tyo-yo / seqgan Goto Github PK

Hello,
I tried to run the main notebook but while running this cell:

trainer = Trainer(B, T, g_E, g_H, d_E, d_filter_sizes, d_num_filters, d_dropout,d_lr=d_lr, n_sample=n_sample, generate_samples=generate_samples)

I am getting this error:

`TypeError Traceback (most recent call last)
in
----> 1 trainer = Trainer(B, T, g_E, g_H, d_E, d_filter_sizes, d_num_filters, d_dropout,d_lr=d_lr, n_sample=n_sample, generate_samples=generate_samples)

F:\seqGAN\SeqGAN-keras\SeqGAN\train.py in init(self, B, T, g_E, g_H, d_E, d_H, d_dropout, g_lr, d_lr, n_sample, generate_samples, init_eps)
43 print(self.V, d_E, d_H, d_dropout)
44
---> 45 self.discriminator = Discriminator(self.V, d_E, d_H, d_dropout)
46 self.env = Environment(self.discriminator, self.g_data, self.g_beta, n_sample=n_sample)
47

F:\seqGAN\SeqGAN-keras\SeqGAN\models.py in Discriminator(V, E, H, dropout)
279 embedding_out = K.reshape(out, [32, 25, E])
280 print(E)
--> 281 out = LSTM(H)(embedding_out, return_sequences=True, input_shape=(32, 25, E))
282 out = Highway(out, num_layers=1)
283 out = Dropout(dropout, name='Dropout')(out)

~\Anaconda3\lib\site-packages\keras\layers\recurrent.py in call(self, inputs, initial_state, constants, **kwargs)
498
499 if initial_state is None and constants is None:
--> 500 return super(RNN, self).call(inputs, **kwargs)
501
502 # If any of initial_state or constants are specified and are Keras

~\Anaconda3\lib\site-packages\keras\engine\base_layer.py in call(self, inputs, **kwargs)
429 'You can build it manually via: '
430 'layer.build(batch_input_shape)')
--> 431 self.build(unpack_singleton(input_shapes))
432 self.built = True
433

~\Anaconda3\lib\site-packages\keras\layers\recurrent.py in build(self, input_shape)
459 self.cell.build([step_input_shape] + constants_shape)
460 else:
--> 461 self.cell.build(step_input_shape)
462
463 # set or validate state_spec

~\Anaconda3\lib\site-packages\keras\layers\recurrent.py in build(self, input_shape)
1797 initializer=self.kernel_initializer,
1798 regularizer=self.kernel_regularizer,
-> 1799 constraint=self.kernel_constraint)
1800 self.recurrent_kernel = self.add_weight(
1801 shape=(self.units, self.units * 4),

~\Anaconda3\lib\site-packages\keras\legacy\interfaces.py in wrapper(*args, **kwargs)
89 warnings.warn('Update your ' + object_name + 90 ' call to the Keras 2 API: ' + signature, stacklevel=2)
---> 91 return func(*args, **kwargs)
92 wrapper._original_function = func
93 return wrapper

~\Anaconda3\lib\site-packages\keras\engine\base_layer.py in add_weight(self, name, shape, dtype, initializer, regularizer, trainable, constraint)
247 if dtype is None:
248 dtype = K.floatx()
--> 249 weight = K.variable(initializer(shape),
250 dtype=dtype,
251 name=name,

~\Anaconda3\lib\site-packages\keras\initializers.py in call(self, shape, dtype)
207 scale /= max(1., fan_out)
208 else:
--> 209 scale /= max(1., float(fan_in + fan_out) / 2)
210 if self.distribution == 'normal':
211 # 0.879... = scipy.stats.truncnorm.std(a=-2, b=2, loc=0., scale=1.)

TypeError: unsupported operand type(s) for +: 'int' and 'list'
`
What should I do?

I have a set of 1D wave signals, and I'd like to generate more by SeqGAN, it is possible? If so, how to set the input (just numbers)?