR Attempt 1: Unexpected error ValueError occurred in executing operand 05f71b4ed53f21cea47398b40c0ec61d in 33.19.117.174:21137
Traceback (most recent call last):
File "/home/admin/work/turing_dev-pymars-0.6.0a3.zip/mars/promise.py", line 378, in _wrapped... | ValueError |
def execute(cls, ctx, op):
def _base_concat(chunk, inputs):
# auto generated concat when executing a DataFrame, Series or Index
if chunk.op.output_types[0] == OutputType.dataframe:
return _auto_concat_dataframe_chunks(chunk, inputs)
elif chunk.op.output_types[0] == OutputType.ser... | def execute(cls, ctx, op):
def _base_concat(chunk, inputs):
# auto generated concat when executing a DataFrame, Series or Index
if chunk.op.output_types[0] == OutputType.dataframe:
return _auto_concat_dataframe_chunks(chunk, inputs)
elif chunk.op.output_types[0] == OutputType.ser... | https://github.com/mars-project/mars/issues/1682 | In [1]: import mars.dataframe as md
In [2]: from datetime import datetime
In [3]: s = md.Series([datetime.now(), datetime.now(), datetime.now()], chunk_si
...: ze=2)
In [4]: s.max().execute()
---------------------------------------------------------------------------
TypeError Traceba... | TypeError |
def _auto_concat_series_chunks(chunk, inputs):
# auto generated concat when executing a Series
if len(inputs) == 1:
concat = inputs[0]
else:
xdf = pd if isinstance(inputs[0], pd.Series) or cudf is None else cudf
if chunk.op.axis is not None:
concat = xdf.concat(inputs, ax... | def _auto_concat_series_chunks(chunk, inputs):
# auto generated concat when executing a Series
if all(np.isscalar(inp) for inp in inputs):
return pd.Series(inputs)
else:
if len(inputs) == 1:
concat = inputs[0]
else:
xdf = pd if isinstance(inputs[0], pd.Series)... | https://github.com/mars-project/mars/issues/1682 | In [1]: import mars.dataframe as md
In [2]: from datetime import datetime
In [3]: s = md.Series([datetime.now(), datetime.now(), datetime.now()], chunk_si
...: ze=2)
In [4]: s.max().execute()
---------------------------------------------------------------------------
TypeError Traceba... | TypeError |
def _execute_map_with_count(cls, ctx, op, reduction_func=None):
# Execution with specified `min_count` in the map stage
xdf = cudf if op.gpu else pd
in_data = ctx[op.inputs[0].key]
if isinstance(in_data, pd.Series):
count = in_data.count()
else:
count = in_data.count(axis=op.axis, n... | def _execute_map_with_count(cls, ctx, op, reduction_func=None):
# Execution with specified `min_count` in the map stage
xdf = cudf if op.gpu else pd
in_data = ctx[op.inputs[0].key]
if isinstance(in_data, pd.Series):
count = in_data.count()
else:
count = in_data.count(axis=op.axis, n... | https://github.com/mars-project/mars/issues/1682 | In [1]: import mars.dataframe as md
In [2]: from datetime import datetime
In [3]: s = md.Series([datetime.now(), datetime.now(), datetime.now()], chunk_si
...: ze=2)
In [4]: s.max().execute()
---------------------------------------------------------------------------
TypeError Traceba... | TypeError |
def _execute_combine_with_count(cls, ctx, op, reduction_func=None):
# Execution with specified `min_count` in the combine stage
xdf = cudf if op.gpu else pd
in_data, concat_count = ctx[op.inputs[0].key]
count = concat_count.sum(axis=op.axis)
r = cls._execute_reduction(in_data, op, reduction_func=re... | def _execute_combine_with_count(cls, ctx, op, reduction_func=None):
# Execution with specified `min_count` in the combine stage
xdf = cudf if op.gpu else pd
in_data, concat_count = ctx[op.inputs[0].key]
count = concat_count.sum(axis=op.axis)
r = cls._execute_reduction(in_data, op, reduction_func=re... | https://github.com/mars-project/mars/issues/1682 | In [1]: import mars.dataframe as md
In [2]: from datetime import datetime
In [3]: s = md.Series([datetime.now(), datetime.now(), datetime.now()], chunk_si
...: ze=2)
In [4]: s.max().execute()
---------------------------------------------------------------------------
TypeError Traceba... | TypeError |
def _execute_without_count(cls, ctx, op, reduction_func=None):
# Execution for normal reduction operands.
# For dataframe, will keep dimensions for intermediate results.
xdf = cudf if op.gpu else pd
in_data = ctx[op.inputs[0].key]
r = cls._execute_reduction(
in_data, op, min_count=op.min_co... | def _execute_without_count(cls, ctx, op, reduction_func=None):
# Execution for normal reduction operands.
# For dataframe, will keep dimensions for intermediate results.
xdf = cudf if op.gpu else pd
in_data = ctx[op.inputs[0].key]
r = cls._execute_reduction(
in_data, op, min_count=op.min_co... | https://github.com/mars-project/mars/issues/1682 | In [1]: import mars.dataframe as md
In [2]: from datetime import datetime
In [3]: s = md.Series([datetime.now(), datetime.now(), datetime.now()], chunk_si
...: ze=2)
In [4]: s.max().execute()
---------------------------------------------------------------------------
TypeError Traceba... | TypeError |
def _execute_combine(cls, ctx, op):
xdf = cudf if op.gpu else pd
in_data = ctx[op.inputs[0].key]
count_sum = in_data.sum(axis=op.axis)
if isinstance(in_data, xdf.Series):
if op.output_types[0] == OutputType.series and not isinstance(
count_sum, xdf.Series
):
count... | def _execute_combine(cls, ctx, op):
xdf = cudf if op.gpu else pd
in_data = ctx[op.inputs[0].key]
count_sum = in_data.sum(axis=op.axis)
if isinstance(in_data, xdf.Series):
ctx[op.outputs[0].key] = count_sum
else:
ctx[op.outputs[0].key] = (
xdf.DataFrame(count_sum)
... | https://github.com/mars-project/mars/issues/1682 | In [1]: import mars.dataframe as md
In [2]: from datetime import datetime
In [3]: s = md.Series([datetime.now(), datetime.now(), datetime.now()], chunk_si
...: ze=2)
In [4]: s.max().execute()
---------------------------------------------------------------------------
TypeError Traceba... | TypeError |
def _execute_map(cls, ctx, op):
xdf = cudf if op.gpu else pd
in_data = ctx[op.inputs[0].key]
if isinstance(in_data, pd.Series):
count = in_data.count()
else:
count = in_data.count(axis=op.axis, numeric_only=op.numeric_only)
r = cls._execute_reduction(in_data, op, reduction_func="sum"... | def _execute_map(cls, ctx, op):
xdf = cudf if op.gpu else pd
in_data = ctx[op.inputs[0].key]
if isinstance(in_data, pd.Series):
count = in_data.count()
else:
count = in_data.count(axis=op.axis, numeric_only=op.numeric_only)
