cannot import name '_validate_lengths' from 'numpy.lib.arraypad'

在Anaconda下新配置了tensorflow环境，结果在引入skimage 包时报错，错误提示from numpy.lib.arraypad import _validate_lengths，找不到_validate_lengths函数，在arraypad.py文件中确实找不到对应的函数，所以找到以前配置过的环境中对应的文件，拷贝这个缺失的函数，问题解决(****************一定要重启环境)。

(flappbird1) luo@luo-All-Series:~/MyFile/COCO/coco/PythonAPI$
(flappbird1) luo@luo-All-Series:~/MyFile/COCO/coco/PythonAPI$ python\
>
Python 3.7.2 (default, Dec 29 2018, 06:19:36)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>>
>>>
>>>
>>> from skimage import io
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/luo/anaconda3/envs/flappbird1/lib/python3.7/site-packages/skimage/__init__.py", line 167, in <module>
    from .util.dtype import (img_as_float32,
  File "/home/luo/anaconda3/envs/flappbird1/lib/python3.7/site-packages/skimage/util/__init__.py", line 8, in <module>
    from .arraycrop import crop
  File "/home/luo/anaconda3/envs/flappbird1/lib/python3.7/site-packages/skimage/util/arraycrop.py", line 8, in <module>
    from numpy.lib.arraypad import _validate_lengths
ImportError: cannot import name '_validate_lengths' from 'numpy.lib.arraypad' (/home/luo/anaconda3/envs/flappbird1/lib/python3.7/site-packages/numpy/lib/arraypad.py)
>>>
>>>
>>>
>>>
>>> from skimage import data, io, filters
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/luo/anaconda3/envs/flappbird1/lib/python3.7/site-packages/skimage/__init__.py", line 176, in <module>
    from .util.lookfor import lookfor
  File "/home/luo/anaconda3/envs/flappbird1/lib/python3.7/site-packages/skimage/util/__init__.py", line 8, in <module>
    from .arraycrop import crop
  File "/home/luo/anaconda3/envs/flappbird1/lib/python3.7/site-packages/skimage/util/arraycrop.py", line 8, in <module>
    from numpy.lib.arraypad import _validate_lengths
ImportError: cannot import name '_validate_lengths' from 'numpy.lib.arraypad' (/home/luo/anaconda3/envs/flappbird1/lib/python3.7/site-packages/numpy/lib/arraypad.py)
>>>
>>>
>>>
>>>
>>> from skimage import data, io, filters
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/luo/anaconda3/envs/flappbird1/lib/python3.7/site-packages/skimage/__init__.py", line 176, in <module>
    from .util.lookfor import lookfor
  File "/home/luo/anaconda3/envs/flappbird1/lib/python3.7/site-packages/skimage/util/__init__.py", line 8, in <module>
    from .arraycrop import crop
  File "/home/luo/anaconda3/envs/flappbird1/lib/python3.7/site-packages/skimage/util/arraycrop.py", line 8, in <module>
    from numpy.lib.arraypad import _validate_lengths
ImportError: cannot import name '_validate_lengths' from 'numpy.lib.arraypad' (/home/luo/anaconda3/envs/flappbird1/lib/python3.7/site-packages/numpy/lib/arraypad.py)
>>>
>>>
>>>
>>> from skimage import io
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/luo/anaconda3/envs/flappbird1/lib/python3.7/site-packages/skimage/__init__.py", line 176, in <module>
    from .util.lookfor import lookfor
  File "/home/luo/anaconda3/envs/flappbird1/lib/python3.7/site-packages/skimage/util/__init__.py", line 8, in <module>
    from .arraycrop import crop
  File "/home/luo/anaconda3/envs/flappbird1/lib/python3.7/site-packages/skimage/util/arraycrop.py", line 8, in <module>
    from numpy.lib.arraypad import _validate_lengths
ImportError: cannot import name '_validate_lengths' from 'numpy.lib.arraypad' (/home/luo/anaconda3/envs/flappbird1/lib/python3.7/site-packages/numpy/lib/arraypad.py)
>>>
>>>
>>>
>>> exit()
(flappbird1) luo@luo-All-Series:~/MyFile/COCO/coco/PythonAPI$
(flappbird1) luo@luo-All-Series:~/MyFile/COCO/coco/PythonAPI$

