kears | Tutorial and case demo of deep learning library keras

when I build my experiment model using tf.kears.layer functional API, I got GraphDisconnected Error as follow:

ValueError Traceback (most recent call last)

in () 35 outputs = x 36 ---> 37 model = tf.keras.Model(inputs=inputs, outputs=outputs) 38 model.summary()

4 frames

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/functional.py in _map_graph_network(inputs, outputs) 988 'The following previous layers ' 989 'were accessed without issue: ' + --> 990 str(layers_with_complete_input)) 991 for x in nest.flatten(node.outputs): 992 computable_tensors.add(id(x))

ValueError: Graph disconnected: cannot obtain value for tensor Tensor("input_63:0", shape=(?, 32, 32, 32), dtype=float32) at layer "tf_op_layer_Pow_105". The following previous layers were accessed without issue: []

to understand this error, I looked into possible SO post but not able to remove the error. I think it is because of shape mismatching at some layers. I double-checked the shape of each layer but the error still persists. I am not sure what caused the problem. Can anyone suggest a possible idea of solving this error? any quick solution to fix this?

update: my full coding attempt:

I am doing disease classification using Multi-Layer Perceptron with keras and below the description of the process, Split the dataset into train_x, train_y, test_x, test_y:

I am beginner to learning ML and DL. I already have faced some problems in windows operating system that's why I want moved on Linux operating system but I am confused which one is better to learn ML and DL.

Which problems I have faced in windows OS,

1. I can't install tensorflow with keras
2. After trying about 5 or more days when I failed to Install tensorflow and keras in anaconda
3. Although finally I successed to install tensorflow and kears to create the new environment in anaconda navigator but some of packages are installed step by step
4. Related to point-3: Again I had faced problems for specific packages
5. Then I decided to use google colab
6. In google colab, It takes more time to load the datasets and for every entre time I should load datasets, it takes more time

And for these above reason and some more , I further have decided to Linux OS. But I am confused about Ubuntu and Kali. I have listen that Kali is better for Hacking and Ubuntu is for Development.

My laptop details are below,

• 8 GB RAM
• 1TB hard disk
• 7th Gen
• Core i5

I'm using python3.7 and trying to use MNIST train data images. Instead of using PyTorch, tf, kears framwork which help to use dataset easily, I tried using mnist module directly.

I was following a tutorial for CNN, there was