[SWE-Paddle] Add task PaddlePaddle__Paddle_74439

swe-paddle/tasks/PaddlePaddle__Paddle-74439/README.md

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+# PaddlePaddle__Paddle-74439
+
+This directory converts Paddle PR #74439 into a SWE-Paddle community task candidate.
+
+## Source
+
+| Field | Value |
+| --- | --- |
+| Repo | `PaddlePaddle/Paddle` |
+| PR | [74439](https://github.com/PaddlePaddle/Paddle/pull/74439) |
+| PR title | `[API compatibility] add paddle.ravel` |
+| Base commit | `cb81162732f15ae02e82b07f8462e04b093c2464` |
+| Merged at | `2025-08-08` |
+| Task type | `feature_enhancement` |
+| Resource | CPU |
+
+## Summary
+
+Add a public `paddle.ravel` API that returns a one-dimensional flattened result for tensors of any rank, including scalars and empty tensors.
+
+## Why This Is A Good SWE-Paddle Candidate
+
+- It comes from a merged Paddle API-compatibility pull request with a small, well-defined production scope.
+- The target behavior is user-visible through both `paddle.ravel` and `paddle.tensor.ravel`.
+- The existing `flatten` API provides a stable regression guard for behavior that must remain unchanged.
+- The Python-only implementation can be verified deterministically with AST overlays and controlled doubles without a Paddle source build.
+
+## Files
+
+- `proposal.md`: candidate proposal for maintainer triage.
+- `instruction.md`: self-contained problem statement for the coding agent.
+- `solution/code.patch`: production-only gold patch from the merged PR.
+- `tests/test.patch`: test patch exposing the target behavior.
+- `tests/test.sh`: minimal target test command.
+- `environment/README.md`: environment notes for reproduction.
+- `README.md`: task overview and verification entrypoint.
+
+## Verification
+
+```bash
+bash tests/test.sh
+```
+
+Expected behavior: applying `tests/test.patch` to the base commit should preserve the existing `flatten` regression test while failing the new `ravel` behavior tests; applying both patches should make all target tests pass.

swe-paddle/tasks/PaddlePaddle__Paddle-74439/environment/README.md

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+# Environment Notes
+
+This candidate is part of the SWE-Paddle community task set.
+
+## Expected Environment
+
+- Repository: `PaddlePaddle/Paddle`
+- Base commit: `cb81162732f15ae02e82b07f8462e04b093c2464`
+- Resource: CPU
+- GPU required: no
+- Build path: Paddle source checkout at the base commit. This Python-only task is verified with AST overlays and controlled doubles; a source build is not required.
+
+## Run Order
+
+1. Check out `PaddlePaddle/Paddle` at the base commit.
+2. Apply `tests/test.patch`.
+3. Run `bash tests/test.sh`; the target behavior should fail before the fix.
+4. Apply `solution/code.patch`.
+5. Run `bash tests/test.sh` again; the target behavior should pass after the gold patch.
+
+## Minimal Test Command
+
+```bash
+bash tests/test.sh
+```
+
+The verifier is responsible for deriving stable F2P and P2P node IDs from repeated runs.

swe-paddle/tasks/PaddlePaddle__Paddle-74439/instruction.md

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+# 新增 `paddle.ravel` API
+
+## 详细描述
+
+Paddle 当前缺少用于完整展平 Tensor 的 `ravel` 公共接口。调用方需要能够将任意维度的 Tensor 转换为一维 Tensor，同时保持原有的元素顺序和数据类型。需要新增 `paddle.ravel`，并使其能够处理标量、一维 Tensor、多维 Tensor，以及包含零长度维度的 Tensor。该接口应同时支持动态图和静态图模式，并保持正确的梯度传播行为。同时保持现有 `flatten` 接口的合法调用方式和行为不得受到影响。
+
+## 验收说明
+
+* `paddle.ravel` 应作为公开 API 提供，并能够从 `paddle` 和 `paddle.tensor` 命名空间访问
+* API 应支持通过 `input` 参数传入 Tensor
+* 返回结果应为一维 Tensor，元素顺序和数据类型应与输入保持一致
+* 标量输入应得到只包含一个元素的一维结果
+* 一维和多维 Tensor 应得到符合完整展平语义的结果
+* 包含零长度维度的 Tensor 应得到形状正确的空一维结果
+* API 应能够在动态图和静态图模式下正常使用
+* 动态图模式下的反向传播行为应正确
+* 现有 `flatten` 接口的行为不得发生变化
+
+## 技术要求
+
+* 熟悉 Paddle Python Tensor API 及公共接口导出方式
+* 理解 Tensor 的形状、维数和完整展平语义
+* 了解 Paddle 动态图、静态图和自动求导机制

