def test_merger():
merger = joint.Merger()
pipe1 = base.PIPE()
pipe2 = base.PIPE()
for i in range(5):
pipe1.put(
base.Packet({"mfcc": np.ones([
5,
], dtype="float32")},
cid=i,
idmaker=0))
pipe2.put(
base.Packet({"fbank": np.ones([
4,
], dtype="float32")},
cid=i,
idmaker=0))
pipe1.stop()
pipe2.stop()
merger.link(inPIPE=[pipe1, pipe2])
merger.start()
merger.wait()
print(merger.outPIPE)
print(merger.outPIPE[0].size())
print(merger.outPIPE[0].get().items())
#test_merger()
def test_sender():
pipe = base.PIPE()
for i in range(5):
pipe.put(base.Packet({"element": 1}, cid=i, idmaker=0))
for i in range(5, 10):
pipe.put(
base.Packet({"vector": np.ones([
5,
], dtype="float32")},
cid=i,
idmaker=0))
for i in range(10, 15):
pipe.put(
base.Packet({"matrix": np.ones([5, 10], dtype="float32")},
cid=i,
idmaker=0))
for i in range(15, 20):
pipe.put(base.Packet({"string": "this is a test"}, cid=i, idmaker=0))
pipe.stop()
# define a packet sender
sender = transmit.PacketSender(thost="192.168.1.11", tport=9509)
sender.start(inPIPE=pipe)
sender.wait()
def test_combiner():
pipe1 = base.PIPE()
pipe2 = base.PIPE()
for i in range(5):
pipe1.put(
base.Packet({"mfcc": np.ones([
5,
], dtype="float32")},
cid=i,
idmaker=0))
pipe2.put(
base.Packet({"fbank": np.zeros([
5,
], dtype="float32")},
cid=i,
idmaker=0))
pipe1.stop()
pipe2.stop()
def combine_function(items):
return {
"mixedFeat": np.concatenate([items[0]["mfcc"], items[1]["fbank"]])
}
combiner = joint.Combiner(func=combine_function)
combiner.link(inPIPE=[pipe1, pipe2])
combiner.start()
combiner.wait()
print(combiner.outPIPE)
print(combiner.outPIPE[0].get().items())
def test_estimator():
pipe = base.PIPE()
for i in range(5):
pipe.put(base.Packet({"data": np.ones([10, 13])}, cid=i, idmaker=0))
pipe.stop()
def test_func(frames):
return np.zeros_like(frames)
estimator = decode.AcousticEstimator(
func=test_func,
leftContext=3,
rightContext=3,
applySoftmax=False,
applyLog=False,
)
estimator.start(inPIPE=pipe)
estimator.wait()
print(estimator.outPIPE.size())
print(estimator.outPIPE.get()["data"].shape)
def test_processor_cmvn():
wavData = stream.read(wavPath).value
frames = stream.cut_frames(wavData)
pipe = base.PIPE()
for i in range(10):
pipe.put( base.Packet( {"rawWave":frames[i*50:(i+1)*50]}, cid=i, idmaker=0 ) )
pipe.stop()
extractor = feature.MfccExtractor(minParallelSize=100,oKey="mfcc")
processor = feature.MatrixFeatureProcessor(
spliceLeft=3,
spliceRight=3,
cmvNormalizer=feature.FrameSlideCMVNormalizer(),
oKey="mfcc",
)
extractor.start(inPIPE=pipe)
processor.start(inPIPE=extractor.outPIPE,iKey="mfcc")
processor.wait()
print( processor.outPIPE.size() )
packet = processor.outPIPE.get()
print( packet.keys() )
print( packet.mainKey )
print( packet["mfcc"].shape ) # 273 = 13 * 3 * 7
def test_spliter():
pipe = base.PIPE()
for i in range(5):
pipe.put(
base.Packet(items={
"mfcc": np.ones([
5,
], dtype="float32"),
"fbank": np.ones([
5,
], dtype="float32"),
},
cid=i,
idmaker=0))
pipe.stop()
def split_function(items):
return [{key: value} for key, value in items.items()]
spliter = joint.Spliter(func=split_function, outNums=2)
spliter.start(inPIPE=pipe)
spliter.wait()
print(spliter.outPIPE)
print(spliter.outPIPE[0].get().keys())
print(spliter.outPIPE[1].get().keys())
def test_mixture_feature_parallel():
wavData = stream.read(wavPath).value
frames = stream.cut_frames(wavData)
pipe = base.PIPE()
for i in range(10):
pipe.put(
base.Packet({"rawWave": frames[i * 50:(i + 1) * 50]},
