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TypeError: kernel_initializer keyword not understood when building a dense layer.

1

Here is the output: Using MXNet backend. Traceback (most recent call last): File "run.py", line 128, in model = Model(config_args['alpha'], config_args['gamma'], config_args['input_size'], config_args['hidden_size']) File "/tmp/Model.py", line 37, in __init__ kernel_initializer='glorot_normal'))...

decisivesacha

add mxnet module extraction support

1

resolves #85

joeddav

Merge this branch with Keras 2.0

15

Hi, Wanted to ask what are the plans to pull in Keras 2.0 as there have been interface level changes from 1.2.2. Rahul

rravu3

``` model.add(Embedding(max_features, embedding_dims, input_length=maxlen, dropout=0.2)) ``` This line throws this exception: ``` train_ret = func(*args, **kwargs) File "env\lib\site-packages\keras\backend\mxnet_backend.py", line 3007, in random_binomial raise NotImplementedError NotImplementedError ```

zsong

self.mod_ids = Lambda(lambda sent: sent % (nr_tune-1)+1, output_shape=(self.max_length,)) Returns an error saying - TypeError: unsupported operand type(s) for %: 'KerasSymbol' and 'int'

dmadeka

The line: LSTM (1000,activation = 'tanh',return_sequences = True)(ht) produces a strange error for me: /usr/local/lib/python3.5/dist-packages/keras/layers/recurrent.py in get_initial_states(self, x) 202 def get_initial_states(self, x): 203 # build an all-zero tensor of shape...

dmadeka

Prediction incorrect when load saved model

2

Hi, Now I am using Keras 1.2.2 with mxnet backend on ResNet50. I observed a very weird phenomenon: If we use **mxnet** as backend, when we finish training and save...

MaJieCornell

This prevents the unfortunate scenario in which layer.set_weights() is called before training on some or all layers in a model, and then the model is trained and saved. When the...

jricheimer

errors while call the keras.applications.inception_v3

2

I turn my keras backend from tensorflow to mxnet to use mxnet's multi gpu training. However the code I run successfully in keras tensorflow backend seems not compatible with keras...

heroxrq

fixes #82

rajendra2