title: I can't load my trained h5 model with load.models(), how do I fix this error?
body: <p>So I think tensorflow.keras and the independant keras packages are in conflict and I can't load my model, which I have made with transfer learning.
  Import in the CNN ipynb:</p>
  
  <pre><code>!pip install tensorflow-gpu==2.0.0b1
  
  import tensorflow as tf
  from tensorflow import keras
  print(tf.__version__) 
  </code></pre>
  
  <p>Loading this pretrained model</p>
  
  <pre><code>base_model = keras.applications.xception.Xception(weights="imagenet",
                                                include_top=False)
  avg = keras.layers.GlobalAveragePooling2D()(base_model.output)
  output = keras.layers.Dense(n_classes, activation="softmax")(avg)
  model = keras.models.Model(inputs=base_model.input, outputs=output)
  </code></pre>
  
  <p>Saving with:</p>
  
  <pre><code>model.save('Leavesnet Model 2.h5')
  </code></pre>
  
  <p>Then in the new ipynb for the already trained model (the imports are the same as in the CNN ipynb:</p>
  
  <pre><code>from keras.models import load_model
  
  model =load_model('Leavesnet Model.h5')
  </code></pre>
  
  <p>I get the error: </p>
  
  <pre><code>AttributeError                            Traceback (most recent call last)
  &lt;ipython-input-4-77ca5a1f5f24&gt; in &lt;module&gt;()
        2 from keras.models import load_model
        3 
  ----&gt; 4 model =load_model('Leavesnet Model.h5')
  
  13 frames
  /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py in placeholder(shape, ndim, dtype, sparse, name)
      539         x = tf.sparse_placeholder(dtype, shape=shape, name=name)
      540     else:
  --&gt; 541         x = tf.placeholder(dtype, shape=shape, name=name)
      542     x._keras_shape = shape
      543     x._uses_learning_phase = False
  
  AttributeError: module 'tensorflow' has no attribute 'placeholder' 
  
  </code></pre>
  
  <p>I think there might be a conflict between tf.keras and the independant keras, can someone help me out?</p>