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Added Fix for test config

tags/v0.6.0-beta
Eric 5 years ago
parent
commit
a4f5802924
1 changed files with 31 additions and 28 deletions
  1. +31
    -28
      tests/ut/python/dataset/test_config.py

+ 31
- 28
tests/ut/python/dataset/test_config.py View File

@@ -21,7 +21,7 @@ import glob
import numpy as np

import mindspore.dataset as ds
import mindspore.dataset.transforms.vision.c_transforms as vision
import mindspore.dataset.transforms.vision.c_transforms as c_vision
import mindspore.dataset.transforms.vision.py_transforms as py_vision
from mindspore import log as logger

@@ -85,12 +85,12 @@ def test_pipeline():

data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False)
ds.config.set_num_parallel_workers(2)
data1 = data1.map(input_columns=["image"], operations=[vision.Decode(True)])
data1 = data1.map(input_columns=["image"], operations=[c_vision.Decode(True)])
ds.serialize(data1, "testpipeline.json")

data2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False)
ds.config.set_num_parallel_workers(4)
data2 = data2.map(input_columns=["image"], operations=[vision.Decode(True)])
data2 = data2.map(input_columns=["image"], operations=[c_vision.Decode(True)])
ds.serialize(data2, "testpipeline2.json")

# check that the generated output is different
@@ -128,8 +128,8 @@ def test_deterministic_run_fail():
# Assuming we get the same seed on calling constructor, if this op is re-used then result won't be
# the same in between the two datasets. For example, RandomCrop constructor takes seed (0)
# outputs a deterministic series of numbers, e,g "a" = [1, 2, 3, 4, 5, 6] <- pretend these are random
random_crop_op = vision.RandomCrop([512, 512], [200, 200, 200, 200])
decode_op = vision.Decode()
random_crop_op = c_vision.RandomCrop([512, 512], [200, 200, 200, 200])
decode_op = c_vision.Decode()
data1 = data1.map(input_columns=["image"], operations=decode_op)
data1 = data1.map(input_columns=["image"], operations=random_crop_op)

@@ -153,24 +153,24 @@ def test_deterministic_run_fail():
ds.config.set_seed(seed_original)


def test_deterministic_run_pass():
def test_seed_undeterministic():
"""
Test deterministic run with setting the seed
Test seed with num parallel workers in c, this test is expected to fail some of the time
"""
logger.info("test_deterministic_run_pass")
logger.info("test_seed_undeterministic")

# Save original configuration values
num_parallel_workers_original = ds.config.get_num_parallel_workers()
seed_original = ds.config.get_seed()

ds.config.set_seed(0)
ds.config.set_num_parallel_workers(1)
ds.config.set_num_parallel_workers(3)

# First dataset
data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
# We get the seed when constructor is called
random_crop_op = vision.RandomCrop([512, 512], [200, 200, 200, 200])
decode_op = vision.Decode()
random_crop_op = c_vision.RandomCrop([512, 512], [200, 200, 200, 200])
decode_op = c_vision.Decode()
data1 = data1.map(input_columns=["image"], operations=decode_op)
data1 = data1.map(input_columns=["image"], operations=random_crop_op)

@@ -179,7 +179,7 @@ def test_deterministic_run_pass():
data2 = data2.map(input_columns=["image"], operations=decode_op)
# Since seed is set up on constructor, so the two ops output deterministic sequence.
# Assume the generated random sequence "a" = [1, 2, 3, 4, 5, 6] <- pretend these are random
random_crop_op2 = vision.RandomCrop([512, 512], [200, 200, 200, 200])
random_crop_op2 = c_vision.RandomCrop([512, 512], [200, 200, 200, 200])
data2 = data2.map(input_columns=["image"], operations=random_crop_op2)
try:
for item1, item2 in zip(data1.create_dict_iterator(), data2.create_dict_iterator()):
@@ -194,11 +194,11 @@ def test_deterministic_run_pass():
ds.config.set_seed(seed_original)


def test_seed_undeterministic():
def test_seed_deterministic():
"""
Test seed with num parallel workers in c, this test is expected to fail some of the time
Test deterministic run with setting the seed, only works with num_parallel worker = 1
"""
logger.info("test_seed_undeterministic")
logger.info("test_seed_deterministic")

