[API Compatibility] Align paddle.Tensor.is_sparse, paddle.Tensor.type, paddle.Tensor.size api, paddle.nn.PReLU and paddle.distributions.categorical.Categorical -part by Manfredss · Pull Request #79550 · PaddlePaddle/Paddle

Manfredss · 2026-07-27T07:56:03Z

PR Category

User Experience

PR Types

Improvements

Description

Align the following Paddle APIs with their PyTorch counterparts:

Align paddle.Tensor.numel() to return a Python int under enable_compat(level=2).
Align paddle.Tensor.is_sparse as a property and return True only for sparse COO tensors.
Align paddle.Tensor.type() behavior, including type queries, dtype/class/string conversions, device handling, and same-type identity preservation.
Extend paddle.nn.PReLU to accept PyTorch-style device and dtype positional and keyword arguments.
Align paddle.distributions.categorical.Categorical

Paddle-internal callers retain native Tensor semantics, and all patched attributes are restored after disabling compat.

Also refine the compat level semantics and make use_compat_guard restore the original compat state. Add lifecycle and real-torch regression tests. This is related to

[API Compatibility] Change compatibility apis to ChangePrefixMatcher, inject paddle.enable_compat(), fix test environment context pollution -part PaConvert#895

是否引起精度变化

否

paddle-bot · 2026-07-27T07:56:10Z

你的PR提交成功，感谢你对开源项目的贡献!
请关注后续CI自动化测试结果，详情请参考Paddle-CI手册。
Your PR has been submitted. Thanks for your contribution!
Please wait for the result of CI firstly. See Paddle CI Manual for details.

risemeup1111

序号	位置	优先级	状态
1	`python/paddle/utils/decorator_utils.py`		🚧
2	`python/paddle/compat/proxy.py`		🚧

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P0、P1 级别的评审必须提交新的 commit 进行修改；
P2、P3 级别的评审可以通过评论进行修改。

状态说明：

已解决	无需修复	待修复
✅	🟡	🚧

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risemeup1111 · 2026-07-27T08:07:42Z

+        is_torch_device = weight_attr is None or (
+            isinstance(weight_attr, str)
+            and weight_attr.split(':', 1)[0].lower()
+            in {'cpu', 'cuda', 'gpu', 'xpu', 'mps', 'meta'}
+        )
+        if is_torch_device:
+            if not isinstance(data_format, str):
+                device, dtype = weight_attr, data_format
+                weight_attr, data_format = None, "NCHW"
+            elif weight_attr is not None and data_format == "NCHW":
+                device, weight_attr = weight_attr, None


优先级：P1

问题： 这里把第三个位置参数为 "cpu"/"cuda" 等字符串且 data_format 仍为默认值的调用重解释成 PyTorch 的 device。但 weight_attr: ParamAttrLike 旧 API 明确支持字符串参数名，ParamAttr._to_attr("cpu") 会创建名为 "cpu" 的参数；现在 paddle.nn.PReLU(2, 0.5, "cpu") 会丢掉 weight_attr 并创建匿名参数。

影响： 这是原生 paddle.nn.PReLU 构造函数的全局行为变化，不需要开启 enable_compat(level=2) 就会触发，会破坏依赖参数名的旧模型代码、静态图或 checkpoint/state_dict 兼容性。

处理要求：请针对该评论修复并提交新的 commit。

期望： 保留旧的字符串 weight_attr 语义；PyTorch 的无 dtype 位置参数 device 形态建议放到 paddle.compat.nn.PReLU/level=2 alias 中处理，或至少只在不会与旧 weight_attr 字符串冲突的形态下重解释。例如可以按下面的形态收窄 native 构造函数里的自动重解释：

# 伪代码：仅处理第四个位置参数明确是 dtype/device pair 的无冲突形态 if not isinstance(data_format, str): device, dtype = weight_attr, data_format weight_attr, data_format = None, "NCHW" # PReLU(..., "cpu") 这种无 dtype 的 PyTorch 形态不要在 native paddle.nn.PReLU # 中覆盖字符串 weight_attr；如需支持，请放到 compat-only wrapper 中。

… three_Tensor_and_PReLU

codecov-commenter · 2026-07-27T11:41:46Z

Codecov Report

❌ Patch coverage is 96.35036% with 5 lines in your changes missing coverage. Please review.
⚠️ Please upload report for BASE (develop@c228e06). Learn more about missing BASE report.

