def getAll(self):
import plugins
''' gets all of the plugins '''
rPath = plugins.__dict__['__path__'][0]
## it should turn out something like
## shovel.sys.http.download => [plugins]/sys/http.py[function:download]
for loadable in locate('*.py', rPath):
pyElement = loadable.split('/')[-1:]
## i only want the end element
if pyElement[0] != '__init__.py':
cwd = os.getcwd()
diff = pathDifference(cwd.split('/'), loadable.split('/'))
diffList = ['shovel']
## so our list is only ['shovel'] currently
for k in diff[1:-1]:
diffList.append(k)
## now append all of the elements in the path
## list should be something like ['shovel','path','path']
diffList.append(diff[-1:][0].split('.')[0])
## now append the last bit, stripped of the .py
## should be somethg like ['shovel','path','path','file']
useString = '.'.join(diffList)
## concat it so
## 'shovel.path.path.file'
debug(useString, DEBUG)
## print useString
self.config.putFeature(useString)
def mkdirIfAbsent(*args):
''' Create a directory if its not there '''
for dirName in args:
debug("ensuring that dir exists: %s" % dirName,DEBUG)
if not os.path.exists(dirName):
debug("creating dir: %s" % dirName,DEBUG)
os.makedirs(dirName)
def test_convolution2d_plotting(self):
image_path = self.get_image( 'Vd-Orig.png')
image = plt.imread(image_path)
shape = image.shape
print("shape {}".format(shape))
img_node = node.VarNode('x')
x_image = self.rgb2gray(image * 20)
print(x_image.shape)
plt.imshow(x_image)
plt.show()
debug("Now showing ..")
var_map = {'x': x_image}
x_shape = (image.shape[0], image.shape[1])
conv_node = conv.Convolution2D(img_node, x_shape)
img_node.forward(var_map)
final_image = conv_node.value()
plt.imshow(final_image)
plt.show()
edge_kernel = np.array([[-1, -1, -1], [-1, 8, -1], [-1, -1, -1]])
img_node = node.VarNode('x')
conv_node = conv.Convolution2D(img_node, x_shape, kernel=edge_kernel)
img_node.forward(var_map)
edge_img = conv_node.value()
plt.imshow(edge_img)
plt.show()
def stun(line, time, backrefs):
if core.is_paused():
return
if player.stunned is False:
player.stun_ticks = 0
core.enable_trigger('cures_stun', 'cures')
core.enable_trigger('cures_unconciousness', 'cures')
core.enable_trigger('ai_stun_check', 'anti-illusion')
player.stunned = True
player.stun_ticks += 1
player.stun_time = time
if player.stun_ticks < 3:
if core.aeon_mode == False:
core.write('touch stun')
core.debug("stunned")
# should probably add more balance resets here
if player.focus_balance == .5:
player.focus_balance = 1
if player.herb_balance == .5:
player.herb_balance = 1
if player.salve_balance == .5:
player.salve_balance = 1
if player.hmsip_balance == .5:
player.hmsip_balance = 1
player.waiting_for_aeon = 0
def test_cross_entropy(self):
predicted = np.array([[1, 3, -1, 0], [0, 9, 1, 3.]]).T
target = np.array([[0, 1, 0, 0], [0, 0, 0, 1]]).T
predicted_node = node.VarNode('predicted')
target_node = node.VarNode('target')
softmax = Softmax(predicted_node)
cross_entropy = CrossEntropy(softmax, target_node)
var_map = {'predicted': predicted, 'target': target}
predicted_node.forward(var_map)
target_node.forward(var_map)
loss = cross_entropy.value()
debug("loss = {}".format(loss))
expected_loss = 6.188115770824936
self.assertAlmostEqual(expected_loss, loss)
cross_entropy.backward(1.0, self, var_map)
x_grad = predicted_node.total_incoming_gradient()
debug("x_grad = np.{}".format(repr(x_grad)))
# Note that this grad is 1/8 the size reported by pytorch
# because pytorch does not average out during softmax for CrossEntropy
# whereas I use softmax node
expected_grad = np.array([[1.40571517e-02, 1.53810418e-05],
[-2.11309174e-02, 1.24633872e-01],
[1.90242861e-03, 4.18100064e-05],
[5.17133712e-03, -1.24691064e-01]])
np.testing.assert_array_almost_equal(expected_grad, x_grad)
def unstun(line, time, backrefs):
player.stunned = False
player.stun_ticks = 0
core.disable_trigger('cures_stun', 'cures')
core.disable_trigger('cures_unconciousness', 'cures')
core.disable_trigger('ai_stun_check', 'anti-illusion')
core.debug("unstunned")
def clean_queues(type, defence):
if type == 'action':
_truncate_queue(defence, action_queue)
elif type == 'immediate':
_truncate_queue(defence, immediate_queue)
elif type == 'free':
_truncate_queue(defence, free_queue)
elif type == 'herb':
if defence != 'deaf':
_truncate_queue(defence, herb_queue)
elif type == 'salve':
_truncate_queue(defence, salve_queue)
elif type == 'asip':
_truncate_queue(defence, asip_queue)
elif type == 'balance':
_truncate_queue(defence, balance_queue)
elif type == 'equilibrium':
_truncate_queue(defence, equilibrium_queue)
elif type == 'hmsip':
_truncate_queue(defence, hmsip_queue)
elif type == 'smoke':
_truncate_queue(defence, smoke_queue)
if defence == 'rebounding':
player.rebounding_pending = False
core.disable_trigger('failure_rebounding', 'failures')
core.debug("ondef " + defence)
def herb_balance(line, time, backrefs):
if time - player.herb_lastate <= 1.3 and player.ate_offbal == False:
core.debug("Herb balance restored too soon! Illusion?")
