Category "tensorflow"

How to extract 'image' and 'label' out of Tensorflow?

I've loaded in my train and validation sets from CIFAR10 like so: train = tfds.load('cifar10', split='train[:90%]', shuffle_files=True) validation = tfds.load('

Using tf.keras.utils.image_dataset_from_directory with label list

I have list of labels corresponding numbers of files in directory example: [1,2,3] train_ds = tf.keras.utils.image_dataset_from_directory( train_path, label

TypeError: __init__() missing 1 required positional argument: 'units' while coding an neural net

import pandas as pd import numpy as np from sklearn.preprocessing import StandardScaler from keras import Sequential from tensorflow.keras.layers import Dense f

tensorflow ModelCheckpoint on validation precision and recall

I want to checkpoint model whenever validation precision and recall improves - this is on top of validation accuracy and validation loss. So I have added follow

How to call TensorFlow model with linspace?

I'm trying to call a TensorFlow model on a linspace but I can't seem to get even a very simple example (based on https://www.tensorflow.org/api_docs/python/tf/k

sliding window on a tensor

I'm trying to build a simple word generator. However, I encounter some difficulty with the sliding windows. here is my actual code: files = glob("transfdata/*")

Anaconda Solving Environment fails in New Environment

I'm trying to set up tensorflow-gpu on my local machine to train neural networks on my RTX 2070 super. Unfortunately, I get the issue of the environment failing

'TimeseriesGenerator' object has no attribute 'shape'

I have a LSTM model. which when I try to fit i get the error mentioned in the title. I have an array of timeseries data with multiple features I'm feeding as in

why the value of X_train, y_train and x_test and y_test become - 100 after I put windowed_dataset in python (prediction with deep learning )

i have a problem about my code , i don't know why the value of xtrain ytrain xtest ytest diminue 100 (time_step) - 1 because i have keep the same value like thi

Keras early stopping callback error, val_loss metric not available

I am training a Keras (Tensorflow backend, Python, on MacBook) and am getting an error in the early stopping callback in fit_generator function. The error is a

Audio resampling layer for tensorflow

It is required to resample audio signals within a custom model structure. This resampling task is not a kind of pre/post-processing operation that can be develo

how to plot input and output shapes on top of each other using polt_model in keras

I want to plot my model using Keras.utils.plot_model function. my problem is that when I plot the model, the input and output shapes do not place on top of each

How to import a manually downloaded dataset in Tensorflow?

I know that it can be loaded using tfds.load('nyu_depth_v2') and I have try it but it fails I suspect due to my slow internet connection I have downloaded the d

How to train LSTM model with variable-length sequence input

I'm trying to train LSTM model in Keras using data of variable timestep, for example, the data looks like: <tf.RaggedTensor [[[0.0, 0.0, 0.0, 0.0, 0.0, 1.0,

How to speed up Tensorflow 2 keras model for inference?

So there's a big update nowadays, moving from TensorFlow 1.X to 2.X. In TF 1.X I got use to a pipeline which helped me to push my keras model to production. Th

TENSORFLOW: UNSUPPORTABLE CALLABLE

I am trying to build the following model but am getting this error when I am finally training the model and trying to get it's accuracy. It gets stuck when I am

TFlite model.process() sometimes needs input data TensorImage and sometimes TensorBuffer to process an image? Are there different image input data?

Some TFlite models model.process() seems to need TensorBuffer and other rather needs TensorImage . I don't know why? First, I took a regular TensorFlow / Keras

How to reset the state of an LSTM RNN after each epoch within Keras?

I have defined a stateful LSTM RNN, and I want to reset the state of the RNN after each epoch. I have found that one way to do this would be: n_epochs = 50 for

TypeError: 'AutoTrackable' object is not callable

I am trying to run inference on my trained model following this tutorial. I am using TF 2.1.0 and I have tried with tf-nightly 2.5.0.dev20201202. But I get Type

Tensorflow classification predictions

I'm dealing with a simple classification problem and I'm new to it. I want it to give results like 0 and 1, but it gives a percentage ending as below. how can i