def __init__(self, input_size, output_size, num_layers, num_parallels, rnn_size, att_size, bu_size, dropout):
super(LSTM_DOUBLE_ATT_STACK_PARALLEL_MUL_OUT_ATT_WITH_BU, self).__init__()
self.input_size = input_size
self.output_size = output_size
self.num_layers = num_layers
self.num_parallels = num_parallels
self.rnn_size = rnn_size
self.att_size = att_size
self.bu_size = bu_size
self.dropout = dropout
# core
self.cores = nn.ModuleList()
for i in range(self.num_layers * self.num_parallels):
core = CORE.lstm_core_with_att_bu(self.input_size, self.rnn_size)
self.cores.append(core)
# attention
self.attens = nn.ModuleList()
for i in range(self.num_layers * 2):
att = ATT.lstm_att_with_x_att_h(self.rnn_size, self.att_size)
self.attens.append(att)
# bu attention
self.bu_attens = nn.ModuleList()
for i in range(self.num_layers * 2):
att = ATT.lstm_att_with_att_h(self.rnn_size, self.bu_size)
self.bu_attens.append(att)
# proj
self.projs = nn.ModuleList()
for i in range(self.num_layers):
proj = nn.Linear(self.rnn_size, self.output_size)
self.projs.append(proj)
def __init__(self, input_size, output_size, num_layers, num_parallels, rnn_size, att_size, dropout):
super(LSTM_SOFT_ATT_STACK_PARALLEL_WITH_FC_WEIGHT, self).__init__()
self.input_size = input_size
self.output_size = output_size
self.num_layers = num_layers
self.num_parallels = num_parallels
self.rnn_size = rnn_size
self.att_size = att_size
self.dropout = dropout
# core
self.cores = nn.ModuleList()
for i in range(self.num_layers * self.num_parallels):
core = CORE.lstm_core_with_att(self.input_size, self.rnn_size)
self.cores.append(core)
# attention
self.attens = nn.ModuleList()
for i in range(self.num_layers):
att = ATT.lstm_att_with_att_h(self.rnn_size, self.att_size)
self.attens.append(att)
# proj
self.proj = nn.Linear(self.rnn_size, self.output_size)
# proj weight
self.proj_weight = nn.Linear(self.rnn_size, self.output_size)
init.xavier_normal(self.proj.weight)
init.xavier_normal(self.proj_weight.weight)
def __init__(self, input_size, output_size, num_layers, num_parallels,
rnn_size, att_size, bu_size, bu_num, dropout):
super(LSTM_WITH_TOP_DOWN_ATTEN, self).__init__()
self.input_size = input_size
self.output_size = output_size
self.num_layers = num_layers
self.num_parallels = num_parallels
self.rnn_size = rnn_size
self.att_size = att_size
self.bu_size = bu_size
self.bu_num = bu_num
self.dropout = dropout
# core
self.core1 = CORE.lstm_core(self.input_size, self.rnn_size)
self.core2 = CORE.lstm_core_with_att(self.input_size, self.rnn_size)
# bu attention
self.att = ATT.lstm_att_with_att_h(self.rnn_size, self.bu_size)
# proj
self.proj = nn.Linear(self.rnn_size, self.output_size)
init.xavier_normal(self.proj.weight)
def __init__(self, input_size, output_size, num_layers, num_parallels, rnn_size, att_size, num_hop, dropout):
super(LSTM_SOFT_ATT_STACK_PARALLEL_MEMORY, self).__init__()
self.input_size = input_size
self.output_size = output_size
self.num_layers = num_layers
self.num_parallels = num_parallels
self.rnn_size = rnn_size
self.att_size = att_size
self.dropout = dropout
self.num_hop = num_hop
# core
self.cores = nn.ModuleList()
for i in range(self.num_layers * self.num_parallels):
core = CORE.lstm_core_with_att(self.input_size, self.rnn_size)
self.cores.append(core)
# attention
self.attens = nn.ModuleList()
for i in range(self.num_layers):
att = ATT.lstm_att_with_att_h(self.rnn_size, self.att_size)
self.attens.append(att)
# proj
# self.proj = nn.Linear(self.rnn_size, self.output_size)
# memory
self.memory = DMN.DMNCPlus(self.rnn_size, self.output_size, self.num_hop)
def __init__(self, input_size, output_size, num_layers, num_parallels,
rnn_size, att_size, pool_size, spp_num, dropout):
super(LSTM_SOFT_ATT_STACK_PARALLEL_SPP, self).__init__()
self.input_size = input_size
self.output_size = output_size
self.num_layers = num_layers
self.num_parallels = num_parallels
self.rnn_size = rnn_size
self.att_size = att_size
self.pool_size = pool_size
self.spp_num = spp_num
self.dropout = dropout
# core
self.cores = nn.ModuleList()
for i in range(self.num_layers * self.num_parallels):
core = CORE.lstm_core_with_att(self.input_size, self.rnn_size)
self.cores.append(core)
# attention
self.attens = nn.ModuleList()
for i in range(self.num_layers):
att = ATT.lstm_att_with_att_h_spp(self.rnn_size, self.att_size,
self.pool_size, self.spp_num)
self.attens.append(att)
# proj
self.proj = nn.Linear(self.rnn_size, self.output_size)
def temps(motor): audios=["audio1sE.wav","audio1s.wav"] if motor=='Google': a='Google\n' for f in range(2): if f==0: lan="en-US" else: lan="es-US" resposta=GoogleAPI.response_time(lan,audios[f]) a=a+'\n'+str(resposta) return a elif motor=='ATT': a='\n\nAT&T\n' for f in range(2): if f==0: lan="en-US" else: lan="es-US" resposta=ATT.response_time(lan,audios[f]) a=a+'\n'+str(resposta) return a elif motor=='Witai': a='\n\nWit.ai\n' for f in range(2): if f==0: lan="en-US" else: lan="es-US" resposta=witai.response_time(lan,audios[f]) a=a+'\n'+str(resposta) return a