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!3102 [MD] Add additional parameter checks in RandomCropWithBBoxOp and RandomResizeWithBbox 

Merge pull request !3102 from nhussain/random_crop_fixes
This commit is contained in:
mindspore-ci-bot 2020-07-17 22:33:50 +08:00 committed by Gitee
parent 07f1d35ede 5871ba8a05
commit a84092e89d
9 changed files with 87 additions and 19 deletions
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4
mindspore/dataset/core/validator_helpers.py
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@ -189,8 +189,10 @@ def type_check_list(args, types, arg_names):
Exception: when the type is not correct, otherwise nothing.
"""
type_check(args, (list, tuple,), arg_names)
if len(args) != len(arg_names):
if len(args) != len(arg_names) and not isinstance(arg_names, str):
raise ValueError("List of arguments is not the same length as argument_names.")
if isinstance(arg_names, str):
arg_names = ["{0}[{1}]".format(arg_names, i) for i in range(len(args))]
for arg, arg_name in zip(args, arg_names):
type_check(arg, types, arg_name)

6
mindspore/dataset/engine/validators.py
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@ -686,8 +686,7 @@ def check_concat(method):
[ds], _ = parse_user_args(method, *args, **kwargs)
type_check(ds, (list, datasets.Dataset), "datasets")
if isinstance(ds, list):
dataset_names = ["dataset[{0}]".format(i) for i in range(len(ds)) if isinstance(ds, list)]
type_check_list(ds, (datasets.Dataset,), dataset_names)
type_check_list(ds, (datasets.Dataset,), "dataset")
return method(self, *args, **kwargs)
return new_method
@ -751,8 +750,7 @@ def check_add_column(method):
if shape is not None:
type_check(shape, (list,), "shape")
shape_names = ["shape[{0}]".format(i) for i in range(len(shape))]
type_check_list(shape, (int,), shape_names)
type_check_list(shape, (int,), "shape")
return method(self, *args, **kwargs)

3
mindspore/dataset/text/validators.py
View File

@ -297,8 +297,7 @@ def check_from_dataset(method):
if columns is not None:
if not isinstance(columns, list):
columns = [columns]
col_names = ["col_{0}".format(i) for i in range(len(columns))]
type_check_list(columns, (str,), col_names)
type_check_list(columns, (str,), "col")
if freq_range is not None:
type_check(freq_range, (tuple,), "freq_range")

13
mindspore/dataset/transforms/vision/validators.py
View File

@ -78,6 +78,8 @@ def check_fill_value(fill_value):
def check_padding(padding):
"""Parsing the padding arguments and check if it is legal."""
type_check(padding, (tuple, list, numbers.Number), "padding")
if isinstance(padding, numbers.Number):
check_value(padding, (0, INT32_MAX), "padding")
if isinstance(padding, (tuple, list)):
if len(padding) not in (2, 4):
raise ValueError("The size of the padding list or tuple should be 2 or 4.")
@ -163,10 +165,13 @@ def check_random_resize_crop(method):
check_crop_size(size)
if scale is not None:
type_check(scale, (tuple,), "scale")
type_check_list(scale, (float, int), "scale")
check_range(scale, [0, FLOAT_MAX_INTEGER])
if ratio is not None:
type_check(ratio, (tuple,), "ratio")
type_check_list(ratio, (float, int), "ratio")
check_range(ratio, [0, FLOAT_MAX_INTEGER])
check_positive(ratio[0], "ratio[0]")
if interpolation is not None:
type_check(interpolation, (Inter,), "interpolation")
if max_attempts is not None:
@ -450,8 +455,7 @@ def check_random_affine(method):
if translate is not None:
if type_check(translate, (list, tuple), "translate"):
translate_names = ["translate_{0}".format(i) for i in range(len(translate))]
type_check_list(translate, (int, float), translate_names)
type_check_list(translate, (int, float), "translate")
if len(translate) != 2:
raise TypeError("translate should be a list or tuple of length 2.")
for i, t in enumerate(translate):
@ -508,8 +512,7 @@ def check_uniform_augment_cpp(method):
if num_ops > len(operations):
raise ValueError("num_ops is greater than operations list size")
tensor_ops = ["tensor_op_{0}".format(i) for i in range(len(operations))]
type_check_list(operations, (TensorOp,), tensor_ops)
type_check_list(operations, (TensorOp,), "tensor_ops")
return method(self, *args, **kwargs)

