I have a flask application that I would like to run it on an EC2 instance and TensorFlow is needed cause it is image classification. However, after the necessar
I am trying to learn and understand how to implement multiclass classification using ANN. In my case, I have 16 classes(0-15), and my label dataset contains one
I'm trying to train research model ssd_mobilenet_v1_fpn_640x640_coco17_tpu-8 using the MultiWorkerMirroredStrategy (by setting --num_workers=2 in the invocation
I am trying to import import tensorflow.python.keras.applications but it gives the bellow error: ModuleNotFoundError: No module named 'tensorflow.python.keras.
I have a conda env that I build from a requirements.yml file that I obtained from a classmate so we could work on a project together. I tried installing matplot
I am using the Physics Informed Neural Networks (PINNs) methodology to solve non-linear PDEs in high dimension. Specifically, I am using this class https://git
I am training a U-Net in keras by minimizing the dice_loss function that is popularly used for this problem: adapted from here and here def dsc(y_true, y_pred)
I am new to Tensorflow and deep leaning. I am trying to see how the loss decreases over 10 epochs in my RNN model that I created to read a dataset from kaggle w
tf.unique currently only works on 1D tensors. How can I find unique values in a 2D tensor. ip=tf.constant([[1,2,1],[3,4,1],[5,6,1],[1,2,1]]) #op should be = [
tf.unique currently only works on 1D tensors. How can I find unique values in a 2D tensor. ip=tf.constant([[1,2,1],[3,4,1],[5,6,1],[1,2,1]]) #op should be = [
Hey everyone this is my first question post. If I do something wrong or u need more information please just tell me I will try to give my best. I tried to creat
Do you know any elegant way to do inference on 2 python processes with 1 GPU tensorflow? Suppose I have 2 processes, first one is classifying cats/dogs, 2nd on
What does it mean to "unroll a RNN dynamically". I've seen this specifically mentioned in the Tensorflow source code, but I'm looking for a conceptual explanati
# lstm model import tensorflow as tf from numpy import mean from numpy import std from numpy import dstack from pandas import read_csv from tensorflow.keras.mod
How can I have python3.6 in tensorflow docker images. All the images I tried (latest, nighty) are using python3.5 and I don't want to modify all my scripts.
After I have saved a tensorflow model in HDF5 format, how can I find out what version of tensorflow it was built using?
My system has a GPU. When I run Tensorflow on it, TF automatically detects GPU and starts running the thread on the GPU. How can I change this? I.e. how can I r
https://www.youtube.com/watch?v=z1PGJ9quPV8&t=28s Here is the little project of Cancer dectection, and it has already offer the dataset and colab code, but
I'm trying to run the YoloV4 (Demo 5) in TensorRt demos repo on AWS ec2. I created ec2 VM with nvidia-gpu (with AMI - Amazon Linux 2 AMI with NVIDIA TESLA GPU D
I have my data in multiple pickle files stored on disk. I want to use tensorflow's tf.data.Dataset to load my data into training pipeline. My code goes: def _p