Input array dimensions not matching

I am trying to run PredNet using the pre-processed data and the pretrained model, nothing modified in the code. (Unrelated: It would be nice to indicate somewhere that your model doesn’t support Python 3! Or maybe it was written and I missed it?)

For

python kitti_evaluate.py

I get the following error:

Using Theano backend.
Traceback (most recent call last):
  File "kitti_evaluate.py", line 52, in <module>
    X_hat = test_model.predict(X_test, batch_size)
  File "//anaconda/lib/python2.7/site-packages/keras/engine/training.py", line 1197, in predict
    batch_size=batch_size, verbose=verbose)
  File "//anaconda/lib/python2.7/site-packages/keras/engine/training.py", line 896, in _predict_loop
    batch_outs = f(ins_batch)
  File "//anaconda/lib/python2.7/site-packages/keras/backend/theano_backend.py", line 792, in __call__
    return self.function(*inputs)
  File "//anaconda/lib/python2.7/site-packages/theano/compile/function_module.py", line 871, in __call__
    storage_map=getattr(self.fn, 'storage_map', None))
  File "//anaconda/lib/python2.7/site-packages/theano/gof/link.py", line 314, in raise_with_op
    reraise(exc_type, exc_value, exc_trace)
  File "//anaconda/lib/python2.7/site-packages/theano/compile/function_module.py", line 859, in __call__
    outputs = self.fn()
  File "//anaconda/lib/python2.7/site-packages/theano/scan_module/scan_op.py", line 951, in rval
    r = p(n, [x[0] for x in i], o)
  File "//anaconda/lib/python2.7/site-packages/theano/scan_module/scan_op.py", line 940, in <lambda>
    self, node)
  File "theano/scan_module/scan_perform.pyx", line 405, in theano.scan_module.scan_perform.perform (/Users/lana/.theano/compiledir_Darwin-15.6.0-x86_64-i386-64bit-i386-2.7.10-64/scan_perform/mod.cpp:4316)
  File "//anaconda/lib/python2.7/site-packages/theano/gof/link.py", line 314, in raise_with_op
    reraise(exc_type, exc_value, exc_trace)
  File "theano/scan_module/scan_perform.pyx", line 397, in theano.scan_module.scan_perform.perform (/Users/lana/.theano/compiledir_Darwin-15.6.0-x86_64-i386-64bit-i386-2.7.10-64/scan_perform/mod.cpp:4193)
ValueError: all the input array dimensions except for the concatenation axis must match exactly
Apply node that caused the error: Join(TensorConstant{1}, <TensorType(float32, 4D)>, <TensorType(float32, 4D)>, Reshape{4}.0)
Toposort index: 61
Inputs types: [TensorType(int8, scalar), TensorType(float32, 4D), TensorType(float32, 4D), TensorType(float32, 4D)]
Inputs shapes: [(), (10, 96, 32, 40), (10, 192, 32, 40), (10, 384, 32, 20)]
Inputs strides: [(), (491520, 5120, 160, 4), (983040, 5120, 160, 4), (983040, 2560, 80, 4)]
Inputs values: [array(1, dtype=int8), 'not shown', 'not shown', 'not shown']
Outputs clients: [[CorrMM{half, (1, 1)}(Join.0, Subtensor{::, ::, ::int64, ::int64}.0), CorrMM{half, (1, 1)}(Join.0, Subtensor{::, ::, ::int64, ::int64}.0), CorrMM{half, (1, 1)}(Join.0, Subtensor{::, ::, ::int64, ::int64}.0), CorrMM{half, (1, 1)}(Join.0, Subtensor{::, ::, ::int64, ::int64}.0)]]

[LanaSina]

There is a default setting in the keras.json file in .keras mine had as default

“image_dim_ordering”: “tf”,

I just changed it back to th. Everything works now. In the end @bill-lotter 's 1st message was very close to the issue - it wasn’t K.dim_ordering or the backend setting itself, but image_dim_ordering. I will mark the issue as closed.

[bill-lotter]

Sorry about this, I tried to make it compatible with both dimension orderings (e.g. https://github.com/coxlab/prednet/blob/master/data_utils.py#L22), but guess it didn’t work. I’ll work to make it compatible for both.