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)
Does PyTorch's nn.Embedding support manually setting the embedding weights for only specific values? I know I could set the weights of the entire embedding laye
The app can be viewed in huggingface https://huggingface.co/spaces/rowel/asr import gradio as gr from transformers import pipeline model = pipeline(task="auto
I have Keras model: pre-trained CV model + a few added layers on top I would want to be able to do model.predict before model.fit Q: how do I instantiate model
I am trying to figure out if I can use fastai for my problem. I am trying to classify sequences of floats. Each sequence is a vector of 24 floats. In principle,
I am new to tensorflow. i've tried to fit X and y both shape=8 float64 tensors X as feature set and y as target set. X = np.array([-7.0, -4.0, -1.0, 2.0, 5.0, 8
Hello guys i am a biggner at computer vision and classification, i am trying to train a model using cnn method with tensorflow and keras, but i keep getting the
I'm trying to split DNN Models in order to execute part of the network on the edge and the rest on the cloud. Because it has to be cross-platform and work with
I am building an address matching algorithm. The main problem is that previous models like Conditional Random fields (CRF)from Paserator and Averaged Perceptron
I am trying to run some example python3 code https://docs.databricks.com/applications/deep-learning/distributed-training/horovod-runner.html on databricks GPU c
input_shape=(100,100,6) input_tensor=keras.Input(input_shape) model.add(Conv2D(32, 3, padding='same', activation='relu', input_shape=input_shape))
This is the code from https://keras.io/examples/vision/image_classification_from_scratch/ import tensorflow as tf from tensorflow import keras from tensorflo
I am building a multi-class Vision Transformer Network. When passing my values through my loss function, it always returns zero. My output layer consisits of 37
I am using easyocr methods to recognize the text on the license plate but the results are not good. I have developed deep learning model which detects license p
I'm trying to train a UNet, but for some reason I get the following error: Traceback (most recent call last): File "<ipython-input-54-b56497e81356>", l
How to apply the initializer to the tf.Variable function? Am I on the right track? def initialize_parameters(): initializer
I have a keras model with 5 outputs. My labels include 5 values to compare these to, but also 25 additional values representing a correlation matrix for the 5 v
I designed a CNN for a multitask classification in keras, where I have one input and two different class of classes in output. I compiled the model in this way
I designed a CNN for a multitask classification in keras, where I have one input and two different class of classes in output. I compiled the model in this way
I have a task for my project paper and I do not get how to train the model. This model is supposed to take an image and segment it into different classes. The h
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