How to fine-tune a functional model in Keras?

Taking a pre-trained model in Keras and replacing the top classification layer to retrain the network to a new task has several examples using a Sequential model in Keras. A sequential model has methods model.pop() and model.add() which make this fairly easy. However, how is this achieved when using a functional model? This framework does not have method model.add(). How can I load a pretrained functional model in Keras, crop the last layer and replace it with a new one? Current approach so far: AttributeError: ‘Model’ object has no attribute ‘add’ Answer You can use a pretrained functional model with

Input Shape for 1D CNN (Keras)

I’m building a CNN using Keras, with the following Conv1D as my first layer: cnn.add(Conv1D( filters=512, kernel_size=3, strides=2, activation=hyperparameters[“activation_fn”], …

Keras CNN Error: expected Sequence to have 3 dimensions, but got array with shape (500, 400)

I’m getting this error: ValueError: Error when checking input: expected Sequence to have 3 dimensions, but got array with shape (500, 400) These are the below codes that I’m using. print(X1_Train….

tflite: get_tensor on non-output tensors gives random values

I’m trying to debug my tflite model, that uses custom ops. I’ve found the correspondence between op names (in *.pb) and op ids (in *.tflite), and I’m doing a layer-per-layer comparison (to make sure …

Keras: Adding MDN Layer to LSTM Network

My question in brief: Is the Long Short Term Memory Network detailed below appropriately designed to generate new dance sequences, given dance sequence training data? Context: I am working with a …

Save and load model optimizer state

I have a set of fairly complicated models that I am training and I am looking for a way to save and load the model optimizer states. The “trainer models” consist of different combinations of several …

What is the use of verbose in Keras while validating the model?

I’m running the LSTM model for the first time. Here is my model: opt = Adam(0.002) inp = Input(…) print(inp) x = Embedding(….)(inp) x = LSTM(…)(x) x = BatchNormalization()(x) pred = Dense(5,…

Getting a list of all known classes of vgg-16 in keras

I use the pre-trained VGG-16 model from Keras. My working source code so far is like this: from keras.applications.vgg16 import VGG16 from keras.preprocessing.image import load_img from keras….

Mixture usage of CPU and GPU in Keras

I am building a neural network on Keras, including multiple layers of LSTM, Permute and Dense. It seems LSTM is GPU-unfriendly. So I did research and use But based on my understanding about with, with is try…finally block to ensure that clean-up code is executed. I don’t know whether the following CPU/GPU mixture usage code works or not? Will they accelerate speed of training? Answer As you may read here – tf.device is a context manager which switches a default device to this passed as its argument in a context (block) created by it. So this code should run all