return
player.herb_balance = 1
player.ate_offbal = False
core.disable_trigger('herb_balance', 'balances')
def backward(self, downstream_grad, downstream_node, var_map):
r"""
This implements some of the common processing needed for backprop to work properly.
:param downstream_grad: gradient coming from downstream. This should be the
gradient flowing upstream from this node. you can also get to it through the
downstream_node.total_incoming_gradient() method but this API is still quite fluid
so not sure what is the best approach
:param downstream_node: downstream node that invoked backward
:param var_map:
:return:
"""
calling_node_name = downstream_node.simple_name()
if type(downstream_grad).__module__ == np.__name__:
grad_shape = downstream_grad.shape
else:
grad_shape = "(float)"
if is_debug_on():
_value = self.value()
debug("Backprop@{} from:{} downstream grad shape:{}".format(self.simple_name(),
calling_node_name,
grad_shape
))
debug("Downstream grad received:")
debug(repr(downstream_grad))
debug("Value:")
debug(repr(_value))
should_continue = self._process_backprop(downstream_grad)
if not should_continue:
return
self._collect_grads()
self._do_backprop(downstream_grad, downstream_node, var_map)
def test_softmax(self):
r"""
See TestActivations.Softmax.ipynb for corresponding pytorch calculations
:return:
"""
x = np.array([[1, 3, -1, 0], [0, 9, 1, 3]]).T
x_node = node.VarNode('x')
softmax = Softmax(x_node)
target = np.zeros(x.shape)
target_node = node.VarNode('target')
var_map = {'x': x, 'target': target}
l2loss = L2DistanceSquaredNorm(softmax, target_node)
x_node.forward(var_map)
target_node.forward(var_map)
expected_value = np.array([[1.12457214e-01, 1.23048334e-04],
[8.30952661e-01, 9.97070980e-01],
[1.52194289e-02, 3.34480051e-04],
[4.13706969e-02, 2.47149186e-03]])
value = softmax.value()
np.testing.assert_almost_equal(expected_value, value)
loss_value = l2loss.value()
debug("Loss = {}".format(loss_value))
l2loss.backward(1.0, self, var_map)
x_grad = x_node.total_incoming_gradient()
expected_grad = np.array([[-0.01666096, -0.00003058],
[0.02615019, 0.00072642],
[-0.00262479, -0.0000831],
[-0.00686445, -0.00061274]])
debug("x_grad = np.{}".format(repr(x_grad)))
np.testing.assert_almost_equal(expected_grad, x_grad)
def pkgconfig(self,Name):
p = subprocess.Popen("/usr/bin/env pkg-config",shell=True,stdout=subprocess.PIPE,stderr=subprocess.PIPE)
while p.stdout.readline():
if p.stdout.readline() != "Must specify package names on the command line":
debug("pkg-config not found!", ERROR)
else:
debug("pkg-config found!", INFO)
def database_setvalue(key,keyto,name):
#no try
debug("数据库更新： "+"UPDATE userdata SET "+ key +" = "+str(keyto)+" where NAME = '"+ name+"'")
conn = sqlite3.connect(dbname)
retstr = conn.execute("UPDATE userdata SET "+ key +" = "+str(keyto)+" where NAME = '"+ name+"'")
conn.commit()
conn.close()
def test_rnn_var_node(self):
x = np.array([[1, 2, 1], [-1, 0, -.5]]).T
x = x.reshape((3, 1, 2))
x0_var = rnn.RnnVarNode(0, x)
x1_var = rnn.RnnVarNode(1, x)
np.testing.assert_equal(x0_var.value(), x[:, :, 0])
np.testing.assert_equal(x1_var.value(), x[:, :, 1])
debug("[SimpleRnnCellTests.test_rnn_var_node()] x0_var.value() = np.{}".format(repr(x0_var.value())))
def herbs_container_single(line, time, backrefs):
herb = backrefs[1]
if herb in herbs.rift_name_conversion.keys():
herb = herbs.rift_name_conversion[herb]
herbs.herbs[herb].inv -= 1
if herbs.herbs[herb].inv < 0:
core.debug("inventory fault: got negative inventory count")
herbs.herbs[herb].inv = 0
def runBlock(self, block):
""" run the block of code """
debug(self._os[0], DEBUG)
for gen in self.gen.featureBlock(self.dirtY):
if gen["os"] == self._os[0]:
if gen["block"] == block and gen["fb"][0] == "use":
feature = self.config.getFeature(gen["fb"][1])
self.featureDebug(feature, gen["fb"][1])
def GetTables():
dbtables = []
s = database_query("select name from sqlite_master where type = 'table' order by name;")
for table in s:
if table[0].find('malf')<0:
dbtables.append(table[0])
debug("GetTables Return---->"+str(dbtables),3)
return dbtables
def setUp(self):
x = np.array([[1, 2, -1, 4], [2, -1, 3, 1], [4, 9, -4, 5]])
debug("x = np.{}".format(repr(x)))
self.x_node = node.VarNode('x')
self.var_map = {'x': x}
self.max_pool_node = conv.MaxPool2D(self.x_node,
pool_size=(2, 2),
name="maxpool")
debug("x = np.{}".format(repr(x)))
def GetMessageLine(strrawmsg):
p = re.compile('text="(.*?)"')