r = cls._execute_reduction(in_data, op, reduction_func="sum"... | https://github.com/mars-project/mars/issues/1682 | In [1]: import mars.dataframe as md
In [2]: from datetime import datetime
In [3]: s = md.Series([datetime.now(), datetime.now(), datetime.now()], chunk_si
...: ze=2)
In [4]: s.max().execute()
---------------------------------------------------------------------------
TypeError Traceba... | TypeError |
def _execute_combine(cls, ctx, op):
data, concat_count, var_square = ctx[op.inputs[0].key]
xdf = cudf if op.gpu else pd
count = concat_count.sum(axis=op.axis)
r = cls._execute_reduction(data, op, reduction_func="sum")
avg = cls._keep_dim(r / count, op)
avg_diff = data / concat_count - avg
... | def _execute_combine(cls, ctx, op):
data, concat_count, var_square = ctx[op.inputs[0].key]
xdf = cudf if op.gpu else pd
count = concat_count.sum(axis=op.axis)
r = cls._execute_reduction(data, op, reduction_func="sum")
avg = cls._keep_dim(r / count, op)
avg_diff = data / concat_count - avg
... | https://github.com/mars-project/mars/issues/1682 | In [1]: import mars.dataframe as md
In [2]: from datetime import datetime
In [3]: s = md.Series([datetime.now(), datetime.now(), datetime.now()], chunk_si
...: ze=2)
In [4]: s.max().execute()
---------------------------------------------------------------------------
TypeError Traceba... | TypeError |
def _tile_with_tensor(cls, op):
out = op.outputs[0]
axis = op.axis
rhs_is_tensor = isinstance(op.rhs, TENSOR_TYPE)
tensor, other = (op.rhs, op.lhs) if rhs_is_tensor else (op.lhs, op.rhs)
if tensor.shape == other.shape:
tensor = tensor.rechunk(other.nsplits)._inplace_tile()
else:
... | def _tile_with_tensor(cls, op):
rhs_is_tensor = isinstance(op.rhs, TENSOR_TYPE)
tensor, other = (op.rhs, op.lhs) if rhs_is_tensor else (op.lhs, op.rhs)
if tensor.shape == other.shape:
tensor = tensor.rechunk(other.nsplits)._inplace_tile()
else:
# shape differs only when dataframe add 1-d... | https://github.com/mars-project/mars/issues/1674 | In [9]: df = md.DataFrame({'a': [1, 2, 3], 'b': [1.1, 2.2, 3.3],
...: 'c': [datetime(2020, 1, 1), datetime.now(), datetime(2000, 3, 3, 11, 22, 23)]})
In[10]: df[(df['c'] > md.to_datetime('2020-08-01')) & (df['c'] < md.to_datetime('2020-11-01'))].head().execute()
Traceback (most r... | IndexError |
def execute(cls, ctx, op):
if len(op.inputs) == 2:
df, other = ctx[op.inputs[0].key], ctx[op.inputs[1].key]
if isinstance(op.inputs[0], SERIES_CHUNK_TYPE) and isinstance(
op.inputs[1], DATAFRAME_CHUNK_TYPE
):
df, other = other, df
func_name = getattr(cls, ... | def execute(cls, ctx, op):
if len(op.inputs) == 2:
df, other = ctx[op.inputs[0].key], ctx[op.inputs[1].key]
if isinstance(op.inputs[0], SERIES_CHUNK_TYPE) and isinstance(
op.inputs[1], DATAFRAME_CHUNK_TYPE
):
df, other = other, df
func_name = getattr(cls, ... | https://github.com/mars-project/mars/issues/1674 | In [9]: df = md.DataFrame({'a': [1, 2, 3], 'b': [1.1, 2.2, 3.3],
...: 'c': [datetime(2020, 1, 1), datetime.now(), datetime(2000, 3, 3, 11, 22, 23)]})
In[10]: df[(df['c'] > md.to_datetime('2020-08-01')) & (df['c'] < md.to_datetime('2020-11-01'))].head().execute()
Traceback (most r... | IndexError |
def _calc_properties(cls, x1, x2=None, axis="columns"):
if isinstance(x1, (DATAFRAME_TYPE, DATAFRAME_CHUNK_TYPE)) and (
x2 is None or pd.api.types.is_scalar(x2) or isinstance(x2, TENSOR_TYPE)
):
if x2 is None:
dtypes = x1.dtypes
elif pd.api.types.is_scalar(x2):
dt... | def _calc_properties(cls, x1, x2=None, axis="columns"):
if isinstance(x1, (DATAFRAME_TYPE, DATAFRAME_CHUNK_TYPE)) and (
x2 is None or pd.api.types.is_scalar(x2) or isinstance(x2, TENSOR_TYPE)
):
if x2 is None:
dtypes = x1.dtypes
elif pd.api.types.is_scalar(x2):
dt... | https://github.com/mars-project/mars/issues/1674 | In [9]: df = md.DataFrame({'a': [1, 2, 3], 'b': [1.1, 2.2, 3.3],
...: 'c': [datetime(2020, 1, 1), datetime.now(), datetime(2000, 3, 3, 11, 22, 23)]})
In[10]: df[(df['c'] > md.to_datetime('2020-08-01')) & (df['c'] < md.to_datetime('2020-11-01'))].head().execute()
Traceback (most r... | IndexError |
def execute(cls, ctx, op):
def _base_concat(chunk, inputs):
# auto generated concat when executing a DataFrame, Series or Index
if chunk.op.output_types[0] == OutputType.dataframe:
return _auto_concat_dataframe_chunks(chunk, inputs)
elif chunk.op.output_types[0] == OutputType.ser... | def execute(cls, ctx, op):
def _base_concat(chunk, inputs):
# auto generated concat when executing a DataFrame, Series or Index
if chunk.op.output_types[0] == OutputType.dataframe:
return _auto_concat_dataframe_chunks(chunk, inputs)
elif chunk.op.output_types[0] == OutputType.ser... | https://github.com/mars-project/mars/issues/1674 | In [9]: df = md.DataFrame({'a': [1, 2, 3], 'b': [1.1, 2.2, 3.3],
...: 'c': [datetime(2020, 1, 1), datetime.now(), datetime(2000, 3, 3, 11, 22, 23)]})
In[10]: df[(df['c'] > md.to_datetime('2020-08-01')) & (df['c'] < md.to_datetime('2020-11-01'))].head().execute()
Traceback (most r... | IndexError |
def _auto_concat_dataframe_chunks(chunk, inputs):
xdf = (
pd if isinstance(inputs[0], (pd.DataFrame, pd.Series)) or cudf is None else cudf
)
if chunk.op.axis is not None:
return xdf.concat(inputs, axis=op.axis)
# auto generated concat when executing a DataFrame
if len(inputs) == 1:... | def _auto_concat_dataframe_chunks(chunk, inputs):
xdf = pd if isinstance(inputs[0], (pd.DataFrame, pd.Series)) else cudf
if chunk.op.axis is not None:
return xdf.concat(inputs, axis=op.axis)
# auto generated concat when executing a DataFrame
if len(inputs) == 1:
ret = inputs[0]
els... | https://github.com/mars-project/mars/issues/1674 | In [9]: df = md.DataFrame({'a': [1, 2, 3], 'b': [1.1, 2.2, 3.3],
...: 'c': [datetime(2020, 1, 1), datetime.now(), datetime(2000, 3, 3, 11, 22, 23)]})
In[10]: df[(df['c'] > md.to_datetime('2020-08-01')) & (df['c'] < md.to_datetime('2020-11-01'))].head().execute()
Traceback (most r... | IndexError |
def _auto_concat_series_chunks(chunk, inputs):
# auto generated concat when executing a Series
if all(np.isscalar(inp) for inp in inputs):
return pd.Series(inputs)
else:
if len(inputs) == 1:
concat = inputs[0]
else:
xdf = pd if isinstance(inputs[0], pd.Series)... | def _auto_concat_series_chunks(chunk, inputs):
# auto generated concat when executing a Series
if all(np.isscalar(inp) for inp in inputs):
