You tried to call count_params on ..., but the layer isn't built. TensorFlow 2.0

keras model has not yet been built
keras custom layer
tensorflow custom layer
tf-fit
tensorflow verbose
model.build keras
model summary not working
linear layer tensorflow

I receive the following error in in Pyhotn 3 and TF 2.0.

"ValueError: You tried to call count_params on digits, but the layer isn't built. You can build it manually via: digits.build(batch_input_shape)." at line new_model.summary().

what is the problem and how to solve it?

inputs = keras.Input(shape=(784,), name='digits')
x = layers.Dense(64, activation='relu', name='dense_1')(inputs)
x = layers.Dense(64, activation='relu', name='dense_2')(x)
outputs = layers.Dense(10, activation='softmax', name='predictions')(x)

model = keras.Model(inputs=inputs, outputs=outputs, name='3_layer_mlp')
model.summary()

(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()
x_train = x_train.reshape(60000, 784).astype('float32') / 255
x_test = x_test.reshape(10000, 784).astype('float32') / 255

model.compile(loss='sparse_categorical_crossentropy',
              optimizer=keras.optimizers.RMSprop(),
              metrics=['accuracy'])
history = model.fit(x_train, y_train,
                    batch_size=64,
                    epochs=2)

model.save('saved_model', save_format='tf')
new_model = keras.models.load_model('saved_model')
new_model.summary()

For 2.0 version Model can be saved in .h5 format, please use model.save('my_model.h5') while saving.

Please find the link of working gist.

Also issue seems to be resolved in the Latest TF-nightly version,as going forward 2.1 will be official version try using pip install tf-nightly

Find the link of working gist here.

You tried to call `count_params` on embedding, but the , You tried to call `count_params` on embedding, but the layer isn't built. You can build it manually via: `embedding.build(batch_input_shape)`. You tried to call `count_params` on z_input, but the layer isn't built. You can build it manually via: `z_input.build(batch_input_shape #35353 JonLeeCSDN opened this issue Dec 23, 2019 · 6 comments

I met the same error, and it solved after upgraded tf2.0 to tf2.1.

model.summary() isn't works when dropout layer is in the model , weights)) 1589 ValueError: You tried to call `count_params` on dropout, but the layer isn't built. You can build it manually via: `dropout.build(  You tried to call `count_params` on embedding, but the layer isn't built. You can build it manually via: `embedding.build(batch_input_shape)`. #36368 Goofy-G opened this issue Jan 31, 2020 · 13 comments

I had the same problem, I was using tensorflow==2.0.0. I tried running the same code using tensorflows nightly build (in my case pip install tf-nightly==2.1.0.dev20191003).

It worked on the nightly build but you may have to save the model again using the nightly build.

Subclassing the tf.keras.model.Model class, throw "ValueError: You , Model class, throw "ValueError: You tried to call `count_params` on dense_81, but the layer isn't built. You can build it manually via: `dense_81.build(  I receive "ValueError: You tried to call count_params on digits, but the layer isn't built. You can build it manually via: digits.build(batch_input_shape) ." at line new_model.summary().

you can use the model properly if there is not the last line of you codes, that is to say you just can not use summary here.

You tried to call count_params on , but the layer isn't built , For 2.0 version Model can be saved in .h5 format, please use model.save('​my_model.h5') while saving. Please find the link of working gist. count_params should report count for all weights. ('You tried to call `count_params` on ' + but the layer isn \' t built. ' 'You can build it manually via

You tried to call `count_params` on embedding, but the , Ask questionsYou tried to call `count_params` on embedding, but the layer isn't built. You can build it manually via: `embedding.build(batch_input_shape)`. By clicking “Sign up for GitHub”, you agree to our 1589 ValueError: You tried to call `count_params` on dropout, but the layer isn't built. You can build it

You tried to call `count_params` on z_input, but the , Ask questionsYou tried to call `count_params` on z_input, but the layer isn't built. You can build it manually via: `z_input.build(batch_input_shape. when saved  The following are code examples for showing how to use numpy.__name__().They are from open source Python projects. You can vote up the examples you like or vote down the ones you don't like.

hub.KerasLayer, This is the preferred API to load a TF2-style SavedModel from TF Hub into a Keras Now, if you try to call the layer on an input that isn't rank 4 (for instance,  self.input_spec = tf.keras.layers.InputSpec(ndim=4) Now, if you try to call the layer on an input that isn't rank 4 (for instance, an input of shape (2,), it will raise a nicely-formatted error: ValueError: Input 0 of layer conv2d is incompatible with the layer: expected ndim=4, found ndim=1. Full shape received: [2]

Comments
  • I get this error when I load a model from a folder, it works properly on models that weren't loaded from disk.
  • Is there any alternative to the last line of my code (new_model.summary())? I want to print the summary using this new model.