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How to use iModel method in fMBT

Best Python code snippet using fMBT_python

mtransaction.py

Source:mtransaction.py

1from __future__ import absolute_import2############################################################################3#   Copyright (C) 2005 by Reithinger GmbH4#   mreithinger@web.de5#6#   This file is part of metapie.7#                                                                         8#   metapie is free software; you can redistribute it and/or modify9#   it under the terms of the GNU General Public License as published by10#   the Free Software Foundation; either version 2 of the License, or11#   (at your option) any later version.12#13#   pyplan is distributed in the hope that it will be useful,14#   but WITHOUT ANY WARRANTY; without even the implied warranty of15#   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the16#   GNU General Public License for more details.17#18#   You should have received a copy of the GNU General Public License19#   along with this program; if not, write to the20#   Free Software Foundation, Inc.,21#   59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.22############################################################################23from builtins import filter24from builtins import str25from builtins import map26from builtins import object27from . import events28import weakref29import metapie30class ConstraintError(ValueError):31    def __init__(self, **kwargs):32        ValueError.__init__(self, "Model constraints are not satisfied")33        self.message = kwargs34class _SequenceProxy(object):35    def __init__(self, proxy, sequence):36        self.proxy = proxy37        self.sequence = sequence38        for im in proxy._removed_imodels.values():39            try:40                del sequence[im]41            except KeyError:42                pass43            44    def __len__(self):45        return len(self.sequence) + len(self.proxy._new_imodels)46    def __delitem__(self, index):47        imodel = self[index]48        del self.proxy[imodel]49        try:50            del self.sequence[imodel]51        except KeyError:52            pass53    def is_dead(self):54        return self.proxy._dead55    def insert(self, imodel):56        self.proxy.insert(imodel)57    def __getitem__(self, index):58        if index >= len(self.sequence):59            return self.proxy._new_imodels[index - len(self.sequence)]60        imodel = self.sequence[index]61        self.proxy.mark(imodel)62        return imodel63class Transaction(events.Subject):64    active_transactions = { }65    class ContainerProxy(object):66        def __init__(self, src):67            self._src = src68            self._dead = False69            self._removed_imodels = {}70            self._new_imodels = []71            self._transaction = Transaction.get_transaction(src._imodel)72            try:73                keys = src._keys74            except AttributeError:75                return76            for k in list(keys.keys()):77                setattr(self, k, getattr(src, k))78        def mark(self, imodel):79            Transaction.mark_imodel(imodel, self._transaction)80        def commit(self):81            self._dead = True82            if not self._removed_imodels and not self._new_imodels: return83            for v in self._removed_imodels.values():84                self._src.delete(v, False)85            for v in self._new_imodels:86                self._src.insert(v, False)87        def rollback(self):88            self._dead = True89        def insert(self, imodel):90            self._src.check_peer(imodel)91            92            if imodel.id() in self._removed_imodels:93                del self._removed_imodels[imodel.id()]94                self._src._add_to_peer(imodel, self._src._imodel)95                self._src.fire()96            elif (imodel not in self._src \97                  and id(imodel) not in list(map(id, self._new_imodels))):98                99                self.mark(imodel)100                self._new_imodels.append(imodel)101                self._src._add_to_peer(imodel, self._src._imodel)102                self._src.fire()103        def delete(self, imodel):104            def exclude_model():105                try:106                    proxy = self._transaction.active_imodels[imodel]107                except KeyError:108                    pass109                else:110                    proxy.rollback(imodel)111                    del self._transaction.active_imodels[imodel]112            if imodel.id() in self._removed_imodels:113                raise KeyError("model does not exist in container", imodel)114            if imodel in self._src:115                exclude_model()116                self._removed_imodels[imodel.id()] = imodel117                self._src._remove_from_peer(imodel, self._src._imodel)118                self._src.fire()119            else:120                try:121                    index = list(map(id, self._new_imodels)).index(id(imodel))122                except ValueError:123                    raise KeyError("model does not exist in container", imodel)124                else:125                    exclude_model()126                    del self._new_imodels[index]127                    self._src.fire()128        def recatalog(self, obj):129            return self._src.recatalog(obj)130        def __delitem__(self, imodel):131            self.delete(imodel)132            133        def __len__(self):134            return len(self._src) \135                   - len(self._removed_imodels) \136                   + len(self._new_imodels)137        138        def __iter__(self):139            return iter(_SequenceProxy(self, self._src.sequence()))140        def subset(self, idset):141            return _SequenceProxy(self, self._src.subset(idset))142        def sequence(self):143            return _SequenceProxy(self, self._src.sequence())144        145        def __contains__(self, imodel):146            id_ = imodel.id()147            if id_ in self._removed_imodels: return False148            return imodel in self._src or imodel in self._new_imodels149        def __getitem__(self, key):150            if key in self._removed_imodels:151                raise KeyError("key does not exist", key)152            try:153                return self._src[key]154            except KeyError:155                for m in self._new_imodels:156                    if m.id() == key: return m157            raise KeyError158    class ModelProxy(object):159        def __init__(self, transaction):160            self._transaction = weakref.ref(transaction)161            self.error = None162        def remove_error(self, attrib):163            try:164                del self.error.message[attrib]165                if not self.error.message: self.error = None166            except AttributeError:167                pass168            except KeyError:169                pass170                171        def rollback(self, imodel):172            for t in imodel.