def new_method(self, *args, **kwargs):
[image_batch_format, alpha, prob], _ = parse_user_args(method, *args, **kwargs)
type_check(image_batch_format, (ImageBatchFormat,), "image_batch_format")
check_pos_float32(alpha)
check_positive(alpha, "alpha")
check_value(prob, [0, 1], "prob")
return method(self, *args, **kwargs)
def new_method(self, *args, **kwargs):
[length, num_patches], _ = parse_user_args(method, *args, **kwargs)
check_value(length, (1, FLOAT_MAX_INTEGER))
check_value(num_patches, (1, FLOAT_MAX_INTEGER))
return method(self, *args, **kwargs)
def check_size_scale_ration_max_attempts_paras(size, scale, ratio,
max_attempts):
"""Wrapper method to check the parameters of RandomCropDecodeResize and SoftDvppDecodeRandomCropResizeJpeg."""
check_crop_size(size)
if scale is not None:
type_check(scale, (tuple, list), "scale")
if len(scale) != 2:
raise TypeError("scale should be a list/tuple of length 2.")
type_check_list(scale, (float, int), "scale")
if scale[0] > scale[1]:
raise ValueError(
"scale should be in (min,max) format. Got (max,min).")
check_range(scale, [0, FLOAT_MAX_INTEGER])
check_positive(scale[1], "scale[1]")
if ratio is not None:
type_check(ratio, (tuple, list), "ratio")
if len(ratio) != 2:
raise TypeError("ratio should be a list/tuple of length 2.")
type_check_list(ratio, (float, int), "ratio")
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]")
if max_attempts is not None:
check_value(max_attempts, (1, FLOAT_MAX_INTEGER))
def check_normalize_py_param(mean, std):
if len(mean) != len(std):
raise ValueError("Length of mean and std must be equal.")
for mean_value in mean:
check_value(mean_value, [0., 1.], "mean_value")
for std_value in std:
check_value_normalize_std(std_value, [0., 1.], "std_value")
def new_method(self, *args, **kwargs):
[batch_size, alpha, is_single], _ = parse_user_args(method, *args, **kwargs)
check_value(batch_size, (1, FLOAT_MAX_INTEGER))
check_positive(alpha, "alpha")
type_check(is_single, (bool,), "is_single")
return method(self, *args, **kwargs)
def new_method(self, *args, **kwargs):
[transform, ratio], _ = parse_user_args(method, *args, **kwargs)
type_check(ratio, (float, int), "ratio")
check_value(ratio, [0., 1.], "ratio")
if transform and getattr(transform, 'parse', None):
transform = transform.parse()
type_check(transform, (TensorOp, TensorOperation), "transform")
return method(self, *args, **kwargs)
def new_method(self, *args, **kwargs):
[distortion_scale, prob, interpolation], _ = parse_user_args(method, *args, **kwargs)
check_value(distortion_scale, [0., 1.], "distortion_scale")
check_value(prob, [0., 1.], "prob")
type_check(interpolation, (Inter,), "interpolation")
return method(self, *args, **kwargs)
def check_normalize_c_param(mean, std):
type_check(mean, (list, tuple), "mean")
type_check(std, (list, tuple), "std")
if len(mean) != len(std):
raise ValueError("Length of mean and std must be equal.")
for mean_value in mean:
check_value(mean_value, [0, 255], "mean_value")
for std_value in std:
check_value_normalize_std(std_value, [0, 255], "std_value")
def new_method(self, *args, **kwargs):
[prob], _ = parse_user_args(method, *args, **kwargs)
type_check(prob, (
float,
int,
), "prob")
check_value(prob, [0., 1.], "prob")
return method(self, *args, **kwargs)
def check_resize_size(size):
"""Wrapper method to check the parameters of resize."""
if isinstance(size, int):
check_value(size, (1, FLOAT_MAX_INTEGER))
elif isinstance(size, (tuple, list)) and len(size) == 2:
for i, value in enumerate(size):
check_value(value, (1, INT32_MAX), "size at dim {0}".format(i))
else:
raise TypeError("Size should be a single integer or a list/tuple (h, w) of length 2.")
def check_crop_size(size):
"""Wrapper method to check the parameters of crop size."""
type_check(size, (int, list, tuple), "size")
if isinstance(size, int):
check_value(size, (1, FLOAT_MAX_INTEGER))
elif isinstance(size, (tuple, list)) and len(size) == 2:
for value in size:
check_value(value, (1, FLOAT_MAX_INTEGER))
else:
raise TypeError("Size should be a single integer or a list/tuple (h, w) of length 2.")
