chore: import upstream snapshot with attribution

python/paddle/onnx/export.py

@@ -0,0 +1,123 @@
+# 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 annotations
+
+import os
+from typing import TYPE_CHECKING
+
+from paddle.utils import try_import
+
+if TYPE_CHECKING:
+    from collections.abc import Sequence
+
+    from typing_extensions import Unpack
+
+    from paddle import Tensor
+    from paddle.jit.api import _SaveOptions
+    from paddle.nn import Layer
+    from paddle.static import InputSpec
+
+
+__all__ = []
+
+
+def export(
+    layer: Layer,
+    path: str,
+    input_spec: Sequence[InputSpec | Tensor | object] | None = None,
+    opset_version: int = 9,
+    **configs: Unpack[_SaveOptions],
+) -> None:
+    """
+    Export Layer to ONNX format, which can use for inference via onnxruntime or other backends.
+    For more details, Please refer to `paddle2onnx <https://github.com/PaddlePaddle/paddle2onnx>`_ .
+
+    Args:
+        layer (Layer): The Layer to be exported.
+        path (str): The path prefix to export model. The format is ``dirname/file_prefix`` or ``file_prefix`` ,
+            and the exported ONNX file suffix is ``.onnx`` .
+        input_spec (list[InputSpec|Tensor]|None, optional): Describes the input of the exported model's forward
+            method, which can be described by InputSpec or example Tensor. If None, all input variables of
+            the original Layer's forward method would be the inputs of the exported ``ONNX`` model. Default: None.
+        opset_version(int, optional): Opset version of exported ONNX model.
+            Now, stable supported opset version include 9, 10, 11. Default: 9.
+        **configs (dict, optional): Other export configuration options for compatibility. We do not
+            recommend using these configurations, they may be removed in the future. If not necessary,
+            DO NOT use them. Default None.
+            The following options are currently supported:
+            (1) output_spec (list[Tensor]): Selects the output targets of the exported model.
+            By default, all return variables of original Layer's forward method are kept as the
+            output of the exported model. If the provided ``output_spec`` list is not all output variables,
+            the exported model will be pruned according to the given ``output_spec`` list.
+    Returns:
+        None
+    Examples:
+        .. code-block:: pycon
+
+            >>> import paddle
+
+            >>> class LinearNet(paddle.nn.Layer):
+            ...     def __init__(self):
+            ...         super().__init__()
+            ...         self._linear = paddle.nn.Linear(128, 10)
+            ...
+            ...     def forward(self, x):
+            ...         return self._linear(x)
+            >>> # Export model with 'InputSpec' to support dynamic input shape.
+            >>> def export_linear_net():
+            ...     model = LinearNet()
+            ...     x_spec = paddle.static.InputSpec(shape=[None, 128], dtype='float32')
+            ...     paddle.onnx.export(model, 'linear_net', input_spec=[x_spec])
+            >>> # doctest: +SKIP('Need install Paddle2ONNX')
+            >>> export_linear_net()
+
+            >>> class Logic(paddle.nn.Layer):
+            ...     def __init__(self):
+            ...         super().__init__()
+            ...
+            ...     def forward(self, x, y, z):
+            ...         if z:
+            ...             return x
+            ...         else:
+            ...             return y
+            >>> # Export model with 'Tensor' to support pruned model by set 'output_spec'.
+            >>> def export_logic():
+            ...     model = Logic()
+            ...     x = paddle.to_tensor([1])
+            ...     y = paddle.to_tensor([2])
+            ...     # Static and run model.
+            ...     paddle.jit.to_static(model)
+            ...     out = model(x, y, z=True)
+            ...     paddle.onnx.export(model, 'pruned', input_spec=[x, y, True], output_spec=[out], input_names_after_prune=[x.name])
+            >>> export_logic()
+    """
+
+    p2o = try_import('paddle2onnx')
+
+    file_prefix = os.path.basename(path)
+    if file_prefix == "":
+        raise ValueError(
+            "The input path MUST be format of dirname/file_prefix "
+            "[dirname\\file_prefix in Windows system], but "
+            f"the file_prefix is empty in received path: {path}"
+        )
+    save_file = path + '.onnx'
+
+    p2o.dygraph2onnx(
+        layer,
+        save_file,
+        input_spec=input_spec,
+        opset_version=opset_version,
+        **configs,
+    )