__attributes_map__.values():173                if hasattr(self, t.private_name):174                    t._rollback_value(imodel, self)175                    delattr(self, t.private_name)176                    imodel.fire(t.name, t.name)177            self.error = None178        def commit(self, imodel):179            self.error = None180            181            for t in imodel.__attributes_map__.values():182                try:183                    pname = t.private_name184                except AttributeError:185                    #readonly attributes don't have a private_name186                    return187                188                if hasattr(self, pname):189                    t._commit_value(imodel, self)190                    delattr(self, pname)191            imodel.reindex()192                193    def remove_proxy(cls, imodel):194        try:195            transaction = cls.get_transaction(imodel)196        except RuntimeError:197            return198        del transaction.active_transactions[imodel]199        try:200            del transaction.active_imodels[imodel]201        except KeyError: pass202    remove_proxy = classmethod(remove_proxy)203    def make_proxy(cls, imodel):204        #proxy or transaction205        206        p_or_t = cls.active_transactions.get(imodel)207        try:208            if not p_or_t: return imodel209        except ReferenceError:210            del cls.active_transactions[imodel]211            return imodel212        213        if isinstance(p_or_t, cls.ModelProxy):214            #it is a proxy215            return p_or_t216        #it is a transaction (weakproxy)217        return p_or_t.include(imodel)218        219        220    make_proxy = classmethod(make_proxy)221    def get_proxy(cls, imodel):222        try:223            p_or_t = cls.active_transactions.get(imodel)224            p_or_t.__class__225            226            if isinstance(p_or_t, cls.ModelProxy):227                return p_or_t228        except ReferenceError:229            del cls.active_transactions[imodel]230        return imodel231        232    get_proxy = classmethod(get_proxy)233    def get_transaction(cls, imodel):234        try:235            p_or_t = cls.active_transactions.get(imodel)236            return weakref.proxy(p_or_t._transaction())237        except ReferenceError:238            raise RuntimeError("no active transaction")239        except AttributeError:240            raise RuntimeError("no active transaction")241    242    243    get_transaction = classmethod(get_transaction)244    def mark_imodel(cls, imodel, transaction):245        assert(type(transaction) is weakref.ProxyType)246        try:247            proxy = cls.active_transactions.setdefault(imodel, transaction)248            proxy.__class__ #causes a ReferenceError if it is a broken reference249        except ReferenceError:250            cls.active_transactions[imodel] = transaction251    mark_imodel = classmethod(mark_imodel)252    253    def __init__(self):254        self.active_imodels = { }255    def __del__(self):256        self.destroy()257        258    def include(self, imodel):259        proxy = self.active_transactions.get(imodel, self)260        if proxy._transaction() is not self:261            raise RuntimeError("the object '%s' belongs "\262                               "already to a transaction" % str(imodel))263        if isinstance(proxy, self.ModelProxy):264            #allready included265            return266            267        proxy = self.ModelProxy(self)268        self.active_transactions[imodel] = proxy269        self.active_imodels[imodel] = proxy270        return proxy271        272    def _transaction(self):273        return self274    275    def commit(self):276        #phase one try commit277        commit_ok = True278        for imodel, proxy in self.active_imodels.items():279            try:280                imodel.check_constraints()281            except ConstraintError as e:282                proxy.error = e283                commit_ok = False284            else:285                proxy.error = None286                287        if commit_ok:288            for imodel, proxy in self.active_imodels.items():289                proxy.commit(imodel)290            self.fire("commit", True)291            metapie._dbcommit()292        else:293            self.fire("commit", False)294        return commit_ok295    def get_errors(self):296        result = {}297        for imodel, proxy in self.active_imodels.items():298            try:299                result[imodel] = proxy.error300            except AttributeError:301                pass302        return result303        304    def rollback(self):305        for imodel, proxy in self.active_imodels.items():306            proxy.rollback(imodel)307        self.fire("rollback")308    def destroy(self):309        def is_my_item(item):310            imodel, p_or_t = item311            try:312                t = p_or_t._transaction()313                return t is self or not t314            except ReferenceError:315                return True316        my_models = list(filter(is_my_item, iter(self.active_transactions.items())))317        for k, v in my_models:318            del self.active_transactions[k]319        ...

