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tensorflow load_data

Load and preprocess images | TensorFlow Core
https://www.tensorflow.org › images
Load data using a Keras utility. Create a dataset; Visualize the data; Standardize the data; Configure the dataset for performance ...
Load and preprocess images | TensorFlow Core
https://www.tensorflow.org/tutorials/load_data/images
11.11.2021 · This tutorial shows how to load and preprocess an image dataset in three ways: First, you will use high-level Keras preprocessing utilities (such as tf.keras.utils.image_dataset_from_directory) and layers (such as tf.keras.layers.Rescaling) to read a directory of images on disk.; Next, you will write your own input pipeline from scratch using …
tf.keras.datasets.imdb.load_data | TensorFlow Core v2.7.0
https://www.tensorflow.org/api_docs/python/tf/keras/datasets/imdb/load_data
09.01.2022 · TensorFlow 1 version View source on GitHub Loads the IMDB dataset. tf.keras.datasets.imdb.load_data ( path='imdb.npz', num_words=None, skip_top=0, maxlen=None, seed=113, start_char=1, oov_char=2, index_from=3, **kwargs ) This is a dataset of 25,000 movies reviews from IMDB, labeled by sentiment (positive/negative).
Load NumPy data | TensorFlow Core
www.tensorflow.org › tutorials › load_data
Nov 11, 2021 · import numpy as np import tensorflow as tf Load from .npz file DATA_URL = 'https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz' path = tf.keras.utils.get_file('mnist.npz', DATA_URL) with np.load(path) as data: train_examples = data['x_train'] train_labels = data['y_train'] test_examples = data['x_test'] test_labels = data['y_test']
Load and preprocess images | TensorFlow Core
www.tensorflow.org › tutorials › load_data
Nov 11, 2021 · def process_path(file_path): label = get_label(file_path) # Load the raw data from the file as a string. img = tf.io.read_file(file_path) img = decode_img(img) return img, label. Use Dataset.map to create a dataset of image, label pairs: # Set `num_parallel_calls` so multiple images are loaded/processed in parallel.
tf.keras.datasets.boston_housing.load_data - TensorFlow
https://www.tensorflow.org › api_docs › python › load_d...
TensorFlow Core v2.7.0 · Python. Was this helpful? tf.keras.datasets.boston_housing.load_data. On this page; Args; Returns ...
tf.keras.datasets.cifar100.load_data | TensorFlow Core v2.7.0
https://www.tensorflow.org › api_docs › python › load_d...
TensorFlow Core v2.7.0 · Python. Was this helpful? tf.keras.datasets.cifar100.load_data. On this page; Args; Returns ...
tf.keras.datasets.imdb.load_data | TensorFlow Core v2.7.0
www.tensorflow.org › keras › datasets
TensorFlow 1 version. View source on GitHub. Loads the IMDB dataset. View aliases. Compat aliases for migration. See Migration guide for more details. tf.compat.v1.keras.datasets.imdb.load_data. tf.keras.datasets.imdb.load_data ( path='imdb.npz', num_words=None, skip_top=0, maxlen=None, seed=113, start_char=1, oov_char=2, index_from=3, **kwargs ) This is a dataset of 25,000 movies reviews from IMDB, labeled by sentiment (positive/negative).
tf.keras.datasets.mnist.load_data | TensorFlow Core v2.7.0
https://www.tensorflow.org/api_docs/python/tf/keras/datasets/mnist/load_data
TensorFlow 1 version View source on GitHub Loads the MNIST dataset. tf.keras.datasets.mnist.load_data ( path='mnist.npz' ) Used in the notebooks This is a dataset of 60,000 28x28 grayscale images of the 10 digits, along with a test set of 10,000 images. More info can be found at the MNIST homepage. Returns
Load text | TensorFlow Core
https://www.tensorflow.org › text
Dataset and tf.keras.layers.TextVectorization for data standardization, tokenization, and vectorization. If you are new to TensorFlow, you ...
Python Examples of tensorflow.keras.datasets.mnist.load_data
https://www.programcreek.com › t...
load_data() Examples. The following are 24 code examples for showing how to use tensorflow.keras.datasets.mnist.load_data(). These ...
tf.keras.datasets.mnist.load_data | TensorFlow Core v2.7.0
www.tensorflow.org › datasets › mnist
Multi-worker training with Keras. Convolutional Variational Autoencoder. Deep Convolutional Generative Adversarial Network. Save and load models. This is a dataset of 60,000 28x28 grayscale images of the 10 digits, along with a test set of 10,000 images. More info can be found at the MNIST homepage.