In keras example imdb_lstm.py:
ValueError: Cannot unroll a RNN if the time dimension is undefined
This requires RNN support.
In keras example conv_lstm.py:
mxnet.base.MXNetError: value 0 for Parameter num_outputs should be greater equal to 1, in operator SliceChannel(name="", num_outputs="0", squeeze_axis="1"
This requires implementation of rnn symbolic loop.
In keras example mnist_acgan.py:
Error: SoftmaxCrossEntropy only accept 1D label
In keras example variational_autoencoder_deconv.py:
mxnet.base.MXNetError: Error in operator uniform15: [18:19:01] src/operator/./deconvolution-inl.h:75: Check failed: pad_y >= target_shape[0] (28 vs. 29) too big target shape
This requires support for oversized target_shape.
In keras example imdb_lstm.py: ValueError: Cannot unroll a RNN if the time dimension is undefined This requires RNN support.
In keras example conv_lstm.py: mxnet.base.MXNetError: value 0 for Parameter num_outputs should be greater equal to 1, in operator SliceChannel(name="", num_outputs="0", squeeze_axis="1" This requires implementation of rnn symbolic loop.
In keras example mnist_acgan.py: Error: SoftmaxCrossEntropy only accept 1D label
In keras example variational_autoencoder_deconv.py: mxnet.base.MXNetError: Error in operator uniform15: [18:19:01] src/operator/./deconvolution-inl.h:75: Check failed: pad_y >= target_shape[0] (28 vs. 29) too big target shape This requires support for oversized target_shape.