forked from huawei/mindspore2022
246 lines
9.9 KiB
Python
246 lines
9.9 KiB
Python
# Copyright 2022 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""
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Test Dataset AutoTune's Save and Load Configuration support
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"""
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import os
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import json
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import random
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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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import mindspore.dataset.transforms.c_transforms as c_transforms
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import mindspore.dataset.vision.c_transforms as c_vision
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MNIST_DATA_DIR = "../data/dataset/testMnistData"
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DATA_DIR = "../data/dataset/testPK/data"
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def data_pipeline_same(file1, file2):
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assert file1.exists()
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assert file2.exists()
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with file1.open() as f1, file2.open() as f2:
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pipeline1 = json.load(f1)
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pipeline1 = pipeline1["tree"] if "tree" in pipeline1 else pipeline1
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pipeline2 = json.load(f2)
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pipeline2 = pipeline2["tree"] if "tree" in pipeline2 else pipeline2
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return pipeline1 == pipeline2
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@pytest.mark.forked
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class TestAutotuneSaveLoad:
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# Note: Use pytest fixture tmp_path to create files within this temporary directory,
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# which is automatically created for each test and deleted at the end of the test.
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@staticmethod
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def setup_method():
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os.environ['RANK_ID'] = str(random.randint(0, 9))
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@staticmethod
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def teardown_method():
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del os.environ['RANK_ID']
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@staticmethod
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def test_autotune_generator_pipeline(tmp_path):
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"""
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Feature: Autotuning
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Description: Test save final config with GeneratorDataset pipeline: Generator -> Shuffle -> Batch
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Expectation: pipeline runs successfully
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"""
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original_autotune = ds.config.get_enable_autotune()
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ds.config.set_enable_autotune(True, str(tmp_path / "test_autotune_generator_atfinal"))
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source = [(np.array([x]),) for x in range(1024)]
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data1 = ds.GeneratorDataset(source, ["data"])
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data1 = data1.shuffle(64)
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data1 = data1.batch(32)
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ds.serialize(data1, str(tmp_path / "test_autotune_generator_serialized.json"))
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itr = data1.create_dict_iterator(num_epochs=5)
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for _ in range(5):
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for _ in itr:
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pass
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del itr
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ds.config.set_enable_autotune(original_autotune)
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file = tmp_path / ("test_autotune_generator_atfinal_" + os.environ['RANK_ID'] + ".json")
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assert file.exists()
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@staticmethod
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def test_autotune_save_overwrite_generator(tmp_path):
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"""
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Feature: Autotuning
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Description: Test set_enable_autotune and existing json_filepath is overwritten
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Expectation: set_enable_autotune() executes successfully with file-exist warning produced.
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Execution of 2nd pipeline overwrites AutoTune configuration file of 1st pipeline.
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"""
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source = [(np.array([x]),) for x in range(1024)]
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at_final_json_filename = "test_autotune_save_overwrite_generator_atfinal.json"
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original_autotune = ds.config.get_enable_autotune()
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ds.config.set_enable_autotune(True, str(tmp_path / at_final_json_filename))
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data1 = ds.GeneratorDataset(source, ["data"])
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for _ in data1.create_dict_iterator(num_epochs=1, output_numpy=True):
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pass
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ds.config.set_enable_autotune(False)
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ds.config.set_enable_autotune(True, str(tmp_path) + at_final_json_filename)
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data2 = ds.GeneratorDataset(source, ["data"])
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data2 = data2.shuffle(64)
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for _ in data2.create_dict_iterator(num_epochs=1, output_numpy=True):
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pass
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ds.config.set_enable_autotune(original_autotune)
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@staticmethod
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def test_autotune_mnist_pipeline(tmp_path):
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"""
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Feature: Autotuning
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Description: Test save final config with Mnist pipeline: Mnist -> Batch -> Map
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Expectation: pipeline runs successfully
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"""
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original_autotune = ds.config.get_enable_autotune()
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ds.config.set_enable_autotune(True, str(tmp_path / "test_autotune_mnist_pipeline_atfinal"))
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original_seed = ds.config.get_seed()
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ds.config.set_seed(1)
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data1 = ds.MnistDataset(MNIST_DATA_DIR, num_samples=100)
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one_hot_encode = c_transforms.OneHot(10) # num_classes is input argument
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data1 = data1.map(operations=one_hot_encode, input_columns="label")
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data1 = data1.batch(batch_size=10, drop_remainder=True)
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ds.serialize(data1, str(tmp_path / "test_autotune_mnist_pipeline_serialized.json"))
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for _ in data1.create_dict_iterator(num_epochs=1, output_numpy=True):
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pass
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ds.config.set_enable_autotune(original_autotune)
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# Confirm final AutoTune config file pipeline is identical to the serialized file pipeline.