swe-paddle/tasks/PaddlePaddle__Paddle-74439/proposal.md

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+# Task Proposal: PaddlePaddle__Paddle-74439
+
+## 1. 来源信息
+
+* Instance ID：`PaddlePaddle__Paddle-74439`
+* PR 链接：https://github.com/PaddlePaddle/Paddle/pull/74439
+* PR 标题：`[API compatibility] add paddle.ravel`
+* `base_commit`：`cb81162732f15ae02e82b07f8462e04b093c2464`
+* merged 时间：`2025-08-08`
+* 你的身份：熟悉该模块的 contributor
+* 后续联系人：TBD
+
+## 2. 问题一句话
+
+为 Paddle 新增公开的 `ravel` API，使任意维度的 Tensor 都能够在保持元素顺序的前提下完整展平为一维结果。
+
+## 3. 为什么适合作为 SWE-Paddle 样本
+
+* **真实性**：该任务来自已经合入 Paddle `develop` 分支的 API compatibility PR #74439，不是人工构造的需求。
+* **代表性**：该任务涉及 Tensor 形状变换、公共 API 导出、动态图与静态图支持，以及不同维度输入的边界行为。
+* **边界清楚**：production change 集中在三个 Python 文件中，功能范围明确；原 PR 测试覆盖 `ravel` 的前向结果、反向传播和不同维度输入。
+* **非平凡性**：任务不仅需要新增公开接口，还要正确处理标量、一维、多维和空 Tensor，并保证现有 `flatten` 行为不受影响。
+
+## 4. 任务类型和标签
+
+* 任务类型：`feature_enhancement`
+* 执行后端：`cpu`
+* 设备范围：`cpu_only`
+* 模块标签：`[tensor, manipulation, api_compatibility, flatten, python_api]`
+
+## 5. 验证思路
+
+* 目标测试命令：`bash tests/test.sh`
+* 目标测试文件：`test/swe_paddle/test_pr74439_ravel.py`
+* 修复前预期：现有 `flatten` 动态图路径的回归测试应通过；`ravel` 的公共导出、展平结果和边界输入测试应失败。
+* 修复后预期：继续应用 `solution/code.patch` 后，现有 `flatten` 测试应继续通过；`ravel` 对标量、一维、多维和空 Tensor 的测试，以及公共命名空间导出测试均应通过。
+* P2P 候选：现有 `flatten` 在 dynamic/PIR 路径下的参数处理、底层调用和返回行为保持不变。
+
+## 6. 环境与资源
+
+* 资源需求：CPU
+* Paddle 来源：`PaddlePaddle/Paddle` source checkout at `base_commit`
+* 是否能提供 Docker：暂无
+* patch 类型：Python-only
+* 最小测试命令：`bash tests/test.sh`
+* 是否有 oracle 日志：由 SWE-Paddle verifier 结果另行维护
+
+## 7. 风险自查
+
+* 泄露风险：`instruction.md` 只描述 `ravel` 的公开接口、展平语义、边界输入和兼容性要求，不透露 Gold patch 的具体函数调用方式或修改位置。
+* 环境风险：测试不导入历史 Paddle package 的完整运行环境，而是执行 source checkout 中相关的 Python 控制流程，避免对 native extension 的依赖。
+* flaky 风险：测试使用固定输入并验证确定性的形状、元素顺序和对象行为，不依赖随机数、GPU、设备调度或异步执行。
+* 拆分风险：公共命名空间导出、完整展平语义和边界输入支持共同构成 `ravel` API 的完整能力，适合作为单个任务。

