Raise error if inputs are not connected with output in functional model

[Surya2k1]

Raise error if inputs are not connected with output in functional model.

The below code fails with tensor_dict related error which is not useful to users.

model_1 = Sequential([
    Input(shape=(6,)),
    layers.Dense(3, activation="sigmoid"),
])

model_2 = Sequential([
    Input(shape=(3,)),
    layers.Dense(1, activation="sigmoid"),
], )

combined = Model(Input(shape=(6,)), model_2(model_1(Input(shape=(6,)))), name='nested_model')
combined.compile(loss='binary_crossentropy', optimizer='adam')
output = combined.train_on_batch(np.random.normal(0, 1, (8, 6)), np.random.normal(0, 1, (8, 1)))

[codecov-commenter]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 82.02%. Comparing base (c8c2c6f) to head (3ebb7b0).
Report is 43 commits behind head on master.

Additional details and impacted files

@@            Coverage Diff             @@
##           master   #20705      +/-   ##
==========================================
+ Coverage   81.94%   82.02%   +0.07%     
==========================================
  Files         548      557       +9     
  Lines       51128    52017     +889     
  Branches     7906     8039     +133     
==========================================
+ Hits        41897    42667     +770     
- Misses       7296     7398     +102     
- Partials     1935     1952      +17     

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keras	81.84% <100.00%> (+0.07%)	⬆️
keras-jax	64.23% <100.00%> (+0.24%)	⬆️
keras-numpy	58.97% <100.00%> (+0.04%)	⬆️
keras-openvino	30.09% <100.00%> (+0.20%)	⬆️
keras-tensorflow	64.80% <100.00%> (+0.12%)	⬆️
keras-torch	64.19% <100.00%> (+0.13%)	⬆️

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[fchollet]

Thanks for the PR! This seems to be triggering a test failure for the TF backend, can you take a look?

[Surya2k1]

The test is failing as the inputs and outputs not connected. Hence re-writing the testcase.

[Surya2k1]

Ping: @fchollet