【Hackathon No.4】为 Paddle 新增 masked_scatter API -part

python/paddle/__init__.py

@@ -258,6 +258,8 @@
     unfold,
     masked_fill,
     masked_fill_,
+    masked_scatter_,
+    masked_scatter,
     index_fill,
     index_fill_,
     diagonal_scatter,
@@ -929,6 +931,8 @@
     'polygamma_',
     'masked_fill',
     'masked_fill_',
+    'masked_scatter',
+    'masked_scatter_',
     'hypot',
     'hypot_',
     'index_fill',

python/paddle/tensor/__init__.py

@@ -163,6 +163,8 @@
     index_put_,
     masked_fill,
     masked_fill_,
+    masked_scatter,
+    masked_scatter_,
     moveaxis,
     put_along_axis,
     put_along_axis_,
@@ -763,6 +765,8 @@
     'atleast_2d',
     'atleast_3d',
     'diagonal_scatter',
+    'masked_scatter',
+    'masked_scatter_',
     "combinations",
 ]
 

python/paddle/tensor/manipulation.py

@@ -4034,6 +4034,92 @@ def get_attr_shape(list_shape):
         return out
 
 
+def masked_scatter(x, mask, value, name=None):
+    """
+    Copies elements from `value` into `x` tensor at positions where the `mask` is True.
+
+    Elements from source are copied into `x` starting at position 0 of `value` and continuing in order one-by-one for
+    each occurrence of `mask` being True. The shape of `mask` must be broadcastable with the shape of the underlying tensor.
+    The `value` should have at least as many elements as the number of ones in `mask`.
+
+    Args:
+        x (Tensor): An N-D Tensor. The data type is ``float16``, ``float32``, ``float64``, ``int32``,
+            ``int64`` or ``bfloat16``.
+        mask (Tensor): The boolean tensor indicate the position to be filled.
+            The data type of mask must be bool.
+        value (Tensor): The value used to fill the target tensor.
+            Supported data types are same as x.
+        name (str, optional): Name for the operation (optional, default is None). For more information,
+            please refer to :ref:`api_guide_Name`.
+
+    Returns:
+        Tensor, A reshaped Tensor with the same data type as ``x``.
+
+    Examples:
+        .. code-block:: python
+
+            >>> import paddle
+            >>> paddle.seed(2048)
+            >>> x = paddle.randn([2, 2])
+            Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+                   [[ 0.74132639, -1.79502666],
+                    [-0.01776697, -0.93422651]])
+
+            >>> mask = paddle.randn([2, 2])
+            >>> mask = mask>0.6
+            Tensor(shape=[2, 2], dtype=bool, place=Place(gpu:0), stop_gradient=True,
+                   [[True , True ],
+                    [False, False]])
+            >>> value = paddle.to_tensor([1, 2, 3, 4, 5,], dtype="float32")
+
+            >>> out = paddle.masked_scatter(x, mask, value)
+            >>> print(out)
+            Tensor(shape=[2, 2], dtype=float32, place=Place(gpu:0), stop_gradient=True,
+                   [[ 1, 2],
+                    [-0.01776697, -0.93422651]])
+
+    """
+    # make sure the dtype of x and value is the same
+    assert (
+        x.dtype == value.dtype
+    ), f'x and value must have the same dtype, but got x dtype is {x.dtype}, value dtype is {value.dtype}'
+    assert mask.dtype == paddle.bool
+
+    zeros_like_x = paddle.zeros_like(x, dtype=int)
+    mask = paddle.add(paddle.cast(mask, dtype="int"), zeros_like_x)
+    mask_prefix = paddle.clip(mask.cumsum() - 1, min=0)
+    assert (
+        mask_prefix[-1] <= value.numel()
+    ), f'mask true nums must be <= value size, but got mask true nums is {mask.sum().item()}, value size is {value.numel().item()}'
+
+    value = value.flatten()[mask_prefix].reshape(mask.shape)
+    mask = paddle.logical_not(mask)
+    return paddle.where(mask, x, value)
+
+
+@inplace_apis_in_dygraph_only
+def masked_scatter_(x, mask, value, name=None):
+    """
+    Inplace version of ``masked_scatter`` API, the output Tensor will be inplaced with input ``x``.
+    Please refer to :ref:`api_paddle_masked_scatter`.
+    """
+    assert (
+        x.dtype == value.dtype
+    ), f'x and value must have the same dtype, but got x dtype is {x.dtype}, value dtype is {value.dtype}'
+    assert mask.dtype == paddle.bool
+    zeros_like_x = paddle.zeros_like(x, dtype=int)
+    mask = paddle.add(paddle.cast(mask, dtype="int"), zeros_like_x)
+    mask_prefix = paddle.clip(mask.cumsum() - 1, min=0)
+    assert (
+        mask_prefix[-1] <= value.numel()
+    ), f'mask true nums must be <= value size, but got mask true nums is {mask_prefix[-1].item()}, value size is {value.numel().item()}'
+
+    value = value.flatten()[mask_prefix].reshape(mask.shape)
+    mask = paddle.logical_not(mask)
+    out = paddle.where_(mask, x, value)
+    return out
+
+
 @inplace_apis_in_dygraph_only
 def reshape_(x, shape, name=None):
     """

test/legacy_test/test_inplace.py

@@ -316,6 +316,22 @@ def init_data(self):
         self.mask = paddle.to_tensor(self.mask, dtype='bool')
 
 
+class TestDygraphInplaceMaskedScatter(TestDygraphInplace):
+    def non_inplace_api_processing(self, var):
+        return paddle.masked_scatter(var, self.mask, self.value)
+
+    def inplace_api_processing(self, var):
+        return paddle.masked_scatter_(var, self.mask, self.value)
+
+    def init_data(self):
+        self.dtype = "float32"
+        self.input_var_numpy = np.random.uniform(-5, 5, [30, 3])
+        self.value = np.random.uniform(size=(30, 30))
+        self.value = paddle.to_tensor(self.value, dtype=self.dtype)
+        self.mask = np.random.randint(0, 2, [30, 1]).astype('bool')
+        self.mask = paddle.to_tensor(self.mask, dtype='bool')
+
+
 class TestDygraphInplaceWithContinuous(TestDygraphInplace):
     def init_data(self):
         self.input_var_numpy = np.random.uniform(-5, 5, [10, 20, 1])