swe-paddle/tasks/PaddlePaddle__Paddle-74439/solution/code.patch

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+diff --git a/python/paddle/__init__.py b/python/paddle/__init__.py
+index a138b8d52324f1dd99ddc9526270e25cf529fbbb..4ebc15fdc9753cc7b70071b143974f5140b81239 100644
+--- a/python/paddle/__init__.py
++++ b/python/paddle/__init__.py
+@@ -328,6 +328,7 @@ from .tensor.manipulation import (
+     masked_scatter_,
+     moveaxis,
+     put_along_axis,
++    ravel,
+     repeat_interleave,
+     reshape,
+     reshape_,
+@@ -1094,6 +1095,7 @@ __all__ = [
+     'std',
+     'flatten',
+     'flatten_',
++    'ravel',
+     'asin',
+     'multiply',
+     'multiply_',
+diff --git a/python/paddle/tensor/__init__.py b/python/paddle/tensor/__init__.py
+index 3f0495ac94fffc7bdcc95a557c40f57900136351..32425a36ee145d5851b81a782ff30bec5b9a3d5e 100644
+--- a/python/paddle/tensor/__init__.py
++++ b/python/paddle/tensor/__init__.py
+@@ -193,6 +193,7 @@ from .manipulation import (  # noqa: F401
+     moveaxis,
+     put_along_axis,
+     put_along_axis_,
++    ravel,
+     repeat_interleave,
+     reshape,
+     reshape_,
+diff --git a/python/paddle/tensor/manipulation.py b/python/paddle/tensor/manipulation.py
+index 9904dd9b1ee64d89e732f329eb871e5bd85a8954..857554b5dd1f2a005437b8548f5027ef9e79204d 100644
+--- a/python/paddle/tensor/manipulation.py
++++ b/python/paddle/tensor/manipulation.py
+@@ -1992,6 +1992,46 @@ def flatten(
+         return out
+
+
++def ravel(input: Tensor) -> Tensor:
++    """
++    Return a contiguous flattened tensor. A copy is made only if needed.
++    Note:
++        The output Tensor will share data with origin Tensor and doesn't have a Tensor copy in ``dygraph`` mode.
++        If you want to use the Tensor copy version, please use `Tensor.clone` like ``ravel_clone_x = x.ravel().clone()``.
++        For example:
++
++        .. code-block:: text
++            Case 1:
++              Given
++                X.shape = (3, 100, 100, 4)
++
++              We get:
++                Out.shape = (3 * 100 * 100 * 4)
++    Args:
++        x (Tensor): A tensor of number of dimensions >= axis. A tensor with data type float16, float32,
++                      float64, int8, int32, int64, uint8.
++
++    Returns:
++        Tensor: A tensor with the contents of the input tensor, whose input axes are flattened by indicated :attr:`start_axis` and :attr:`stop_axis`, and data type is the same as input :attr:`x`.
++
++    Examples:
++
++        .. code-block:: python
++
++            >>> import paddle
++
++            >>> image_shape=(2, 3, 4, 4)
++
++            >>> x = paddle.arange(end=image_shape[0] * image_shape[1] * image_shape[2] * image_shape[3])
++            >>> img = paddle.reshape(x, image_shape)
++
++            >>> out = paddle.ravel(img)
++            >>> print(out.shape)
++            [96]
++    """
++    return flatten(input)
++
++
+ @inplace_apis_in_dygraph_only
+ def flatten_(
+     x: Tensor, start_axis: int = 0, stop_axis: int = -1, name: str | None = None

