AttributeError: у объекта 'int' нет атрибута 'value' - PullRequest
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AttributeError: у объекта 'int' нет атрибута 'value'

0 голосов
/ 10 октября 2019

Я не могу обернуть голову вокруг этой проблемы, которую я получаю здесь. Я работаю на Tensorflow 2, и я действительно не понимаю, почему эта ошибка появляется. Что-то мне не хватает?

Это соответствующая часть кода, где появляется ошибка: 

from tensorflow.lite.experimental.examples.lstm.rnn import bidirectional_dynamic_rnn
from tensorflow.lite.experimental.examples.lstm.rnn_cell import TFLiteLSTMCell

...

lstm_cells = []
lstm_0 = TFLiteLSTMCell(num_units=256, forget_bias=0, name='rnn_0')
lstm_1 = TFLiteLSTMCell(num_units=256, forget_bias=0, name='rnn_1')
lstm_2 = TFLiteLSTMCell(num_units=128, forget_bias=0, name='rnn_2')
lstm_3 = TFLiteLSTMCell(num_units=128, forget_bias=0, name='rnn_3')

lstm_cells.append(lstm_0)
lstm_cells.append(lstm_1)
lstm_cells.append(lstm_2)
lstm_cells.append(lstm_3)

bi_LSTM_2 = layers.Lambda(buildLstmLayer, arguments={'layers' : lstm_cells})(fc_1)

...

Это соответствующий лямбда-слой. Я создаю двунаправленные RNN, но я думаю, что ошибка больше связана с самим TFLiteLSTMCell, но я думаю, что я использую его правильно. 

def buildLstmLayer(inputs, layers):


  inputs = tf.transpose(inputs, [1,0,2])
  # inputs = tf.unstack(inputs, axis=1)

  inter_output, _ = bidirectional_dynamic_rnn (
      layers[0],
      layers[1],
      inputs,
      dtype='float32',
      time_major=True)

  inter_output = tf.concat(inter_output, 2)

  output, _ = bidirectional_dynamic_rnn (
      layers[2],
      layers[3],
      inter_output,
      dtype='float32',
      time_major=True)

  output = tf.concat(output, 2)
  # output = tf.stack(output, axis=1)

  output = tf.transpose(output, [1,0,2])

  return output

Это отслеживание, которое я получаю: 

Traceback (most recent call last):
  File "crnn_architecture.py", line 279, in <module>
    model, base_model = CRNN_model(is_training=True)
  File "crnn_architecture.py", line 108, in CRNN_model
    bi_LSTM_2 = layers.Lambda(buildLstmLayer, arguments={'layers' : lstm_cells})(fc_1)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/engine/base_layer.py", line 847, in __call__
    outputs = call_fn(cast_inputs, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/layers/core.py", line 795, in call
    return self.function(inputs, **arguments)
  File "crnn_architecture.py", line 146, in buildLstmLayer
    time_major=True)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/lite/experimental/examples/lstm/rnn.py", line 379, in bidirectional_dynamic_rnn
    scope=fw_scope)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/lite/experimental/examples/lstm/rnn.py", line 266, in dynamic_rnn
    dtype=dtype)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/rnn.py", line 916, in _dynamic_rnn_loop
    swap_memory=swap_memory)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/control_flow_ops.py", line 2675, in while_loop
    back_prop=back_prop)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/while_v2.py", line 198, in while_loop
    add_control_dependencies=add_control_dependencies)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/func_graph.py", line 915, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/while_v2.py", line 176, in wrapped_body
    outputs = body(*_pack_sequence_as(orig_loop_vars, args))
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/rnn.py", line 884, in _time_step
    (output, new_state) = call_cell()
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/rnn.py", line 870, in <lambda>
    call_cell = lambda: cell(input_t, state)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/engine/base_layer.py", line 847, in __call__
    outputs = call_fn(cast_inputs, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/layers/recurrent.py", line 137, in call
    inputs, states = cell.call(inputs, states, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/lite/experimental/examples/lstm/rnn_cell.py", line 440, in call
    if input_size.value is None:
AttributeError: 'int' object has no attribute 'value'
...