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build/CMakeCache.txt
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# Copyright (c) 2018 by contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# coding: utf-8
from __future__ import absolute_import
import os
from .xlearn import *
VERSION_FILE = os.path.join(os.path.dirname(__file__), 'VERSION')
with open(VERSION_FILE) as f:
__version__ = f.read().strip()
try:
import numpy
from sklearn.base import BaseEstimator
from sklearn.datasets import dump_svmlight_file
SKLEARN_INSTALLED = True
except ImportError:
SKLEARN_INSTALLED = False
if SKLEARN_INSTALLED:
from ._sklearn import FMModel, \
LRModel, \
FFMModel, \
write_data_to_xlearn_format
\ No newline at end of file
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This diff is collapsed.
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# Copyright (c) 2018 by contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# coding: utf-8
import sys
import os
import ctypes
from .libpath import find_lib_path
class XLearnError(Exception):
"""Error thrown by xlearn trainer"""
pass
def _load_lib():
"""Load xlearn shared library"""
lib_path = find_lib_path()
if len(lib_path) == 0:
return None
lib = ctypes.cdll.LoadLibrary(lib_path[0])
return lib
# load the xlearn library globally
_LIB = _load_lib()
def _check_call(ret):
"""Check the return value of C API call
This function will raise exception when error occurs.
Wrap every API call with this function
Parameters
----------
ret : int
return value from API calls
"""
if ret != 0:
msg = ""
# raise XLearnError()
_LIB.XLearnGetLastError.restype = ctypes.POINTER(ctypes.c_ubyte)
ptr = _LIB.XLearnGetLastError()
idx = 0
while(ptr[idx] != 0):
msg += chr(ptr[idx])
idx += 1
raise XLearnError(msg)
# type definitions
XLearnHandle = ctypes.c_void_p
if sys.version_info[0] < 3:
def c_str(string):
"""Create ctypes char * from a Python string.
Parameters
----------
string : string type
Pyrhon string.
Returns
-------
str : c_char_p
A char pointer that can be passed to C API.
Examples
--------
>>> x = c_str("Hello, world!")
>>> print x.value
Hello, world!
"""
return ctypes.c_char_p(string)
else:
def c_str(string):
"""Create ctypes char * from a Python string.
Parameters
----------
string : string type
Pyrhon string.
Returns
-------
str : c_char_p
A char pointer that can be passed to C API.
Examples
--------
>>> x = c_str("Hello, world!")
>>> print(x.value)
Hello, world!
"""
return ctypes.c_char_p(string.encode('utf-8'))
"""pandas"""
try:
from pandas import Series, DataFrame
except ImportError:
class Series(object):
"""Dummy class for pandas.Series."""
pass
class DataFrame(object):
"""Dummy class for pandas.DataFrame."""
pass
build/python-package/build/lib/xlearn/data.py deleted 100644 → 0
View file @ 5cf9bfd4
# Copyright (c) 2018 by contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# coding: utf-8
import os, ctypes
from numpy import ndarray
from .base import DataFrame, Series
import numpy as np
from .base import _LIB, XLearnHandle
from .base import _check_call, c_str
# This class is the xLearn core data
class DMatrix(object):
def __init__(self, data, label=None, field_map=None):
"""
Initial function.
Parameters:
data: NumPy 2D or pandas DataFrame of features data.
label: one-dimensional array, it presents samples label.
field_map: one-dimensional array, it presents the features'field respectively.
This field_map like, [1, 2, 1, 3] means, the first and third features belong to field one, and the second belongs to field two, and so on.
this parameter only useful for ffm model.
Note: we only do roughly check, and do detail check in true work function.
"""
self.__handle = ctypes.c_void_p()
if (isinstance(data, ndarray) or isinstance(data, DataFrame)):
self._init_from_npy2d(data, label, field_map)
else:
raise ValueError('Input data must be numpy.ndarray or pandas.DataFrame')
# TODO(etveritas): support init DMatrix from other data type in memory,
# and unite init DMatrix from file.
# we now, only define the function for init DMatrix from NumPy 2D and pandas DataFrame.
def _init_from_npy2d(self, mat, label, field_map):
"""
This function do initialize DMatrix from numpy 2D and pandas DataFrame.