# Save original configuration values
num_parallel_workers_original = ds.config.get_num_parallel_workers()
@@ -210,8 +210,8 @@ def test_seed_undeterministic():
# First dataset
data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
# seed will be read in during constructor call
random_crop_op = vision.RandomCrop([512, 512], [200, 200, 200, 200])
decode_op = vision.Decode()
random_crop_op = c_vision.RandomCrop([512, 512], [200, 200, 200, 200])
decode_op = c_vision.Decode()
data1 = data1.map(input_columns=["image"], operations=decode_op)
data1 = data1.map(input_columns=["image"], operations=random_crop_op)

@@ -219,7 +219,7 @@ def test_seed_undeterministic():
data2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
data2 = data2.map(input_columns=["image"], operations=decode_op)
# If seed is set up on constructor, so the two ops output deterministic sequence
random_crop_op2 = vision.RandomCrop([512, 512], [200, 200, 200, 200])
random_crop_op2 = c_vision.RandomCrop([512, 512], [200, 200, 200, 200])
data2 = data2.map(input_columns=["image"], operations=random_crop_op2)

for item1, item2 in zip(data1.create_dict_iterator(), data2.create_dict_iterator()):
@@ -246,8 +246,8 @@ def test_deterministic_run_distribution():

# First dataset
data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
random_crop_op = vision.RandomHorizontalFlip(0.1)
decode_op = vision.Decode()
random_crop_op = c_vision.RandomHorizontalFlip(0.1)
decode_op = c_vision.Decode()
data1 = data1.map(input_columns=["image"], operations=decode_op)
data1 = data1.map(input_columns=["image"], operations=random_crop_op)

@@ -255,7 +255,7 @@ def test_deterministic_run_distribution():
data2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
data2 = data2.map(input_columns=["image"], operations=decode_op)
# If seed is set up on constructor, so the two ops output deterministic sequence
random_crop_op2 = vision.RandomHorizontalFlip(0.1)
random_crop_op2 = c_vision.RandomHorizontalFlip(0.1)
data2 = data2.map(input_columns=["image"], operations=random_crop_op2)

for item1, item2 in zip(data1.create_dict_iterator(), data2.create_dict_iterator()):
@@ -270,7 +270,7 @@ def test_deterministic_python_seed():
"""
Test deterministic execution with seed in python
"""
logger.info("deterministic_random_crop_op_python_2")
logger.info("test_deterministic_python_seed")

# Save original configuration values
num_parallel_workers_original = ds.config.get_num_parallel_workers()
@@ -315,11 +315,12 @@ def test_deterministic_python_seed_multi_thread():
"""
Test deterministic execution with seed in python, this fails with multi-thread pyfunc run
"""
logger.info("deterministic_random_crop_op_python_2")
logger.info("test_deterministic_python_seed_multi_thread")

# Save original configuration values
num_parallel_workers_original = ds.config.get_num_parallel_workers()
seed_original = ds.config.get_seed()
ds.config.set_num_parallel_workers(3)
ds.config.set_seed(0)
# when we set the seed all operations within our dataset should be deterministic
# First dataset
@@ -355,15 +356,17 @@ def test_deterministic_python_seed_multi_thread():
assert "Array" in str(e)

# Restore original configuration values
ds.config.set_num_parallel_workers(num_parallel_workers_original)
ds.config.set_seed(seed_original)


if __name__ == '__main__':
test_basic()
test_get_seed()
test_pipeline()
test_deterministic_run_pass()
test_deterministic_run_distribution()
test_deterministic_run_fail()
test_deterministic_python_seed()
test_seed_undeterministic()
test_get_seed()
test_seed_deterministic()
test_deterministic_run_distribution()
test_deterministic_python_seed()
test_deterministic_python_seed_multi_thread()

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