I need help installing TensorFlow/Keras on raspberry pi 3B+ Python version 3.9.2 Keras version 2.8.0 TensorFlow version 1.8.0 I downloaded them via pip3 on pro
Note: there are many similar questions but for different versions of ubuntu and somewhat different specific libraries. I have not been able to figure out what
I'm trying to deploy a simple model on the Triton Inference Server. It is loaded well but I'm having trouble formatting the input to do a proper inference reque
I used google collaboratory to train a simple mnist example model to get myself familiar with tensorflow serving but my tensorflow model server is not able to r
When I limit GPU by os.environ["CUDA_VISIBLE_DEVICES"]="1" and load trained model like below, tacotron1.15.5[horovod] load model to all GPUs(8) with same proces
I have being trying to fit the error during my Tensorflow course (Section 3: Neural network Regression with Tensorflow) with Udemy. import tensorflow as tf impo
I am Training a cnn in Keras at the moment. Now I want to log the history of the training process for later visualizations, which I do with: history_callback =
I am running an Apple Macbook with 16 GB of RAM and the M1 chip. I am trying to import Keras through the command: from tensorflow.keras.models import Sequential
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 la
I trained a model using Transfer Learning(InceptionV3) and when I tried to predict the results it shows: ValueError: cannot reshape array of size 921600 into sh
"after converting the dataset to the tfrecord file format, I tried to train the model I created with it, but I couldn't convert it to the input format suitable
I'm trying to run saved serving models in my local machine. However, it takes string tensor as input, and I'm having trouble converting the images to the correc
I have TensorFlow (2.8.0) installed and running on my Apple Silicon M1 MacBook. But facing dependency error on trying to install tensorflow-federated with the b
The original question was in regard to TensorFlow implementations specifically. However, the answers are for implementations in general. This general answer is
i have been getting valueError issue. Currently using python3.9.11., keras2.8. if loss_init=="r2": parallel_model.compile(loss=custom_r2_loss, o
I know that output of keras layers (like keras.layers.Dense()) produce so-called 'keras tensors'. Also, there are 'tensorflow tensors' that are produced by tens
We can pass the training = False argument while calling the pre-trained model when using Keras Functional API as shown in this tutorial. How to implement the sa
It's weird, I wrote a functioning program on a Jupyter notebook and I wanted to have it in a normal python file with VSCode aswell. However, while copying and p
I have cloned https://github.com/akTwelve/Mask_RCNN and run the demo code. Everything works fine and runs correctly but the image processing part has incorrect
I am doing classification of citrus leaves dataset. I came up with a very basic model and ran it in Jupyter notebook on my machine, using anaconda. Exact same m