[内部 review] add paddle.nn.functional.pairwise_distance

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

@@ -0,0 +1,23 @@
+#   Copyright (c) 2020 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 paddle
+import paddle.nn.functional as F
+import paddle.fluid as fluid
+import paddle.fluid.core as core
+import numpy as np
+from paddle.fluid.framework import _test_eager_guard

python/paddle/nn/functional/__init__.py

@@ -69,6 +69,7 @@
 from .conv import conv2d_transpose  # noqa: F401
 from .conv import conv3d  # noqa: F401
 from .conv import conv3d_transpose  # noqa: F401
+from .distance import pairwise_distance # noqa: F401
 from .extension import diag_embed  # noqa: F401
 from .extension import sequence_mask
 from .loss import binary_cross_entropy  # noqa: F401

python/paddle/nn/functional/distance.py

@@ -0,0 +1,104 @@
+#   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.
+
+import numpy as np
+
+import paddle
+from .. import Layer
+from ...fluid.data_feeder import check_variable_and_dtype, check_type
+from ...fluid.layer_helper import LayerHelper
+from paddle import _C_ops
+from paddle import in_dynamic_mode
+from paddle.fluid.framework import in_dygraph_mode, _in_legacy_dygraph
+
+__all__ = []
+
+def pairwise_distance(x, y, p=2., epsilon=1e-6, keepdim=False, name=None):
+    r"""
+    This operator computes the pairwise distance between two vectors. The
+    distance is calculated by p-oreder norm:
+
+    .. math::
+
+        \Vert x \Vert _p = \left( \sum_{i=1}^n \vert x_i \vert ^ p \right) ^ {1/p}.
+
+    Parameters:
+        x (Tensor):The input is N-D Tensor , the data type of input is float16 or float32 or float64.
+        y (Tensor):The input is N-D Tensor , the data type of input is float16 or float32 or float64.
+        p (float): The order of norm. The default value is 2.
+        epsilon (float, optional): Add small value to avoid division by zero,
+            default value is 1e-6.
+        keepdim (bool, optional): Whether to reserve the reduced dimension
+            in the output Tensor. The result tensor is one dimension less than
+            the result of ``'x-y'`` unless :attr:`keepdim` is True, default
+            value is False.
+        name (str, optional): Name for the operation (optional, default is None).
+            For more information, please refer to :ref:`api_guide_Name`.
+
+    Shape:
+        x: :math:`[N, D]` where `D` is the dimension of vector, available dtype
+            is float32, float64.
+        y: :math:`[N, D]`, y have the same shape and dtype as x.
+        out: :math:`[N]`. If :attr:`keepdim` is ``True``, the out shape is :math:`[N, 1]`.
+            The same dtype as input tensor.
+
+    Examples:
+        .. code-block:: python
+
+            import paddle
+            import numpy as np
+            paddle.disable_static()
+            x_np = np.array([[1., 3.], [3., 5.]]).astype(np.float64)
+            y_np = np.array([[5., 6.], [7., 8.]]).astype(np.float64)
+            x = paddle.to_tensor(x_np)
+            y = paddle.to_tensor(y_np)
+            dist = paddle.nn.PairwiseDistance()
+            distance = dist(x, y)
+            print(distance.numpy()) # [5. 5.]
+
+    """
+    check_type(p, 'porder', (float, int), 'PairwiseDistance')
+    check_type(epsilon, 'epsilon', (float), 'PairwiseDistance')
+    check_type(keepdim, 'keepdim', (bool), 'PairwiseDistance')
+    if in_dygraph_mode():
+                sub = _C_ops.elementwise_sub(x, y)
+                return _C_ops.final_state_p_norm(sub, p, -1, epsilon,
+                                                keepdim, False)
+
+    if _in_legacy_dygraph():
+        sub = _C_ops.elementwise_sub(x, y)
+        return _C_ops.p_norm(sub, 'axis', -1, 'porder', p, 'keepdim',
+                            keepdim, 'epsilon', epsilon)
+
+    check_variable_and_dtype(x, 'x', ['float32', 'float64'],
+                                 'PairwiseDistance')
+    check_variable_and_dtype(y, 'y', ['float32', 'float64'],
+                                'PairwiseDistance')
+    sub = paddle.subtract(x, y)
+
+    helper = LayerHelper("PairwiseDistance", name=name)
+    attrs = {
+        'axis': -1,
+        'porder': p,
+        'keepdim': keepdim,
+        'epsilon': epsilon,
+    }
+    out = helper.create_variable_for_type_inference(dtype=x.dtype)
+    helper.append_op(type='p_norm',
+                        inputs={'X': sub},
+                        outputs={'Out': out},
+                        attrs=attrs)
+
+    return out
+