cid=i,
idmaker=0))
pipe.stop()
extractor = feature.MixtureExtractor(mixType=["fbank", "mfcc"], )
# Split packets
def split_rule(items):
return {"fbank": items["fbank"]}, {"mfcc": items["mfcc"]}
spliter = joint.Spliter(split_rule, outNums=2)
# use a processor to transform fbank feature
processor1 = feature.MatrixFeatureProcessor(
spliceLeft=2,
spliceRight=2,
cmvNormalizer=feature.FrameSlideCMVNormalizer(),
oKey="fbank",
)
# use a processor to transform mfcc feature
processor2 = feature.MatrixFeatureProcessor(
spliceLeft=3,
spliceRight=3,
cmvNormalizer=feature.FrameSlideCMVNormalizer(),
oKey="mfcc",
)
# combine packets
def combine_rule(items):
return {
"feat": np.concatenate([items[0]["fbank"], items[1]["mfcc"]],
axis=1)
}
combiner = joint.Combiner(combine_rule)
extractor.start(inPIPE=pipe)
spliter.start(inPIPE=extractor.outPIPE)
processor1.start(
inPIPE=spliter.outPIPE[0]) # specify which key you want to process
processor2.start(
inPIPE=spliter.outPIPE[1]) # specify which key you want to process
combiner.start(inPIPE=[processor1.outPIPE, processor2.outPIPE])
combiner.wait()
print(combiner.outPIPE[0].size())
packet = combiner.outPIPE[0].get()
print(packet.keys())
print(packet["feat"].shape) # 211 = 120 + 91
def test_mfcc_extractor():
# get wave data
wavData = stream.read(wavPath).value
frames = stream.cut_frames(wavData)
# define an input pipe
pipe = base.PIPE()
for i in range(10):
pipe.put( base.Packet( {"rawWave":frames[i*50:(i+1)*50]}, cid=i, idmaker=0 ) )
pipe.stop()
print( pipe.size() )
# run a mfcc extractor
extractor = feature.MfccExtractor(oKey="mfcc")
extractor.start(inPIPE=pipe)
extractor.wait()
print( extractor.outPIPE.size() )
packet = extractor.outPIPE.get()
print( packet.keys() )
print( packet.mainKey )
print( packet["mfcc"].shape )
def test_decoder():
prob = np.load("../examples/1272-135031-0000_mlp.npy")
frames = prob.shape[0]
dim = prob.shape[1]
batchSize = 50
N = int(math.ceil(frames / batchSize))
buffer = np.zeros([N * batchSize, dim], dtype="float32")
buffer[0:frames] = prob
pipe = base.PIPE()
for i in range(N):
s = i * batchSize
e = (i + 1) * batchSize
pipe.put(base.Packet({"data": buffer[s:e]}, cid=i, idmaker=0))
pipe.stop()
print(pipe.size())
decoder = decode.WfstDecoder(
symbolTable=
"/Work18/wangyu/kaldi/egs/mini_librispeech/s5/exp/tri3b/graph_tgsmall/words.txt",
silencePhones="1:2:3:4:5:6:7:8:9:10",
frameShiftSec=0.01,
tmodel=
"/Work18/wangyu/kaldi/egs/mini_librispeech/s5/exp/tri3b_ali_dev_clean_2/final.mdl",
graph=
"/Work18/wangyu/kaldi/egs/mini_librispeech/s5/exp/tri3b/graph_tgsmall/HCLG.fst",
beam=10,
latticeBeam=8,
minActive=200,
maxActive=7000,
acousticScale=0.1,
maxBatchSize=50,
)
decoder.start(inPIPE=pipe)
base.dynamic_display(decoder.outPIPE)
#decoder.wait()
#print( decoder.outPIPE.size() )
#result = decode.dump_text_PIPE(decoder.outPIPE)
#print( result )
# online : BECAUSE YOU ARE A SLEEPING IN SOME OF CONQUERING THE LOVELY RUSE PRINCES WAS PUT TO A FATAL WITHOUT A BULL OLD TORE SHAGGY SINCERE OR COOING DOVE
# offline: BECAUSE YOU ARE A SLEEPING IN SOME OF CONQUERING THE LOVELY RUSE PRINCES WAS PUT TO A FATAL WITHOUT A BULL OLD TORE SHAGGY SINCERE OR COOING DOVE
#test_decoder()
def test_mapper():
pipe = base.PIPE()
for i in range(5):
pipe.put( base.Packet({"mfcc":np.ones([5,],dtype="float32")},cid=i,idmaker=0) )
pipe.stop()
def map_function(items):
return { "scaledMFCC": 2*items["mfcc"] }
mapper = joint.Mapper(mapFunc=map_function)