2
tests/ut/python/dataset/test_from_dataset.py
View File

@ -134,7 +134,7 @@ def test_from_dataset_exceptions():
test_config("text", (), 1, "freq_range needs to be a tuple of 2 integers or an int and a None.")
test_config("text", (2, 3), 1.2345,
"Argument top_k with value 1.2345 is not of type (<class 'int'>, <class 'NoneType'>)")
test_config(23, (2, 3), 1.2345, "Argument col_0 with value 23 is not of type (<class 'str'>,)")
test_config(23, (2, 3), 1.2345, "Argument col[0] with value 23 is not of type (<class 'str'>,)")
test_config("text", (100, 1), 12, "frequency range [a,b] should be 0 <= a <= b (a,b are inclusive)")
test_config("text", (2, 3), 0, "top_k must be greater than 0")
test_config([123], (2, 3), -1, "top_k must be greater than 0")

29
tests/ut/python/dataset/test_random_crop_and_resize.py
View File

@ -332,11 +332,37 @@ def test_random_crop_and_resize_comp(plot=False):
image_c_cropped.append(c_image)
image_py_cropped.append(py_image)
mse = diff_mse(c_image, py_image)
assert mse < 0.02 # rounding error
assert mse < 0.02 # rounding error
if plot:
visualize_list(image_c_cropped, image_py_cropped, visualize_mode=2)
def test_random_crop_and_resize_06():
"""
Test RandomCropAndResize with c_transforms: invalid values for scale,
expected to raise ValueError
"""
logger.info("test_random_crop_and_resize_05_c")
# Generate dataset
data = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
decode_op = c_vision.Decode()
try:
random_crop_and_resize_op = c_vision.RandomResizedCrop((256, 512), scale="", ratio=(1, 0.5))
data = data.map(input_columns=["image"], operations=decode_op)
data.map(input_columns=["image"], operations=random_crop_and_resize_op)
except TypeError as e:
logger.info("Got an exception in DE: {}".format(str(e)))
assert "Argument scale with value \"\" is not of type (<class 'tuple'>,)" in str(e)
try:
random_crop_and_resize_op = c_vision.RandomResizedCrop((256, 512), scale=(1, "2"), ratio=(1, 0.5))
data = data.map(input_columns=["image"], operations=decode_op)
data.map(input_columns=["image"], operations=random_crop_and_resize_op)
except TypeError as e:
logger.info("Got an exception in DE: {}".format(str(e)))
assert "Argument scale[1] with value 2 is not of type (<class 'float'>, <class 'int'>)." in str(e)
if __name__ == "__main__":
test_random_crop_and_resize_op_c(True)
test_random_crop_and_resize_op_py(True)
@ -347,4 +373,5 @@ if __name__ == "__main__":
test_random_crop_and_resize_04_py()
test_random_crop_and_resize_05_c()
test_random_crop_and_resize_05_py()
test_random_crop_and_resize_06()
test_random_crop_and_resize_comp(True)