return pd.Series(inputs)
else:
if len(inputs) == 1:
concat = inputs[0]
else:
xdf = pd if isinstance(inputs[0], pd.Series)... | https://github.com/mars-project/mars/issues/1674 | In [9]: df = md.DataFrame({'a': [1, 2, 3], 'b': [1.1, 2.2, 3.3],
...: 'c': [datetime(2020, 1, 1), datetime.now(), datetime(2000, 3, 3, 11, 22, 23)]})
In[10]: df[(df['c'] > md.to_datetime('2020-08-01')) & (df['c'] < md.to_datetime('2020-11-01'))].head().execute()
Traceback (most r... | IndexError |
def _auto_concat_index_chunks(chunk, inputs):
if len(inputs) == 1:
xdf = pd if isinstance(inputs[0], pd.Index) or cudf is None else cudf
concat_df = xdf.DataFrame(index=inputs[0])
else:
xdf = pd if isinstance(inputs[0], pd.Index) or cudf is None else cudf
empty_dfs = [xdf.DataFra... | def _auto_concat_index_chunks(chunk, inputs):
if len(inputs) == 1:
xdf = pd if isinstance(inputs[0], pd.Index) else cudf
concat_df = xdf.DataFrame(index=inputs[0])
else:
xdf = pd if isinstance(inputs[0], pd.Index) else cudf
empty_dfs = [xdf.DataFrame(index=inp) for inp in inputs]... | https://github.com/mars-project/mars/issues/1674 | In [9]: df = md.DataFrame({'a': [1, 2, 3], 'b': [1.1, 2.2, 3.3],
...: 'c': [datetime(2020, 1, 1), datetime.now(), datetime(2000, 3, 3, 11, 22, 23)]})
In[10]: df[(df['c'] > md.to_datetime('2020-08-01')) & (df['c'] < md.to_datetime('2020-11-01'))].head().execute()
Traceback (most r... | IndexError |
def get_output_types(*objs, unknown_as=None):
output_types = []
for obj in objs:
if obj is None:
continue
elif isinstance(obj, (FuseChunk, FuseChunkData)):
obj = obj.chunk
try:
output_types.append(_get_output_type_by_cls(type(obj)))
except Typ... | def get_output_types(*objs, unknown_as=None):
output_types = []
for obj in objs:
if obj is None:
continue
for tp in OutputType.__members__.values():
try:
tileable_types = _OUTPUT_TYPE_TO_TILEABLE_TYPES[tp]
chunk_types = _OUTPUT_TYPE_TO_CHUN... | https://github.com/mars-project/mars/issues/1664 | TypeError Traceback (most recent call last)
~\AppData\Roaming\Python\Python37\site-packages\mars\serialize\pbserializer.pyx in mars.serialize.pbserializer.ProtobufSerializeProvider.serialize_field()
640 try:
--> 641 self._set_value(value, field_obj, field.type... | TypeError |
def get_fetch_op_cls(self, obj):
output_types = get_output_types(obj, unknown_as=OutputType.object)
fetch_cls, fetch_shuffle_cls = get_fetch_class(output_types[0])
if isinstance(self, ShuffleProxy):
cls = fetch_shuffle_cls
else:
cls = fetch_cls
def _inner(**kw):
return cls(o... | def get_fetch_op_cls(self, obj):
raise NotImplementedError
| https://github.com/mars-project/mars/issues/1664 | TypeError Traceback (most recent call last)
~\AppData\Roaming\Python\Python37\site-packages\mars\serialize\pbserializer.pyx in mars.serialize.pbserializer.ProtobufSerializeProvider.serialize_field()
640 try:
--> 641 self._set_value(value, field_obj, field.type... | TypeError |
def __init__(self, to_fetch_key=None, **kw):
kw.pop("output_types", None)
kw.pop("_output_types", None)
super().__init__(_to_fetch_key=to_fetch_key, **kw)
| def __init__(self, to_fetch_key=None, **kw):
super().__init__(_to_fetch_key=to_fetch_key, **kw)
| https://github.com/mars-project/mars/issues/1664 | TypeError Traceback (most recent call last)
~\AppData\Roaming\Python\Python37\site-packages\mars\serialize\pbserializer.pyx in mars.serialize.pbserializer.ProtobufSerializeProvider.serialize_field()
640 try:
--> 641 self._set_value(value, field_obj, field.type... | TypeError |
def get_fetch_op_cls(self, obj):
output_types = get_output_types(obj, unknown_as=OutputType.object)
fetch_cls, fetch_shuffle_cls = get_fetch_class(output_types[0])
if isinstance(self, ShuffleProxy):
cls = fetch_shuffle_cls
else:
cls = fetch_cls
def _inner(**kw):
return cls(o... | def get_fetch_op_cls(self, obj):
return ObjectFetch
| https://github.com/mars-project/mars/issues/1664 | TypeError Traceback (most recent call last)
~\AppData\Roaming\Python\Python37\site-packages\mars\serialize\pbserializer.pyx in mars.serialize.pbserializer.ProtobufSerializeProvider.serialize_field()
640 try:
--> 641 self._set_value(value, field_obj, field.type... | TypeError |
def __init__(self, dtype=None, to_fetch_key=None, sparse=False, **kw):
kw.pop("output_types", None)
kw.pop("_output_types", None)
super().__init__(_dtype=dtype, _to_fetch_key=to_fetch_key, _sparse=sparse, **kw)
| def __init__(self, dtype=None, to_fetch_key=None, sparse=False, **kw):
super().__init__(_dtype=dtype, _to_fetch_key=to_fetch_key, _sparse=sparse, **kw)
| https://github.com/mars-project/mars/issues/1664 | TypeError Traceback (most recent call last)
~\AppData\Roaming\Python\Python37\site-packages\mars\serialize\pbserializer.pyx in mars.serialize.pbserializer.ProtobufSerializeProvider.serialize_field()
640 try:
--> 641 self._set_value(value, field_obj, field.type... | TypeError |
def __init__(self, dtype=None, to_fetch_keys=None, to_fetch_idxes=None, **kw):
kw.pop("output_types", None)
kw.pop("_output_types", None)
super().__init__(
_dtype=dtype, _to_fetch_keys=to_fetch_keys, _to_fetch_idxes=to_fetch_idxes, **kw
)
| def __init__(self, dtype=None, to_fetch_keys=None, to_fetch_idxes=None, **kw):
super().__init__(
_dtype=dtype, _to_fetch_keys=to_fetch_keys, _to_fetch_idxes=to_fetch_idxes, **kw
)
| https://github.com/mars-project/mars/issues/1664 | TypeError Traceback (most recent call last)
~\AppData\Roaming\Python\Python37\site-packages\mars\serialize\pbserializer.pyx in mars.serialize.pbserializer.ProtobufSerializeProvider.serialize_field()
640 try:
--> 641 self._set_value(value, field_obj, field.type... | TypeError |
def _tile_dataframe(cls, op):
from ..indexing.iloc import DataFrameIlocGetItem
out_df = op.outputs[0]
inputs = op.inputs
check_chunks_unknown_shape(inputs, TilesError)
normalized_nsplits = (
{1: inputs[0].nsplits[1]} if op.axis == 0 else {0: inputs[0].nsplits[0]}
)
inputs = [item.... | def _tile_dataframe(cls, op):
from ..indexing.iloc import DataFrameIlocGetItem
out_df = op.outputs[0]
inputs = op.inputs
normalized_nsplits = (
{1: inputs[0].nsplits[1]} if op.axis == 0 else {0: inputs[0].nsplits[0]}
)
inputs = [item.rechunk(normalized_nsplits)._inplace_tile() for item... | https://github.com/mars-project/mars/issues/1654 | Traceback (most recent call last):
File "/home/admin/work/tip_dev-pymars-0.6.0a3.zip/mars/utils.py", line 365, in _wrapped