s = " ".join(p.findall(strrawmsg))
try:
mhint = s.find("：")
s = s[mhint+2:]
except:
pass
debug("GetMessageLine---->"+s,3)
return s
def pipe_fill_skullcap(line, time, backrefs):
player.waiting_for_aeon = 0
player.skullcap_puffs = 10
herbs.skullcap.inv -= 1
player.pipe_reloading = ''
free_queue.remove_by_name('reload_skullcap')
core.disable_trigger('skullcap', 'pipes')
core.disable_trigger('pipe_full', 'pipes')
core.disable_trigger('pipes_paralysis_nofill', 'pipes')
core.debug("filled skullcap pipe")
def herbs_inb(line, time, backrefs):
num = int(backrefs[0])
herb = backrefs[1]
if herb in herbs.rift_name_conversion.keys():
herb = herbs.rift_name_conversion[herb]
herbs.herbs[herb].inv -= num
if herbs.herbs[herb].inv < 0:
core.debug("inventory fault: got negative inventory count")
herbs.herbs[herb].inv = 0
def pipe_fill_elm(line, time, backrefs):
player.waiting_for_aeon = 0
player.elm_puffs = 10
herbs.elm.inv -= 1
player.pipe_reloading = ''
free_queue.remove_by_name('reload_elm')
core.disable_trigger('elm', 'pipes')
core.disable_trigger('pipe_full', 'pipes')
core.disable_trigger('pipes_paralysis_nofill', 'pipes')
core.debug("filled elm pipe")
def pipe_fill_valerian(line, time, backrefs):
player.waiting_for_aeon = 0
player.valerian_puffs = 10
herbs.valerian.inv -= 1
player.pipe_reloading = ''
free_queue.remove_by_name('reload_valerian')
core.disable_trigger('valerian', 'pipes')
core.disable_trigger('pipe_full', 'pipes')
core.disable_trigger('pipes_paralysis_nofill', 'pipes')
core.debug("filled valerian pipe")
def test_backprop(self):
self.forward()
value = self.max_pool_node.value()
debug("value = np.{}".format(repr(value)))
ones = np.ones_like(value)
self.max_pool_node.backward(ones, self, self.var_map)
grad_from_maxpool = self.x_node.total_incoming_gradient()
debug("grad_from_maxpool = np.{}".format(repr(grad_from_maxpool)))
expected_grad = np.array([[0, 1, 0, 1], [0, 0, 1, 0], [0, 2, 0, 1]])
np.testing.assert_almost_equal(expected_grad, grad_from_maxpool)
def _copyDirs(self):
copyDirs = [
'bin', 'usr/bin'
]
for dir in copyDirs:
rPath = file.buildPath('/',dir)
chPath = file.buildPath(self.baseDir,dir)
## if os.path.exists(chPath):
## os.remove(chPath)
debug('%s --> %s' % (rPath,chPath), DEBUG)
shutil.copytree(rPath,chPath)
def database_query(query_str):
try:
conn = sqlite3.connect(dbname)
retstr = conn.execute(query_str).fetchall()
except Exception as err:
debug("***database_query error: " +str(err)+", 使用代替方式",1)
filename = str(random.randint(0,99999999))
shutil.copyfile(dbname,tempdir+"\\"+filename)
connnew = sqlite3.connect(tempdir+"\\"+filename)
retstr = connnew.execute(query_str).fetchall()
connnew.close()
os.remove(tempdir+"\\"+filename)
return retstr
def test_rnn_layer(self):
x = np.array([[1, 2, 1], [-1, 0, -.5]]).T
x = x.reshape((3, 1, 2))
input_node = n.VarNode('x')
var_map = {'x': x}
rnn_layer = rnn.SimpleRnnLayer(input_node, 4, 2)
input_node.forward(var_map)
y = rnn_layer.value()
dely = y * .1
rnn_layer.backward(dely, self, var_map)
x_grad = input_node.total_incoming_gradient()
debug("[SimpleRnnCellTests.test_rnn_layer()] x_grad = np.{}".format(
repr(x_grad)))
def text_reply(msg):
#itchat.send('%s: %s' % (msg['Type'], msg['Text']), msg['FromUserName'])
try:
