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  1. from tensorflow.keras import models
  2. from tensorflow.keras.layers import Conv2D, MaxPooling2D, Dense, Flatten
  3.  
  4. model = models.Sequential()
  5. model.add(Conv2D(filters=64, kernel_size=(10, 10), strides=(2, 2), padding='valid', input_shape=(1024, 1024, 3)))
  6. model.add(MaxPooling2D(pool_size=(2, 2),strides=(2, 2)))
  7. model.add(Flatten())
  8. model.add(Dense(units=1, activation='sigmoid'))
  9. #model.add(Dense(10, activation='softmax'))
  10. model.summary()
Success #stdin #stdout 2.59s 370128KB
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Model: "sequential"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d (Conv2D)             (None, 508, 508, 64)      19264     
                                                                 
 max_pooling2d (MaxPooling2D  (None, 254, 254, 64)     0         
 )                                                               
                                                                 
 flatten (Flatten)           (None, 4129024)           0         
                                                                 
 dense (Dense)               (None, 1)                 4129025   
                                                                 
=================================================================
Total params: 4,148,289
Trainable params: 4,148,289
Non-trainable params: 0
_________________________________________________________________
https://ideone.com/0MFZio
language:
Python 3 (python  3.9.5)
created:
1 year ago
visibility:
public

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