return func(*args, **kwargs)
File "/home/admin/work/tip_dev-pymars-0.6.0a3.zip/mars/scheduler/graph.py", line 382, in execute_graph
self._execute_graph(compose=compose)
File "/home/admin/work/tip_d... | ValueError |
def _tile_series(cls, op):
from ..indexing.iloc import SeriesIlocGetItem
out = op.outputs[0]
inputs = op.inputs
out_chunks = []
if op.axis == 1:
check_chunks_unknown_shape(inputs, TilesError)
inputs = [item.rechunk(op.inputs[0].nsplits)._inplace_tile() for item in inputs]
cum_... | def _tile_series(cls, op):
from ..indexing.iloc import SeriesIlocGetItem
out = op.outputs[0]
inputs = op.inputs
out_chunks = []
if op.axis == 1:
inputs = [item.rechunk(op.inputs[0].nsplits)._inplace_tile() for item in inputs]
cum_index = 0
nsplits = []
for series in inputs:
... | https://github.com/mars-project/mars/issues/1654 | Traceback (most recent call last):
File "/home/admin/work/tip_dev-pymars-0.6.0a3.zip/mars/utils.py", line 365, in _wrapped
return func(*args, **kwargs)
File "/home/admin/work/tip_dev-pymars-0.6.0a3.zip/mars/scheduler/graph.py", line 382, in execute_graph
self._execute_graph(compose=compose)
File "/home/admin/work/tip_d... | ValueError |
def watch_workers(self):
from kubernetes import client, config
cls = type(self)
if os.environ.get("KUBE_API_ADDRESS"): # pragma: no cover
k8s_config = client.Configuration()
k8s_config.host = os.environ["KUBE_API_ADDRESS"]
else:
k8s_config = config.load_incluster_config()
... | def watch_workers(self):
from kubernetes import client, config
cls = type(self)
worker_set = set()
workers_from_resource = set()
if os.environ.get("KUBE_API_ADDRESS"): # pragma: no cover
k8s_config = client.Configuration()
k8s_config.host = os.environ["KUBE_API_ADDRESS"]
else:... | https://github.com/mars-project/mars/issues/1654 | Traceback (most recent call last):
File "/home/admin/work/tip_dev-pymars-0.6.0a3.zip/mars/utils.py", line 365, in _wrapped
return func(*args, **kwargs)
File "/home/admin/work/tip_dev-pymars-0.6.0a3.zip/mars/scheduler/graph.py", line 382, in execute_graph
self._execute_graph(compose=compose)
File "/home/admin/work/tip_d... | ValueError |
def tile(cls, op):
tensor = op.tensor
pk = op.pk
out = op.outputs[0]
index_path = op.index_path
ctx = get_context()
fs = None
if index_path is not None:
fs = get_fs(index_path, op.storage_options)
# check index_path for distributed
if getattr(ctx, "running_mode", None) == Ru... | def tile(cls, op):
tensor = op.tensor
pk = op.pk
out = op.outputs[0]
index_path = op.index_path
ctx = get_context()
# check index_path for distributed
if getattr(ctx, "running_mode", None) == RunningMode.distributed:
if index_path is not None:
fs = get_fs(index_path, op.... | https://github.com/mars-project/mars/issues/1654 | Traceback (most recent call last):
File "/home/admin/work/tip_dev-pymars-0.6.0a3.zip/mars/utils.py", line 365, in _wrapped
return func(*args, **kwargs)
File "/home/admin/work/tip_dev-pymars-0.6.0a3.zip/mars/scheduler/graph.py", line 382, in execute_graph
self._execute_graph(compose=compose)
File "/home/admin/work/tip_d... | ValueError |
def _execute_map(cls, ctx, op: "ProximaBuilder"):
inp = ctx[op.tensor.key]
out = op.outputs[0]
pks = ctx[op.pk.key]
proxima_type = get_proxima_type(inp.dtype)
# holder
holder = proxima.IndexHolder(type=proxima_type, dimension=op.dimension)
for pk, record in zip(pks, inp):
pk = pk.it... | def _execute_map(cls, ctx, op: "ProximaBuilder"):
inp = ctx[op.tensor.key]
out = op.outputs[0]
pks = ctx[op.pk.key]
proxima_type = get_proxima_type(inp.dtype)
# holder
holder = proxima.IndexHolder(type=proxima_type, dimension=op.dimension)
for pk, record in zip(pks, inp):
pk = pk.it... | https://github.com/mars-project/mars/issues/1654 | Traceback (most recent call last):
File "/home/admin/work/tip_dev-pymars-0.6.0a3.zip/mars/utils.py", line 365, in _wrapped
return func(*args, **kwargs)
File "/home/admin/work/tip_dev-pymars-0.6.0a3.zip/mars/scheduler/graph.py", line 382, in execute_graph
self._execute_graph(compose=compose)
File "/home/admin/work/tip_d... | ValueError |
def build_index(
tensor,
pk,
dimension=None,
index_path=None,
need_shuffle=False,
distance_metric="SquaredEuclidean",
index_builder="SsgBuilder",
index_builder_params=None,
index_converter=None,
index_converter_params=None,
topk=None,
storage_options=None,
run=True,
... | def build_index(
tensor,
pk,
dimension=None,
index_path=None,
need_shuffle=False,
distance_metric="SquaredEuclidean",
index_builder="SsgBuilder",
index_builder_params=None,
index_converter=None,
index_converter_params=None,
topk=None,
storage_options=None,
run=True,
... | https://github.com/mars-project/mars/issues/1654 | Traceback (most recent call last):
File "/home/admin/work/tip_dev-pymars-0.6.0a3.zip/mars/utils.py", line 365, in _wrapped
return func(*args, **kwargs)
File "/home/admin/work/tip_dev-pymars-0.6.0a3.zip/mars/scheduler/graph.py", line 382, in execute_graph
self._execute_graph(compose=compose)
File "/home/admin/work/tip_d... | ValueError |
def tile(cls, op: "ProximaSearcher"):
tensor = op.tensor
index = op.index
topk = op.topk
outs = op.outputs
# make sure all inputs have known chunk sizes
check_chunks_unknown_shape(op.inputs, TilesError)
if tensor.chunk_shape[1] > 1:
tensor = tensor.rechunk({1: tensor.shape[1]})._in... | def tile(cls, op: "ProximaSearcher"):
tensor = op.tensor
index = op.index
topk = op.topk
outs = op.outputs
# make sure all inputs have known chunk sizes
check_chunks_unknown_shape(op.inputs, TilesError)
if tensor.chunk_shape[1] > 1:
tensor = tensor.rechunk({1: tensor.shape[1]})._in... | https://github.com/mars-project/mars/issues/1654 | Traceback (most recent call last):
File "/home/admin/work/tip_dev-pymars-0.6.0a3.zip/mars/utils.py", line 365, in _wrapped
return func(*args, **kwargs)
File "/home/admin/work/tip_dev-pymars-0.6.0a3.zip/mars/scheduler/graph.py", line 382, in execute_graph
self._execute_graph(compose=compose)
File "/home/admin/work/tip_d... | ValueError |
def execute_sort_values(data, op, inplace=None, by=None):
if inplace is None:
inplace = op.inplace
# ignore_index is new in Pandas version 1.0.0.
ignore_index = getattr(op, "ignore_index", False)
if isinstance(data, (pd.DataFrame, pd.Series)):
kwargs = dict(
axis=op.axis,
... | def execute_sort_values(data, op, inplace=None):
if inplace is None:
