forked from mindspore-Ecosystem/mindspore
add testcase for padded dataset with decode op
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@ -1,8 +1,12 @@
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from io import BytesIO
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import os
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import numpy as np
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import pytest
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import mindspore.dataset as ds
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from mindspore.mindrecord import FileWriter
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import mindspore.dataset.transforms.vision.c_transforms as V_C
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from PIL import Image
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FILES_NUM = 4
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CV_FILE_NAME = "../data/mindrecord/imagenet.mindrecord"
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CV_DIR_NAME = "../data/mindrecord/testImageNetData"
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@ -197,7 +201,7 @@ def test_raise_error():
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ds3.use_sampler(testsampler)
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assert excinfo.type == 'ValueError'
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def test_imagefolden_padded():
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def test_imagefolder_padded():
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DATA_DIR = "../data/dataset/testPK/data"
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data = ds.ImageFolderDatasetV2(DATA_DIR)
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@ -220,6 +224,32 @@ def test_imagefolden_padded():
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assert verify_list[8] == 1
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assert verify_list[9] == 6
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def test_imagefolder_padded_with_decode():
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DATA_DIR = "../data/dataset/testPK/data"
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data = ds.ImageFolderDatasetV2(DATA_DIR)
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white_io = BytesIO()
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Image.new('RGB', (224, 224), (255, 255, 255)).save(white_io, 'JPEG')
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padded_sample = {}
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padded_sample['image'] = np.array(bytearray(white_io), dtype='uint8')
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padded_sample['label'] = np.array(-1, np.int32)
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white_samples = [padded_sample, padded_sample, padded_sample, padded_sample]
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data2 = ds.PaddedDataset(white_samples)
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data3 = data + data2
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num_shards = 5
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count = 0
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for shard_id in range(num_shards):
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testsampler = ds.DistributedSampler(num_shards=num_shards, shard_id=shard_id, shuffle=False, num_samples=None)
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data3.use_sampler(testsampler)
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data3.map(input_columns="image", operations=V_C.Decode())
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for ele in data3.create_dict_iterator():
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print("label: {}".format(ele['label']))
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count += 1
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assert count == 48
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def test_more_shard_padded():
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result_list = []
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for i in range(8):
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