linux pip install supporting & code reconstructing
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Young
Родитель
e5bd34c91f
Коммит
185b871072
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@ -1,4 +0,0 @@
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.PHONY: test
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test:
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cd ./multiverso && python -m unittest test.TestMultiversoTables.test_array
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cd ./multiverso && python -m unittest test.TestMultiversoTables.test_matrix
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@ -1,10 +1,12 @@
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# Requirements
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I presume you followed the [README](../../README.md) and have build multiverso successfully.
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# Run tests
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```
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make test
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nosetests
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```
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@ -1,5 +1,5 @@
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#!/usr/bin/env python
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# coding:utf8
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from api import init, shutdown, barrier, workers_num, worker_id, server_id,\
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ArrayTableHandler, MatrixTableHandler
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from api import init, shutdown, barrier, workers_num, worker_id, server_id
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from tables import ArrayTableHandler, MatrixTableHandler
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@ -1,7 +1,7 @@
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#!/usr/bin/env python
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# coding:utf8
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from ctypes import *
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import ctypes
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from utils import Loader
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import numpy as np
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@ -11,8 +11,8 @@ mv_lib = Loader.get_lib()
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def init(args=[]):
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n = len(args)
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args_type = c_char_p * n
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mv_lib.MV_Init(pointer(c_int(n)), args_type(*[c_char_p(arg) for arg in args]))
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args_type = ctypes.c_char_p * n
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mv_lib.MV_Init(ctypes.pointer(ctypes.c_int(n)), args_type(*[ctypes.c_char_p(arg) for arg in args]))
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def shutdown():
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@ -32,95 +32,4 @@ def worker_id():
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def server_id():
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return my_lib.MV_ServerId()
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class TableHandler(object):
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def __init__(self, size):
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raise NotImplementedError("You must implement the __init__ method.")
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def get(self, size):
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raise NotImplementedError("You must implement the get method.")
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def add(self, data):
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raise NotImplementedError("You must implement the add method.")
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# types
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C_FLOAT_P = POINTER(c_float)
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class ArrayTableHandler(TableHandler):
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def __init__(self, size):
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self._handler = c_void_p()
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self._size = size
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mv_lib.MV_NewArrayTable(size, byref(self._handler))
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def get(self):
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'''
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Data type of return value is numpy.ndarray
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'''
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data = np.zeros((self._size, ), dtype=np.dtype("float32"))
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mv_lib.MV_GetArrayTable(self._handler, data.ctypes.data_as(C_FLOAT_P), self._size)
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return data
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def add(self, data):
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'''
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Data type of `data` is numpy.ndarray
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'''
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if not isinstance(data, np.ndarray):
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data = np.array(data)
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assert(data.size == self._size)
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data = data.astype(np.float32)
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mv_lib.MV_AddArrayTable(self._handler, data.ctypes.data_as(C_FLOAT_P), self._size)
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class MatrixTableHandler(TableHandler):
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def __init__(self, num_row, num_col):
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self._handler = c_void_p()
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self._num_row = num_row
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self._num_col = num_col
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self._size = num_col * num_row
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mv_lib.MV_NewMatrixTable(num_row, num_col, byref(self._handler))
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def get(self, row_ids=None):
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'''
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If row_ids is None, we will return all rows as numpy.narray , e.g.
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array([[1, 3], [3, 4]]). Otherwise we will return the data according
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to the row_ids
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'''
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if row_ids is None:
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data = np.zeros((self._num_row, self._num_col), dtype=np.dtype("float32"))
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mv_lib.MV_GetMatrixTableAll(self._handler, data.ctypes.data_as(C_FLOAT_P), self._size)
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return data
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else:
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row_ids_n = len(row_ids)
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int_array_type = c_int * row_ids_n
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data = np.zeros((row_ids_n, self._num_col), dtype=np.dtype("float32"))
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mv_lib.MV_GetMatrixTableByRows(self._handler, data.ctypes.data_as(C_FLOAT_P),
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row_ids_n * self._num_col,
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int_array_type(*row_ids), row_ids_n)
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return data
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def add(self, data=None, row_ids=None):
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'''
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If row_ids is None, we will add all data, and the data
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should be a list, e.g. [1, 2, 3, ...]