userinfo = itchat.update_friend(msg['FromUserName'])
usernick = userinfo['NickName']
debug("收到消息！来源：" + usernick + " 内容：" + msg['Text'])
except Exception as e:
debug("回复消息：解析用户错误！错误原因：" + str(e) + ",msg = " + str(msg))
if core.settings.get_value('TIEBA_SHIDA_UPDATEING_STATE') == False:
core.game.core_input(usernick, int(time.time()), msg['Text'],
msg['FromUserName'])
else:
itchat.send_msg('贴吧更新正在进行中，请稍后访问本公众号！', msg['FromUserName'])
def flash_userdata(player_id):
allinfo = core.userinfo.database_getall(player_id)
if player_id in userdata:
if allinfo == []:
debug("******Database damage in flash_userdata," + player_id)
return
else:
get_userdata(player_id, allinfo)
else:
if allinfo == []:
core.userinfo.database_newuser(player_id)
allinfo = core.userinfo.database_getall(player_id)
get_userdata(player_id, allinfo)
else:
get_userdata(player_id, allinfo)
def RealTimeGetMSG(dbtables,lastmsg):
newlastmsg = {}
for table in dbtables:
msg = GetNewestPrivateChat(table,MAX_CHATCOUNT_IN_INTERVAL)
newlastmsg[table] = str(msg[0][0])+"--"+str(msg[0][1])+"--"+str(msg[0][2])
for (rettime,rettalker,retmsg) in msg:
if (lastmsg[table]==str(rettime)+"--"+rettalker+"--"+retmsg)or(lastmsg[table]==""):
break #considering orderd by time, if encounter equals, the messages after are old.
if retmsg.find("你悄悄地对")<0: # avoid the response interrupting
debug(str(rettime)+"###"+str(rettalker)+"###"+str(GetMessageLine(retmsg)),2)
core.game.core_input(rettalker,rettime,str(GetMessageLine(retmsg)))
return newlastmsg
def workRunner(self, block, work):
debug("block: " + block + " work: " + work)
# [gen for gen in self.gen.featureBlock(self.dirtY) if gen['']]
for gen in self.gen.featureBlock(self.dirtY):
if gen["fb"][0] == "use" and gen["block"] == block and gen["os"] == self._os[0] and gen["subblock"] == work:
feature = self.config.getFeature(gen["fb"][1])
if feature:
self.config.putPackage(work, gen["feature"])
lst = [gen["os"], gen["block"], gen["subblock"]]
features = yamlReduce(self.dirtY, lst)[0][gen["feature"]]
self.features.RunFeature(gen["fb"][1], gen["subblock"], features)
else:
debug("Not loaded: " + gen["fb"][1], ERROR)
def test_sigmoid_node(self):
x_node = node.VarNode('x')
x = (np.array([[1, -1, 2]])).T
var_map = {'x': x}
sigmoid = SigmoidNode(x_node)
x_node.forward(var_map)
value = sigmoid.value()
expected_value = 1 / (1 + np.exp(-x))
np.testing.assert_array_almost_equal(expected_value, value)
debug(value)
sigmoid.backward(np.ones_like(value), self, var_map)
grad = x_node.total_incoming_gradient()
expected_grad = expected_value * (1 - expected_value)
debug(grad)
np.testing.assert_array_almost_equal(expected_grad / expected_grad.size, grad)
def backprop(self, incoming_gradient, **kwargs):
n = self.input.shape[0]
del_s = np.zeros((n, n))
for i in range(n):
for j in range(n):
if i==j:
del_s[i,j] = self.output[i,0]-self.output[i,0]**2
else:
del_s[i,j] = -self.output[i,0]*self.output[j,0]
debug("[Softmax.backprop()] incoming_gradient = np.{}".format(repr(incoming_gradient)))
debug("[Softmax.backprop()] del_s = np.{}".format(repr(del_s)))
self.outgoing_grad = del_s*incoming_gradient
return self.outgoing_grad
def _do_backprop(self, downstream_grad, downstream_node, var_map):
r"""
:param downstream_grad: should be ignored.
