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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.
python keras sequential
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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.
python keras sequential
add a comment
|
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
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
python keras sequential
asked Mar 28 at 13:20
psjpsj
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668 bronze badges
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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.
add a comment
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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.
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.
answered Apr 11 at 9:37
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