Comments (5)
Could you please provide a Minimum Working Example (MWE) to reproduce the error? A plus would be the working scenario.
Thank you
from cvnn.
from tensorflow.keras import datasets, models
import cvnn.layers as complex_layers
model = models.Sequential()
model.add(complex_layers.ComplexConv2D(32, (3, 3), activation='cart_relu', input_shape=(32, 32, 3), dtype=np.float32))
running the above is causing the given error, it is working when replacing activation with just 'relu'. As far as I could understand while defining Complex conv layers you have imported activations from tensorflow.keras and then used activations.get(activation) which might be raising an issue as these activations are defined and created by you and importing t_activations might enable us to use these complex activations.
from cvnn.
For me it's working. See it here.
from cvnn.
Try updating cvnn version to the latest.
Also, beware that the example cast to np.float32 and not complex.
from cvnn.
I used conda to install cvnn, that was giving the error. After doing pip install it works, thanks!!!
from cvnn.
Related Issues (20)
- Model subclassing compatibility HOT 4
- load CVNN model with succes HOT 1
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- ComplexConv2D with bias vector slows down training a lot HOT 7
- "WARNING:tensorflow: You are casting an input of type complex64 to an incompatible dtype float32. This will discard the imaginary part and may not be what you intended." HOT 5
- ModuleNotFoundError: No module named 'cvnn.montecarlo' HOT 1
- Cant find Complex Softmax which takes complex input and output complex output HOT 1
- Best Activation Function in Complex Domain HOT 1
- using this function layers.complex_input(shape=input_shape + (3,)) gives off dtype error HOT 2
- Problem with loading complex valued model HOT 2
- Equivalent Data PreProcessing for complex-valued input
- Data Parallel Distributed support HOT 4
- Best way to convert Real data into complex data type HOT 1
- Type type error for "ComplexInput" HOT 2
- Error while adding a layer HOT 2
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from cvnn.