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Tag: keras

Concatenate two models with tensorflow.keras

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 […]

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 […]