:param downstream_node: should be ignored
:param var_map:
:return:
"""
if self.prev_rnn_node is None:
h0 = self.hidden_state_in
else:
h0 = self.prev_rnn_node._hidden_state_out()
x = self.x_node.value()
xh = np.concatenate((x, h0))
incoming_y_grad, incoming_h_grad = self.total_incoming_gradient()
if incoming_y_grad is None:
if is_debug_on():
debug("[RnnCell._do_backprop()] null incoming_y_grad ")
incoming_y_grad = np.zeros((self.output_shape[0], 1))
if incoming_h_grad is None:
if is_debug_on():
debug("[RnnCell._do_backprop()] Null incoming_h_grad = np.{}")
incoming_h_grad = np.zeros((self.hidden_shape[0], 1))
w_grad = incoming_y_grad @ xh.T
u_grad = incoming_h_grad @ xh.T
wb_grad = np.sum(incoming_y_grad, axis=1).reshape((-1, 1))
ub_grad = np.sum(incoming_h_grad, axis=1).reshape((-1, 1))
x_dim = x.shape[0]
w = self.W.value()
u = self.U.value()
x_grad_from_y = w[:, 0:x_dim].T @ incoming_y_grad
x_grad_from_h = u[:, 0:x_dim].T @ incoming_h_grad
h_grad_from_y = w[:, x_dim:].T @ incoming_y_grad
h_grad_from_h = u[:, x_dim:].T @ incoming_h_grad
x_total_grad = (x_grad_from_h + x_grad_from_y)
h_total_grad = (h_grad_from_h + h_grad_from_y)
self.W.add_gradient(w_grad, self)
self.Wb.add_gradient(wb_grad, self)
self.U.add_gradient(u_grad, self)
self.Ub.add_gradient(ub_grad, self)
self.x_node.backward(x_total_grad, self, var_map)
if not (self.prev_rnn_node is None):
self.prev_rnn_node.backward((None, h_total_grad), self, var_map)
def APP_TuLing(player_id, msg):
if msg == '退出':
PlayerState[player_id] = 1
response(1, player_id, 'from state 6')
else:
apiUrl = 'http://www.tuling123.com/openapi/api'
data = {
'key': TULINGKEY, # 如果这个Tuling Key不能用，那就换一个
'info': msg, # 这是我们发出去的消息
'userid': 'wechat-robot-' + str(player_id), # 这里你想改什么都可以
}
try:
r = requests.post(apiUrl, data=data).json()
sendstr(player_id, r.get('Text'))
except Exception as e:
debug("图灵机器人出错，错误原因：" + str(e))
sendstr(player_id, "群宝在打盹儿= =过会儿再来呗~~~")
def patch(self, Name):
Config = self.Config.GetConfig(Name)
self.Config.CreateOutYaml(Name)
Folder = self.Config.FindInPackage("extract",Name)
PatchDir = ExtractNameFromTar(Folder['file'])
CWD = os.getcwd()
os.chdir("tmp/downloads/" + PatchDir)
for File in Config["file"]:
#IntelliPatcher(Files)
PatchLevel = File.split('@')
pLevel = PatchLevel[1].split(':')[1]
pFile = PatchLevel[0]
Patch = subprocess.Popen('patch -p%d < %s' % (int(pLevel),CWD+"/"+pFile), shell=True, stdout=None, stderr=None)
Patch.wait()
if Patch.returncode > 0:
debug("Patch didn't return 0!",WARNING)
os.chdir(CWD)
def run(self, _all=False):
""" this is the main runner for the yaml parser """
## Run all of the blocks
if _all:
for cmds in self.commands:
debug(cmds, DEBUG)
self.runBlock(cmds)
self.depRunner(cmds)
## If value hasnt changed, raise ParseError
if not _all:
raise ParseError
## Otherwise run specified block
else:
# debug(_all, DEBUG)
self.runBlock(_all)
self.depRunner(_all)
def test_2_debug(self):
self.mock.StubOutWithMock(inspect, 'currentframe')
inspect.currentframe(0).AndReturn('')
self.mock.StubOutWithMock(inspect, 'getouterframes')
inspect.getouterframes('').AndReturn('')
#configurator = self.mock.CreateMockAnything()
#configurator.getGlobal('debug').AndReturn(3)
#self.mock.StubOutWithMock(core.debug, '_dPrint')
#debug._dPrint('').AndReturn('')
self.mock.ReplayAll()
debug('debug test', DEBUG)
#self.assertStdoutEquals('')
self.mock.VerifyAll()
def def_list_disable(line, time, backrefs):
