变量clash inTensorFlow

Question

所以我有一个和this问题一样的问题。只是我找不到哪个名字在冲突。你能指出变量名称冲突的确切位置吗?我已经尝试了很多，但都没有用。或者，您可以提出一些方法来找出错误点。下面是我的TensorFlow代码：

​

def convolutionForwardPropagation(features, labels, mode, params):
    img = features['x']
    
    c1 = tf.layers.conv2d(img, filters = 32, kernel_size = [1,3], padding = 'VALID', activation = tf.nn.relu, kernel_regularizer = tf.contrib.layers.l2_regularizer(20.0))
    c2 = tf.layers.conv2d(c1, filters = 64, kernel_size = [1,3], padding = 'VALID', activation = tf.nn.relu, kernel_regularizer = tf.contrib.layers.l2_regularizer(20.0))
    
    c3 = tf.layers.conv2d(c2, filters = 64, kernel_size = [1,3], padding = 'VALID', activation = tf.nn.relu, kernel_regularizer = tf.contrib.layers.l2_regularizer(20.0))
    c4 = tf.layers.conv2d(c3, filters = 64, kernel_size = [1,3], padding = 'VALID', activation = tf.nn.relu, kernel_regularizer = tf.contrib.layers.l2_regularizer(20.0))
        
    c5 = tf.layers.conv2d(c4, filters = 128, kernel_size = [1,3], padding = 'VALID', activation = tf.nn.relu, kernel_regularizer = tf.contrib.layers.l2_regularizer(20.0))
    
    shape1 = c5.get_shape().as_list()
    fr = tf.reshape(c5, shape = (-1, shape1[3] * shape1[2]))
    
    fc1 = tf.contrib.layers.fully_connected(fr, 20, activation_fn = tf.nn.relu, weights_regularizer = tf.contrib.layers.l2_regularizer(500.0))
    fc2 = tf.contrib.layers.fully_connected(fc1, 2, activation_fn = tf.nn.sigmoid, weights_regularizer = tf.contrib.layers.l2_regularizer(500.0))

    entropy = tf.nn.softmax_cross_entropy_with_logits_v2(logits = fc2, labels = labels, name = 'cross_entropy')
    loss = tf.reduce_mean(entropy, name = 'loss')

    optimizer = tf.train.AdamOptimizer(params)

    hypothesis = tf.nn.softmax(fc2)
    y_pred_class = tf.argmax(hypothesis, axis = 1)
    sparseLabels = tf.argmax(labels, axis = 1)
    
    
    if(mode == tf.estimator.ModeKeys.PREDICT):
        spec = tf.estimator.EstimatorSpec(mode = mode, predictions = y_pred_class)
        return spec
        
    elif(mode == tf.estimator.ModeKeys.TRAIN):
        train_op = optimizer.minimize(loss = loss)
        metrics = {'accuracy':tf.metrics.accuracy(labels = sparseLabels, predictions = y_pred_class)}
        spec = tf.estimator.EstimatorSpec(mode = mode, predictions = y_pred_class, loss = loss, train_op = train_op, eval_metric_ops = metrics)
        return spec
    
    elif(mode == tf.estimator.ModeKeys.EVAL):
        metrics = {'accuracy':tf.metrics.accuracy(labels = sparseLabels, predictions = y_pred_class)}
        spec = tf.estimator.EstimatorSpec(mode = mode, predictions = y_pred_class, loss = loss, eval_metric_ops = metrics)
        return spec



train_input_fn = tf.estimator.inputs.numpy_input_fn(x = {'x':testDataset}, y = labelsTest, batch_size = 350, num_epochs = 20, shuffle = False)
eval_input_fn = tf.estimator.inputs.numpy_input_fn(x = {'x':CVDataset}, y = labelsCV, batch_size = 200, num_epochs = 1, shuffle = False)
model = tf.estimator.Estimator(model_fn = convolutionForwardPropagation, params = learning_rate, model_dir = './checpoints/CNN')
k = model.train(input_fn = train_input_fn, steps = 1)

writer = tf.summary.FileWriter('./graphs/logreg', tf.get_default_graph())
with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())
    sess.run([train_input_fn, eval_input_fn])
    sess.run([model, k])
writer.close()

​

下面是我的错误消息：

​

Traceback (most recent call last):

  File "<ipython-input-36-08caa0f29863>", line 1, in <module>
    runfile('/home/abhigyan/Programming_Projects/Python_Projects/tensorflow_env/Programs/tfCNN3.py', wdir='/home/abhigyan/Programming_Projects/Python_Projects/tensorflow_env/Programs')

  File "/home/abhigyan/.local/lib/python3.5/site-packages/spyder/utils/site/sitecustomize.py", line 705, in runfile
    execfile(filename, namespace)

  File "/home/abhigyan/.local/lib/python3.5/site-packages/spyder/utils/site/sitecustomize.py", line 102, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)

  File "/home/abhigyan/Programming_Projects/Python_Projects/tensorflow_env/Programs/tfCNN3.py", line 222, in <module>
    sess.run([train_input_fn, eval_input_fn])

  File "/home/abhigyan/.local/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 900, in run
    run_metadata_ptr)

  File "/home/abhigyan/.local/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1120, in _run
    self._graph, fetches, feed_dict_tensor, feed_handles=feed_handles)

  File "/home/abhigyan/.local/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 427, in __init__
    self._fetch_mapper = _FetchMapper.for_fetch(fetches)

  File "/home/abhigyan/.local/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 245, in for_fetch
    return _ListFetchMapper(fetch)

  File "/home/abhigyan/.local/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 352, in __init__
    self._mappers = [_FetchMapper.for_fetch(fetch) for fetch in fetches]

  File "/home/abhigyan/.local/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 352, in <listcomp>
    self._mappers = [_FetchMapper.for_fetch(fetch) for fetch in fetches]

  File "/home/abhigyan/.local/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 253, in for_fetch
    return _ElementFetchMapper(fetches, contraction_fn)

  File "/home/abhigyan/.local/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 286, in __init__
    (fetch, type(fetch), str(e)))

TypeError: Fetch argument <function numpy_input_fn.<locals>.input_fn at 0x7f52300b2510> has invalid type <class 'function'>, must be a string or Tensor. (Can not convert a function into a Tensor or Operation.)

​