tf.nn.dynamic_rnn已尝试使用未初始化的值错误

Question

我的graph看起来像这样

with graph.as_default():

    train_inputs = tf.placeholder(tf.int32, shape=[None, None])

    with tf.device('/cpu:0'):
        embeddings = tf.Variable(tf.zeros([vocab_size, options.embed_size]))

        restorer = tf.train.Saver({'embeddings': embeddings})

        init = tf.variables_initializer([embeddings])

        uninit = tf.report_uninitialized_variables()

        embed = tf.nn.embedding_lookup(embeddings, train_inputs)

        # length() returns a [batch_szie,] tensor of true lengths of sentences (lengths before zero-padding)
        sequence_length = length(embed)

        lstm = tf.nn.rnn_cell.LSTMCell(options.rnn_size)

        output, _ = tf.nn.dynamic_rnn(
            lstm,
            embed,
            dtype=tf.float32,
            swequence_length=sequence_length
        )

我的session：

with tf.Session(graph=graph) as session:

    restorer.restore(session, options.restore_path)
    # tf.global_variables_initializer.run()
    init.run()

    print session.run([uninit])

    while len(data.ids):
        # data.generate_batch returns a list of size [batch_size, max_length], and zero-padding is used, when the sentences are shorter than max_length. For example, batch_inputs = [[1,2,3,4], [3,2,1,0], [1,2,0,0]]
        batch_inputs, _ = data.generate_batch(options.batch_size)
        feed_dict = {train_inputs: batch_inputs}

        test = session.run([tf.shape(output)], feed_dict=feed_dict)

        print test

功能length()：

def length(self, sequence):
        length = tf.sign(sequence)
        length = tf.reduce_sum(length, reduction_indices=1)
        length = tf.cast(length, tf.int32)
        return length

我得到的错误：

Traceback (most recent call last):
  File "rnn.py", line 103, in <module>
    test = session.run([tf.shape(output)], feed_dict=feed_dict)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 766, in run
    run_metadata_ptr)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 964, in _run
    feed_dict_string, options, run_metadata)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1014, in _do_run
    target_list, options, run_metadata)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1034, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Attempting to use uninitialized value RNN/LSTMCell/W_0
         [[Node: RNN/LSTMCell/W_0/read = Identity[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](RNN/LSTMCell/W_0)]]

Caused by op u'RNN/LSTMCell/W_0/read', defined at:
  File "rnn.py", line 75, in <module>
    sequence_length=sequence_length,
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn.py", line 845, in dynamic_rnn
    dtype=dtype)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn.py", line 1012, in _dynamic_rnn_loop
    swap_memory=swap_memory)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/control_flow_ops.py", line 2636, in while_loop
    result = context.BuildLoop(cond, body, loop_vars, shape_invariants)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/control_flow_ops.py", line 2469, in BuildLoop
    pred, body, original_loop_vars, loop_vars, shape_invariants)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/control_flow_ops.py", line 2419, in _BuildLoop
    body_result = body(*packed_vars_for_body)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn.py", line 995, in _time_step
    skip_conditionals=True)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn.py", line 403, in _rnn_step
    new_output, new_state = call_cell()
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn.py", line 983, in <lambda>
    call_cell = lambda: cell(input_t, state)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn_cell.py", line 496, in __call__
    dtype, self._num_unit_shards)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn_cell.py", line 329, in _get_concat_variable
    sharded_variable = _get_sharded_variable(name, shape, dtype, num_shards)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn_cell.py", line 359, in _get_sharded_variable
    dtype=dtype))
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.py", line 1024, in get_variable
    custom_getter=custom_getter)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.py", line 850, in get_variable
    custom_getter=custom_getter)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.py", line 346, in get_variable
    validate_shape=validate_shape)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.py", line 331, in _true_getter
    caching_device=caching_device, validate_shape=validate_shape)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.py", line 677, in _get_single_variable
    expected_shape=shape)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variables.py", line 224, in __init__
    expected_shape=expected_shape)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variables.py", line 367, in _init_from_args
    self._snapshot = array_ops.identity(self._variable, name="read")
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 1424, in identity
    result = _op_def_lib.apply_op("Identity", input=input, name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 759, in apply_op
    op_def=op_def)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2240, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1128, in __init__
    self._traceback = _extract_stack()

FailedPreconditionError (see above for traceback): Attempting to use uninitialized value RNN/LSTMCell/W_0
         [[Node: RNN/LSTMCell/W_0/read = Identity[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](RNN/LSTMCell/W_0)]]

然而，当我打印出未初始化的变量时，我得到了[array([], dtype=object)]

当我用init.run()替换tf.global_variables_initializer.run()时，它有效。

知道为什么init.run()不起作用？

Answer 1

您定义init如下：

init = tf.variables_initializer([embeddings])

此定义表示init仅初始化embeddings变量。调用tf.nn.dynamic_rnn()函数会创建更多变量，表示LSTM中的各种内部权重，而这些变量不会由init初始化。

相比之下，tf.global_variables_initializer()返回一个操作，该操作在运行时将初始化模型中的所有（全局）变量，包括为LSTM创建的变量。