【PaddlePaddle Hackathon 3 No.16】为 Paddle 新增 API paddle.take

python/paddle/__init__.py

@@ -280,6 +280,7 @@
 from .tensor.math import heaviside  # noqa: F401
 from .tensor.math import frac  # noqa: F401
 from .tensor.math import sgn  # noqa: F401
+from .tensor.math import take  # noqa: F401
 
 from .tensor.random import bernoulli  # noqa: F401
 from .tensor.random import poisson  # noqa: F401
@@ -656,4 +657,5 @@
     'tril_indices',
     'sgn',
     'triu_indices',
+    'take',
 ]

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

@@ -0,0 +1,220 @@
+#   Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import print_function
+
+import unittest
+import numpy as np
+import paddle
+import paddle.fluid as fluid
+import paddle.fluid.core as core
+from paddle.fluid import Program, program_guard
+
+
+class TestTakeAPI(unittest.TestCase):
+
+    def set_mode(self):
+        self.mode = 'raise'
+
+    def set_dtype(self):
+        self.input_dtype = 'float64'
+        self.index_dtype = 'int64'
+
+    def set_input(self):
+        self.input_shape = [3, 4]
+        self.index_shape = [2, 3]
+        self.input_np = np.arange(0, 12).reshape(self.input_shape).astype(
+            self.input_dtype)
+        self.index_np = np.arange(-4, 2).reshape(self.index_shape).astype(
+            self.index_dtype)
+
+    def setUp(self):
+        self.set_mode()
+        self.set_dtype()
+        self.set_input()
+        self.place = fluid.CUDAPlace(
+            0) if core.is_compiled_with_cuda() else fluid.CPUPlace()
+
+    def test_static_graph(self):
+        paddle.enable_static()
+        startup_program = Program()
+        train_program = Program()
+        with program_guard(startup_program, train_program):
+            x = fluid.data(name='input',
+                           dtype=self.input_dtype,
+                           shape=self.input_shape)
+            index = fluid.data(name='index',
+                               dtype=self.index_dtype,
+                               shape=self.index_shape)
+            out = paddle.take(x, index, mode=self.mode)
+
+            exe = fluid.Executor(self.place)
+            st_result = exe.run(fluid.default_main_program(),
+                                feed={
+                                    'input': self.input_np,
+                                    'index': self.index_np
+                                },
+                                fetch_list=out)
+            np.testing.assert_allclose(
+                st_result[0],
+                np.take(self.input_np, self.index_np, mode=self.mode))
+
+    def test_dygraph(self):
+        paddle.disable_static(self.place)
+        x = paddle.to_tensor(self.input_np)
+        index = paddle.to_tensor(self.index_np)
+        dy_result = paddle.take(x, index, mode=self.mode)
+        np.testing.assert_allclose(
+            np.take(self.input_np, self.index_np, mode=self.mode),
+            dy_result.numpy())
+
+
+class TestTakeInt32(TestTakeAPI):
+    """Test take API with data type int32"""
+
+    def set_dtype(self):
+        self.input_dtype = 'int32'
+        self.index_dtype = 'int64'
+
+
+class TestTakeInt64(TestTakeAPI):
+    """Test take API with data type int64"""
+
+    def set_dtype(self):
+        self.input_dtype = 'int64'
+        self.index_dtype = 'int64'
+
+
+class TestTakeFloat32(TestTakeAPI):
+    """Test take API with data type float32"""
+
+    def set_dtype(self):
+        self.input_dtype = 'float32'
+        self.index_dtype = 'int64'
+
+
+class TestTakeTypeError(TestTakeAPI):
+    """Test take Type Error"""
+
+    def test_static_type_error(self):
+        """Argument 'index' must be Tensor"""
+        paddle.enable_static()
+        with program_guard(Program()):
+            x = fluid.data(name='input',
+                           dtype=self.input_dtype,
+                           shape=self.input_shape)
+            self.assertRaises(TypeError, paddle.take, x, self.index_np,
+                              self.mode)
+
+    def test_dygraph_type_error(self):
+        paddle.disable_static(self.place)
+        x = paddle.to_tensor(self.input_np)
+        self.assertRaises(TypeError, paddle.take, x, self.index_np, self.mode)
+
+    def test_static_dtype_error(self):
+        """Data type of argument 'index' must be in [paddle.int32, paddle.int64]"""
+        paddle.enable_static()
+        with program_guard(Program()):
+            x = fluid.data(name='input',
+                           dtype='float64',
+                           shape=self.input_shape)
+            index = fluid.data(name='index',
+                               dtype='float32',
+                               shape=self.index_shape)
+            self.assertRaises(TypeError, paddle.take, x, index, self.mode)
+
+    def test_dygraph_dtype_error(self):
+        paddle.disable_static(self.place)
+        x = paddle.to_tensor(self.input_np)
+        index = paddle.to_tensor(self.index_np, dtype='float32')
+        self.assertRaises(TypeError, paddle.take, x, index, self.mode)
+
+
+class TestTakeModeRaise(unittest.TestCase):
+    """Test take index out of range error"""
+
+    def set_mode(self):
+        self.mode = 'raise'
+
+    def set_dtype(self):
+        self.input_dtype = 'float64'
+        self.index_dtype = 'int64'
+
+    def set_input(self):
+        self.input_shape = [3, 4]
+        self.index_shape = [5, 8]
+        self.input_np = np.arange(0, 12).reshape(self.input_shape).astype(
+            self.input_dtype)
+        self.index_np = np.arange(-20, 20).reshape(self.index_shape).astype(
+            self.index_dtype)  # Both ends of the index are out of bounds
+
+    def setUp(self):
+        self.set_mode()
+        self.set_dtype()
+        self.set_input()
+        self.place = fluid.CUDAPlace(
+            0) if core.is_compiled_with_cuda() else fluid.CPUPlace()
+
+    def test_static_index_error(self):
+        """When the index is out of range,
+        an error is reported directly through `paddle.index_select`"""
+        paddle.enable_static()
+        with program_guard(Program()):
+            x = fluid.data(name='input',
+                           dtype=self.input_dtype,
+                           shape=self.input_shape)
+            index = fluid.data(name='index',
+                               dtype=self.index_dtype,
+                               shape=self.index_shape)
+            self.assertRaises(ValueError, paddle.index_select, x, index)
+
+    def test_dygraph_index_error(self):
+        paddle.disable_static(self.place)
+        x = paddle.to_tensor(self.input_np)
+        index = paddle.to_tensor(self.index_np, dtype=self.index_dtype)
+        self.assertRaises(ValueError, paddle.index_select, x, index)
+
+
+class TestTakeModeWrap(TestTakeAPI):
+    """Test take index out of range mode"""
+
+    def set_mode(self):
+        self.mode = 'wrap'
+
+    def set_input(self):
+        self.input_shape = [3, 4]
+        self.index_shape = [5, 8]
+        self.input_np = np.arange(0, 12).reshape(self.input_shape).astype(
+            self.input_dtype)
+        self.index_np = np.arange(-20, 20).reshape(self.index_shape).astype(
+            self.index_dtype)  # Both ends of the index are out of bounds
+
+
+class TestTakeModeClip(TestTakeAPI):
+    """Test take index out of range mode"""
+
+    def set_mode(self):
+        self.mode = 'clip'
+
+    def set_input(self):
+        self.input_shape = [3, 4]
+        self.index_shape = [5, 8]
+        self.input_np = np.arange(0, 12).reshape(self.input_shape).astype(
+            self.input_dtype)
+        self.index_np = np.arange(-20, 20).reshape(self.index_shape).astype(
+            self.index_dtype)  # Both ends of the index are out of bounds
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/tensor/__init__.py