inplace = op.inplace
# ignore_index is new in Pandas version 1.0.0.
ignore_index = getattr(op, "ignore_index", False)
if isinstance(data, (pd.DataFrame, pd.Series)):
kwargs = dict(
axis=op.axis,
... | https://github.com/mars-project/mars/issues/1641 | 2020-10-19 19:46:44,463 Unexpected exception occurred in BaseCalcActor._calc_results. graph_key=cfd4b1a2cc914a2b30aa228eda1e7ea8
Traceback (most recent call last):
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line 365, in _wrapped
return func(*args, **kwargs)
File "/Users/wenjun.swj/Code/mars/mars/worker/calc.py",... | KeyError |
def execute(cls, ctx, op):
a = ctx[op.inputs[0].key]
if op.sort_type == "sort_values":
ctx[op.outputs[0].key] = res = execute_sort_values(a, op)
else:
ctx[op.outputs[0].key] = res = execute_sort_index(a, op)
by = op.by
add_distinct_col = (
bool(int(os.environ.get("PSRS_DIST... | def execute(cls, ctx, op):
a = ctx[op.inputs[0].key]
if op.sort_type == "sort_values":
ctx[op.outputs[0].key] = res = execute_sort_values(a, op)
else:
ctx[op.outputs[0].key] = res = execute_sort_index(a, op)
by = op.by
if (
getattr(ctx, "running_mode", None) == RunningMode.... | https://github.com/mars-project/mars/issues/1641 | 2020-10-19 19:46:44,463 Unexpected exception occurred in BaseCalcActor._calc_results. graph_key=cfd4b1a2cc914a2b30aa228eda1e7ea8
Traceback (most recent call last):
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line 365, in _wrapped
return func(*args, **kwargs)
File "/Users/wenjun.swj/Code/mars/mars/worker/calc.py",... | KeyError |
def _execute_dataframe_map(cls, ctx, op):
a, pivots = [ctx[c.key] for c in op.inputs]
out = op.outputs[0]
if isinstance(a, pd.DataFrame):
# use numpy.searchsorted to find split positions.
by = op.by
distinct_col = (
_PSRS_DISTINCT_COL
if a.columns.nlevels ==... | def _execute_dataframe_map(cls, ctx, op):
a, pivots = [ctx[c.key] for c in op.inputs]
out = op.outputs[0]
if isinstance(a, pd.DataFrame):
# use numpy.searchsorted to find split positions.
by = op.by
distinct_col = (
_PSRS_DISTINCT_COL
if a.columns.nlevels ==... | https://github.com/mars-project/mars/issues/1641 | 2020-10-19 19:46:44,463 Unexpected exception occurred in BaseCalcActor._calc_results. graph_key=cfd4b1a2cc914a2b30aa228eda1e7ea8
Traceback (most recent call last):
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line 365, in _wrapped
return func(*args, **kwargs)
File "/Users/wenjun.swj/Code/mars/mars/worker/calc.py",... | KeyError |
def loads(buf):
mv = memoryview(buf)
header = read_file_header(mv)
compress = header.compress
if compress == CompressType.NONE:
data = buf[HEADER_LENGTH:]
else:
data = decompressors[compress](mv[HEADER_LENGTH:])
if header.type == SerialType.ARROW:
try:
retur... | def loads(buf):
mv = memoryview(buf)
header = read_file_header(mv)
compress = header.compress
if compress == CompressType.NONE:
data = buf[HEADER_LENGTH:]
else:
data = decompressors[compress](mv[HEADER_LENGTH:])
if header.type == SerialType.ARROW:
try:
retur... | https://github.com/mars-project/mars/issues/1641 | 2020-10-19 19:46:44,463 Unexpected exception occurred in BaseCalcActor._calc_results. graph_key=cfd4b1a2cc914a2b30aa228eda1e7ea8
Traceback (most recent call last):
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line 365, in _wrapped
return func(*args, **kwargs)
File "/Users/wenjun.swj/Code/mars/mars/worker/calc.py",... | KeyError |
def _execute_map(cls, ctx, op):
(data,), device_id, xp = as_same_device(
[ctx[op.inputs[0].key]], device=op.device, ret_extra=True
)
index = ctx[op.inputs[1].key] if len(op.inputs) == 2 else None
with device(device_id):
data = xp.ascontiguousarray(data)
if index is not None:
... | def _execute_map(cls, ctx, op):
(data,), device_id, _ = as_same_device(
[ctx[op.inputs[0].key]], device=op.device, ret_extra=True
)
index = ctx[op.inputs[1].key] if len(op.inputs) == 2 else None
with device(device_id):
if index is not None:
# fetch the trained index
... | https://github.com/mars-project/mars/issues/1629 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
~/Workspace/mars/mars/serialize/pbserializer.pyx in mars.serialize.pbserializer.ProtobufSerializeProvider.serialize_field()
648 try:
--> 649 ... | TypeError |
def __call__(self, a):
shape = tuple(s if np.isnan(s) else int(s) for s in _reorder(a.shape, self._axes))
if self._axes == list(reversed(range(a.ndim))):
# order reversed
tensor_order = reverse_order(a.order)
else:
tensor_order = TensorOrder.C_ORDER
return self.new_tensor([a], sh... | def __call__(self, a):
shape = _reorder(a.shape, self._axes)
if self._axes == list(reversed(range(a.ndim))):
# order reversed
tensor_order = reverse_order(a.order)
else:
tensor_order = TensorOrder.C_ORDER
return self.new_tensor([a], shape, order=tensor_order)
| https://github.com/mars-project/mars/issues/1629 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
~/Workspace/mars/mars/serialize/pbserializer.pyx in mars.serialize.pbserializer.ProtobufSerializeProvider.serialize_field()
648 try:
--> 649 ... | TypeError |
def tile(cls, op):
tensor = op.outputs[0]
out_chunks = []
for c in op.inputs[0].chunks:
chunk_op = op.copy().reset_key()
chunk_shape = tuple(
s if np.isnan(s) else int(s) for s in _reorder(c.shape, op.axes)
)
chunk_idx = _reorder(c.index, op.axes)
out_chu... | def tile(cls, op):
tensor = op.outputs[0]
out_chunks = []
for c in op.inputs[0].chunks:
chunk_op = op.copy().reset_key()
chunk_shape = _reorder(c.shape, op.axes)
chunk_idx = _reorder(c.index, op.axes)
out_chunk = chunk_op.new_chunk(
[c], shape=chunk_shape, index=... | https://github.com/mars-project/mars/issues/1629 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
~/Workspace/mars/mars/serialize/pbserializer.pyx in mars.serialize.pbserializer.ProtobufSerializeProvider.serialize_field()
648 try:
--> 649 ... | TypeError |
def _pandas_read_csv(cls, f, op):
csv_kwargs = op.extra_params.copy()
out_df = op.outputs[0]
start, end = _find_chunk_start_end(f, op.offset, op.size)
f.seek(start)
b = FixedSizeFileObject(f, end - start)
if hasattr(out_df, "dtypes"):
dtypes = out_df.dtypes
else:
# Output wil... | def _pandas_read_csv(cls, f, op):
csv_kwargs = op.extra_params.copy()
out_df = op.outputs[0]
start, end = _find_chunk_start_end(f, op.offset, op.size)
f.seek(start)
b = FixedSizeFileObject(f, end - start)
if hasattr(out_df, "dtypes"):
dtypes = out_df.dtypes
else:
# Output wil... | https://github.com/mars-project/mars/issues/1604 | In [9]: df = pd.DataFrame({
...: 'col1': np.random.randint(0, 100, (100000,)),
...: 'col2': np.random.choice(['a', 'b', 'c'], (100000,)),
...: 'col3': np.arange(100000)
...: })
...: df.iloc[-100:, :] = pd.NA
In [10]: df.to_csv('test.csv', index=False)
In [11]: md.read_csv('test.csv').execute()
-----------... | ValueError |
def _cudf_read_csv(cls, op): # pragma: no cover
if op.usecols:
usecols = op.usecols if isinstance(op.usecols, list) else [op.usecols]
else:
usecols = op.usecols
csv_kwargs = op.extra_params
if op.offset == 0:
df = cudf.read_csv(
op.path,
byte_range=(op.of... | def _cudf_read_csv(cls, op): # pragma: no cover
if op.usecols:
usecols = op.usecols if isinstance(op.usecols, list) else [op.usecols]
else:
usecols = op.usecols
csv_kwargs = op.extra_params
if op.offset == 0:
df = cudf.read_csv(
op.path,
byte_range=(op.of... | https://github.com/mars-project/mars/issues/1604 | In [9]: df = pd.DataFrame({
...: 'col1': np.random.randint(0, 100, (100000,)),
...: 'col2': np.random.choice(['a', 'b', 'c'], (100000,)),
...: 'col3': np.arange(100000)
...: })
...: df.iloc[-100:, :] = pd.NA
In [10]: df.to_csv('test.csv', index=False)
In [11]: md.read_csv('test.csv').execute()
-----------... | ValueError |
def execute(cls, ctx, op):
xdf = cudf if op.gpu else pd
out_df = op.outputs[0]
csv_kwargs = op.extra_params.copy()
with open_file(
op.path, compression=op.compression, storage_options=op.storage_options
) as f:
if op.compression is not None:
# As we specify names and dty... | def execute(cls, ctx, op):
xdf = cudf if op.gpu else pd
out_df = op.outputs[0]
csv_kwargs = op.extra_params.copy()
with open_file(
op.path, compression=op.compression, storage_options=op.storage_options
) as f:
if op.compression is not None:
# As we specify names and dty... | https://github.com/mars-project/mars/issues/1604 | In [9]: df = pd.DataFrame({
...: 'col1': np.random.randint(0, 100, (100000,)),
...: 'col2': np.random.choice(['a', 'b', 'c'], (100000,)),
...: 'col3': np.arange(100000)
...: })
...: df.iloc[-100:, :] = pd.NA
In [10]: df.to_csv('test.csv', index=False)
In [11]: md.read_csv('test.csv').execute()
-----------... | ValueError |
def agg(groupby, func, method="auto", *args, **kwargs):
"""
Aggregate using one or more operations on grouped data.
