Creating keys for long tensor in TensorFlow
I'm just a novice in learning tensorflow but encountered a problem.
I want to build a regression model with DNN. In Tensorflow, the dataset input into the tf.estimator.Estimator must be a nested dictionary which contains keys and values. As shown in the given examples, every column of a tensor will be given a key. For example, SepalLength, PetalWidth, PetalLength, SepalWidth are given as keys for the input data in the iris example.
But in my situation, there are 200 input features, and 100 output values. How to create the key for these features? I can create keys by list("feature"+i for i in range(200)). The key will be like "feature0","feature1",... But when I use zip function to pack the input and output like [("feature0": 0.0),("feature1",0.0),...,("output0":0.0),("output1":0.0),...], sequence of the zipped dictionary will change randomly. The final result will be like [("feature90": 0.0),("feature15",0.0),...,("output15":0.0),("output30":0.0),...].
I'm very confused how to create keys for long tensors automatically? Does anyone know how to solve it? Thank you.
python tensorflow dataset
edited Nov 14 '18 at 6:19
Tomothy32
5,7121425
asked Nov 14 '18 at 6:10
ShannonShannon
12
add a comment |
I'm just a novice in learning tensorflow but encountered a problem.
I want to build a regression model with DNN. In Tensorflow, the dataset input into the tf.estimator.Estimator must be a nested dictionary which contains keys and values. As shown in the given examples, every column of a tensor will be given a key. For example, SepalLength, PetalWidth, PetalLength, SepalWidth are given as keys for the input data in the iris example.
But in my situation, there are 200 input features, and 100 output values. How to create the key for these features? I can create keys by list("feature"+i for i in range(200)). The key will be like "feature0","feature1",... But when I use zip function to pack the input and output like [("feature0": 0.0),("feature1",0.0),...,("output0":0.0),("output1":0.0),...], sequence of the zipped dictionary will change randomly. The final result will be like [("feature90": 0.0),("feature15",0.0),...,("output15":0.0),("output30":0.0),...].
I'm very confused how to create keys for long tensors automatically? Does anyone know how to solve it? Thank you.
python tensorflow dataset
edited Nov 14 '18 at 6:19
Tomothy32
5,7121425
asked Nov 14 '18 at 6:10
ShannonShannon
12
add a comment |
I'm just a novice in learning tensorflow but encountered a problem.
I want to build a regression model with DNN. In Tensorflow, the dataset input into the tf.estimator.Estimator must be a nested dictionary which contains keys and values. As shown in the given examples, every column of a tensor will be given a key. For example, SepalLength, PetalWidth, PetalLength, SepalWidth are given as keys for the input data in the iris example.
But in my situation, there are 200 input features, and 100 output values. How to create the key for these features? I can create keys by list("feature"+i for i in range(200)). The key will be like "feature0","feature1",... But when I use zip function to pack the input and output like [("feature0": 0.0),("feature1",0.0),...,("output0":0.0),("output1":0.0),...], sequence of the zipped dictionary will change randomly. The final result will be like [("feature90": 0.0),("feature15",0.0),...,("output15":0.0),("output30":0.0),...].
I'm very confused how to create keys for long tensors automatically? Does anyone know how to solve it? Thank you.
python tensorflow dataset
edited Nov 14 '18 at 6:19
Tomothy32
5,7121425
asked Nov 14 '18 at 6:10
ShannonShannon
12
I'm just a novice in learning tensorflow but encountered a problem.
I want to build a regression model with DNN. In Tensorflow, the dataset input into the tf.estimator.Estimator must be a nested dictionary which contains keys and values. As shown in the given examples, every column of a tensor will be given a key. For example, SepalLength, PetalWidth, PetalLength, SepalWidth are given as keys for the input data in the iris example.
But in my situation, there are 200 input features, and 100 output values. How to create the key for these features? I can create keys by list("feature"+i for i in range(200)). The key will be like "feature0","feature1",... But when I use zip function to pack the input and output like [("feature0": 0.0),("feature1",0.0),...,("output0":0.0),("output1":0.0),...], sequence of the zipped dictionary will change randomly. The final result will be like [("feature90": 0.0),("feature15",0.0),...,("output15":0.0),("output30":0.0),...].
I'm very confused how to create keys for long tensors automatically? Does anyone know how to solve it? Thank you.
python tensorflow dataset
python tensorflow dataset
edited Nov 14 '18 at 6:19
Tomothy32
5,7121425
asked Nov 14 '18 at 6:10
ShannonShannon
12
edited Nov 14 '18 at 6:19
Tomothy32
5,7121425
asked Nov 14 '18 at 6:10
ShannonShannon
12
edited Nov 14 '18 at 6:19
Tomothy32
5,7121425
edited Nov 14 '18 at 6:19
Tomothy32
5,7121425
edited Nov 14 '18 at 6:19
Tomothy32
5,7121425
5,7121425
asked Nov 14 '18 at 6:10
ShannonShannon
12
asked Nov 14 '18 at 6:10
ShannonShannon
12
asked Nov 14 '18 at 6:10
ShannonShannon
12
12
add a comment |
add a comment |
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