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- #! /usr/bin/python
- # -*- coding: utf-8 -*-
-
- import os
- # os.environ['TL_BACKEND'] = 'tensorflow'
- os.environ['TL_BACKEND'] = 'mindspore'
-
- import tensorlayerx as tlx
- from tensorlayerx.nn import Module
- from tensorlayerx.nn import Linear, Flatten
- from tensorlayerx.vision.transforms import Normalize, Compose
- from tensorlayerx.dataflow import Dataset, IterableDataset
-
- transform = Compose([Normalize(mean=[127.5], std=[127.5], data_format='HWC')])
-
- print('download training data and load training data')
-
- X_train, y_train, X_val, y_val, X_test, y_test = tlx.files.load_mnist_dataset(shape=(-1, 28, 28, 1))
- X_train = X_train * 255
-
- print('load finished')
-
-
- class mnistdataset(Dataset):
-
- def __init__(self, data=X_train, label=y_train, transform=transform):
- self.data = data
- self.label = label
- self.transform = transform
-
- def __getitem__(self, index):
- data = self.data[index].astype('float32')
- data = self.transform(data)
- label = self.label[index].astype('int64')
-
- return data, label
-
- def __len__(self):
-
- return len(self.data)
-
-
- train_dataset = mnistdataset(data=X_train, label=y_train, transform=transform)
- train_loader = tlx.dataflow.DataLoader(train_dataset, batch_size=128, shuffle=True)
-
- for i in train_loader:
- print(i[0].shape, type(i[0]), i[1])
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