Parameters
----------
groupby : Mars Groupby
Groupby data.
func : str or list-like
Aggregation functions.
method : {'auto', 'shuffle', 'tree'}, default 'auto'
... | def agg(groupby, func, method="auto", *args, **kwargs):
"""
Aggregate using one or more operations on grouped data.
:param groupby: Groupby data.
:param func: Aggregation functions.
:param method: 'shuffle' or 'tree', 'tree' method provide a better performance, 'shuffle' is recommended
if aggreg... | https://github.com/mars-project/mars/issues/1604 | In [9]: df = pd.DataFrame({
...: 'col1': np.random.randint(0, 100, (100000,)),
...: 'col2': np.random.choice(['a', 'b', 'c'], (100000,)),
...: 'col3': np.arange(100000)
...: })
...: df.iloc[-100:, :] = pd.NA
In [10]: df.to_csv('test.csv', index=False)
In [11]: md.read_csv('test.csv').execute()
-----------... | ValueError |
def dataframe_sort_values(
df,
by,
axis=0,
ascending=True,
inplace=False,
kind="quicksort",
na_position="last",
ignore_index=False,
parallel_kind="PSRS",
psrs_kinds=None,
):
"""
Sort by the values along either axis.
Parameters
----------
df : Mars DataFrame
... | def dataframe_sort_values(
df,
by,
axis=0,
ascending=True,
inplace=False,
kind="quicksort",
na_position="last",
ignore_index=False,
parallel_kind="PSRS",
psrs_kinds=None,
):
"""
Sort by the values along either axis.
:param df: input DataFrame.
:param by: Name or l... | https://github.com/mars-project/mars/issues/1604 | In [9]: df = pd.DataFrame({
...: 'col1': np.random.randint(0, 100, (100000,)),
...: 'col2': np.random.choice(['a', 'b', 'c'], (100000,)),
...: 'col3': np.arange(100000)
...: })
...: df.iloc[-100:, :] = pd.NA
In [10]: df.to_csv('test.csv', index=False)
In [11]: md.read_csv('test.csv').execute()
-----------... | ValueError |
def einsum(
subscripts, *operands, dtype=None, order="K", casting="safe", optimize=False
):
"""
Evaluates the Einstein summation convention on the operands.
Using the Einstein summation convention, many common multi-dimensional,
linear algebraic array operations can be represented in a simple fashi... | def einsum(
subscripts, *operands, dtype=None, order="K", casting="safe", optimize=False
):
"""
Evaluates the Einstein summation convention on the operands.
Using the Einstein summation convention, many common multi-dimensional,
linear algebraic array operations can be represented in a simple fashi... | https://github.com/mars-project/mars/issues/1604 | In [9]: df = pd.DataFrame({
...: 'col1': np.random.randint(0, 100, (100000,)),
...: 'col2': np.random.choice(['a', 'b', 'c'], (100000,)),
...: 'col3': np.arange(100000)
...: })
...: df.iloc[-100:, :] = pd.NA
In [10]: df.to_csv('test.csv', index=False)
In [11]: md.read_csv('test.csv').execute()
-----------... | ValueError |
def _wrap_train_tuple(cls, data, label, sample_weight=None, init_score=None):
data = cls._convert_tileable(data)
label = cls._convert_tileable(label)
sample_weight = cls._convert_tileable(sample_weight)
init_score = cls._convert_tileable(init_score)
return TrainTuple(data, label, sample_weight, init... | def _wrap_train_tuple(data, label, sample_weight=None, init_score=None):
return TrainTuple(data, label, sample_weight, init_score)
| https://github.com/mars-project/mars/issues/1605 | In [1]: from mars.learn.contrib import lightgbm as lgb
/Users/qinxuye/miniconda3/envs/mars3.6/lib/python3.6/site-packages/lightgbm/__init__.py:48: UserWarning: Starting from version 2.2.1, the library file in distribution wheels for macOS is built by the Apple Clang (Xcode_8.3.3) compiler.
This means that in case of in... | TypeError |
def predict(self, X, **kw):
session = kw.pop("session", None)
run_kwargs = kw.pop("run_kwargs", None)
X = self._convert_tileable(X)
return predict(self, X, session=session, run_kwargs=run_kwargs, **kw)
| def predict(self, X, **kw):
session = kw.pop("session", None)
run_kwargs = kw.pop("run_kwargs", None)
return predict(self, X, session=session, run_kwargs=run_kwargs, **kw)
| https://github.com/mars-project/mars/issues/1605 | In [1]: from mars.learn.contrib import lightgbm as lgb
/Users/qinxuye/miniconda3/envs/mars3.6/lib/python3.6/site-packages/lightgbm/__init__.py:48: UserWarning: Starting from version 2.2.1, the library file in distribution wheels for macOS is built by the Apple Clang (Xcode_8.3.3) compiler.
This means that in case of in... | TypeError |
def kill_process_tree(pid, include_parent=True):
try:
import psutil
except ImportError: # pragma: no cover
return
try:
proc = psutil.Process(pid)
except psutil.NoSuchProcess:
return
plasma_sock_dir = None
try:
children = proc.children(recursive=True)
... | def kill_process_tree(pid, include_parent=True):
try:
import psutil
except ImportError: # pragma: no cover
return
try:
proc = psutil.Process(pid)
except psutil.NoSuchProcess:
return
plasma_sock_dir = None
children = proc.children(recursive=True)
if include_p... | https://github.com/mars-project/mars/issues/1605 | In [1]: from mars.learn.contrib import lightgbm as lgb
/Users/qinxuye/miniconda3/envs/mars3.6/lib/python3.6/site-packages/lightgbm/__init__.py:48: UserWarning: Starting from version 2.2.1, the library file in distribution wheels for macOS is built by the Apple Clang (Xcode_8.3.3) compiler.
