Category : tensorflow-datasets

When I was downloading "imbd_reviews" dataset I am facing the below error, ‘utf-8’ codec can’t decode byte 0xc5 in position 171: invalid continuation byte import tensorflow_datasets as tfds datasets, info = tfds.load("imdb_reviews",as_supervised=True, with_info=True) Downloading and preparing dataset imdb_reviews (80.23 MiB) to C:Usersdesigtensorflow_datasetsimdb_reviewsplain_text{$content}.1.0… Dl Completed…: 0/0 [00:00<?, ? url/s] Dl Size…: 0/0 [00:00<?, ? MiB/s] ————————————————————————— ..

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As per the example in https://keras.io/examples/generative/cyclegan/, a pre-existing dataset has been loaded for implementation. I am trying to add my dataset. import tensorflow_datasets as tfds data = tfds.folder_dataset.ImageFolder(‘Images’, shape=(256, 256, 3)) ds = data.as_dataset() where ‘Images’ is the root folder containing two subfolders train and test. train folder containing trainA and trainB , test containing ..

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I am getting this error for my code: ValueError: Expect x to be a non-empty array or dataset. ”’ history_101_horses_or_humans_feature_extract = model.fit(train_data, epochs=5, steps_per_epoch=int(0.01 * len(train_data)), validation_data=test_data, validation_steps=int(0.01 * len(test_data)), callbacks=[create_tensorboard_callback(‘training_logs’, ‘efficientnetb0_horses_or_humans_feature_extract’), model_checkpoint]) ”’ Should I do tf.expand_dims or something else? I’m very new at this. Thank you very much! Josh Source: Python-3x..

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this is my model def define_model(vocab_size, max_length): input = Input(shape=(1120,)) x = Dropout(0.2)(input) x = Dense(256, activation=’relu’) input1 = Input(shape=(max_length,)) y = Embedding(vocab_size, 256, mask_zero=True)(input1) y = GRU(512,return_sequences = True) y = GRU(512,return_sequences = False) z = Concatenate()([x, y]) t = Dropout(0.2)(z) t = Dense(vocab_size, activation=’softmax’) model = Model(inputs=[input, input1], outputs=t) model.compile(loss=’categorical_crossentropy’, optimizer=’adam’, metrics=[‘accuracy’]) return ..

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I have downloaded tensorflow and tensorflow_datasets (pip3 install tensorflow_datasets for the latter) and they both show up in my pip3 list when I run it in the terminal. When I try to run code after doing import tensorflow_datasets as tfds I get an error saying ModuleNotFoundError: No module named ‘tensorflow_datasets’ . I don’t believe I ..

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I have a dataset of images and I am using tf.keras.preprocessing.image_dataset_from_directory to load images in batches and potentially create a data pipeline. I’m trying to process the images and convert them to Lab colorspace. I am able to do it manually by using .take() and parsing through the tensors but I can’t make it so ..

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