My goal is to tune over possible network architectures that meet the following criteria: Layer 1 can have any number of hidden units from this list: [32, 64, 12
I'm trying to make neural network training reproducible using RStudio's Keras interface. Setting a seed in the R script (set.seed(42)) doesn't seem to work. Is
----> 6 from mrcnn.model import MaskRCNN /usr/local/lib/python3.7/dist-packages/mrcnn/model.py in () 253 254 --> 255 class ProposalLayer(KE.Layer): 256
I am using the TensorFlow federated framework for a multiclassification problem. I am following the tutorials and most of them use the metric (tf.keras.metrics.
validation_split parameter is able to allow ImageDataGenerator to split the data sets reading from the folder into 2 different disjoint sets. Is there any way t
I'm try learning TensorFlow but i have a problem. I'm importing TensorFlow like in official website but i take a error. import pandas as pd import numpy as np i
I'm trying to reload or access the Keras-Tuner Trials after the Tuner's search has completed for inspecting the results. I'm not able to find any documentation
I am currently working on my bachelor's thesis at FIIT STU, the primary goal of which is to attempt to replicate and verify the results of the following study.
While attempting an NLP exercise, I tried to make use of BERT architecture to get a good training model. So I defined a function that builds and compiles the mo
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
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 want to know the most similar words to another from a pretrained embedding vectors in R. E.g: words similar to "beer". For this, I download the pretrained emb
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 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