I am running this simple code on Spyder 3.3 with Python 3.7 and Tensorlow 2.0: import tensorflow as tf print(tf.__version__) When I try to run it again in th
I have a seasonal timeseries dataset containing 3 target variables and n feature variables. I am trying to apply a PCA algorithm before feeding the data to a si
I am following this tutorial to train my own models. https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/latest/ I followed all the steps exactly
I'm trying to use a modified version of this custom loss and I'm getting the error below InvalidArgumentError: The second input must be a scalar, but it has sh
I want to use the Segmentation_Models UNet (with ResNet34 Backbone) for uncertainty estimation, so i want to add some Dropout Layers into the upsampling part. T
I am new to deep learning and I have been trying to install tensorflow-gpu version in my pc in vain for the last 2 days. I avoided installing CUDA and cuDNN dri
I'm trying to train the model using pretrained faster_rcnn_inception_v2_coco. I'm using the following config file: model { faster_rcnn { num_classes: 37
I am doing multi class segmentation using UNet. My input to the model is HxWxC and my output is, outputs = layers.Conv2D(n_classes, (1, 1), activation='sigmoid'
Here is my code. from keras.optimizers import gradient_descent_v2 as SGD sgd=SGD(lr=0.01,momentum=0.9,decay=(0.01/25),nesterov=False) I get the following er
TF 2.x - just for the experience I tried with a simple experimental dataset - to show the problem: import numpy as np import tensorflow as tf import keras from
I want to disable a computation of several filters during Predict call with Tensorflow 2 and Keras. Do i have to modify the source code of Tensorflow to achieve
I need to use the librosa and tensorflow packages for a Neural Network audio classification project. librosa has a dependency on the numba package, which requir
Do we need these files?, The Tensorflow Doc don't say anything about them
I'm trying to run my code Keras CuDNNGRU on tensorflow using gpu but it always get error "Fail to find dnn implementation" even though I already installed CUDA
I am trying to save the model from here https://github.com/greatwhiz/tft_tf2/blob/master/README.md in SavedModel format (preferably with Functional API). The so
I know dataset has output_shapes, but it shows like below: data_set: DatasetV1Adapter shapes: {item_id_hist: (?, ?), tags: (?, ?), client_platform: (?,), en
I want to use tf.data.Dataset.list_files function to feed my datasets. But because the file is not image, I need to load it manually. The problem is tf.data.Dat
I am using Keras with TensorFlow to implement a deep neural network. When I plot the loss and number of iterations, there is a significant jump in loss after ea
I've been attempting to install and run anipose in Ubuntu 18.04 I keep getting the same import error though I've made sure keras is installed. I've also searche
I am missing information about the 'val_acc' attribute when I fit a compiled sequential model. I have a sequential model that is compiled with 'accuracy' metr