This means that in case of in... | TypeError |
def post_create(self):
from ..dispatcher import DispatchActor
from ..status import StatusActor
super().post_create()
self.register_actors_down_handler()
self._dispatch_ref = self.promise_ref(DispatchActor.default_uid())
parse_num, is_percent = parse_readable_size(options.worker.min_spill_size)... | def post_create(self):
from ..dispatcher import DispatchActor
from ..status import StatusActor
super().post_create()
self.register_actors_down_handler()
self._dispatch_ref = self.promise_ref(DispatchActor.default_uid())
parse_num, is_percent = parse_readable_size(options.worker.min_spill_size)... | https://github.com/mars-project/mars/issues/1605 | In [1]: from mars.learn.contrib import lightgbm as lgb
/Users/qinxuye/miniconda3/envs/mars3.6/lib/python3.6/site-packages/lightgbm/__init__.py:48: UserWarning: Starting from version 2.2.1, the library file in distribution wheels for macOS is built by the Apple Clang (Xcode_8.3.3) compiler.
This means that in case of in... | TypeError |
def _tile_chunks(cls, op, in_tensor, faiss_index, n_sample):
"""
If the distribution on each chunk is the same,
refer to:
https://github.com/facebookresearch/faiss/wiki/FAQ#how-can-i-distribute-index-building-on-several-machines
1. train an IndexIVF* on a representative sample of the data, store it... | def _tile_chunks(cls, op, in_tensor, faiss_index, n_sample):
"""
If the distribution on each chunk is the same,
refer to:
https://github.com/facebookresearch/faiss/wiki/FAQ#how-can-i-distribute-index-building-on-several-machines
1. train an IndexIVF* on a representative sample of the data, store it... | https://github.com/mars-project/mars/issues/1608 | In [1]: from sklearn.datasets import make_classification
In [2]: x, y = make_classification()
In [3]: import mars.tensor as mt
/Users/qinxuye/miniconda3/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from Py... | AssertionError |
def _execute_one_chunk(cls, ctx, op):
(inp,), device_id, xp = as_same_device(
[ctx[c.key] for c in op.inputs], device=op.device, ret_extra=True
)
with device(device_id):
inp = inp.astype(np.float32, copy=False)
# create index
index = faiss.index_factory(inp.shape[1], op.fais... | def _execute_one_chunk(cls, ctx, op):
(inp,), device_id, xp = as_same_device(
[ctx[c.key] for c in op.inputs], device=op.device, ret_extra=True
)
with device(device_id):
# create index
index = faiss.index_factory(inp.shape[1], op.faiss_index, op.faiss_metric_type)
# GPU
... | https://github.com/mars-project/mars/issues/1608 | In [1]: from sklearn.datasets import make_classification
In [2]: x, y = make_classification()
In [3]: import mars.tensor as mt
/Users/qinxuye/miniconda3/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from Py... | AssertionError |
def _make_indexable(iterable):
"""Ensure iterable supports indexing or convert to an indexable variant.
Convert sparse matrices to csr and other non-indexable iterable to arrays.
Let `None` and indexable objects (e.g. pandas dataframes) pass unchanged.
Parameters
----------
iterable : {list, d... | def _make_indexable(iterable):
"""Ensure iterable supports indexing or convert to an indexable variant.
Convert sparse matrices to csr and other non-indexable iterable to arrays.
Let `None` and indexable objects (e.g. pandas dataframes) pass unchanged.
Parameters
----------
iterable : {list, d... | https://github.com/mars-project/mars/issues/1603 | In [1]: import mars.dataframe as md
In [8]: X = df[['userId', 'rating']]
In [9]: y = df['movieId']
In [11]: train_test_split(X, y, train_size=0.7, random_state=0)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<i... | ValueError |
def execute(cls, ctx, op: "LGBMTrain"):
if op.merge:
return super().execute(ctx, op)
from lightgbm.basic import _safe_call, _LIB
data_val = ctx[op.data.key]
label_val = ctx[op.label.key]
sample_weight_val = (
ctx[op.sample_weight.key] if op.sample_weight is not None else None
)... | def execute(cls, ctx, op: "LGBMTrain"):
if op.merge:
return super().execute(ctx, op)
from lightgbm.basic import _safe_call, _LIB
data_val = ctx[op.data.key]
label_val = ctx[op.label.key]
sample_weight_val = (
ctx[op.sample_weight.key] if op.sample_weight is not None else None
)... | https://github.com/mars-project/mars/issues/1597 | Attempt 4: Unexpected error TypeError occurred in executing operand affdad0be8e3430b7b6088cd112ed634 in 10.xxx:8083
Traceback (most recent call last):
File "/data/platform/anaconda3/envs/mars-dev/lib/python3.7/site-packages/mars/promise.py", line 100, in _wrapped
result = func(*args, **kwargs)
File "/data/platform/anac... | TypeError |
def _calc_properties(cls, x1, x2=None, axis="columns"):
if isinstance(x1, (DATAFRAME_TYPE, DATAFRAME_CHUNK_TYPE)) and (
x2 is None or pd.api.types.is_scalar(x2) or isinstance(x2, TENSOR_TYPE)
):
if x2 is None:
dtypes = x1.dtypes
elif pd.api.types.is_scalar(x2):
dt... | def _calc_properties(cls, x1, x2=None, axis="columns"):
if isinstance(x1, (DATAFRAME_TYPE, DATAFRAME_CHUNK_TYPE)) and (
x2 is None or pd.api.types.is_scalar(x2) or isinstance(x2, TENSOR_TYPE)
):
if x2 is None:
dtypes = x1.dtypes
elif pd.api.types.is_scalar(x2):
dt... | https://github.com/mars-project/mars/issues/1590 | import numpy as np
import pandas as pd
import mars.dataframe as md
rs = np.random.RandomState(0)
raw_df = rs.rand(20, 10)
raw_df = pd.DataFrame(np.where(raw_df > 0.4, raw_df, np.nan), columns=list('ABCDEFGHIJ'))
df = md.DataFrame(raw_df, chunk_size=6)
raw_df2 = rs.rand(20, 10)
raw_df2 = pd.DataFrame(np.where(raw_df2 > ... | ValueError |
def build_df(df_obj, fill_value=1, size=1):
empty_df = build_empty_df(df_obj.dtypes, index=df_obj.index_value.to_pandas()[:0])
dtypes = empty_df.dtypes
record = [_generate_value(dtype, fill_value) for dtype in dtypes]
if len(record) != 0: # columns is empty in some cases
if isinstance(empty_df.... | def build_df(df_obj, fill_value=1, size=1):
empty_df = build_empty_df(df_obj.dtypes, index=df_obj.index_value.to_pandas()[:0])
dtypes = empty_df.dtypes
record = [_generate_value(dtype, fill_value) for dtype in dtypes]
if isinstance(empty_df.index, pd.MultiIndex):
index = tuple(
_gene... | https://github.com/mars-project/mars/issues/1590 | import numpy as np
import pandas as pd
import mars.dataframe as md
rs = np.random.RandomState(0)
raw_df = rs.rand(20, 10)
raw_df = pd.DataFrame(np.where(raw_df > 0.4, raw_df, np.nan), columns=list('ABCDEFGHIJ'))
df = md.DataFrame(raw_df, chunk_size=6)
raw_df2 = rs.rand(20, 10)
raw_df2 = pd.DataFrame(np.where(raw_df2 > ... | ValueError |
def fetch(self, *tileables, **kw):
ret_list = False
if len(tileables) == 1 and isinstance(tileables[0], (tuple, list)):
ret_list = True
tileables = tileables[0]
elif len(tileables) > 1:
ret_list = True
result = self._sess.fetch(*tileables, **kw)
ret = []
for r, t in zip... | def fetch(self, *tileables, **kw):
ret_list = False
if len(tileables) == 1 and isinstance(tileables[0], (tuple, list)):
ret_list = True
tileables = tileables[0]
elif len(tileables) > 1:
ret_list = True
result = self._sess.fetch(*tileables, **kw)
ret = []
for r, t in zip... | https://github.com/mars-project/mars/issues/1580 | ---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
~/.local/lib/python3.6/site-packages/IPython/core/formatters.py in __call__(self, obj)
700 type_pprinters=self.type_printers,
701 deferr... | ValueError |
def swapaxes(a, axis1, axis2):
"""
Interchange two axes of a tensor.
