fix collections.Iterable in python3.10 (#42295)

python/paddle/distribution/multinomial.py

@@ -16,6 +16,10 @@ import collections
 
 import paddle
 from paddle.distribution import categorical, distribution
+try:
+    from collections.abc import Iterable
+except:
+    from collections import Iterable
 
 
 class Multinomial(distribution.Distribution):
@@ -138,7 +142,7 @@ class Multinomial(distribution.Distribution):
         Args:
             sample_shape (tuple, optional): [description]. Defaults to ().
         """
-        if not isinstance(shape, collections.Iterable):
+        if not isinstance(shape, Iterable):
             raise TypeError('sample shape must be Iterable object.')
 
         samples = self._categorical.sample([self.total_count, ] + list(shape))

python/paddle/fluid/layers/nn.py

@@ -6781,6 +6781,9 @@ def lod_append(x, level):
             x = fluid.layers.data(name='x', shape=[6, 10], lod_level=1)
             out = fluid.layers.lod_append(x, [1,1,1,1,1,1])
     """
+    try:
+        from collections.abc import Iterable
+    except:
         from collections import Iterable
     if x is None:
         raise ValueError("Input(x) can't be None.")

python/paddle/framework/io.py

@@ -34,6 +34,10 @@ from paddle.fluid.framework import Variable, _varbase_creator, _dygraph_tracer,
 from paddle.fluid.dygraph.jit import _SaveLoadConfig
 from paddle.fluid.dygraph.io import _construct_program_holders, _construct_params_and_buffers
 from paddle.fluid.dygraph.io import INFER_MODEL_SUFFIX, INFER_PARAMS_SUFFIX, INFER_PARAMS_INFO_SUFFIX
+try:
+    from collections.abc import Iterable
+except:
+    from collections import Iterable
 
 __all__ = []
 
@@ -424,7 +428,7 @@ def _parse_every_object(obj, condition_func, convert_func):
     elif type(obj) == set:
         return set(_parse_every_object(list(obj), condition_func, convert_func))
     else:
-        if isinstance(obj, collections.Iterable) and not isinstance(
+        if isinstance(obj, Iterable) and not isinstance(
                 obj,
             (str, np.ndarray, core.VarBase, core.eager.Tensor, core.LoDTensor)):
             raise NotImplementedError(