dbtransient.py

Source:dbtransient.py

1############################################################################2#   Copyright (C) 2005 by Reithinger GmbH3#   mreithinger@web.de4#5#   This file is part of metapie.6#                                                                         7#   metapie is free software; you can redistribute it and/or modify8#   it under the terms of the GNU General Public License as published by9#   the Free Software Foundation; either version 2 of the License, or10#   (at your option) any later version.11#12#   pyplan is distributed in the hope that it will be useful,13#   but WITHOUT ANY WARRANTY; without even the implied warranty of14#   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the15#   GNU General Public License for more details.16#17#   You should have received a copy of the GNU General Public License18#   along with this program; if not, write to the19#   Free Software Foundation, Inc.,20#   59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.21############################################################################22"""23Objects that will not be persistent24"""25from __future__ import absolute_import26from builtins import str27from builtins import object28import metapie29from . import peer30import bisect31class _ResultSet(object):32    """Lazily accessed set of objects."""33    def __init__(self, uids, uidutil):34        self.uids = uids35        self.uidutil = uidutil36    def __len__(self):37        return len(self.uids)38    def __delitem__(self, imodel):39        try:40            index = self.uids.index(imodel.id())41        except ValueError:42            raise KeyError("model does not exist in container", imodel)43        else:44            del self.uids[index]45        46    def __getitem__(self, index):47        return self.uidutil[self.uids[index]]48    49class FieldIndex(object):50    def __init__(self):51        self.index = []52    def index_id(self, docid, value):53        bisect.insort_right(self.index, (value, docid))54    def unindex_id(self, docid):55        pos = 056        while pos < len(self.index):57            if self.index[pos][1] == docid:58                del self.index[pos]59            else:60                pos += 161    def apply(self, min, max=None, excludemin=False, excludemax=False):62        pos = bisect.bisect_right(self.index, (min, 0))63        if excludemin:64            while pos < len(self.index):65                value, docid = self.index[pos]66                if value != min: break67                pos += 168        def all_keys():69            while pos < len(self.index):70                value, docid = self.index[pos]71                if max:72                    if excludemax and value == max: break73                    if value > max: break74                yield docid75                pos += 176        return list(all_keys())77class Container(peer.Peer):78    def __init__(self, imodel, peer_class, name_to_me, name_to_peer, index):79        self._container = {}80        self._imodel = imodel81        self._peer_class = peer_class82        self._name_to_me = name_to_me83        self._name_to_peer = name_to_peer84        85    def check_peer(self, imodel):86        if not isinstance(imodel, self._peer_class):87            raise ValueError("'%s' is not of type '%s'"%88                             (str(imodel), self.contained_class.__name__))89    def fire(self):90        self._imodel.fire(self._name_to_peer, self._name_to_peer)91        self._imodel.fire("default", self._name_to_peer)92        93    def insert(self, imodel, fire=True):94        self.check_peer(imodel)95        if self._insert_item(imodel):96            self._add_to_peer(imodel, self._imodel)97            if fire: self.fire()98    def delete(self, imodel, fire=True):99        if self._del_item(imodel):100            self._remove_from_peer(imodel, self._imodel)101            if fire: self.fire()102        else:103            raise KeyError("model does not exist in container", imodel)104    def recatalog(self, obj):105        return False106    def sequence(self):107        keys = list(self._container.keys())108        keys.sort()109        return _ResultSet(keys, self._container)110    def __bool__(self): return len(self._container) > 0111    def __len__(self): return len(self._container)112    def __iter__(self): return iter(self._container.values())113    def __contains__(self, imodel): return imodel.id() in self._container114    def __getitem__(self, key): return self._container[key]115    def __delitem__(self, imodel): self.delete(imodel)116    def _insert_item(self, imodel):117        if imodel.id() not in self._container:118            self._container[imodel.id()] = imodel119            return True120        121        return False122    def _del_item(self, imodel):123        try:124            del self._container[imodel.id()]125        except KeyError:126            return False127        return True128class IdGenerator(object):129    instance = None130    def get_id(cls, type="default"):131        if not cls.instance: cls.instance = cls()132        counter = getattr(cls.instance, type, 0)133        setattr(cls.instance, type, counter + 1)134        return counter135    get_id = classmethod(get_id)136    137class _PersistentBase(object):138    __id_type__ = None139    140    def __init__(self):141        #generate a unique long lasting id142        self.__id = IdGenerator.get_id(self.__id_type__ \143                                       or self.__class__.__name__)144        #self.__id = int(time.time()) % 100000 + (id(self) % 10000) * 100000145    146    def id(self): return self.__id147    148def _commitdumy(): pass149metapie._init_db_module("transient", _PersistentBase, Container, _commitdumy)...