---------------------------------------------------------------------------------------------------

找到：Anaconda3/envs/your dir/lib/python3.7/site-packages/numpy/lib/arraypad.py   954行，添加洗下面两个函数保存，重新加载即可消除错误(****************一定要重启环境)

--------------------------------------------------------------------------------------------------

def _normalize_shape(ndarray, shape, cast_to_int=True):
    """
    Private function which does some checks and normalizes the possibly
    much simpler representations of 'pad_width', 'stat_length',
    'constant_values', 'end_values'.

Parameters
    ----------
    narray : ndarray
        Input ndarray
    shape : {sequence, array_like, float, int}, optional
        The width of padding (pad_width), the number of elements on the
        edge of the narray used for statistics (stat_length), the constant
        value(s) to use when filling padded regions (constant_values), or the
        endpoint target(s) for linear ramps (end_values).
        ((before_1, after_1), ... (before_N, after_N)) unique number of
        elements for each axis where `N` is rank of `narray`.
        ((before, after),) yields same before and after constants for each
        axis.
        (constant,) or val is a shortcut for before = after = constant for
        all axes.
    cast_to_int : bool, optional
        Controls if values in ``shape`` will be rounded and cast to int
        before being returned.

Returns
    -------
    normalized_shape : tuple of tuples
        val                               => ((val, val), (val, val), ...)
        [[val1, val2], [val3, val4], ...] => ((val1, val2), (val3, val4), ...)
        ((val1, val2), (val3, val4), ...) => no change
        [[val1, val2], ]                  => ((val1, val2), (val1, val2), ...)
        ((val1, val2), )                  => ((val1, val2), (val1, val2), ...)
        [[val ,     ], ]                  => ((val, val), (val, val), ...)
        ((val ,     ), )                  => ((val, val), (val, val), ...)

"""
    ndims = ndarray.ndim

# Shortcut shape=None
    if shape is None:
        return ((None, None), ) * ndims

# Convert any input `info` to a NumPy array
    shape_arr = np.asarray(shape)

try:
        shape_arr = np.broadcast_to(shape_arr, (ndims, 2))
    except ValueError:
        fmt = "Unable to create correctly shaped tuple from %s"
        raise ValueError(fmt % (shape,))

# Cast if necessary
    if cast_to_int is True:
        shape_arr = np.round(shape_arr).astype(int)

# Convert list of lists to tuple of tuples
    return tuple(tuple(axis) for axis in shape_arr.tolist())

def _validate_lengths(narray, number_elements):
    """
    Private function which does some checks and reformats pad_width and
    stat_length using _normalize_shape.

Parameters
    ----------
    narray : ndarray
        Input ndarray
    number_elements : {sequence, int}, optional
        The width of padding (pad_width) or the number of elements on the edge
        of the narray used for statistics (stat_length).
        ((before_1, after_1), ... (before_N, after_N)) unique number of
        elements for each axis.
        ((before, after),) yields same before and after constants for each
        axis.
        (constant,) or int is a shortcut for before = after = constant for all
        axes.

Returns
    -------
    _validate_lengths : tuple of tuples
        int                               => ((int, int), (int, int), ...)
        [[int1, int2], [int3, int4], ...] => ((int1, int2), (int3, int4), ...)
        ((int1, int2), (int3, int4), ...) => no change
        [[int1, int2], ]                  => ((int1, int2), (int1, int2), ...)
        ((int1, int2), )                  => ((int1, int2), (int1, int2), ...)
        [[int ,     ], ]                  => ((int, int), (int, int), ...)
        ((int ,     ), )                  => ((int, int), (int, int), ...)

"""
    normshp = _normalize_shape(narray, number_elements)
    for i in normshp:
        chk = [1 if x is None else x for x in i]
        chk = [1 if x >= 0 else -1 for x in chk]
        if (chk[0] < 0) or (chk[1] < 0):
            fmt = "%s cannot contain negative values."
            raise ValueError(fmt % (number_elements,))
    return normshp

###############################################################################
# Public functions