swe-paddle/tasks/PaddlePaddle__Paddle-74439/tests/test.patch

@@ -0,0 +1,154 @@
+diff --git a/test/swe_paddle/test_pr74439_ravel.py b/test/swe_paddle/test_pr74439_ravel.py
+new file mode 100644
+--- /dev/null
++++ b/test/swe_paddle/test_pr74439_ravel.py
+@@ -0,0 +1,149 @@
++import ast
++import copy
++import sys
++import types
++from pathlib import Path
++
++import numpy as np
++
++TARGET = Path("python/paddle/tensor/manipulation.py")
++ROOT_INIT = Path("python/paddle/__init__.py")
++TENSOR_INIT = Path("python/paddle/tensor/__init__.py")
++
++
++def _extract_function(name, namespace):
++    tree = ast.parse(TARGET.read_text(encoding="utf-8"), filename=str(TARGET))
++    node = next(
++        (
++            copy.deepcopy(item)
++            for item in tree.body
++            if isinstance(item, (ast.FunctionDef, ast.AsyncFunctionDef))
++            and item.name == name
++        ),
++        None,
++    )
++    assert node is not None, f"paddle.tensor.manipulation must provide {name}"
++    node.decorator_list = []
++    ast.fix_missing_locations(node)
++    scope = dict(namespace)
++    exec(compile(ast.Module(body=[node], type_ignores=[]), str(TARGET), "exec"), scope)
++    return scope[name]
++
++
++def _execute_public_import(path, package_name):
++    tree = ast.parse(path.read_text(encoding="utf-8"), filename=str(path))
++    node = next(
++        (
++            copy.deepcopy(item)
++            for item in tree.body
++            if isinstance(item, ast.ImportFrom)
++            and any(alias.name == "ravel" for alias in item.names)
++        ),
++        None,
++    )
++    assert node is not None, f"{path} must publicly import ravel"
++    assert node.level == 1 and node.module
++
++    module_parts = node.module.split(".")
++    module_name = ".".join([package_name, *module_parts])
++    module_names = [package_name]
++    for index in range(1, len(module_parts)):
++        module_names.append(".".join([package_name, *module_parts[:index]]))
++    module_names.append(module_name)
++
++    saved = {name: sys.modules.get(name) for name in module_names}
++    for name in module_names[:-1]:
++        package = types.ModuleType(name)
++        package.__path__ = []
++        sys.modules[name] = package
++
++    imported = types.ModuleType(module_name)
++    marker = object()
++    for alias in node.names:
++        setattr(imported, alias.name, marker if alias.name == "ravel" else object())
++    sys.modules[module_name] = imported
++
++    try:
++        scope = {"__package__": package_name, "__name__": f"{package_name}.probe"}
++        ast.fix_missing_locations(node)
++        exec(compile(ast.Module(body=[node], type_ignores=[]), str(path), "exec"), scope)
++    finally:
++        for name in reversed(module_names):
++            previous = saved[name]
++            if previous is None:
++                sys.modules.pop(name, None)
++            else:
++                sys.modules[name] = previous
++    return scope, marker
++
++
++class _Variable:
++    def __init__(self, shape):
++        self.shape = shape
++
++
++class _PirValue:
++    pass
++
++
++def test_existing_flatten_dynamic_path_remains_compatible():
++    calls = []
++    marker = object()
++
++    def native_flatten(value, start_axis, stop_axis):
++        calls.append((value, start_axis, stop_axis))
++        return marker
++
++    paddle = types.SimpleNamespace(pir=types.SimpleNamespace(Value=_PirValue))
++    function = _extract_function(
++        "flatten",
++        {
++            "Tensor": object,
++            "Variable": _Variable,
++            "paddle": paddle,
++            "in_dynamic_or_pir_mode": lambda: True,
++            "_C_ops": types.SimpleNamespace(flatten=native_flatten),
++            "check_variable_and_dtype": lambda *args, **kwargs: None,
++            "LayerHelper": object,
++        },
++    )
++    value = _Variable((2, 3, 4))
++    assert function(value, start_axis=1, stop_axis=-1) is marker
++    assert calls == [(value, 1, 2)]
++
++
++def test_ravel_flattens_scalar_multidimensional_and_empty_inputs():
++    def controlled_flatten(value, *args, **kwargs):
++        return np.asarray(value).reshape(-1)
++
++    function = _extract_function(
++        "ravel",
++        {
++            "Tensor": object,
++            "flatten": controlled_flatten,
++            "reshape": lambda value, shape: np.asarray(value).reshape(shape),
++            "paddle": types.SimpleNamespace(
++                flatten=controlled_flatten,
++                reshape=lambda value, shape: np.asarray(value).reshape(shape),
++            ),
++            "np": np,
++        },
++    )
++    cases = [
++        np.array(5.0, dtype="float32"),
++        np.array([7.0, 8.0, 9.0], dtype="float32"),
++        np.arange(24, dtype="float32").reshape(2, 3, 4),
++        np.array([], dtype="float32").reshape(0, 3),
++    ]
++    for value in cases:
++        result = function(value)
++        expected = value.reshape(-1)
++        assert result.ndim == 1
++        np.testing.assert_array_equal(result, expected)
++
++
++def test_ravel_is_reexported_from_public_namespaces():
++    tensor_scope, tensor_marker = _execute_public_import(TENSOR_INIT, "swe_fake_paddle_tensor")
++    assert tensor_scope.get("ravel") is tensor_marker
++    root_scope, root_marker = _execute_public_import(ROOT_INIT, "swe_fake_paddle")
++    assert root_scope.get("ravel") is root_marker

swe-paddle/tasks/PaddlePaddle__Paddle-74439/tests/test.sh

@@ -0,0 +1,4 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+python -m pytest test/swe_paddle/test_pr74439_ravel.py -q