Suppose I execute the following code W = tf.random.uniform(shape = (100,1), minval = 0, maxval = 1) Z = tf.random.uniform(shape = (100,1), minval = 0, maxval =
I have a script which goes through a simple 2d CNN and I'm trying to run through a range of different values for the number of layers and neurons per layer in m
please I'm trying to build an NLP classifier on top of BERT but I'm struggling with data imbalance. I'm looking for an implementation of weighted CategoricalCro
Trying to understand 2D convolutions, I ran into the following image, which has me confused: If I understood correctly: the blue shape is the input the orange
i'm trying to use DPAdamGaussianOptimizer from tensorflow privacy to switch my original optimizer so i could protect privacy during the training. but when i cre
I was training a network and I decided to add more data for training. my data set is selected from another data but both have (460,620,3) and Uint8 type. but wh
I am trying to move my code from Tensorflow to Pytorch. Before doing this, I just simply test myself two frameworks. I expected two frameworks should show simil
I have a code to forecast a time series using an attention mechanism. Here's what I've got so far, but I'm getting an error. def dot_product(x, kernel): if
I have 2 tensorflow (1.15.4) models running sequentially. The output from the first model will be fed into the second model. Is there a way to run the first mod
I would like to generate a Lookup table in TensorFlow with key is string and value is list of strings. But it seems currently no classes in tf.lookup support th
Task: Mask RCNN train_shapes.ipynb tutorial. Training to segment different shapes in the artificially generated shapes dataset. Problem: Matterport's Mask RCNN
I have a new MacBook with the Apple M1 chipset. To install tensorflow, I follow the instructions here, i.e., installing tensorflow-metal and tensorflow-macos in
I wan to use upgrade the CUDNN version from 8.0 to 8.1 and CUDA version to 11.2, but I am not sure how we can do this on colab. Below is the script I wrote to r
I'm following this tutorial: Tensorflow Image Segmentation I want to make my own dataset. Ideally, following the same format as the Oxford pet dataset used in
I use tensorflow for image classification (20 classes) with convolutions. My dataset contains about 20000 train images and 5000 test images. Images (RGB) have 2
I'm having trouble using DataLoader.from_pascal_voc from TFLite Model Maker. I've successfully mounted Google Drive into Google Colab and when I printed the len
I have been using bert and trying to compile the model using the below line of code. model = TFBertForSequenceClassification.from_pretrained('bert-base-uncased'
Is the GlobalAveragePooling1D Layer the same like calculating the mean with a custom Lambda Layer? The data is temporal, so x has shape (batch, time, features)
I am trying to load a pandas dataframe into a tensor Dataset. The columns are text[string] and labels[a list in string format] A row would look something like:
I am using a Keras network which I am calling predict() many times on a single input. A rough calculation based on the layers gives ~3Mops. Running on my CPU sh