TensorFlow2: ResNet50 - ValueError - python-3.x

Question

I am trying to use Transfer Learning using ResNet-50 in TensorFlow2 and Keras on CIFAR-10 dataset which has (32, 32, 3) images.
The default ResNet-50's first conv layer uses a filter size of (7, 7) with stride = 2, the resulting CIFAR-10 is reduced too much spatially here which is to be avoided. As a 'hack', the images are attempted to be upscaled from (32, 32) to (224, 224). The code is:
import tensorflow.keras as K
# Define KerasTensor as input-
input_t = K.Input(shape = (32, 32, 3))
res_model = K.applications.ResNet50(
include_top = False,
weights = "imagenet",
input_tensor = input_t
)
# Since CIFAR-10 dataset is small as compared to ImageNet, the images are upscaled to (224, 224)-
to_res = (224, 224)
model = K.models.Sequential()
model.add(K.layers.Lambda(lambda image: tf.image.resize(image, to_res)))
model.add(res_model)
model.add(K.layers.Flatten())
model.add(K.layers.BatchNormalization())
model.add(K.layers.Dense(units = 10, activation = 'softmax'))
# Choose an optimizer and loss function for training-
loss_fn = tf.keras.losses.CategoricalCrossentropy()
optimizer = tf.keras.optimizers.SGD(learning_rate = 0.1, momentum = 0.9)
model.compile(
# loss = 'categorical_crossentropy',
loss = loss_fn,
# optimizer = K.optimizers.RMSprop(lr=2e-5),
optimizer = optimizer,
metrics=['accuracy']
)
history = model.fit(
x = X_train, y = y_train,
batch_size = batch_size, epochs = 10,
validation_data = (X_test, y_test),
# callbacks=[check_point]
)
To which I get the error:
Epoch 1/10 WARNING:tensorflow:Model was constructed with shape (None,
32, 32, 3) for input KerasTensor(type_spec=TensorSpec(shape=(None, 32,
32, 3), dtype=tf.float32, name='input_1'), name='input_1',
description="created by layer 'input_1'"), but it was called on an
input with incompatible shape (None, 224, 224, 3).
ValueError Traceback (most recent call
last)
in ()
2 x = X_train, y = y_train,
3 batch_size = batch_size, epochs = 10,
----> 4 validation_data = (X_test, y_test),
5 # callbacks=[check_point]
6 )
9 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/func_graph.py
in wrapper(*args, **kwargs)
975 except Exception as e: # pylint:disable=broad-except
976 if hasattr(e, "ag_error_metadata"):
--> 977 raise e.ag_error_metadata.to_exception(e)
978 else:
979 raise
ValueError: in user code:
ValueError: Input 0 is incompatible with layer resnet50: expected
shape=(None, 32, 32, 3), found shape=(None, 224, 224, 3)

Answer 1

The input of the model is still (32, 32, 3)
input_t = K.Input(shape = (32, 32, 3))