add shape check for fill_constant OP and remove doc of type error (#26919) (#27080)

python/paddle/fluid/layers/tensor.py

@@ -29,6 +29,7 @@ from ..data_feeder import check_variable_and_dtype, check_type, check_dtype, con
 from paddle.utils import deprecated
 import numpy
 import warnings
+from .utils import check_shape
 
 __all__ = [
     'create_tensor', 'create_parameter', 'create_global_var', 'cast',
@@ -652,12 +653,6 @@ def fill_constant(shape, dtype, value, force_cpu=False, out=None, name=None):
     Returns:
         Tensor: Tensor which is created according to shape and dtype.
 
-    Raises:
-        TypeError: The dtype must be one of bool, float16, float32, float64, int32 and int64
-            and the data type of ``out`` must be the same as the ``dtype``. 
-        TypeError: The shape must be one of list, tuple and Tensor, the data type of ``shape``
-            must be int32 or int64 when ``shape`` is a Tensor
-
     Examples:
         .. code-block:: python
 
@@ -713,14 +708,12 @@ def fill_constant(shape, dtype, value, force_cpu=False, out=None, name=None):
             value = cast(value, dtype)
         inputs['ValueTensor'] = value
 
+    check_shape(shape)
     check_dtype(dtype, 'dtype',
                 ['bool', 'float16', 'float32', 'float64', 'int32', 'int64'],
                 'fill_constant')
     check_type(shape, 'shape', (Variable, list, tuple), 'fill_constant')
 
-    if isinstance(shape, Variable):
-        check_dtype(shape.dtype, 'shape', ['int32', 'int64'], 'fill_constant')
-
     if out is not None:
         check_variable_and_dtype(out, 'out', [convert_dtype(dtype)],
                                  'fill_constant')
@@ -1045,10 +1038,6 @@ def ones(shape, dtype, force_cpu=False):
 
     Returns:
         Tensor: A tensor of data type :attr:`dtype` with shape :attr:`shape` and all elements set to 1.
-    Raises:
-        TypeError: The ``dtype`` must be one of bool, float16, float32, float64, int32, int64.
-        TypeError: The ``shape`` must be one of list, tuple and Tensor. The data type of ``shape`` must
-            be int32 or int64 when it's a Tensor.
 
     Examples:
         .. code-block:: python
@@ -1081,10 +1070,6 @@ def zeros(shape, dtype, force_cpu=False, name=None):
     Returns:
         Tensor: A tensor of data type :attr:`dtype` with shape :attr:`shape` and all elements set to 0.
 
-    Raises:
-        TypeError: The ``dtype`` must be one of bool, float16, float32, float64, int32, int64.
-        TypeError: The ``shape`` must be one of list, tuple and Tensor. The data type of ``shape`` must
-            be int32 or int64 when it's a Tensor.
     Examples:
         .. code-block:: python
 

python/paddle/fluid/layers/utils.py

@@ -20,6 +20,7 @@ import numpy as np
 from ..framework import Variable
 from ..data_feeder import convert_dtype, check_variable_and_dtype, check_type, check_dtype
 from ..layer_helper import LayerHelper
+from sys import version_info
 
 
 def convert_to_list(value, n, name, dtype=np.int):
@@ -358,3 +359,22 @@ def convert_shape_to_list(shape):
     else:
         shape = list(shape.numpy().astype(int))
     return shape
+
+
+def check_shape(shape):
+    """
+    Check shape type and shape elements type before passing it to fill_constant
+    """
+    if isinstance(shape, Variable):
+        check_dtype(shape.dtype, 'shape', ['int32', 'int64'], 'fill_constant')
+    else:
+        for ele in shape:
+            if not isinstance(ele, Variable):
+                if ele < 0:
+                    raise ValueError(
+                        "All elements in ``shape`` must be positive when it's a list or tuple"
+                    )
+                if not isinstance(ele, six.integer_types):
+                    raise TypeError(
+                        "All elements in ``shape`` must be integers when it's a list or tuple"
+                    )

python/paddle/fluid/tests/unittests/test_fill_constant_op.py

@@ -350,6 +350,14 @@ class TestFillConstantOpError(unittest.TestCase):
                 dtype='int16',
                 out=x1)
 
+            self.assertRaises(
+                TypeError,
+                fluid.layers.fill_constant,
+                shape=[1.1],
+                value=5,
+                dtype='float32',
+                out=x1)
+
             # The argument dtype of fill_constant_op must be one of bool, float16,
             #float32, float64, int32 or int64
             x2 = fluid.layers.data(name='x2', shape=[1], dtype="int32")