chore: import upstream snapshot with attribution

python/paddle/distributed/entry_attr.py

@@ -0,0 +1,200 @@
+#   Copyright (c) 2018 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 annotations
+
+__all__ = []
+
+
+class EntryAttr:
+    """
+    Entry Config for paddle.static.nn.sparse_embedding with Parameter Server.
+
+    Examples:
+        .. code-block:: pycon
+
+            >>> import paddle
+            >>> paddle.enable_static()
+
+            >>> sparse_feature_dim = 1024
+            >>> embedding_size = 64
+
+            >>> entry = paddle.distributed.ProbabilityEntry(0.1)
+
+            >>> input = paddle.static.data(name='ins', shape=[1], dtype='int64')
+
+            >>> emb = paddle.static.nn.sparse_embedding(
+            ...     input=input,
+            ...     size=[sparse_feature_dim, embedding_size],
+            ...     is_test=False,
+            ...     entry=entry,
+            ...     param_attr=paddle.ParamAttr(
+            ...         name="SparseFeatFactors",
+            ...         initializer=paddle.nn.initializer.Uniform(),
+            ...     ),
+            ... )
+
+    """
+
+    def __init__(self) -> None:
+        self._name = None
+
+    def _to_attr(self) -> str:
+        """
+        Returns the attributes of this parameter.
+
+        Returns:
+            Parameter attributes(map): The attributes of this parameter.
+        """
+        raise NotImplementedError("EntryAttr is base class")
+
+
+class ProbabilityEntry(EntryAttr):
+    """
+    Examples:
+        .. code-block:: pycon
+
+            >>> # doctest: +SKIP("paddle.distributed.ProbabilityEntry is not supported in PIR mode currently")
+            >>> import paddle
+            >>> paddle.enable_static()
+
+            >>> sparse_feature_dim = 1024
+            >>> embedding_size = 64
+
+            >>> entry = paddle.distributed.ProbabilityEntry(0.1)
+
+            >>> input = paddle.static.data(name='ins', shape=[1], dtype='int64')
+
+            >>> emb = paddle.static.nn.sparse_embedding(
+            ...     input=input,
+            ...     size=[sparse_feature_dim, embedding_size],
+            ...     is_test=False,
+            ...     entry=entry,
+            ...     param_attr=paddle.ParamAttr(
+            ...         name="SparseFeatFactors",
+            ...         initializer=paddle.nn.initializer.Uniform(),
+            ...     ),
+            ... )
+
+
+    """
+
+    def __init__(self, probability: float) -> None:
+        super().__init__()
+
+        if not isinstance(probability, float):
+            raise ValueError("probability must be a float in (0,1)")
+
+        if probability <= 0 or probability >= 1:
+            raise ValueError("probability must be a float in (0,1)")
+
+        self._name = "probability_entry"
+        self._probability = probability
+
+    def _to_attr(self) -> str:
+        return ":".join([self._name, str(self._probability)])
+
+
+class CountFilterEntry(EntryAttr):
+    """
+    Examples:
+        .. code-block:: pycon
+
+            >>> # doctest: +SKIP("paddle.distributed.CountFilterEntry is not supported in PIR mode currently")
+            >>> import paddle
+            >>> paddle.enable_static()
+
+            >>> sparse_feature_dim = 1024
+            >>> embedding_size = 64
+
+            >>> entry = paddle.distributed.CountFilterEntry(10)
+
+            >>> input = paddle.static.data(name='ins', shape=[1], dtype='int64')
+
+            >>> emb = paddle.static.nn.sparse_embedding(
+            ...     input=input,
+            ...     size=[sparse_feature_dim, embedding_size],
+            ...     is_test=False,
+            ...     entry=entry,
+            ...     param_attr=paddle.ParamAttr(
+            ...         name="SparseFeatFactors",
+            ...         initializer=paddle.nn.initializer.Uniform(),
+            ...     ),
+            ... )
+
+    """
+
+    def __init__(self, count_filter: int) -> None:
+        super().__init__()
+
+        if not isinstance(count_filter, int):
+            raise ValueError(
+                "count_filter must be a valid integer greater than 0"
+            )
+
+        if count_filter < 0:
+            raise ValueError(
+                "count_filter must be a valid integer greater or equal than 0"
+            )
+
+        self._name = "count_filter_entry"
+        self._count_filter = count_filter
+
+    def _to_attr(self) -> str:
+        return ":".join([self._name, str(self._count_filter)])
+
+
+class ShowClickEntry(EntryAttr):
+    """
+    Examples:
+        .. code-block:: pycon
+
+            >>> # doctest: +SKIP("paddle.distributed.ShowClickEntry is not supported in PIR mode currently")
+            >>> import paddle
+            >>> paddle.enable_static()
+
+            >>> sparse_feature_dim = 1024
+            >>> embedding_size = 64
+
+            >>> shows = paddle.static.data(name='show', shape=[1], dtype='int64')
+            >>> clicks = paddle.static.data(name='click', shape=[1], dtype='int64')
+            >>> input = paddle.static.data(name='ins', shape=[1], dtype='int64')
+
+            >>> entry = paddle.distributed.ShowClickEntry("show", "click")
+
+            >>> emb = paddle.static.nn.sparse_embedding(
+            ...     input=input,
+            ...     size=[sparse_feature_dim, embedding_size],
+            ...     is_test=False,
+            ...     entry=entry,
+            ...     param_attr=paddle.ParamAttr(
+            ...         name="SparseFeatFactors",
+            ...         initializer=paddle.nn.initializer.Uniform(),
+            ...     ),
+            ... )
+
+
+    """
+
+    def __init__(self, show_name: str, click_name: str) -> None:
+        super().__init__()
+
+        if not isinstance(show_name, str) or not isinstance(click_name, str):
+            raise ValueError("show_name click_name must be a str")
+
+        self._name = "show_click_entry"
+        self._show_name = show_name
+        self._click_name = click_name
+
+    def _to_attr(self) -> str:
+        return ":".join([self._name, self._show_name, self._click_name])