train.py

Source:train.py

1import tensorflow as tf2import keras3from keras.models import Sequential4from keras.layers import Dense, MaxPool2D, AveragePooling2D5from keras.layers import Conv2D, Activation, Dropout, Flatten6from keras.preprocessing.image import ImageDataGenerator7import numpy as np8import matplotlib.pyplot as plt9# cpu configuration10config = tf.ConfigProto( device_count = {'GPU': 1 , 'CPU': 56} ) #max: 1 gpu, 56 cpu11sess = tf.Session(config=config)12keras.backend.set_session(sess)13#14num_classes = 7 # sad, happy, surprise, angry, fear, nutral, disgust15batch_size = 25616epoch = 4417with open("fer2013.csv") as f:18    content = f.readlines()19lines = np.array(content)20num_instance =lines.size21# train test22x_train, y_train, x_test, y_test = [], [], [], []23for i in range(1,num_instance):24    try:25        emotion, img, usage = lines[i].split(",")26        val = img.split(" ")27        pixels = np.array(val, 'float32')28        emotion = keras.utils.to_categorical(emotion, num_classes)29        if 'Training' in usage:30            y_train.append(emotion)31            x_train.append(pixels)32        elif 'PublicTest' in usage:33            y_test.append(emotion)34            x_test.append(pixels)35    except:36        print("", end="")37# data transformation for train and test sets38x_train = np.array(x_train, 'float32')39y_train = np.array(y_train, 'float32')40x_test = np.array(x_test, 'float32')41y_test = np.array(y_test, 'float32')42x_train /= 255 #normalize inputs between [0, 1]43x_test /= 25544x_train = x_train.reshape(x_train.shape[0], 48, 48, 1)45x_train = x_train.astype('float32')46x_test = x_test.reshape(x_test.shape[0], 48, 48, 1)47x_test = x_test.astype('float32')48print(x_train.shape[0], 'train samples')49print(x_test.shape[0], 'test samples')50# creating the sequential model51imodel_fe = Sequential()52#1st convolution layer53imodel_fe.add(Conv2D(64, (5, 5), activation='relu', input_shape=(48,48,1)))54imodel_fe.add(MaxPool2D(pool_size=(5, 5), strides=(2, 2)))55#2nd c layer56imodel_fe.add(Conv2D(64, (3, 3), activation='relu'))#12857imodel_fe.add(Conv2D(64, (3,3), activation='relu'))58imodel_fe.add(AveragePooling2D(pool_size=(3, 3),strides=(2, 2)))59#3rd c layer60imodel_fe.add(Conv2D(64, (3, 3), activation='relu'))#12861imodel_fe.add(Conv2D(64, (3,3), activation='relu'))62imodel_fe.add(AveragePooling2D(pool_size=(3, 3),strides=(2, 2)))63imodel_fe.add(Flatten())64# fully connected neural network65imodel_fe.add(Dense(1024, activation='relu'))66imodel_fe.add(Dropout(0.2))67imodel_fe.add(Dense(1024, activation='relu'))68imodel_fe.add(Dropout(0.2))69imodel_fe.add(Dense(num_classes, activation='softmax'))70#--------------------------------------71#batch process72gen = ImageDataGenerator()# this is used to normalise images in format keras can understand73train_generator = gen.flow(x_train, y_train, batch_size=batch_size)74imodel_fe.compile(loss='categorical_crossentropy'75    , optimizer=keras.optimizers.Adam()76    , metrics=['accuracy']77)78#---------------------------------------------79fit = True80if fit == True:81	#model.fit_generator(x_train, y_train, epochs=epochs) #train for all trainset82	imodel_fe.fit_generator(train_generator, steps_per_epoch=batch_size, epochs=epoch) #train for randomly selected one83else:84	imodel_fe.load_weights('model33.h5') #load weights85# ------------------------------86# function for drawing bar chart for emotion preditions87def emotion_analysis(emotions):88    objects = ('angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral')89    y_pos = np.arange(len(objects))90    plt.bar(y_pos, emotions, align='center', alpha=0.5)91    plt.xticks(y_pos, objects)92    plt.ylabel('percentage')93    plt.title('emotion')94    plt.show()95# ------------------------------96imodel_fe.save('model2.h5')97#--------------------------------98monitor_testset_results = True99if monitor_testset_results == True:100    # make predictions for test set101    predictions = imodel_fe.predict(x_test)102    index = 0103    for i in predictions:104        if index < 30 and index >= 20:105            # print(i) #predicted scores106            # print(y_test[index]) #actual scores107            testing_img = np.array(x_test[index], 'float32')108            testing_img = testing_img.reshape([48, 48]);109            plt.gray()110            plt.imshow(testing_img)111            plt.show()112            print(i)113            emotion_analysis(i)114            print("----------------------------------------------")115        index = index + 1116#------------------------------------------------------------------------------117from keras.models import load_model...

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