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Otherwise we will add the data according to the row_ids
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'''
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assert(data is not None)
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if not isinstance(data, np.ndarray):
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data = np.array(data)
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data = data.astype(np.float32)
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if row_ids is None:
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assert(data.size == self._size)
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mv_lib.MV_AddMatrixTableAll(self._handler, data.ctypes.data_as(C_FLOAT_P), self._size)
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else:
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row_ids_n = len(row_ids)
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assert(data.size == row_ids_n * self._num_col)
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int_array_type = c_int * row_ids_n
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mv_lib.MV_AddMatrixTableByRows(self._handler, data.ctypes.data_as(C_FLOAT_P),
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row_ids_n * self._num_col,
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int_array_type(*row_ids), row_ids_n)
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return mv_lib.MV_ServerId()
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@ -0,0 +1,100 @@
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#!/usr/bin/env python
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# coding:utf8
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import ctypes
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from utils import Loader
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import numpy as np
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mv_lib = Loader.get_lib()
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class TableHandler(object):
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def __init__(self, size):
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raise NotImplementedError("You must implement the __init__ method.")
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def get(self, size):
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raise NotImplementedError("You must implement the get method.")
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def add(self, data):
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raise NotImplementedError("You must implement the add method.")
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# types
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C_FLOAT_P = ctypes.POINTER(ctypes.c_float)
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class ArrayTableHandler(TableHandler):
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def __init__(self, size):
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self._handler = ctypes.c_void_p()
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self._size = size
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mv_lib.MV_NewArrayTable(size, ctypes.byref(self._handler))
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def get(self):
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'''
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Data type of return value is numpy.ndarray
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'''
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data = np.zeros((self._size, ), dtype=np.dtype("float32"))
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mv_lib.MV_GetArrayTable(self._handler, data.ctypes.data_as(C_FLOAT_P), self._size)
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return data
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def add(self, data):
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'''
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Data type of `data` is numpy.ndarray
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'''
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if not isinstance(data, np.ndarray):
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data = np.array(data)
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assert(data.size == self._size)
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data = data.astype(np.float32)
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mv_lib.MV_AddArrayTable(self._handler, data.ctypes.data_as(C_FLOAT_P), self._size)
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class MatrixTableHandler(TableHandler):
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def __init__(self, num_row, num_col):
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self._handler = ctypes.c_void_p()
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self._num_row = num_row
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self._num_col = num_col
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self._size = num_col * num_row
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mv_lib.MV_NewMatrixTable(num_row, num_col, ctypes.byref(self._handler))
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def get(self, row_ids=None):
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'''
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If row_ids is None, we will return all rows as numpy.narray , e.g.
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array([[1, 3], [3, 4]]). Otherwise we will return the data according
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to the row_ids
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'''
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if row_ids is None:
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data = np.zeros((self._num_row, self._num_col), dtype=np.dtype("float32"))
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mv_lib.MV_GetMatrixTableAll(self._handler, data.ctypes.data_as(C_FLOAT_P), self._size)
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return data
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else:
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row_ids_n = len(row_ids)
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int_array_type = ctypes.c_int * row_ids_n
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data = np.zeros((row_ids_n, self._num_col), dtype=np.dtype("float32"))
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mv_lib.MV_GetMatrixTableByRows(self._handler, data.ctypes.data_as(C_FLOAT_P),
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row_ids_n * self._num_col,
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int_array_type(*row_ids), row_ids_n)
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return data
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def add(self, data=None, row_ids=None):
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'''
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If row_ids is None, we will add all data, and the data
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should be a list, e.g. [1, 2, 3, ...]
