fix bug and remove f strings

2075 · Feb 14, 2019 · 7cdac14 · 7cdac14
1 parent e33295b
commit 7cdac14
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Showing 2 changed files with 9 additions and 6 deletions.
diff --git a/src/generate_unconditional_samples.py b/src/generate_unconditional_samples.py
@@ -28,7 +28,7 @@ def sample_model(
     if length is None:
         length = hparams.n_ctx
     elif length > hparams.n_ctx:
-        raise ValueError(f"can't get samples longer than window size: {hparams.n_ctx}")
+        raise ValueError("Can't get samples longer than window size: %s" % hparams.n_ctx)
 
     with tf.Session(graph=tf.Graph()) as sess:
         output = sample.sample_sequence(
@@ -49,7 +49,7 @@ def sample_model(
                 generated += batch_size
                 text = enc.decode(out[i])
                 print("=" * 40 + " SAMPLE " + str(generated) + " " + "=" * 40)
-                print(f"{text}")
+                print(text)
 
 if __name__ == '__main__':
     fire.Fire(sample_model)

diff --git a/src/interactive_conditional_samples.py b/src/interactive_conditional_samples.py
@@ -31,7 +31,7 @@ def interact_model(
     if length is None:
         length = hparams.n_ctx // 2
     elif length > hparams.n_ctx:
-        raise ValueError(f"can't get samples longer than window size: {hparams.n_ctx}")
+        raise ValueError("Can't get samples longer than window size: %s" % hparams.n_ctx)
 
     with tf.Session(graph=tf.Graph()) as sess:
         context = tf.placeholder(tf.int32, [batch_size, None])
@@ -40,25 +40,28 @@ def interact_model(
             context=context,
             batch_size=batch_size,
             temperature=temperature, top_k=top_k
-        )[:, 1:]
+        )
 
         saver = tf.train.Saver()
         ckpt = tf.train.latest_checkpoint(os.path.join('models', model_name))
         saver.restore(sess, ckpt)
 
         while True:
             raw_text = input("Model prompt >>> ")
+            while not raw_text:
+                print('Prompt should not be empty!')
+                raw_text = input("Model prompt >>> ")
             context_tokens = enc.encode(raw_text)
             generated = 0
             for _ in range(nsamples // batch_size):
                 out = sess.run(output, feed_dict={
                     context: [context_tokens for _ in range(batch_size)]
-                })
+                })[:, len(context_tokens):]
                 for i in range(batch_size):
                     generated += 1
                     text = enc.decode(out[i])
                     print("=" * 40 + " SAMPLE " + str(generated) + " " + "=" * 40)
-                    print(f"{text}")
+                    print(text)
             print("=" * 80)
 
 if __name__ == '__main__':