fix bug

python/mxnet/ndarray/numpy/_op.py

@@ -5212,10 +5212,10 @@ def resize(a, new_shape):
 
 
 @set_module('mxnet.ndarray.numpy')
-def full_like(a, fill_value=0, dtype=None, order='K', subok=True, shape=None):
+def full_like(a, fill_value=0, dtype=None, order='K', subok=True, shape=None): # pylint: disable=too-many-arguments
     """
     Return a full array with the same shape and type as a given array.
-    
+
     Parameters
     ----------
     a : ndarray
@@ -5239,19 +5239,20 @@ def full_like(a, fill_value=0, dtype=None, order='K', subok=True, shape=None):
         Overrides the shape of the result. If order='K' and the number of
         dimensions is unchanged, will try to keep order, otherwise,
         order='C' is implied.
-    
+        (Not support at this moment)
+
     Returns
     -------
     out : ndarray
         Array of `fill_value` with the same shape and type as `a`.
-    
+
     See Also
     --------
     empty_like : Return an empty array with shape and type of input.
     ones_like : Return an array of ones with shape and type of input.
     zeros_like : Return an array of zeros with shape and type of input.
     full : Return a new array of given shape filled with value.
-    
+
     Examples
     --------
     >>> x = np.arange(6, dtype=int)

python/mxnet/numpy/multiarray.py

@@ -7205,10 +7205,10 @@ def resize(a, new_shape):
 
 
 @set_module('mxnet.numpy')
-def full_like(a, fill_value=0, dtype=None, order='K', subok=True, shape=None):
+def full_like(a, fill_value=0, dtype=None, order='K', subok=True, shape=None): # pylint: disable=too-many-arguments
     """
     Return a full array with the same shape and type as a given array.
-    
+
     Parameters
     ----------
     a : ndarray
@@ -7231,19 +7231,19 @@ def full_like(a, fill_value=0, dtype=None, order='K', subok=True, shape=None):
         Overrides the shape of the result. If order='K' and the number of
         dimensions is unchanged, will try to keep order, otherwise,
         order='C' is implied.
-    
+
     Returns
     -------
     out : ndarray
         Array of `fill_value` with the same shape and type as `a`.
-    
+
     See Also
     --------
     empty_like : Return an empty array with shape and type of input.
     ones_like : Return an array of ones with shape and type of input.
     zeros_like : Return an array of zeros with shape and type of input.
     full : Return a new array of given shape filled with value.
-    
+
     Examples
     --------
     >>> x = np.arange(6, dtype=int)

python/mxnet/numpy_op_fallback.py

@@ -56,18 +56,13 @@ def __init__(self, fill_value, dtype, order, subok, shape):
         super(FullLike, self).__init__()
         self._fill_value = fill_value
         self._dtype = dtype
-        self._order = order 
+        self._order = order
         self._subok = subok
         self._shape = shape
 
     def forward(self, is_train, req, in_data, out_data, aux):
-        np_version = np.version.version
-        if np_version == '1.17.0':
-            out = np.full_like(in_data[0].asnumpy(), self._fill_value, dtype=self._dtype, order=self._order,
-                               subok=self._subok, shape=self._shape)
-        else:
-            out = np.full_like(in_data[0].asnumpy(), self._fill_value, dtype=self._dtype, order=self._order,
-                               subok=self._subok)
+        out = np.full_like(in_data[0].asnumpy(), self._fill_value, dtype=self._dtype, order=self._order,
+                           subok=self._subok)
         self.assign(out_data[0], req[0], _mx_np.array(out, dtype=out.dtype, ctx=out_data[0].ctx))
 
     def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
@@ -106,7 +101,7 @@ def infer_type(self, in_type):
         if self._dtype is None:
             return (in_type[0],), (in_type[0],), ()
         else:
-            out_dtype = eval('np.'+self._dtype)
+            out_dtype = eval('np.'+self._dtype) # pylint: disable=W0123
             return (in_type[0],), (out_dtype,), ()
 
     def infer_shape(self, in_shape):

python/mxnet/symbol/numpy/_symbol.py

@@ -4825,10 +4825,10 @@ def resize(a, new_shape):
 