# TODO: compare this to our keepup list and correct!
core.disable_trigger_group('def_list')
# Flush player defences except channels
for defence in player.defences:
if defence not in ('earth', 'air', 'water', 'fire', 'spirit'):
player.defences[defence] = 0
for defence in player.pre_def:
try:
type = defences.defup_actions[defence][0]
defences.clean_queues(type, defence)
except KeyError:
pass
player.defences[defence] = 1
core.debug("deflist added defence " + defence)
player.pre_def = []
def GET(self, request, artist_id): db = musicdb.model.db.DB() artists = self.get_related(db, artist_id) for artist in artists: if not artist.AliasID: # dan zal het wel een groep zijn, leden ophalen artist['Members'] = [a.ArtistID for a in db.artist.get_group_members(artist.ArtistID)] else: artist['Members'] = [] graph = dict( (a.ArtistID, ([a.AliasID] if a.AliasID else []) + a.Members) for a in artists) node_text = dict((a.ArtistID, a.Name) for a in artists) core.debug(request, repr(graph)+'\n') core.debug(request, repr(node_text)+'\n') return webob.Response( body=musicdb.view.graph.draw_graph(graph, node_text, directed=False), content_type='image/png', cache_control='no-store, no-cache')
def test_batch(self):
sx = sl.SoftmaxCrossEntropy()
debug("------------- Batch with 2 samples -----------------")
predicted = np.array([[1, 3, -1, 0], [0, 9, 1, 3.]]).T.reshape(4, 2)
debug("[SoftmaxTestCase.test_batch()] predicted = np.{}".format(
repr(predicted)))
target = np.array([[0, 1, 0, 0], [0, 0, 0, 1]]).T.reshape(4, 2)
loss = sx.forward(predicted, target)
debug("[SoftmaxTestCase.test_forward()] Loss = {}".format(repr(loss)))
grad = sx.backward(1.0)
debug("[SoftmaxTestCase.test_forward()] grad = np.{}".format(
repr(grad.T)))
def __init__(self, data_dir):
self.all_letters = string.ascii_letters + " .,;'"
self.n_letters = len(self.all_letters)
self.data_dir = data_dir
self.file_list = u.get_file_list(self.data_dir, u.ext_filter(".txt"))
self.category_files = {}
self.categories_list = []
self.data = {}
self.total_names = 0
for file_name in self.file_list:
language = os.path.splitext(os.path.basename(file_name))[0]
self.category_files[language] = file_name
lines = self.read_lines(file_name)
self.data[language] = lines
self.total_names += len(lines)
self.categories_list.append(language)
self.n_categories = len(self.category_files)
debug("[NameDS.__init__()] self.total_names = {}".format(
self.total_names))
def __init__(self, name=None, is_trainable=False):
global compute_node_list
idx = len(compute_node_list)
compute_node_list.append(self)
if name:
self.name = name + "-" + str(idx)
else:
self.name = self.__class__.__name__ + str(idx)
debug("Created Node named:{}".format(self.name))
self.upstream_nodes = {}
self.downstream_nodes = {}
self.grad_from_downstream = []
self.fwd_count = 0
self.back_count = 0
self.node_value = None
self._total_incoming_grad_value = None
self.is_trainable = is_trainable
self.optimization_storage = {}
def depRunner(self, block):
""" resolves the dependencies """
lst = [
gen["subblock"]
for gen in self.gen.featureBlock(self.dirtY)
if gen["block"] == block and gen["os"] == self._os[0]
]
for gen in self.gen.featureBlock(self.dirtY):
if gen["os"] == self._os[0]:
if gen["block"] == block or block == True:
if gen["fb"][0].lower() == "dependencies":
for deps in gen["fb"][1]:
debug("[" + gen["subblock"] + "] depends on: " + deps, INFO)
self.deps.depGenAdd(gen["subblock"], deps)
else:
self.deps.depGenAdd(gen["subblock"])
depList = self.deps.dependencyGenRun()
for revDep in depList[0]:
self.workRunner(block, revDep)
def tar(self, Name, filename=None):
Tar = {}
Config = self.Config.GetConfig(Name)
debug(Config, DEBUG)
File = Config["file"]
if filename:
File = Filename
self.Config.CreateOutYaml(Name)
if not os.path.exists("tmp/downloads/"+ExtractNameFromTar(File)):
print "[tar] Extracting: " + File
if os.path.exists("tmp/downloads/"+File):
End = File.split(".")
if End[-1] == "bz2":
tar = tarfile.open(name="tmp/downloads/" + File,mode='r:bz2')
try:
extract = tar.extractall(path="tmp/downloads/",members=None)
except EOFError,e:
print "The file appears to be corrupt, run with",
print "--clean and then retry building"
debug(e, ERROR)
sys.exit(0)
if End[-1] == "gz":
tar = tarfile.open(name="tmp/downloads/" + File,mode='r:gz')
try:
extract = tar.extractall(path="tmp/downloads/",members=None)
except EOFError,e:
print "The file appears to be corrupt, run with",
print "--clean and then retry building"
debug(e, ERROR)
sys.exit(0)
def forward(self, var_map: ComputeContext):
if self.prev_rnn_node is None:
h0 = self.hidden_state_in
else:
h0 = self.prev_rnn_node._hidden_state_out()
x = self.x_node.value()