@@ -234,6 +234,7 @@
 from .math import heaviside  # noqa: F401
 from .math import frac  # noqa: F401
 from .math import sgn  # noqa: F401
+from .math import take  # noqa: F401
 
 from .random import multinomial  # noqa: F401
 from .random import standard_normal  # noqa: F401
@@ -280,8 +281,8 @@
 
 from .einsum import einsum  # noqa: F401
 
-#this list used in math_op_patch.py for _binary_creator_
-tensor_method_func = [  #noqa
+# this list used in math_op_patch.py for _binary_creator_
+tensor_method_func = [  # noqa
     'matmul',
     'dot',
     'cov',
@@ -505,11 +506,12 @@
     'put_along_axis_',
     'exponential_',
     'heaviside',
+    'take',
     'bucketize',
     'sgn',
 ]
 
-#this list used in math_op_patch.py for magic_method bind
+# this list used in math_op_patch.py for magic_method bind
 magic_method_func = [
     ('__and__', 'bitwise_and'),
     ('__or__', 'bitwise_or'),

python/paddle/tensor/math.py

@@ -4735,7 +4735,6 @@ def frac(x, name=None):
                 type="trunc", inputs=inputs, attrs=attrs, outputs={"Out": y})
             return _elementwise_op(LayerHelper(op_type, **locals()))
 
