Issue changing input_shape to (100,100,3)
jaimerodric opened this issue · 0 comments
jaimerodric commented
My code is this one, and changing only the input_shape I get a error:
`
def fine_VGGFace():
model = VGGFace(model="resnet50", include_top=False, input_shape=(100, 100, 3), pooling="avg", weights='vggface')
model.trainable = False
x = model.output
x = tf.keras.layers.Dense(1024, name='fc8', activation=None)(x)
output = tf.keras.layers.Lambda(lambda x: tf.math.l2_normalize(x, axis=1))(x) # L2 normalize embeddings
model_finetuning2 = tf.keras.Model(inputs=model.inputs, outputs=[output])
model_finetuning2.summary()
return model_finetuning2`
Exception encountered when calling layer "avg_pool" (type AveragePooling2D).
Negative dimension size caused by subtracting 7 from 3 for '{{node avg_pool/AvgPool}} = AvgPoolT=DT_FLOAT, data_format="NHWC", ksize=[1, 7, 7, 1], padding="VALID", strides=[1, 7, 7, 1]' with input shapes: [?,3,3,2048].