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.")
for i, pad_value in enumerate(padding):
type_check(pad_value, (int,), "padding[{}]".format(i))
check_value(pad_value, (0, INT32_MAX), "pad_value")
def new_method(self, *args, **kwargs):
[prob, scale, ratio, value, inplace, max_attempts], _ = parse_user_args(method, *args, **kwargs)
check_value(prob, [0., 1.], "prob")
check_range(scale, [0, FLOAT_MAX_INTEGER])
check_range(ratio, [0, FLOAT_MAX_INTEGER])
check_erasing_value(value)
type_check(inplace, (bool,), "inplace")
check_value(max_attempts, (1, FLOAT_MAX_INTEGER))
return method(self, *args, **kwargs)
def check_degrees(degrees):
"""Check if the degrees is legal."""
type_check(degrees, (numbers.Number, list, tuple), "degrees")
if isinstance(degrees, numbers.Number):
check_value(degrees, (0, float("inf")), "degrees")
elif isinstance(degrees, (list, tuple)):
if len(degrees) == 2:
type_check_list(degrees, (numbers.Number,), "degrees")
if degrees[0] > degrees[1]:
raise ValueError("degrees should be in (min,max) format. Got (max,min).")
else:
raise TypeError("If degrees is a sequence, the length must be 2.")
def new_method(self, *args, **kwargs):
[threshold], _ = parse_user_args(method, *args, **kwargs)
type_check(threshold, (tuple,), "threshold")
type_check_list(threshold, (int,), "threshold")
if len(threshold) != 2:
raise ValueError("threshold must be a sequence of two numbers.")
for element in threshold:
check_value(element, (0, UINT8_MAX))
if threshold[1] < threshold[0]:
raise ValueError("threshold must be in min max format numbers.")
return method(self, *args, **kwargs)
def new_method(self, *args, **kwargs):
[cutoff, ignore], _ = parse_user_args(method, *args, **kwargs)
type_check(cutoff, (int, float), "cutoff")
check_value_cutoff(cutoff, [0, 50], "cutoff")
if ignore is not None:
type_check(ignore, (list, tuple, int), "ignore")
if isinstance(ignore, int):
check_value(ignore, [0, 255], "ignore")
if isinstance(ignore, (list, tuple)):
for item in ignore:
type_check(item, (int, ), "item")
check_value(item, [0, 255], "ignore")
return method(self, *args, **kwargs)
def new_method(self, *args, **kwargs):
[degrees, translate, scale, shear, resample,
fill_value], _ = parse_user_args(method, *args, **kwargs)
check_degrees(degrees)
if translate is not None:
type_check(translate, (list, tuple), "translate")
type_check_list(translate, (int, float), "translate")
if len(translate) != 2 and len(translate) != 4:
raise TypeError(
"translate should be a list or tuple of length 2 or 4.")
for i, t in enumerate(translate):
check_value(t, [-1.0, 1.0], "translate at {0}".format(i))
if scale is not None:
type_check(scale, (tuple, list), "scale")
type_check_list(scale, (int, float), "scale")
if len(scale) == 2:
if scale[0] > scale[1]:
raise ValueError(
"Input scale[1] must be equal to or greater than scale[0]."
)
check_range(scale, [0, FLOAT_MAX_INTEGER])
check_positive(scale[1], "scale[1]")
else:
raise TypeError("scale should be a list or tuple of length 2.")
if shear is not None:
type_check(shear, (numbers.Number, tuple, list), "shear")
if isinstance(shear, numbers.Number):
check_positive(shear, "shear")
else:
type_check_list(shear, (int, float), "shear")
if len(shear) not in (2, 4):
raise TypeError("shear must be of length 2 or 4.")
if len(shear) == 2 and shear[0] > shear[1]:
raise ValueError(
"Input shear[1] must be equal to or greater than shear[0]"
)
if len(shear) == 4 and (shear[0] > shear[1]
or shear[2] > shear[3]):
raise ValueError(
"Input shear[1] must be equal to or greater than shear[0] and "
"shear[3] must be equal to or greater than shear[2].")
type_check(resample, (Inter, ), "resample")
if fill_value is not None:
check_fill_value(fill_value)
return method(self, *args, **kwargs)
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).")
check_range(scale, [0, FLOAT_MAX_INTEGER])
check_positive(scale[1], "scale[1]")
if ratio[0] > ratio[1]:
raise ValueError("ratio should be in (min,max) format. Got (max,min).")
