lambdawx / cnn_sentence_tensorflow Goto Github PK

分词之后 获取数据为空 这是为什么

在用cnn训练之前，我用gensim训练好了一份bin的词向量文件，现在想要加载进去作为静态通道，怎么做？是用 load_bin_vec函数进行加载吗？

请问CNN训练时的测试集和训练集是怎么划分的呀，还有训练的终止条件是什么呢，会最终运行多少步？求解答

里面定义了许多的函数，但是注解很少，有一些不太明白意图，能解释一下函数的作用和要实现的目的吗？

您好，
我在使用您提供的代码，在v1.1.0的tf上训练文本分类模型，遇到如下错误：
Traceback (most recent call last):
File "sentence_classfier_with_tensorflow.py", line 236, in
_, step, summaries = sess.run([train_step, global_step, train_summary_op],feed_dict)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 778, in run
run_metadata_ptr)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 982, in _run
feed_dict_string, options, run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1032, in _do_run
target_list, options, run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1052, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: <exception str() failed>
请问一下这是什么情况呢？

运行第三个文件时报错

2017-08-14 10:35:25.884469: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2017-08-14 10:35:25.884480: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-08-14 10:35:25.884488: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-08-14 10:35:25.884495: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Traceback (most recent call last):
File "sentence_classfier_with_tensorflow.py", line 154, in
h_pool = tf.concat(3, h_pool_output)
File "/usr/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.py", line 1043, in concat
dtype=dtypes.int32).get_shape(
File "/usr/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 676, in convert_to_tensor
as_ref=False)
File "/usr/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 741, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/usr/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 113, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "/usr/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 102, in constant
tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "/usr/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 374, in make_tensor_proto
_AssertCompatible(values, dtype)
File "/usr/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 302, in _AssertCompatible
(dtype.name, repr(mismatch), type(mismatch).name))
TypeError: Expected int32, got list containing Tensors of type '_Message' instead.

这是什么原因？？

您好！我训练好模型后，拿来一个文本怎么测试呢？小白一枚，您能git个demo吗？