Hi,
I have a mistake in the third exercise, but I don’t understand why.
this is part of the code
inputs = Input(input_size)
# Contracting Path (encoding)
# Add a conv_block with the inputs of the unet_ model and n_filters
cblock1 = conv_block(inputs, n_filters)
# Chain the first element of the output of each block to be the input of the next conv_block.
# Double the number of filters at each new step
cblock2 = conv_block(cblock1, n_filters=2*n_filters)
and this is the error explanation
ValueError Traceback (most recent call last)
in
4 num_channels = 3
5
----> 6 unet = unet_model((img_height, img_width, num_channels))
7 comparator(summary(unet), outputs.unet_model_output)
in unet_model(input_size, n_filters, n_classes)
17 # Chain the first element of the output of each block to be the input of the next conv_block.
18 # Double the number of filters at each new step
—> 19 cblock2 = conv_block(cblock1, n_filters=2n_filters)
20 cblock3 = conv_block(cblock2, n_filters=4n_filters)
21 cblock4 = conv_block(cblock3, n_filters=6*n_filters, dropout_prob=0.3) # Include a dropout of 0.3 for this layer
in conv_block(inputs, n_filters, dropout_prob, max_pooling)
16 activation=‘relu’,
17 padding=‘same’,
—> 18 kernel_initializer=‘he_normal’)(inputs)
19 conv = Conv2D(filters=n_filters, # Number of filters
20 kernel_size=3, # Kernel size
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py in call(self, *args, **kwargs)
924 if _in_functional_construction_mode(self, inputs, args, kwargs, input_list):
925 return self._functional_construction_call(inputs, args, kwargs,
→ 926 input_list)
927
928 # Maintains info about the Layer.call stack.
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py in _functional_construction_call(self, inputs, args, kwargs, input_list)
1090 # TODO(reedwm): We should assert input compatibility after the inputs
1091 # are casted, not before.
→ 1092 input_spec.assert_input_compatibility(self.input_spec, inputs, self.name)
1093 graph = backend.get_graph()
1094 # Use self._name_scope() to avoid auto-incrementing the name.
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/input_spec.py in assert_input_compatibility(input_spec, inputs, layer_name)
156 str(len(input_spec)) + ’ inputs, ’
157 'but it received ’ + str(len(inputs)) +
→ 158 ’ input tensors. Inputs received: ’ + str(inputs))
159 for input_index, (x, spec) in enumerate(zip(inputs, input_spec)):
160 if spec is None:
ValueError: Layer conv2d_113 expects 1 inputs, but it received 2 input tensors. Inputs received: [<tf.Tensor ‘max_pooling2d_36/MaxPool:0’ shape=(None, 48, 64, 32) dtype=float32>, <tf.Tensor ‘conv2d_112/Relu:0’ shape=(None, 96, 128, 32) dtype=float32>]
I had been stuck for hours, and still, I don’t understand the error. So I appreciate you could help me with this.
Regards,
Carlos