xh = np.concatenate((x, h0))
w = self.W.value()
wb = self.Wb.value()
u = self.U.value()
ub = self.Ub.value()
y = w @ xh + wb
h = u @ xh + ub
self.node_value = y, h
self.hidden_state_out = h
if is_debug_on():
debug("[{}] RnnCell.forward() y=np.{}".format(
self.simple_name(), repr(y)))
debug("[{}] RnnCell.forward() h=np.{}".format(
self.simple_name(), repr(h)))
debug("[{}] RnnCell.forward() x=np.{}".format(
self.simple_name(), repr(x)))
self._forward_downstream(var_map)
def bcure(cure):
now = time.time()
core.debug("registering blackout cure " + cure)
player.waiting_for_aeon = 0
if player.fire_focus and player.focus_balance == .5:
core.debug("fired focus in blackout")
player.fire_focus = False
player.focus_balance = 0
player.actions['focus'] = True
core.enable_trigger('focus_balance', 'balances')
ate = False
for herb in player.blackout_ate:
if player.blackout_ate[herb] == True:
ate = True
ate_herb = herb
core.debug("Ate " + ate_herb + " in blackout")
player.blackout_ate[herb] = False
if ate:
player.herb_balance = 0
player.herb_lastate = now
player.ate[ate_herb] = True
herbs.herbs[ate_herb].inv -= 1
cures.cure(cure)
def output(string):
global conc_curing, next_cure
if core.retardation_mode:
next_cure = string
if rr_auto == False:
return
player.waiting_for_aeon = .5
if player.afflictions['amnesia'] or player.afflictions['concussion']:
core.write(string)
core.write(string)
#core.write(string)
else:
core.write(string)
if player.afflictions['concussion']:
conc_curing = string
else:
conc_curing = False
core.debug("Aeon Event: Firing " + string)
def test_delete(self):
x = np.random.rand(5,4)
debug("[TestingPythonDelete.test_delete()] x= np.{}".format(repr(x)))
c = Container(3,x)
debug("[TestingPythonDelete.test_delete()] c = np.{}".format(repr(c)))
del c
time.sleep(1)
debug("[TestingPythonDelete.test_delete()] x = np.{}".format(repr(x)))
def affliction_event():
global temporary_priorities, temps_focus, preempt_cures
core.disable_trigger_group('venoms')
cures.disable_restro_break_triggers()
real = True
if len(cures.pre_afflictions) > 0:
for aff in cures.pre_afflictions:
if cures.ai['reflection_strike']:
if aff in ('roped', 'impale'):
real = False
if cures.lifevision:
real = False
core.debug("lifevision nulled out affliction " + aff)
# stupidity failures
if aff == 'stupidity' and player.afflictions['stupidity'] is True:
player.waiting_for_aeon = 0
# sleep resetting
if aff == 'sleep':
player.waiting_for_aeon = 0
if real:
cures.escalate_breaks(aff)
player.afflictions[aff] = True
cures.pre_afflictions = []
cures.ai['reflection_strike'] = False
if core.retardation_mode:
dynamic_retardation_priorities()
else:
dynamic_priorities()
load_queue()
def test_batch_norm(self):
x = np.array([[1, 2, 3], [3, 4, 1]])
x_node = node.VarNode('x')
bnorm = reg.BatchNormalization(x_node)
x_node.forward({'x': x})
norm_value = bnorm.value()
debug("normalized value = np.{}".format(repr(norm_value)))
bnorm.backward(np.ones_like(norm_value), self, {'x': x})
grad_at_x = x_node.total_incoming_gradient()
debug("grad_at_x = np.{}".format(repr(grad_at_x)))
debug(
"[BatchNormalizationTest.test_something()] bnorm.gamma_grad = np.{}"
.format(repr(bnorm.gamma_grad)))
debug(
"[BatchNormalizationTest.test_something()] bnorm.beta_grad = np.{}"
.format(repr(bnorm.beta_grad)))
def forward(self, compute_context: ComputeContext):
x = self.input_node.value()
if not self.weights_initialized:
self.input_dim = x.shape[0]
compute_context.initialize_layer(self)
if is_debug_on():
debug("[{}] DenseLayer.forward() W=np.{}".format(self.simple_name(), repr(self.w)))
debug("[{}] DenseLayer.forward() b=np.{}".format(self.simple_name(), repr(self.b)))
debug("[{}] DenseLayer.forward() x=np.{}".format(self.simple_name(), repr(x)))
self.node_value = self.w @ x + self.b
self._forward_downstream(compute_context)
def InitUpdateTieba(self):
debug("初始化贴吧十大 启动", 2)
todayymd = time.strftime("%y-%m-%d")
if not os.path.exists(todayymd + "_2"):
debug("未检测到今日十大")
core.jx3tieba.tiebatop_update("剑网三", todayymd)
time.sleep(1)
else:
debug("检测到今日十大，直接使用已生成文件")
if core.settings.TIEBA_UPDATE_FORCE == 1:
debug("十大强制更新开关 打开，开始更新十大")
core.jx3tieba.tiebatop_update("剑网三", todayymd)
time.sleep(1)
f = open(todayymd + "_2", 'rU', encoding='utf-8')
tmplist = []
for i in range(0, 10):
tmplist.append(f.readline().strip("\n"))
core.settings.set_value('TIEBA_SHIDA', tmplist)
core.settings.set_value('TIEBA_SHIDA_UPDATE', todayymd)
core.settings.set_value('TIEBA_UPDATE_TO', todayymd)
def test_forward(self):
input_x_node = n.VarNode('x')
rnn_cell = rnn.RnnCell(input_x_node, None, self.w_param, self.wb_param,
self.u_param, self.ub_param, self.h)
input_x_node.forward(self.var_map)
y, h = rnn_cell.value()
