I’m currently studying neural network models for image analysis, with the MNIST dataset. I first used only the image to build a first model. Then I created a additionnal variable, which is : 0 when the digit is actually between 0 and 4, and 1 when it’s greater or equal than 5. Therefore, I want […]
Tag: keras
During creating VAE model throws exception “you should implement a `call` method.”
I want to create VAE(variational autoencoder). During model creating it throws exception. When subclassing the Model class, you should implement a call method. I am using Tensorflow 2.0 Models with names I want to get model. Answer The problem is here: You are passing three arguments to the construction, where only two are needed (inputs […]
Model not training and negative loss when whitening input data
I am doing segmentation and my dataset is kinda small (1840 images) so I would like to use data-augmentation. I am using the generator provided in the keras documentation which yield a tuple with a batch of images and corresponding masks that got augmented the same way. I am then training my model with this […]
Tensorflow/keras: “logits and labels must have the same first dimension” How to squeeze logits or expand labels?
I’m trying to make a simple CNN classifier model. For my training images (BATCH_SIZEx227x227x1) and labels (BATCH_SIZEx7) datasets, I’m using numpy ndarrays that are fed to the model in batches via …
Tensorflow 2.0 – AttributeError: module ‘tensorflow’ has no attribute ‘Session’
When I am executing the command sess = tf.Session() in Tensorflow 2.0 environment, I am getting an error message as below: System Information: OS Platform and Distribution: Windows 10 Python Version: 3.7.1 Tensorflow Version: 2.0.0-alpha0 (installed with pip) Steps to reproduce: Installation: pip install –upgrade pip pip install tensorflow==2.0.0-alpha0 pip install keras pip install numpy==1.16.2 […]
Gaierror while importing pretrained vgg model on kaggle
I am trying to import a pre-trained VGG model in keras on kaggle. I run through an gaierror which was unfamiliar. Downloading data from https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg19_weights_tf_dim_ordering_tf_kernels_notop.h5 ————————————————————————— gaierror Traceback (most recent call last) /opt/conda/lib/python3.6/urllib/request.py in do_open(self, http_class, req, **http_conn_args) 1317 h.request(req.get_method(), req.selector, req.data, headers, -> 1318 encode_chunked=req.has_header(‘Transfer-encoding’)) 1319 except OSError as err: # timeout error /opt/conda/lib/python3.6/http/client.py in request(self, method, url, body,
InvalidArgumentError: cannot compute MatMul as input #0(zero-based) was expected to be a float tensor but is a double tensor [Op:MatMul]
Can somebody explain, how does TensorFlow’s eager mode work? I am trying to build a simple regression as follows: Gradient output: [None, None, None, None, None, None] The error is following: Edit I updated my code. Now, the problem comes in gradients calculation, it is returning zero. I have checked the loss value that is […]
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 […]
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….