mirror of
https://github.com/hexastack/hexabot
synced 2024-12-29 15:31:04 +00:00
30 lines
947 B
Python
30 lines
947 B
Python
import tensorflow as tf
|
|
|
|
import boilerplate as tfbp
|
|
|
|
|
|
@tfbp.default_export
|
|
class MNIST(tfbp.DataLoader):
|
|
default_hparams = {"batch_size": 32}
|
|
|
|
def __call__(self):
|
|
train_data, test_data = tf.keras.datasets.mnist.load_data()
|
|
test_data = tf.data.Dataset.from_tensor_slices(test_data)
|
|
|
|
if self.method in ["fit", "train"]:
|
|
train_data = tf.data.Dataset.from_tensor_slices(train_data).shuffle(10000)
|
|
test_data = test_data.shuffle(10000)
|
|
train_data = self._transform_dataset(train_data)
|
|
return train_data, test_data
|
|
|
|
return self._transform_dataset(test_data)
|
|
|
|
def _transform_dataset(self, dataset):
|
|
dataset = dataset.batch(self.hparams.batch_size)
|
|
return dataset.map(
|
|
lambda x, y: (
|
|
tf.reshape(tf.cast(x, tf.float32) / 255.0, [-1, 28 * 28]), # type: ignore
|
|
tf.cast(y, tf.int64),
|
|
)
|
|
)
|