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)
def new_method(self, *args, **kwargs):
[kernel_size, sigma], _ = parse_user_args(method, *args, **kwargs)
type_check(kernel_size, (int, list, tuple), "kernel_size")
if isinstance(kernel_size, int):
check_value(kernel_size, (1, FLOAT_MAX_INTEGER), "kernel_size")
check_odd(kernel_size, "kernel_size")
elif isinstance(kernel_size, (list, tuple)) and len(kernel_size) == 2:
for index, value in enumerate(kernel_size):
type_check(value, (int, ), "kernel_size[{}]".format(index))
check_value(value, (1, FLOAT_MAX_INTEGER), "kernel_size")
check_odd(value, "kernel_size[{}]".format(index))
else:
raise TypeError(
"Kernel size should be a single integer or a list/tuple (kernel_width, kernel_height) of length 2."
)
if sigma is not None:
type_check(sigma, (numbers.Number, list, tuple), "sigma")
if isinstance(sigma, numbers.Number):
check_value(sigma, (0, FLOAT_MAX_INTEGER), "sigma")
elif isinstance(sigma, (list, tuple)) and len(sigma) == 2:
for index, value in enumerate(sigma):
type_check(value, (numbers.Number, ),
"size[{}]".format(index))
check_value(value, (0, FLOAT_MAX_INTEGER), "sigma")
else:
raise TypeError(
"Sigma should be a single number or a list/tuple of length 2 for width and height."
)
return method(self, *args, **kwargs)
def new_method(self, *args, **kwargs):
[bits], _ = parse_user_args(method, *args, **kwargs)
if bits is not None:
type_check(bits, (list, tuple, int), "bits")
if isinstance(bits, int):
check_value(bits, [1, 8])
if isinstance(bits, (list, tuple)):
if len(bits) != 2:
raise TypeError("Size of bits should be a single integer or a list/tuple (min, max) of length 2.")
for item in bits:
check_uint8(item, "bits")
# also checks if min <= max
check_range(bits, [1, 8])
return method(self, *args, **kwargs)
def new_method(self, *args, **kwargs):
[policy], _ = parse_user_args(method, *args, **kwargs)
type_check(policy, (list,), "policy")
if not policy:
raise ValueError("policy can not be empty.")
for sub_ind, sub in enumerate(policy):
type_check(sub, (list,), "policy[{0}]".format([sub_ind]))
if not sub:
raise ValueError("policy[{0}] can not be empty.".format(sub_ind))
for op_ind, tp in enumerate(sub):
check_2tuple(tp, "policy[{0}][{1}]".format(sub_ind, op_ind))
check_tensor_op(tp[0], "op of (op, prob) in policy[{0}][{1}]".format(sub_ind, op_ind))
check_value(tp[1], (0, 1), "prob of (op, prob) policy[{0}][{1}]".format(sub_ind, op_ind))
return method(self, *args, **kwargs)
def new_method(self, *args, **kwargs):
[degrees], _ = parse_user_args(method, *args, **kwargs)
if degrees is not None:
if not isinstance(degrees, (list, tuple)):
raise TypeError("degrees must be either a tuple or a list.")
type_check_list(degrees, (int, float), "degrees")
if len(degrees) != 2:
raise ValueError("degrees must be a sequence with length 2.")
for degree in degrees:
check_value(degree, (0, FLOAT_MAX_INTEGER))
if degrees[0] > degrees[1]:
raise ValueError("degrees should be in (min,max) format. Got (max,min).")
return method(self, *args, **kwargs)
def new_method(self, *args, **kwargs):
[prob, scale, ratio, value, inplace, max_attempts], _ = parse_user_args(method, *args, **kwargs)
check_value(prob, [0., 1.], "prob")
if scale[0] > scale[1]:
raise ValueError("scale should be in (min,max) format. Got (max,min).")
check_range(scale, [0, FLOAT_MAX_INTEGER])
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(max_attempts, (1, FLOAT_MAX_INTEGER))
return method(self, *args, **kwargs)
def new_method(self, *args, **kwargs):
[transform, ratio], _ = parse_user_args(method, *args, **kwargs)
type_check(ratio, (float, int), "ratio")
check_value(ratio, [0., 1.], "ratio")
type_check(transform, (TensorOp,), "transform")
return method(self, *args, **kwargs)