debug("[SimpleRnnCellTests.test_forward()] y = np.{}".format(repr(y)))
debug("[SimpleRnnCellTests.test_forward()] h = np.{}".format(repr(h)))
dely, delh = y * .1, h * .1
rnn_cell.backward((dely, delh), self, self.var_map)
grad_x = input_x_node.total_incoming_gradient()
debug("[SimpleRnnCellTests.test_forward()] grad_x = np.{}".format(repr(grad_x)))
def init_readskills(self):
debug("readskills组件初始化")
try:
f = open(core.settings.APP_skill_filename, encoding='utf-8')
skilllist = f.readlines()
f.close()
core.settings.set_value("APP_SKILL_SKILLLIST", skilllist)
if not os.path.exists(core.settings.APP_skill_savedir):
os.mkdir(core.settings.APP_skill_savedir)
except Exception as e:
debug("readskills组件初始化失败，原因：" + str(e), '错误')
return
debug("readskills组件初始化成功！")
def test_logit_cross_entropy(self):
logits = np.array([[2, 1, 4, -1], [3, 2, 1, -9]])
target_values = np.array([2, 0])
one_hot_target = to_one_hot(target_values, logits.shape[1] - 1)
debug(" [SimpleActivationTests.test_logit_cross_entropy()] one_hot_target = np.{}".format(repr(one_hot_target)))
pred_node = node.VarNode('yp')
target_node = node.VarNode('yt')
var_map = {'yp': logits.T, 'yt': one_hot_target}
lx = LogitsCrossEntropy(pred_node, target_node)
pred_node.forward(var_map)
target_node.forward(var_map)
value = lx.value()
expected = 0.2915627072172198
debug(" [SimpleActivationTests.test_logit_cross_entropy()] value = {}".format(repr(value)))
self.assertAlmostEqual(expected, value)
lx.backward(1.0, self, var_map)
grad = pred_node.total_incoming_gradient()
debug(" [LogitCrossEntropyTests.test_logit_cross_entropy()] grad = np.{}".format(repr(grad)))
expected_grad = np.array([[5.67748097e-02, -1.67380882e-01],
[2.08862853e-02, 1.22363735e-01],
[-8.04877463e-02, 4.50151026e-02],
[2.82665133e-03, 2.04368250e-06]])
debug(" [LogitCrossEntropyTests.test_logit_cross_entropy()] expected_grad = np.{}".format(repr(expected_grad)))
np.testing.assert_array_almost_equal(expected_grad, grad)
def runner(self, recipeName, *arguments):
''' runner, arguments: recipeLocation '''
debug(arguments, DEBUG)
try:
module = sys.modules['recipes.' + recipeName]
except KeyError:
__import__('recipes.' + recipeName)
module = sys.modules['recipes.' + recipeName]
## if the recipe has requirements
if 'requires' in module.__dict__ and isinstance(module.__dict__['requires'], list):
for reqs in module.__dict__['requires']:
if self.config.getFeature(reqs):
debug('feature %s available' % (reqs), DEBUG)
else:
debug('feature %s unavailable' % (reqs), DEBUG)
print 'plugin %s not available, exiting gracefully...' % (reqs)
sys.exit(-1)
## run the run function, run()
for function in module.__dict__:
if function == self.runFunction:
self.run(module, arguments)
def chdir(dir):
''' Wrapper for os.chdir so that it emits debugging code '''
debug("Changing to directory: " + dir, DEBUG)
os.chdir(dir)
def GET(self, request, artist_id): db = musicdb.model.db.DB() related = self.get_related(db, artist_id) core.debug(request, `related`+'\n') return webob.Response(body=musicdb.view.artist.artist_list(related))
def run(self):
''' runs all of the blocks of yaml code '''
block = {}
for blck, a in reversed(self.dyaml.items()):
for subblock, b in a.items():
if isinstance(b, dict):
for feature, value in b.items():
if 'recipe' not in feature:
try:
block[subblock].append({feature:value})
except KeyError:
block[subblock] = []
block[subblock].append({feature:value})
else:
if 'recipe' not in subblock:
try:
block[blck].append({subblock:b})
except KeyError:
block[blck] = []
block[blck].append({subblock:b})
for gen in yGen(self.dyaml):
if isinstance(gen['keys'], dict):
if 'recipe' in gen['keys']:
try:
debug(block[gen['subblock']], DEBUG)
if block.has_key(gen['subblock']):
self.recipe.runner(gen['keys']['recipe'], block[gen['subblock']])
if block.has_key(gen['block']):
self.recipe.runner(gen['keys']['recipe'], block[gen['block']])
except KeyError:
self.recipe.runner(gen['keys']['recipe'])
elif isinstance(gen['keys'], bool):
pass
elif '->' in gen['keys']:
thenCount = 1
thenList = gen['keys'].split('->')
then = []
for thenItr in thenList:
if not thenCount % 2:
if thenItr[:1] == ' ':
thenItr = thenItr[1:]
else:
if thenItr[:-1] == ' ':
thenItr = thenItr[-1:]
then.append(thenItr)
thenCount = thenCount + 1
for recipe in then:
try:
if block.has_key(gen['subblock']):
self.recipe.runner(gen['keys'], block[gen['subblock']])
if block.has_key(gen['block']):
self.recipe.runner(gen['keys'], block[gen['block']])
except Exception, E:
print E
debug(E, ERROR)
debug('%s failed so any dependants will not run' % (recipe), ERROR)
sys.exit(-1)
def __debugSignal(self, *args):
""" Receives debug signal """
debug(str(args))