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file1 = tmp_path / ("test_autotune_mnist_pipeline_atfinal_" + os.environ['RANK_ID'] + ".json")
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file2 = tmp_path / "test_autotune_mnist_pipeline_serialized.json"
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assert data_pipeline_same(file1, file2)
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desdata1 = ds.deserialize(json_filepath=str(file1))
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desdata2 = ds.deserialize(json_filepath=str(file2))
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num = 0
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for newdata1, newdata2 in zip(desdata1.create_dict_iterator(num_epochs=1, output_numpy=True),
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desdata2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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np.testing.assert_array_equal(newdata1['image'], newdata2['image'])
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np.testing.assert_array_equal(newdata1['label'], newdata2['label'])
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num += 1
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assert num == 10
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ds.config.set_seed(original_seed)
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@staticmethod
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def test_autotune_warning_with_offload(tmp_path, capfd):
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"""
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Feature: Autotuning
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Description: Test autotune config saving with offload=True
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Expectation: Autotune should not write the config file and print a log message
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"""
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original_seed = ds.config.get_seed()
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ds.config.set_seed(1)
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at_final_json_filename = "test_autotune_warning_with_offload_config.json"
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config_path = tmp_path / at_final_json_filename
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original_autotune = ds.config.get_enable_autotune()
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ds.config.set_enable_autotune(True, str(config_path))
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# Dataset with offload activated.
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dataset = ds.ImageFolderDataset(DATA_DIR, num_samples=8)
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dataset = dataset.map(operations=[c_vision.Decode()], input_columns="image")
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dataset = dataset.map(operations=[c_vision.HWC2CHW()], input_columns="image", offload=True)
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dataset = dataset.batch(8, drop_remainder=True)
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for _ in dataset.create_tuple_iterator(num_epochs=1, output_numpy=True):
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pass
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_, err = capfd.readouterr()
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assert "Some nodes have been offloaded. AutoTune is unable to write the autotune configuration to disk. " \
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"Disable offload to prevent this from happening." in err
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with pytest.raises(FileNotFoundError):
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with open(config_path) as _:
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pass
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ds.config.set_enable_autotune(original_autotune)
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ds.config.set_seed(original_seed)
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@staticmethod
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def test_autotune_save_overwrite_mnist(tmp_path):
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"""
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Feature: Autotuning
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Description: Test set_enable_autotune and existing json_filepath is overwritten
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Expectation: set_enable_autotune() executes successfully with file-exist warning produced.
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Execution of 2nd pipeline overwrites AutoTune configuration file of 1st pipeline.
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"""
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original_seed = ds.config.get_seed()
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ds.config.set_seed(1)
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at_final_json_filename = "test_autotune_save_overwrite_mnist_atfinal"
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# Pipeline#1
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original_autotune = ds.config.get_enable_autotune()
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ds.config.set_enable_autotune(True, str(tmp_path / at_final_json_filename))
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data1 = ds.MnistDataset(MNIST_DATA_DIR, num_samples=100)
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one_hot_encode = c_transforms.OneHot(10) # num_classes is input argument
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data1 = data1.map(operations=one_hot_encode, input_columns="label")
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data1 = data1.batch(batch_size=10, drop_remainder=True)
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ds.serialize(data1, str(tmp_path / "test_autotune_save_overwrite_mnist_serialized1.json"))
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for _ in data1.create_dict_iterator(num_epochs=1, output_numpy=True):
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pass
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ds.config.set_enable_autotune(False)
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# Pipeline#2
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ds.config.set_enable_autotune(True, str(tmp_path / at_final_json_filename))
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data1 = ds.MnistDataset(MNIST_DATA_DIR, num_samples=200)
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data1 = data1.map(operations=one_hot_encode, input_columns="label")
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data1 = data1.shuffle(40)
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data1 = data1.batch(batch_size=20, drop_remainder=False)
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ds.serialize(data1, str(tmp_path / "test_autotune_save_overwrite_mnist_serialized2.json"))
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for _ in data1.create_dict_iterator(num_epochs=1, output_numpy=True):
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pass
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ds.config.set_enable_autotune(False)
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# Confirm 2nd serialized file is identical to final AutoTune config file.
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file1 = tmp_path / ("test_autotune_save_overwrite_mnist_atfinal_" + os.environ['RANK_ID'] + ".json")
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file2 = tmp_path / "test_autotune_save_overwrite_mnist_serialized2.json"
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assert data_pipeline_same(file1, file2)
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# Confirm the serialized files for the 2 different pipelines are different
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file1 = tmp_path / "test_autotune_save_overwrite_mnist_serialized1.json"
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file2 = tmp_path / "test_autotune_save_overwrite_mnist_serialized2.json"
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assert not data_pipeline_same(file1, file2)
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ds.config.set_seed(original_seed)
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ds.config.set_enable_autotune(original_autotune)
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