Parameters
----------
a : array_like
Input tensor.
axis1 : int
First axis.
axis2 : int
Second axis.
Returns
-------
a_swapped : Tensor
If `a` is a Tensor, then a view of `a` is
... | def swapaxes(a, axis1, axis2):
"""
Interchange two axes of a tensor.
Parameters
----------
a : array_like
Input tensor.
axis1 : int
First axis.
axis2 : int
Second axis.
Returns
-------
a_swapped : Tensor
If `a` is a Tensor, then a view of `a` is
... | https://github.com/mars-project/mars/issues/1552 | In [35]: p = np.random.rand(3,4,5)
In [36]: mt.swapaxes(p, 0, -1)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-36-016cb9916fdb> in <module>
----> 1 mt.swapaxes(p, 0, -1)
~/anaconda3/envs/pymars0.6... | AttributeError |
def yield_execution_pool(self):
actor_cls = self.get("_actor_cls")
actor_uid = self.get("_actor_uid")
op_key = self.get("_op_key")
if not actor_cls or not actor_uid: # pragma: no cover
return
from .actors import new_client
from .actors.errors import ActorAlreadyExist
from .worker.d... | def yield_execution_pool(self):
actor_cls = self.get("_actor_cls")
actor_uid = self.get("_actor_uid")
op_key = self.get("_op_key")
if not actor_cls or not actor_uid: # pragma: no cover
return
from .actors import new_client
from .worker.daemon import WorkerDaemonActor
client = new_... | https://github.com/mars-project/mars/issues/1543 | Traceback (most recent call last):
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 60, in testPartExecutor
yield
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 676, in run
self._callTestMethod(testMethod)
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 633... | AssertionError |
def _call_dataframe(self, df, dtypes=None, index=None):
dtypes, index_value = self._infer_df_func_returns(df, dtypes, index)
if index_value is None:
index_value = parse_index(None, (df.key, df.index_value.key))
for arg, desc in zip((self.output_types, dtypes), ("output_types", "dtypes")):
if... | def _call_dataframe(self, df, dtypes=None, index=None):
dtypes, index_value = self._infer_df_func_returns(df, dtypes, index)
for arg, desc in zip(
(self.output_types, dtypes, index_value), ("output_types", "dtypes", "index")
):
if arg is None:
raise TypeError(
f"C... | https://github.com/mars-project/mars/issues/1543 | Traceback (most recent call last):
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 60, in testPartExecutor
yield
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 676, in run
self._callTestMethod(testMethod)
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 633... | AssertionError |
def df_apply(
df,
func,
axis=0,
raw=False,
result_type=None,
args=(),
dtypes=None,
output_type=None,
index=None,
elementwise=None,
**kwds,
):
if isinstance(func, (list, dict)):
return df.aggregate(func)
output_types = kwds.pop("output_types", None)
object... | def df_apply(
df,
func,
axis=0,
raw=False,
result_type=None,
args=(),
dtypes=None,
output_type=None,
index=None,
elementwise=None,
**kwds,
):
if isinstance(func, (list, dict)):
return df.aggregate(func)
if isinstance(output_type, str):
output_type = g... | https://github.com/mars-project/mars/issues/1543 | Traceback (most recent call last):
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 60, in testPartExecutor
yield
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 676, in run
self._callTestMethod(testMethod)
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 633... | AssertionError |
def _infer_df_func_returns(self, in_groupby, in_df, dtypes, index):
index_value, output_type, new_dtypes = None, None, None
try:
if in_df.op.output_types[0] == OutputType.dataframe:
test_df = build_df(in_df, size=2)
else:
test_df = build_series(in_df, size=2, name=in_df.... | def _infer_df_func_returns(self, in_groupby, in_df, dtypes, index):
index_value, output_type, new_dtypes = None, None, None
try:
if in_df.op.output_types[0] == OutputType.dataframe:
test_df = build_df(in_df, size=2)
else:
test_df = build_series(in_df, size=2, name=in_df.... | https://github.com/mars-project/mars/issues/1543 | Traceback (most recent call last):
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 60, in testPartExecutor
yield
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 676, in run
self._callTestMethod(testMethod)
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 633... | AssertionError |
def __call__(self, groupby, dtypes=None, index=None):
in_df = groupby
while in_df.op.output_types[0] not in (OutputType.dataframe, OutputType.series):
in_df = in_df.inputs[0]
dtypes, index_value = self._infer_df_func_returns(groupby, in_df, dtypes, index)
if index_value is None:
index_v... | def __call__(self, groupby, dtypes=None, index=None):
in_df = groupby
while in_df.op.output_types[0] not in (OutputType.dataframe, OutputType.series):
in_df = in_df.inputs[0]
dtypes, index_value = self._infer_df_func_returns(groupby, in_df, dtypes, index)
for arg, desc in zip(
(self.out... | https://github.com/mars-project/mars/issues/1543 | Traceback (most recent call last):
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 60, in testPartExecutor
yield
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 676, in run
self._callTestMethod(testMethod)
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 633... | AssertionError |
def groupby_apply(
groupby, func, *args, dtypes=None, index=None, output_type=None, **kwargs
):
# todo this can be done with sort_index implemented
if not groupby.op.groupby_params.get("as_index", True):
raise NotImplementedError("apply when set_index == False is not supported")
output_types = ... | def groupby_apply(
groupby, func, *args, dtypes=None, index=None, output_types=None, **kwargs
):
# todo this can be done with sort_index implemented
if not groupby.op.groupby_params.get("as_index", True):
raise NotImplementedError("apply when set_index == False is not supported")
op = GroupByApp... | https://github.com/mars-project/mars/issues/1543 | Traceback (most recent call last):
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 60, in testPartExecutor
yield
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 676, in run
self._callTestMethod(testMethod)
File "/Users/wenjun/miniconda3/lib/python3.8/unittest/case.py", line 633... | AssertionError |
def to_pandas(self):
data = getattr(self, "_data", None)
sortorder = getattr(self, "_sortorder", None)
if data is None:
return pd.MultiIndex.from_arrays(
[np.array([], dtype=dtype) for dtype in self._dtypes],
sortorder=sortorder,
names=self._names,
)
r... | def to_pandas(self):
data = getattr(self, "_data", None)
if data is None:
sortorder = getattr(self, "_sortorder", None)
return pd.MultiIndex.from_arrays(
[np.array([], dtype=dtype) for dtype in self._dtypes],
sortorder=sortorder,
names=self._names,
)
... | https://github.com/mars-project/mars/issues/1542 | In [1]: from mars.session import new_session
In [2]: import mars.dataframe as md
In [3]: new_session(backend='ray').as_default()
2020-09-01 20:05:51,291 INFO resource_spec.py:231 -- Starting Ray with 5.08 GiB memory available for workers and up to 2.56 GiB for objects. You can adjust these settings with ray.init(memo... | TypeError |
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