 
 @set_module('mxnet.symbol.numpy')
-def full_like(a, fill_value=0, dtype=None, order='K', subok=True, shape=None):
+def full_like(a, fill_value=0, dtype=None, order='K', subok=True, shape=None): # pylint: disable=too-many-arguments
     """
     Return a full array with the same shape and type as a given array.
-    
+
     Parameters
     ----------
     a : _Symbol
@@ -4851,12 +4851,12 @@ def full_like(a, fill_value=0, dtype=None, order='K', subok=True, shape=None):
         Overrides the shape of the result. If order='K' and the number of
         dimensions is unchanged, will try to keep order, otherwise,
         order='C' is implied.
-    
+
     Returns
     -------
     out : _Symbol
         Array of `fill_value` with the same shape and type as `a`.
-    
+
     See Also
     --------
     empty_like : Return an empty array with shape and type of input.

tests/python/unittest/test_numpy_op.py

@@ -17,6 +17,7 @@
 
 # pylint: skip-file
 from __future__ import absolute_import
+from distutils.version import StrictVersion
 import sys
 import unittest
 import itertools
@@ -4477,9 +4478,16 @@ def __init__(self, fill_value, dtype, order, subok, shape):
 
         def hybrid_forward(self, F, x, *args, **kwargs):
             return F.np.full_like(x, self._fill_value, self._dtype, self._order, self._subok, self._shape)
-
-    dtypes = [None, 'float16', 'float32', np.int8, np.uint8, np.int32, np.int64,
-              np.float16, np.float32, np.float64]
+    def check_python2():
+        if StrictVersion(platform.python_version()) < platform.python_version('3.0.0'):
+            return True
+        return False
+    def check_int(dtype1, dtype2):
+        if 'int' in dtype1 or 'int' in dtype2:
+            return True
+        return False
+
+    dtypes = ['float64', 'float32', 'float16', 'int64', 'int32', 'int8']
     shapes = [
         (),
         (1,),
@@ -4498,22 +4506,20 @@ def hybrid_forward(self, F, x, *args, **kwargs):
     _np_version = _np.version.version
     for fill_value, dtype, shape, hybridize, order, subok in itertools.product(
         fill_values, dtypes, shapes, flags, orders, subok_list):
+        param_dtype= _np.random.choice(dtypes)
+        if check_python2 and check_int(dtype, param_dtype):
+            continue
         a = np.random.uniform(low=0, high=100, size=shape, dtype='float64').astype(dtype)
-        dtype = _np.random.choice(dtypes)
-        test = TestFullLike(fill_value, dtype, order, subok, shape)
-        if _np_version == '1.17.0':
-            expected_ret = _np.full_like(a, fill_value=fill_value, dtype=dtype, order=order,
-                                         subok=subok, shape=shape)
-        else:
-            expected_ret = _np.full_like(a, fill_value=fill_value, dtype=dtype, order=order,
-                                         subok=subok)     
+        test = TestFullLike(fill_value, param_dtype, order, subok, shape)
+        expected_ret = _np.full_like(a, fill_value=fill_value, dtype=param_dtype, order=order,
+                                     subok=subok)     
         if hybridize:
             test.hybridize()
         ret = test(a)
         assert_almost_equal(ret.asnumpy(), expected_ret, rtol=1e-3, atol=1e-5)
 
         # check imperative again
-        ret = np.full_like(a, fill_value, dtype, order, subok, shape)
+        ret = np.full_like(a, fill_value, param_dtype, order, subok, shape)
         assert_almost_equal(ret.asnumpy(), expected_ret, rtol=1e-3, atol=1e-5)