[cherry-pick]新增API：paddle.nn.functional.sparse_attention

[Liu-xiandong]

给paddle添加API：paddle.nn.functional.sparse_attention
cherry-pick

示例：

import paddle
import numpy as np

query_data = np.array([[[[0, 1,], [2, 3], [ 0, 1], [2, 3]]]]).astype("float32")
key_data = np.array([[[[0, 1,], [2, 3], [ 0, 1], [2, 3]]]]).astype("float32")
value_data = np.array([[[[0, 1,], [2, 3], [ 0, 1], [2, 3]]]]).astype("float32")
sparse_csr_offset_data = np.array([[[0, 2, 4, 6, 8]]]).astype("int32")
sparse_csr_columns_data = np.array([[[0, 1, 0, 1, 2, 3, 2, 3]]]).astype("int32")
print(query_data.shape)
# (1, 1, 4, 2)
print(sparse_csr_offset_data.shape)
# (1, 1, 5)
print(sparse_csr_columns_data.shape)
# (1, 1, 8)
paddle.disable_static()
query = paddle.to_tensor(query_data, stop_gradient=False, place=paddle.CUDAPlace(0))
key = paddle.to_tensor(key_data, stop_gradient=False, place=paddle.CUDAPlace(0))
value = paddle.to_tensor(value_data, stop_gradient=False, place=paddle.CUDAPlace(0))
offset = paddle.to_tensor(sparse_csr_offset_data, stop_gradient=False, place=paddle.CUDAPlace(0))
columns = paddle.to_tensor(sparse_csr_columns_data, stop_gradient=False, place=paddle.CUDAPlace(0))
output = paddle.nn.functional.sparse_attention(query, key, value, offset, columns)
print(output)

# [[[[1.60885942, 2.60885954],
#       [1.99830270, 2.99830270],
#       [1.60885942, 2.60885954],
#       [1.99830270, 2.99830270]]]]