Parameters
"""
if len(mat.shape) != 2:
raise ValueError('Input numpy.ndarray must be 2 dimensional')
if isinstance(mat, DataFrame):
mat = mat.values
data = np.array(mat.reshape(mat.size), copy=False, dtype=np.float32)
data_ptr = data.ctypes.data_as(ctypes.POINTER(ctypes.c_float))
label_ptr = None
field_ptr = None
if label is not None:
if isinstance(label, DataFrame):
label = label.values
if isinstance(label, Series):
label = label.values
if isinstance(label, list):
label = np.array(label)
if isinstance(label, ndarray):
if (len(label.shape) > 2):
raise ValueError('Input numpy.ndarray of label must be 1 dimensional or 2 dimensional with one dimensional is 1')
if (len(label.shape) == 2) and (label.shape[0] != 1) and (label.shape[1] != 1):
print(len(label.shape))
raise ValueError('Input numpy.ndarray of label must be 1 dimensional or 2 dimensional with one dimensional is 1')
if (label.size != mat.shape[0]):
raise ValueError('Input label must has same elements as the data lines')
labels = np.array(label.reshape(label.size), copy=False, dtype=np.float32)
label_ptr = labels.ctypes.data_as(ctypes.POINTER(ctypes.c_float))
else:
raise ValueError('Input label must be numpy.ndarray')
if field_map is not None:
if isinstance(field_map, DataFrame):
field_map = field_map.values
if isinstance(field_map, Series):
field_map = field_map.values
if isinstance(field_map, list):
field_map = np.array(field_map)
if isinstance(field_map, ndarray):
if (len(field_map.shape) > 2):
raise ValueError('Input numpy.ndarray of label must be 1 dimensional or 2 dimensional with one dimensional is 1')
if (len(field_map.shape) == 2) and (field_map.shape[0] != 1) and (label.shape[1] != 1):
raise ValueError('Input numpy.ndarray of field_map must be 1 dimensional or 2 dimensional with the one dimensional is 1')
if (field_map.size != mat.shape[1]):
raise ValueError('Input field_map must has same elements as the data columns')
fields = np.array(field_map.reshape(field_map.size), copy=False, dtype=np.int32)
field_ptr = fields.ctypes.data_as(ctypes.POINTER(ctypes.c_uint))
else:
raise ValueError('Input of field_map must numpy.ndarray')
_check_call(_LIB.XlearnCreateDataFromMat(data_ptr,
ctypes.c_uint64(mat.shape[0]),
ctypes.c_uint64(mat.shape[1]),
label_ptr,
field_ptr,
ctypes.byref(self.__handle)))
@property
def handle(self):
return self.__handle
# release the resource of DMatrix
def __del__(self):
_check_call(_LIB.XlearnDataFree(ctypes.byref(self.__handle)))
self.__handle = None
\ No newline at end of file
build/python-package/build/lib/xlearn/libpath.py deleted 100644 → 0
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# Copyright (c) 2018 by contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# coding: utf-8
"""Find the path to xlearn dynamic library files."""
import os
import platform
import sys
class XLearnLibraryNotFound(Exception):
"""Error thrown by when xlearn is not found"""
pass
def find_lib_path():
"""Find the path to xlearn dynamic library files.
Returns
-------
lib_path: list(string)
List of all found library path to xlearn
"""
curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__)))
# make pythonpack hack: copy this directory one level upper for setup.py
dll_path = [curr_path, os.path.join(curr_path, '../../lib/'),
os.path.join(curr_path, '../../build/lib/'),
os.path.join(curr_path, './lib/'),
os.path.join(sys.prefix, 'xlearn')]
if sys.platform == 'win32':
if platform.architecture()[0] == '64bit':
dll_path.append(os.path.join(curr_path, '../../windows/x64/Release/'))
# hack for pip installation when copy all parent source directory here
dll_path.append(os.path.join(curr_path, './windows/x64/Release/'))
# for windows install
dll_path.append(os.path.join(curr_path, '../../test/c_api/Release/'))
else:
dll_path.append(os.path.join(curr_path, '../../windows/Release/'))
# hack for pip installation when copy all parent source directory here
dll_path.append(os.path.join(curr_path, './windows/Release/'))
# for windows install
dll_path.append(os.path.join(curr_path, '../../test/c_api/Release/'))
dll_path = [os.path.join(p, 'xlearn_api.dll') for p in dll_path]
elif sys.platform.startswith('linux'):
dll_path = [os.path.join(p, 'libxlearn_api.so') for p in dll_path]
elif sys.platform == 'darwin':
dll_path = [os.path.join(p, 'libxlearn_api.dylib') for p in dll_path]
lib_path = [p for p in dll_path if os.path.exists(p) and os.path.isfile(p)]
# From github issues, most of installation errors come from machines w/o compilers
if not lib_path:
raise XLearnLibraryNotFound(
'Cannot find xlearn Library in the candidate path'
)
return lib_path
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Metadata-Version: 1.2
Name: xlearn
Version: 0.4.4
Summary: xLearn Python Package
Home-page: https://github.com/aksnzhy/xlearn
Maintainer: Chao Ma
Maintainer-email: mctt90@gmail.com
License: Apache-2.0
Description: UNKNOWN
Platform: UNKNOWN
Classifier: License :: OSI Approved :: Apache Software License
build/python-package/xlearn.egg-info/SOURCES.txt deleted 100644 → 0
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setup.py
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test/test_data_conversion.py
test/test_python.py
xlearn/VERSION
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xlearn/_sklearn.py
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xlearn/xlearn.py
xlearn.egg-info/PKG-INFO
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xlearn.egg-info/dependency_links.txt
xlearn.egg-info/not-zip-safe
xlearn.egg-info/requires.txt
xlearn.egg-info/top_level.txt
\ No newline at end of file
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