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fix minddata issues

This commit is contained in:
luoyang 2021-03-18 22:15:02 +08:00
parent 34b16e6a64
commit e063146b3c
6 changed files with 37 additions and 14 deletions
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7
mindspore/ccsrc/minddata/dataset/api/iterator.cc
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@ -38,7 +38,6 @@ Status Iterator::GetNextRowCharIF(MSTensorMapChar *row) {
return rc;
}
for (auto de_tensor : md_map) {
CHECK_FAIL_RETURN_UNEXPECTED(de_tensor.second->HasData(), "Apply transform failed, output tensor has no data");
std::vector<char> col_name(de_tensor.first.begin(), de_tensor.first.end());
row->insert(std::make_pair(col_name, mindspore::MSTensor(std::make_shared<DETensor>(de_tensor.second))));
}
@ -57,10 +56,8 @@ Status Iterator::GetNextRow(MSTensorVec *row) {
row->clear();
return rc;
}
for (auto de_tensor : md_row) {
CHECK_FAIL_RETURN_UNEXPECTED(de_tensor->HasData(), "Apply transform failed, output tensor has no data");
row->push_back(mindspore::MSTensor(std::make_shared<DETensor>(de_tensor)));
}
std::transform(md_row.begin(), md_row.end(), std::back_inserter(*row),
[](auto t) { return mindspore::MSTensor(std::make_shared<DETensor>(t)); });
return Status::OK();
}

2
mindspore/ccsrc/minddata/dataset/include/vision.h
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@ -398,6 +398,7 @@ class RandomCropDecodeResize final : public TensorTransform {
/// \brief RandomCropWithBBox TensorTransform.
/// \notes Crop the input image at a random location and adjust bounding boxes accordingly.
/// If cropped area is out of bbox, the return bbox will be empty.
class RandomCropWithBBox final : public TensorTransform {
public:
/// \brief Constructor.
@ -578,6 +579,7 @@ class RandomResizedCrop final : public TensorTransform {
/// \brief RandomResizedCropWithBBox TensorTransform.
/// \notes Crop the input image to a random size and aspect ratio.
/// If cropped area is out of bbox, the return bbox will be empty.
class RandomResizedCropWithBBox final : public TensorTransform {
public:
/// \brief Constructor.

8
mindspore/dataset/core/validator_helpers.py
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@ -84,6 +84,14 @@ def check_value_cutoff(value, valid_range, arg_name=""):
valid_range[1]))
def check_value_ratio(value, valid_range, arg_name=""):
arg_name = pad_arg_name(arg_name)
if value <= valid_range[0] or value > valid_range[1]:
raise ValueError(
"Input {0}is not within the required interval of ({1}, {2}].".format(arg_name, valid_range[0],
valid_range[1]))
def check_value_normalize_std(value, valid_range, arg_name=""):
arg_name = pad_arg_name(arg_name)
if value <= valid_range[0] or value > valid_range[1]:

2
mindspore/dataset/transforms/c_transforms.py
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@ -172,7 +172,7 @@ class Slice(cde.SliceOp):
2. :py:obj:`list(int)`: Slice these indices along the first dimension. Negative indices are supported.
3. :py:obj:`slice`: Slice the generated indices from the slice object along the first dimension.
Similar to start:stop:step.
4. :py:obj:`None`: Slice the whole dimension. Similar to :py:obj:`[:]' in Python indexing.
4. :py:obj:`None`: Slice the whole dimension. Similar to :py:obj:`[:]` in Python indexing.
5. :py:obj:`Ellipsis`: Slice the whole dimension, same result with `None`.
Examples:

2
mindspore/dataset/vision/py_transforms.py
View File

@ -974,7 +974,7 @@ class RandomErasing:
"""
Erase the pixels, within a selected rectangle region, to the given value.
Randomly applied on the input NumPy image array with a given probability.
Randomly applied on the input NumPy image array of shape (C, H, W) with a given probability.
Zhun Zhong et al. 'Random Erasing Data Augmentation' 2017 See https://arxiv.org/pdf/1708.04896.pdf

30
mindspore/dataset/vision/validators.py
View File

@ -21,7 +21,7 @@ from mindspore._c_dataengine import TensorOp, TensorOperation
from mindspore.dataset.core.validator_helpers import check_value, check_uint8, FLOAT_MAX_INTEGER, check_pos_float32, \
check_float32, check_2tuple, check_range, check_positive, INT32_MAX, parse_user_args, type_check, type_check_list, \
check_c_tensor_op, UINT8_MAX, check_value_normalize_std, check_value_cutoff
check_c_tensor_op, UINT8_MAX, check_value_normalize_std, check_value_cutoff, check_value_ratio
from .utils import Inter, Border, ImageBatchFormat
@ -153,7 +153,8 @@ def check_random_color_adjust_param(value, input_name, center=1, bound=(0, FLOAT
def check_erasing_value(value):
if not (isinstance(value, (numbers.Number, str, bytes)) or
if not (isinstance(value, (numbers.Number,)) or
(isinstance(value, (str,)) and value == 'random') or
(isinstance(value, (tuple, list)) and len(value) == 3)):
raise ValueError("The value for erasing should be either a single value, "
"or a string 'random', or a sequence of 3 elements for RGB respectively.")
@ -479,6 +480,18 @@ def check_random_erasing(method):
def new_method(self, *args, **kwargs):
[prob, scale, ratio, value, inplace, max_attempts], _ = parse_user_args(method, *args, **kwargs)
type_check(prob, (float, int,), "prob")
type_check_list(scale, (float, int,), "scale")
if len(scale) != 2:
raise TypeError("scale should be a list or tuple of length 2.")
type_check_list(ratio, (float, int,), "ratio")
if len(ratio) != 2:
raise TypeError("ratio should be a list or tuple of length 2.")
type_check(value, (int, list, tuple, str), "value")
type_check(inplace, (bool,), "inplace")
type_check(max_attempts, (int,), "max_attempts")
check_erasing_value(value)
check_value(prob, [0., 1.], "prob")
if scale[0] > scale[1]:
raise ValueError("scale should be in (min,max) format. Got (max,min).")
@ -486,11 +499,14 @@ def check_random_erasing(method):
check_positive(scale[1], "scale[1]")
if ratio[0] > ratio[1]:
raise ValueError("ratio should be in (min,max) format. Got (max,min).")
check_range(ratio, [0, FLOAT_MAX_INTEGER])
check_positive(ratio[0], "ratio[0]")
check_positive(ratio[1], "ratio[1]")
check_erasing_value(value)
type_check(inplace, (bool,), "inplace")
check_value_ratio(ratio[0], [0, FLOAT_MAX_INTEGER])
check_value_ratio(ratio[1], [0, FLOAT_MAX_INTEGER])
if isinstance(value, int):
check_value(value, (0, 255))
if isinstance(value, (list, tuple)):
for item in value:
type_check(item, (int,), "value")
check_value(item, [0, 255], "value")
check_value(max_attempts, (1, FLOAT_MAX_INTEGER))
return method(self, *args, **kwargs)