mapper.start(inPIPE=pipe)
mapper.wait()
print( mapper.outPIPE.size() )
print( mapper.outPIPE.get()["scaledMFCC"] )
def test_replicator():
replicator = joint.Replicator(outNums=2)
pipe = base.PIPE()
for i in range(5):
pipe.put( base.Packet({"mfcc":np.ones([5,],dtype="float32")},cid=i,idmaker=0) )
pipe.stop()
replicator.link(inPIPE=pipe)
replicator.start()
replicator.wait()
print( replicator.outPIPE )
print( replicator.outPIPE[0].get().items() )
print( replicator.outPIPE[1].get().items() )
def test_chain():
# Define a component
class MyComponent(base.Component):
def __init__(self,*args,**kwargs):
super().__init__(*args,**kwargs)
def core_loop(self):
while True:
if self.inPIPE.is_empty():
break
pack = self.get_packet()
self.put_packet(pack)
component = MyComponent()
# Define a joint
def copy_packet(items):
return items[0], copy.deepcopy(items[0])
joint = base.Joint(copy_packet, outNums=2)
# define the input PIPE
pipe = base.PIPE()
for i in range(5):
pipe.put( base.Packet( {"mfcc":np.ones([5,],dtype="float32") },cid=i, idmaker=0) )
pipe.stop()
# Define a chain (container)
chain = base.Chain()
# Add a component
chain.add( component, inPIPE=pipe )
# Add a joint. chain will link the joint to the output of component automatically.
chain.add( joint )
# Start and Wait
chain.start()
chain.wait()
# Chain has similiar API with component and joint
print( chain.outPIPE )
print( chain.outPIPE[0].size() )
print( chain.outPIPE[1].size() )
def test_mixture_feature_series():
wavData = stream.read(wavPath).value
frames = stream.cut_frames(wavData)
pipe = base.PIPE()
for i in range(10):
pipe.put(
base.Packet({"rawWave": frames[i * 50:(i + 1) * 50]},
cid=i,
idmaker=0))
pipe.stop()
extractor = feature.MixtureExtractor(mixType=["fbank", "mfcc"], )
# use a processor to transform fbank feature
processor1 = feature.MatrixFeatureProcessor(
spliceLeft=2,
spliceRight=2,
cmvNormalizer=feature.FrameSlideCMVNormalizer(),
oKey="fbank",
)
# use a processor to transform mfcc feature
processor2 = feature.MatrixFeatureProcessor(
spliceLeft=3,
spliceRight=3,
cmvNormalizer=feature.FrameSlideCMVNormalizer(),
oKey="mfcc",
)
extractor.start(inPIPE=pipe)
processor1.start(inPIPE=extractor.outPIPE,
iKey="fbank") # specify which key you want to process
processor2.start(inPIPE=processor1.outPIPE,
iKey="mfcc") # specify which key you want to process
processor2.wait()
print(processor2.outPIPE.size())
packet = processor2.outPIPE.get()
print(packet.keys())
print(packet["fbank"].shape) # 120 = 24 * 5
print(packet["mfcc"].shape) # 91 = 13 * 7
def test_joint():
# Define a joint: it is used to separate different data.
def combine(items):
# items is a list including multiple input items (dict objects)
return {"mfcc":items[0]["mfcc"]}, {"fbank":items[0]["fbank"]}
joint = base.Joint(jointFunc=combine,outNums=2)
# Define an input PIPE which the joint will get packets from it.
pipe = base.PIPE()
for i in range(5):
packet = base.Packet( items={"mfcc":np.ones([5,],dtype="float32"),
"fbank":np.ones([4,],dtype="float32")
},
cid=i,
idmaker=0
)
pipe.put( packet )
pipe.stop()
# then link joint with this input PIPE
joint.link(inPIPE=pipe)
# start and wait
joint.start()
joint.wait()
# there should be two output PIPEs
print( joint.outPIPE )
# the first PIPE should only include "mfcc" date
# the second PIPE should only include "fbank" date
print( joint.outPIPE[0].get().items() )
print( joint.outPIPE[1].get().items() )
def test_packet():
