forked from mindspore-Ecosystem/mindspore
!29 Add some prompt information for ease of use
Merge pull request !29 from jonyguo/add_more_log_info_and_testcase
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4f5755003a
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@ -66,11 +66,10 @@ def _alter_node(node):
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class Iterator:
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"""
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General Iterator over a dataset.
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Attributes:
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dataset: Dataset to be iterated over
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General Iterator over a dataset.
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Attributes:
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dataset: Dataset to be iterated over
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"""
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def __init__(self, dataset):
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@ -86,6 +85,7 @@ class Iterator:
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root = self.__convert_node_postorder(self.dataset)
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self.depipeline.AssignRootNode(root)
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self.depipeline.LaunchTreeExec()
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self._index = 0
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def __is_tree_node(self, node):
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"""Check if a node is tree node."""
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@ -185,10 +185,7 @@ class Iterator:
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Iterator.__print_local(input_op, level + 1)
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def print(self):
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"""
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Print the dataset tree
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"""
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"""Print the dataset tree"""
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self.__print_local(self.dataset, 0)
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def release(self):
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@ -202,7 +199,10 @@ class Iterator:
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def __next__(self):
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data = self.get_next()
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if not data:
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if self._index == 0:
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logger.warning("No records available.")
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raise StopIteration
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self._index += 1
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return data
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def get_output_shapes(self):
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@ -234,7 +234,7 @@ class DictIterator(Iterator):
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def get_next(self):
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"""
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Returns the next record in the dataset as dictionary
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Returns the next record in the dataset as dictionary
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Returns:
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Dict, the next record in the dataset.
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@ -260,7 +260,7 @@ class TupleIterator(Iterator):
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def get_next(self):
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"""
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Returns the next record in the dataset as a list
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Returns the next record in the dataset as a list
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Returns:
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List, the next record in the dataset.
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@ -328,13 +328,20 @@ class FileWriter:
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self._generator.build()
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self._generator.write_to_db()
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mindrecord_files = []
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index_files = []
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# change the file mode to 600
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for item in self._paths:
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if os.path.exists(item):
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os.chmod(item, stat.S_IRUSR | stat.S_IWUSR)
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mindrecord_files.append(item)
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index_file = item + ".db"
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if os.path.exists(index_file):
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os.chmod(index_file, stat.S_IRUSR | stat.S_IWUSR)
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index_files.append(index_file)
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logger.info("The list of mindrecord files created are: {}, and the list of index files are: {}".format(
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mindrecord_files, index_files))
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return ret
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@ -25,6 +25,7 @@ import mindspore.dataset.transforms.vision.c_transforms as vision
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import numpy as np
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import pytest
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from mindspore._c_dataengine import InterpolationMode
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from mindspore.dataset.transforms.vision import Inter
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from mindspore import log as logger
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import mindspore.dataset as ds
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@ -151,6 +152,51 @@ def test_cv_minddataset_dataset_size(add_and_remove_cv_file):
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assert data_set.get_dataset_size() == 3
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def test_cv_minddataset_repeat_reshuffle(add_and_remove_cv_file):
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"""tutorial for cv minddataset."""
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columns_list = ["data", "label"]
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num_readers = 4
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data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers)
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decode_op = vision.Decode()
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data_set = data_set.map(input_columns=["data"], operations=decode_op, num_parallel_workers=2)
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resize_op = vision.Resize((32, 32), interpolation=Inter.LINEAR)
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data_set = data_set.map(input_columns="data", operations=resize_op, num_parallel_workers=2)
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data_set = data_set.batch(2)
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data_set = data_set.repeat(2)
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num_iter = 0
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labels = []
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for item in data_set.create_dict_iterator():
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logger.info("-------------- get dataset size {} -----------------".format(num_iter))
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logger.info("-------------- item[label]: {} ---------------------".format(item["label"]))
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logger.info("-------------- item[data]: {} ----------------------".format(item["data"]))
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num_iter += 1
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labels.append(item["label"])
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assert num_iter == 10
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logger.info("repeat shuffle: {}".format(labels))
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assert len(labels) == 10
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assert labels[0:5] == labels[0:5]
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assert labels[0:5] != labels[5:5]
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def test_cv_minddataset_batch_size_larger_than_records(add_and_remove_cv_file):
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"""tutorial for cv minddataset."""
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columns_list = ["data", "label"]
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num_readers = 4
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data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers)
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decode_op = vision.Decode()
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data_set = data_set.map(input_columns=["data"], operations=decode_op, num_parallel_workers=2)
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resize_op = vision.Resize((32, 32), interpolation=Inter.LINEAR)
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data_set = data_set.map(input_columns="data", operations=resize_op, num_parallel_workers=2)
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data_set = data_set.batch(32, drop_remainder=True)
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num_iter = 0
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for item in data_set.create_dict_iterator():
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logger.info("-------------- get dataset size {} -----------------".format(num_iter))
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logger.info("-------------- item[label]: {} ---------------------".format(item["label"]))
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logger.info("-------------- item[data]: {} ----------------------".format(item["data"]))
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num_iter += 1
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assert num_iter == 0
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def test_cv_minddataset_issue_888(add_and_remove_cv_file):
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"""issue 888 test."""
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columns_list = ["data", "label"]
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