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Otherwise we will add the data according to the row_ids
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'''
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assert(data is not None)
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if not isinstance(data, np.ndarray):
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data = np.array(data)
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data = data.astype(np.float32)
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if row_ids is None:
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assert(data.size == self._size)
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mv_lib.MV_AddMatrixTableAll(self._handler, data.ctypes.data_as(C_FLOAT_P), self._size)
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else:
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row_ids_n = len(row_ids)
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assert(data.size == row_ids_n * self._num_col)
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int_array_type = ctypes.c_int * row_ids_n
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mv_lib.MV_AddMatrixTableByRows(self._handler, data.ctypes.data_as(C_FLOAT_P),
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row_ids_n * self._num_col,
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int_array_type(*row_ids), row_ids_n)
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@ -1,14 +1,21 @@
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#!/usr/bin/env python
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# coding:utf8
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import api as mv
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import multiverso as mv
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import unittest
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def setUpModule():
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mv.init()
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def tearDownModule():
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mv.shutdown()
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class TestMultiversoTables(unittest.TestCase):
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'''
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Use the commands below to run test
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python -m unittest test.TestMultiversoTables.test_array
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python -m unittest test.TestMultiversoTables.test_matrix
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$ nosetests
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'''
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def _test_array(self, size):
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@ -24,8 +31,12 @@ class TestMultiversoTables(unittest.TestCase):
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mv.barrier()
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def test_small_array(self):
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# TODO : this is not supported by multiverso because of the size limited
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self._test_array(1)
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# TODO : this is not supported by multiverso because of the size
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# limited. Waiting for the solution of this issue
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# https://github.com/Microsoft/multiverso/issues/69
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# self._test_array(1)
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pass
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def test_array(self):
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self._test_array(10000)
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expected = (row_ids[i] * num_col + j) * count * workers_num * 2
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self.assertEqual(expected, actual)
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def setUp(self):
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mv.init()
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def tearDown(self):
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mv.shutdown()
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if __name__ == '__main__':
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unittest.main()
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@ -4,8 +4,7 @@
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import ctypes
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import os
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PROJECT_PATH = os.path.abspath(os.path.join(
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os.path.dirname(__file__), os.path.pardir, os.path.pardir, os.path.pardir))
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PACKAGE_PATH = os.path.abspath(os.path.dirname(__file__))
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class Loader(object):
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@ -16,7 +15,7 @@ class Loader(object):
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def load_lib(cls):
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# TODO: write some scripts load .so or .dll
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# TODO: adapt it for windows
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path = os.path.join(PROJECT_PATH,"build", "src", "libmultiverso.so")
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path = os.path.join(PACKAGE_PATH, "libmultiverso.so")
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return ctypes.cdll.LoadLibrary(path)
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@classmethod
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@ -0,0 +1,51 @@
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from setuptools import setup
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from setuptools.command.install import install
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import shutil
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import os
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PACKAGE_PATH = os.path.abspath(os.path.dirname(__file__))
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PROJECT_PATH = os.path.abspath(os.path.join(PACKAGE_PATH, os.path.pardir, os.path.pardir))
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class mv_install(install):
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'''
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This customized command will place the multiverso.so to the right place.
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'''
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def run(self):
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# TODO: find better way to get the libmultiverso.so
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mv_so = os.path.join(PROJECT_PATH, "build", "src", "libmultiverso.so")
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if os.path.exists(mv_so):
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shutil.copy(mv_so, os.path.join(PACKAGE_PATH, "multiverso"))
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install.run(self)
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else:
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msg = "The libmultiverso.so(" + mv_so + ") can't be found, please"\
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" make sure you have followed the guide here"\
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"(https://github.com/Microsoft/multiverso/#build) and built"\
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"it successfully."
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print "\033[93m" + msg + '\033[0m'
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def readme():
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with open('README.md') as f:
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return f.read()
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setup(name='multiverso-python',
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version='0.1',
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long_description=readme(),
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description="Multiverso is a parameter server framework for distributed"
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" machine learning. This package can leverage multiple machines and GPUs"
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" to speed up the python programs.",
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url='https://github.com/Microsoft/multiverso',
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author='Microsoft',
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license='MIT',
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packages=['examples.theano', 'examples.theano.lasagne', 'multiverso',
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'multiverso.theano_ext', 'multiverso.theano_ext.lasagne_ext'],
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install_requires=["theano", "lasagne"],
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cmdclass={"install": mv_install},
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package_dir={'multiverso': 'multiverso'},
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package_data={
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'multiverso': ['libmultiverso.so'],
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},
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include_package_data=True,
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zip_safe=False)
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