Comments (1)
it can be fix by
--- a/MLE_SeqGAN/model.py
+++ b/MLE_SeqGAN/model.py
@@ -59,7 +59,7 @@ class LSTM(object):
gen_x = gen_x.write(i, next_token) # indices, batch_size
return i + 1, x_tp1, h_t, gen_o, gen_x
-
_, _, _, self.gen_o, self.gen_x = control_flow_ops.While(
-
_, _, _, self.gen_o, self.gen_x = tf.while_loop( cond=lambda i, _1, _2, _3, _4: i < self.sequence_length, body=_g_recurrence, loop_vars=(tf.constant(0, dtype=tf.int32),
@@ -84,7 +84,7 @@ class LSTM(object):
x_tp1 = ta_emb_x.read(i)
return i + 1, x_tp1, h_t, g_predictions
-
_, _, _, self.g_predictions = control_flow_ops.While(
-
_, _, _, self.g_predictions = tf.while_loop( cond=lambda i, _1, _2, _3: i < self.sequence_length, body=_pretrain_recurrence, loop_vars=(tf.constant(0, dtype=tf.int32),
from seqgan.
Related Issues (20)
- About the sequences to process
- 模型问题
- the input data?
- Training on custom dataset HOT 1
- 关于采样的问题
- What is the difference between SeqGAN and LM for text generation? HOT 1
- Nothing. Ignore it.
- About dataset. HOT 1
- About oracle model
- If the positive sample and negative sample of each training are corresponding, will it affect the training result
- gradient decent implementation
- About generator in adversarial training HOT 2
- How should I understand the RL loss function
- data format
- About the accuracy of discriminator during training?
- NLG
- dataset HOT 1
- How can i use my own training data ? HOT 2
- How to resume training in Colab?
- Questions about the recurring results of the code HOT 1
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from seqgan.