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[Solved] Is it right to normalize test dataset with the mean value of the test dataset itself!
Line 89 in 3a51d5b
Basically, the test dataset should be normalized with the mean value of the training dataset, not the test dataset itself.
error with the new tensorflow
When you try to run the code with the latest version of tensorflow (1.14) you'll have this error :
File "cnn_uci.py", line 127, in
h_hidden = tf.concat(1, [h_flat, h_feat])
...
It happens line 127 for the cnn_uci.py and line 139 for the cnn_wisdm.py
To solve it you just have to interchange the 1 and the [h_flat, h_feat], so you have to write this :
h_hidden = tf.concat([h_flat, h_feat],1)
this problem is due to the new tensorflow's API.
Extract_basic_features.m some puzzlement
In this MATLAB function, the input variable x is always 1 by 128 thus n is identical to 1. As a sequence,
hist(x,10)/n == hist(x,10), leading to nondistinctive feature extraction for different segment size(I guess that's what u want to do).
Thx for your open source code. @aiff22
error running cnn_uci.py
/> python cnn_uci.py
/home/rjpg/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
from ._conv import register_converters as _register_converters
Loading UCI dataset...
Dataset was uploaded
Creating CNN architecture
Traceback (most recent call last):
File "cnn_uci.py", line 127, in <module>
h_hidden = tf.concat(1, [h_flat, h_feat])
File "/home/rjpg/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 1110, in concat
dtype=dtypes.int32).get_shape().assert_is_compatible_with(
File "/home/rjpg/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1011, in convert_to_tensor
as_ref=False)
File "/home/rjpg/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1107, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/home/rjpg/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 217, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "/home/rjpg/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 196, in constant
value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "/home/rjpg/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py", line 436, in make_tensor_proto
_AssertCompatible(values, dtype)
File "/home/rjpg/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py", line 347, in _AssertCompatible
(dtype.name, repr(mismatch), type(mismatch).__name__))
TypeError: Expected int32, got list containing Tensors of type '_Message' instead.
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