IM_SIZE = 224
lenet_model = tf.keras.Sequential([
InputLayer(input_shape = (IM_SIZE,IM_SIZE, 3)),
Conv2D(filters = 6 , kernel_size = 5, strides=1, padding = 'valid', activation = 'relu' ),
BatchNormalization(),
MaxPool2D (pool_size = 2, strides=2),
Conv2D(filters = 16 , kernel_size = 3, strides=1, padding = 'valid', activation = 'relu' ),
BatchNormalization(),
MaxPool2D (pool_size = 2, strides=2),
Flatten(),
Dense(100,activation = 'relu'),
BatchNormalization(),
Dense(10,activation = 'relu'),
BatchNormalization(),
Dense(1,activation = 'sigmoid'),
])
lenet_model.summary()
y_true = [0,1,0,0]
y_pred = [0.6,0.51,0.94,1]
bce = tf.keras.losses.BinaryCrossentropy()
bce(y_true, y_pred)
lenet_model.compile(optimizer = Adam(learning_rate = 0.01),
loss = BinaryCrossentropy(),
metrics = ‘accuracy’)
history = lenet_model.fit(train_dataset,validation_data = val_dataset, epochs = 20, verbose=1)
ValueError Traceback (most recent call last)
in <cell line: 1>()
----> 1 history = lenet_model.fit(train_dataset,validation_data = val_dataset, epochs = 20, verbose=1)
1 frames
/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py in tf__train_function(iterator)
13 try:
14 do_return = True
—> 15 retval_ = ag__.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope)
16 except:
17 do_return = False
ValueError: in user code:
File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1401, in train_function *
return step_function(self, iterator)
File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1384, in step_function **
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1373, in run_step **
outputs = model.train_step(data)
File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1150, in train_step
y_pred = self(x, training=True)
File “/usr/local/lib/python3.10/dist-packages/keras/src/utils/traceback_utils.py”, line 70, in error_handler
raise e.with_traceback(filtered_tb) from None
File “/usr/local/lib/python3.10/dist-packages/keras/src/engine/input_spec.py”, line 298, in assert_input_compatibility
raise ValueError(
ValueError: Input 0 of layer "sequential_6" is incompatible with the layer: expected shape=(None, 224, 224, 3), found shape=(None, None, 224, 224, 3)