-
 def sgn(x, name=None):
     """
     For complex tensor, this API returns a new tensor whose elements have the same angles as the corresponding
@@ -4776,3 +4775,107 @@ def sgn(x, name=None):
         return paddle.as_complex(output)
     else:
         return paddle.sign(x)
+
+def take(x, index, mode='raise', name=None):
+    """
+    Returns a new tensor with the elements of input tensor x at the given index.
+    The input tensor is treated as if it were viewed as a 1-D tensor.
+    The result takes the same shape as the index.
+
+    Args:
+        x (Tensor): An N-D Tensor, its data type should be int32, int64, float32, float64.
+        index (Tensor): An N-D Tensor, its data type should be int32, int64.
+        mode (str, optional): Specifies how out-of-bounds index will behave. the candicates are ``'raise'``, ``'wrap'`` and ``'clip'``.
+
+            - ``'raise'``: raise an error (default);
+            - ``'wrap'``: wrap around;
+            - ``'clip'``: clip to the range. ``'clip'`` mode means that all indices that are too large are replaced by the index that addresses the last element. Note that this disables indexing with negative numbers.
+
+        name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
+
+    Returns:
+        Tensor, Tensor with the same shape as index, the data type is the same with input.
+
+    Examples:
+        .. code-block:: python
+
+            import paddle
+
+            x_int = paddle.arange(0, 12).reshape([3, 4])
+            x_float = x_int.astype(paddle.float64)
+
+            idx_pos = paddle.arange(4, 10).reshape([2, 3])  # positive index
+            idx_neg = paddle.arange(-2, 4).reshape([2, 3])  # negative index
+            idx_err = paddle.arange(-2, 13).reshape([3, 5])  # index out of range
+
+            paddle.take(x_int, idx_pos)
+            # Tensor(shape=[2, 3], dtype=int64, place=Place(cpu), stop_gradient=True,
+            #        [[4, 5, 6],
+            #         [7, 8, 9]])
+
+            paddle.take(x_int, idx_neg)
+            # Tensor(shape=[2, 3], dtype=int64, place=Place(cpu), stop_gradient=True,
+            #        [[10, 11, 0 ],
+            #         [1 , 2 , 3 ]])
+
+            paddle.take(x_float, idx_pos)
+            # Tensor(shape=[2, 3], dtype=float64, place=Place(cpu), stop_gradient=True,
+            #        [[4., 5., 6.],
+            #         [7., 8., 9.]])
+
+            x_int.take(idx_pos)
+            # Tensor(shape=[2, 3], dtype=int64, place=Place(cpu), stop_gradient=True,
+            #        [[4, 5, 6],
+            #         [7, 8, 9]])
+
+            paddle.take(x_int, idx_err, mode='wrap')
+            # Tensor(shape=[3, 5], dtype=int32, place=Place(cpu), stop_gradient=True,
+            #        [[10, 11, 0 , 1 , 2 ],
+            #         [3 , 4 , 5 , 6 , 7 ],
+            #         [8 , 9 , 10, 11, 0 ]])
+
+            paddle.take(x_int, idx_err, mode='clip')
+            # Tensor(shape=[3, 5], dtype=int32, place=Place(cpu), stop_gradient=True,
+            #        [[0 , 0 , 0 , 1 , 2 ],
+            #         [3 , 4 , 5 , 6 , 7 ],
+            #         [8 , 9 , 10, 11, 11]])
+
+    """
+    if mode not in ['raise', 'wrap', 'clip']:
+        raise ValueError(
+            "'mode' in 'take' should be 'raise', 'wrap', 'clip', but received {}.".format(mode))
+
+    if paddle.in_dynamic_mode():
+        if not isinstance(index, (paddle.Tensor, Variable)):
+            raise TypeError(
+                "The type of 'index' must be Tensor, but got {}".format(type(index)))
+        if index.dtype not in [paddle.int32, paddle.int64]:
+            raise TypeError(
+                "The data type of 'index' must be one of ['int32', 'int64'], but got {}".format(
+                    index.dtype))
+
+    else:
+        check_variable_and_dtype(index, 'index', ['int32', 'int64'], 'take')
+
+    input_1d = x.flatten()
+    index_1d = index.flatten()
+    max_index = input_1d.shape[-1]
+
+    if mode == 'raise':
+        # This processing enables 'take' to handle negative indexes within the correct range.
+        # Negative indexes can be enabled,
+        # but out-of-range indexes will report an error in the following paddle.index_select
+        index_1d = paddle.where(index_1d < 0, index_1d % max_index, index_1d)
+    elif mode == 'wrap':
+        # The out of range indices are constrained by taking the remainder.
+        index_1d = paddle.where(index_1d < 0,
+                                index_1d % max_index, index_1d)
+        index_1d = paddle.where(index_1d >= max_index,
+                                index_1d % max_index, index_1d)
+    elif mode == 'clip':
+        # 'clip' mode disables indexing with negative numbers.
+        index_1d = clip(index_1d, 0, max_index - 1)
+
+    out = input_1d.index_select(index_1d).reshape(index.shape)
+
+    return out