# Define a packet which carry one frame of mfcc features.
# Each packet must have a unique chunk id, which is made by a component or joint.
packet = base.Packet( items={"mfcc":np.ones([13,],dtype="float32") }, cid=0, idmaker=0 )
# Each packet has a mainKey and you can check all keys in this packet.
# This main key is decided automatically when you initialize packet object.
print( packet.keys(), packet.mainKey )
# It has some similar function with Python doct object.
print( packet.values() )
print( packet.items() )
print( packet["mfcc"] ) # but __setitems__ is unavaliable.
# If you want add a new record in this packet.
# You can set it as main key.
packet.add( key="fbank", data=np.ones([24,],dtype="float32"), asMainKey=True )
print( packet.keys(), packet.mainKey )
# Packet object can be convert to bytes object for, such as remote transmission.
bpack = packet.encode()
print( bpack )
# A packet can be restored from the corrsponded bytes object.
npack = base.Packet.decode( bpack )
print( npack )
print( npack.keys() )
# Endpoint is a special packet the mark speech endpoint.
# It defaultly is an empty packet but also can carries data.
ENDPOINT = base.Endpoint( cid=0, idmaker=0 )
bENDPOINT = ENDPOINT.encode()
print(bENDPOINT)
nENDPOINT = base.Packet.decode( bENDPOINT )
print(nENDPOINT)
def test_pipe():
# Define a PIPE and put a packet int it.
# pipe has 5 states:
# 0 -> silent, 1 -> active, 2 -> terminated, 3 -> wrong, 4 -> stranded (more marks in exkaldirt.base.mark)
# Different states can allow different operations,
# for examples, you can not add a new packet into a terminated PIPE.
pipe = base.PIPE()
print( pipe.state )
pipe.put( base.Packet( items={"stream":100}, cid=0, idmaker=0 ) )
print( pipe.size() )
# If the input port or/and output port is locked,
# password is necessary if others want to access it.
# password is a random int number.
password = pipe.lock_in()
print( password )
print( pipe.is_inlocked() )
pipe.put( base.Packet( items={"stream":101}, cid=1, idmaker=0 ), password=password )
print( pipe.size() )
# When a pipe is locked by a specified component,
# you can not get packet from it unless you know the password.
# you can release it.
pipe.release_in(password=password)
# Note that, we will forcely remove continuous endpoints.
# If the endpoint had data, it will be lost.
# No matter how many endpoints you added, only keep the first one.
pipe.put( base.Endpoint( cid=2, idmaker=0 ) )
print( pipe.size() )
pipe.put( base.Endpoint( cid=3, idmaker=0 ) )
print( pipe.size() )
pipe.put( base.Endpoint( cid=4, idmaker=0 ) )
print( pipe.size() )
# For an active pipe, you can:
# pause it: the state will become "stranded";
# stop it: the state will become "terminated", and an endpoint packet will be appended at the last automatically;
# kill it: the state will become "wrong".
pipe.stop()
print( pipe.state )
# PIPE is actually a LILO queue.
# You can get a packet from head.
print( pipe.get() )
# If the pipe is "wrong" or "terminated", it can be converted to lists devided by endpoints.
# you can design the convert rule.
# defaultly, it only get the main key.
result = pipe.to_list()
print(result)
# If the pipe is "wrong" or "terminated", it can be reset.
pipe.reset()
# PIPE can add callback functions.
# when a packet is appended in PIPE, these functions will work.
def call_func_1(pac):
print("feature shape:", pac[pac.mainKey].shape )
def call_func_2(pac):
print("feature dtype:", pac[pac.mainKey].dtype )
pipe.callback( call_func_1 )
pipe.callback( call_func_2 )
for i in range(5):
pipe.put( base.Packet({"data":np.ones([5,],dtype="float32")},cid=i,idmaker=0) )
# The time info will be recorded when packets are appended and picked out.
pipe.get()
print( pipe.report_time() )
def PF_func1(pipe):
for i in range(5):
pipe.put( base.Packet({"data":1},cid=i,idmaker=0) )
pipe.stop()