30
tests/ut/python/dataset/test_random_crop_with_bbox.py
View File

@ -178,13 +178,15 @@ def test_random_crop_with_bbox_op_edge_c(plot_vis=False):
dataVoc1 = dataVoc1.map(input_columns=["image", "annotation"],
output_columns=["image", "annotation"],
columns_order=["image", "annotation"],
operations=[lambda img, bboxes: (img, np.array([[0, 0, img.shape[1], img.shape[0]]]).astype(bboxes.dtype))])
operations=[lambda img, bboxes: (
img, np.array([[0, 0, img.shape[1], img.shape[0]]]).astype(bboxes.dtype))])
# Test Op added to list of Operations here
dataVoc2 = dataVoc2.map(input_columns=["image", "annotation"],
output_columns=["image", "annotation"],
columns_order=["image", "annotation"],
operations=[lambda img, bboxes: (img, np.array([[0, 0, img.shape[1], img.shape[0]]]).astype(bboxes.dtype)), test_op])
operations=[lambda img, bboxes: (
img, np.array([[0, 0, img.shape[1], img.shape[0]]]).astype(bboxes.dtype)), test_op])
unaugSamp, augSamp = [], []
@ -239,6 +241,29 @@ def test_random_crop_with_bbox_op_bad_c():
check_bad_bbox(data_voc2, test_op, InvalidBBoxType.WrongShape, "4 features")
def test_random_crop_with_bbox_op_negative_padding():
"""
Test RandomCropWithBBox Op on invalid constructor parameters, expected to raise ValueError
"""
logger.info("test_random_crop_with_bbox_op_invalid_c")
dataVoc2 = ds.VOCDataset(DATA_DIR_VOC, task="Detection", mode="train", decode=True, shuffle=False)
try:
test_op = c_vision.RandomCropWithBBox([512, 512], padding=-1)
dataVoc2 = dataVoc2.map(input_columns=["image", "annotation"],
output_columns=["image", "annotation"],
columns_order=["image", "annotation"],
operations=[test_op])
for _ in dataVoc2.create_dict_iterator():
break
except ValueError as err:
logger.info("Got an exception in DE: {}".format(str(err)))
assert "Input padding is not within the required interval of (0 to 2147483647)." in str(err)
if __name__ == "__main__":
test_random_crop_with_bbox_op_c(plot_vis=True)
test_random_crop_with_bbox_op_coco_c(plot_vis=True)
@ -247,3 +272,4 @@ if __name__ == "__main__":
test_random_crop_with_bbox_op_edge_c(plot_vis=True)
test_random_crop_with_bbox_op_invalid_c()
test_random_crop_with_bbox_op_bad_c()
test_random_crop_with_bbox_op_negative_padding()

15
tests/ut/python/dataset/test_resize_with_bbox.py
View File

@ -16,9 +16,10 @@
Testing the resize with bounding boxes op in DE
"""
import numpy as np
import pytest
import mindspore.dataset as ds
import mindspore.dataset.transforms.vision.c_transforms as c_vision
from mindspore import log as logger
from util import visualize_with_bounding_boxes, InvalidBBoxType, check_bad_bbox, \
save_and_check_md5
@ -172,6 +173,18 @@ def test_resize_with_bbox_op_bad_c():
check_bad_bbox(data_voc2, test_op, InvalidBBoxType.WrongShape, "4 features")
def test_resize_with_bbox_op_params_outside_of_interpolation_dict():
"""
Test passing in a invalid key for interpolation
"""
logger.info("test_resize_with_bbox_op_params_outside_of_interpolation_dict")
size = (500, 500)
more_para = None
with pytest.raises(KeyError, match="None"):
c_vision.ResizeWithBBox(size, more_para)
if __name__ == "__main__":
test_resize_with_bbox_op_voc_c(plot_vis=False)
test_resize_with_bbox_op_coco_c(plot_vis=False)

4
tests/ut/python/dataset/test_uniform_augment.py
View File

@ -166,10 +166,10 @@ def test_cpp_uniform_augment_exception_pyops(num_ops=2):
F.Invert()]
with pytest.raises(TypeError) as e:
_ = C.UniformAugment(operations=transforms_ua, num_ops=num_ops)
C.UniformAugment(operations=transforms_ua, num_ops=num_ops)
logger.info("Got an exception in DE: {}".format(str(e)))
assert "Argument tensor_op_5 with value" \
assert "Argument tensor_ops[5] with value" \
" <mindspore.dataset.transforms.vision.py_transforms.Invert" in str(e.value)
assert "is not of type (<class 'mindspore._c_dataengine.TensorOp'>,)" in str(e.value)