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Feed complex64 data into Keras sequential model


“Large data” work flows using pandasUnderstanding Keras LSTMsKeras Sequential Model Data Preparation: observations of single rowAdd hand-crafted features to Keras sequential modelMultiple Embedding layers for Keras Sequential modelFormat mutiple inputs with mutiple categories for a functional keras model and feed it to the modelKeras extending embedding layer inputinitialising and accessing an array of weights in a custom keras layerIs it possible to calculate gradient of layer within sequential model in Keras neural network?






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I am working in training a CNN in fourier domain. To speed up training, I thought of taking the fft of the entire dataset before training and feeding this data to the sequential model. But inside the first layer of the model, which is a custom Keras layer, the training data is shown to have float32 data type. Does the sequential model take in only real input data?
Thanks.










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    1















    I am working in training a CNN in fourier domain. To speed up training, I thought of taking the fft of the entire dataset before training and feeding this data to the sequential model. But inside the first layer of the model, which is a custom Keras layer, the training data is shown to have float32 data type. Does the sequential model take in only real input data?
    Thanks.










    share|improve this question


























      1












      1








      1








      I am working in training a CNN in fourier domain. To speed up training, I thought of taking the fft of the entire dataset before training and feeding this data to the sequential model. But inside the first layer of the model, which is a custom Keras layer, the training data is shown to have float32 data type. Does the sequential model take in only real input data?
      Thanks.










      share|improve this question














      I am working in training a CNN in fourier domain. To speed up training, I thought of taking the fft of the entire dataset before training and feeding this data to the sequential model. But inside the first layer of the model, which is a custom Keras layer, the training data is shown to have float32 data type. Does the sequential model take in only real input data?
      Thanks.







      python keras sequential






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      asked Mar 28 at 13:20









      psjpsj

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          Adding an InputLayer(... dtype='complex64') layer, i.e. an InputLayer() with data type specified as 'complex64' as the first layer of the sequential model allowed me to pass complex64 data to the model.






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            Adding an InputLayer(... dtype='complex64') layer, i.e. an InputLayer() with data type specified as 'complex64' as the first layer of the sequential model allowed me to pass complex64 data to the model.






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              Adding an InputLayer(... dtype='complex64') layer, i.e. an InputLayer() with data type specified as 'complex64' as the first layer of the sequential model allowed me to pass complex64 data to the model.






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                Adding an InputLayer(... dtype='complex64') layer, i.e. an InputLayer() with data type specified as 'complex64' as the first layer of the sequential model allowed me to pass complex64 data to the model.






                share|improve this answer













                Adding an InputLayer(... dtype='complex64') layer, i.e. an InputLayer() with data type specified as 'complex64' as the first layer of the sequential model allowed me to pass complex64 data to the model.







                share|improve this answer












                share|improve this answer



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                answered Apr 11 at 9:37









                psjpsj

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