> = 80之后，张量形状变为（？，）。这导致boolean_mask出错。以下代码用于过滤掉80％以上的精度。
outputs, final_state = tf.contrib.rnn.static_rnn(cell, lstm_in, dtype=tf.float32,
initial_state = initial_state)
logits = tf.layers.dense(outputs[-1], n_classes, name='logits')
np_logits_b = tf.reduce_max(outputs[-1], axis=1) >= 80
labels_filtered = tf.boolean_mask(labels_, np_logits_b)
<ipython-input-13-2615e31971df> in <module>()
23 # Accuracy on >80%
24 np_logits_b = tf.reduce_max(logits, axis=1) >= 80
---> 25 labels_filtered = tf.boolean_mask(labels_, np_logits_b)
26 correct_pred_filtered = tf.equal(tf.argmax(logits_filtered, 1), tf.argmax(labels_filtered, 1))
27 accuracy_filtered = tf.reduce_mean(tf.cast(correct_pred_filtered, tf.float32), name='accuracy_filtered')
~\Anaconda3\lib\site-packages\tensorflow\python\ops\array_ops.py in boolean_mask(tensor, mask, name)
1119 if ndims_mask is None:
1120 raise ValueError(
-> 1121 "Number of mask dimensions must be specified, even if some dimensions"
1122 " are None. E.g. shape=[None] is ok, but shape=None is not.")
1123 shape_tensor[:ndims_mask].assert_is_compatible_with(shape_mask)
ValueError: Number of mask dimensions must be specified, even if some dimensions are None. E.g. shape=[None] is ok, but shape=None is not.
print(tf.shape(np_logits_b))
Tensor("Shape_4:0", shape=(?,), dtype=int32)