deep-learning-with-python-notebooks
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Error with 2.1
Following along with the example in 2.1 when I run
network <- keras_model_sequential() %>%
layer_dense(units = 512, activation = "relu", input_shape = c(28 * 28)) %>%
layer_dense(units = 10, activation = "softmax")
I get the following error:
Error in py_call_impl(callable, dots$args, dots$keywords) :
AttributeError: 'Sequential' object has no attribute 'get_shape'
Detailed traceback:
File "/home/cdsw/.local/lib/python2.7/site-packages/tensorflow/python/keras/_impl/keras/engine/base_layer.py", line 239, in __call__
output = super(Layer, self).__call__(inputs, **kwargs)
File "/home/cdsw/.local/lib/python2.7/site-packages/tensorflow/python/layers/base.py", line 689, in __call__
self._assert_input_compatibility(inputs)
File "/home/cdsw/.local/lib/python2.7/site-packages/tensorflow/python/layers/base.py", line 1183, in _assert_input_compatibility
if x.get_shape().ndims is None:
I had an issue with the second line there but my error was different : 'SyntaxError: positional argument follows keyword argument...'.
I edited the line to: network.add(layers.Dense(512, input_shape=(28*28,), activation='relu')). After this, the code worked without errors. I hope this helps.