Files with missing lines	Patch %	Lines
python/paddle/compat/proxy.py	89.47%	4 Missing ⚠️
python/paddle/utils/decorator_utils.py	94.44%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             develop   #79550   +/-   ##
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==========================================
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Manfredss · 2026-07-27T11:47:55Z

/re-run all-failed

Manfredss · 2026-07-28T01:59:33Z

/re-run all-failed

risemeup1111

已复查当前 head，先前指出的 PReLU(2, 0.5, "cpu") 后向兼容问题在代码上已经修复。本次新增一个非阻塞的行级建议，细节见 inline comment；另外 CI 里 Static-Check / Slice 仍有红灯，合入前还需要继续跟进。

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risemeup1111 · 2026-07-28T02:29:57Z

+        return f"{prefix}.{tensor_type}"
+
+    device = None
+    if isinstance(dtype, type):


优先级：P2

问题： 这里用 isinstance(dtype, type) 捕获所有 Python type，然后只按 FloatTensor/DoubleTensor 这类 tensor factory 名称识别。DTypeLike 里包含 np.float32、np.float64、np.int64 等 numpy scalar type；这些对象也是 type，会在这里因为 dtype.__name__（例如 "float64"）不在 _TENSOR_TYPE_DTYPES 而直接 ValueError，无法走后面的 input.to(dtype=dtype)。

影响： enable_compat(level=2) 后，t.type(np.float64) 这类 Paddle 其他 dtype 参数常见写法会被误判为非法 tensor class。与当前签名里的 DTypeLike | str | type 不一致，也缺少测试覆盖。

处理要求：请针对该评论进行回复（同意并已修改请回复 Done，不同意请说明理由）。

期望： 只把已知 tensor factory class 当作 PyTorch-style class conversion，其他 DTypeLike 继续交给 Tensor.to 校验/转换，并补一个 np.float64 之类的回归测试。可以先把该行收窄为：

Suggested change

if isinstance(dtype, type):

if isinstance(dtype, type) and dtype.__name__ in _TENSOR_TYPE_DTYPES:

优先级：P2

补充复查：新提交的 test_tensor_type_edge_cases 覆盖了 t.type(paddle.float64, **{"async": True})，但这个参数不是 Python type，不会进入当前 if isinstance(dtype, type): 分支；原问题里的 np.float64 / np.int64 等 numpy scalar type 仍会进入该分支并因为 "float64" 不在 _TENSOR_TYPE_DTYPES 里抛 ValueError。

处理要求：请针对该评论进行回复（同意并已修改请回复 Done，不同意请说明理由）。

建议仍按上面 suggestion 收窄 tensor factory class 的判断，并把回归测试补到 numpy dtype 路径，例如：

import numpy as np self.assertEqual(t.type(np.float64).dtype, paddle.float64)

优先级：P1

补充复查：这个提交把原来的判断改成了 dtype.__name__ in _TENSOR_TYPE_NAMES，但 _TENSOR_TYPE_NAMES 的 key 是 "float32"/"float64" 这类 dtype 名；paddle.DoubleTensor 来自 dtype_tensor_factory('float64', 'DoubleTensor')，__name__ 是 "DoubleTensor"。因此 t.type(paddle.DoubleTensor) 不会进入这里的 tensor factory class 分支，会继续把 class 对象传给 input.to(dtype=...)，这不是 DTypeLike 支持的输入，新增的 self.assertEqual(t.type(paddle.DoubleTensor).dtype, paddle.float64) 也会失败。

处理要求：请针对该评论修复并提交新的 commit。

请把 class 分支的 membership 查 _TENSOR_TYPE_DTYPES（反查表）而不是 _TENSOR_TYPE_NAMES，并保留这次补上的 np.float64 回归测试。修复形态可以是：

if isinstance(dtype, type) and dtype.__name__ in _TENSOR_TYPE_DTYPES: tensor_type = dtype.__name__ dtype = _TENSOR_TYPE_DTYPES[tensor_type] device = "cpu"

risemeup1111

已复查最新提交。先前的 PReLU(2, 0.5, "cpu") 后向兼容问题在当前代码里仍是修复状态。

不过 _tensor_type 的 follow-up 修复把 tensor factory class 的查表对象写反了，当前仍会影响 t.type(paddle.DoubleTensor) 这类兼容路径；我已在既有行级线程里补充了具体证据和修复形态。这个问题需要再提交一个修复 commit 后才能通过。当前还有部分 CI 在运行中，请合入前继续确认结果。

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risemeup1111

已复查最新提交，先前关于 PReLU 后向兼容和 Tensor.type dtype/class 处理的意见在当前代码中都已修复，未发现新的需要阻塞合入的问题。当前仍有部分 CI 在运行中，合入前请继续确认最终结果。

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Manfredss · 2026-07-28T06:01:41Z

/re-run all-failed

Manfredss · 2026-07-28T08:28:02Z

/re-run all-failed

risemeup1111

已复查最新提交。此前关于 PReLU 和 Tensor.type 的问题在当前代码中仍是修复状态。

这次新增的 Categorical 参数校验还有一个需要修正的兼容性问题，具体见行级评论。当前仍有部分 CI 在运行中，合入前请继续确认最终结果。

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Manfredss · 2026-07-29T01:44:02Z

/re-run all-failed

risemeup1111

已复查你在 Categorical 线程里的说明，确认当前实现与 PyTorch 的 probs 归一化/校验顺序一致；此前这条阻塞意见已撤回。先前关于 PReLU 和 Tensor.type 的问题在当前 head 中也仍是修复状态，未发现新的需要阻塞合入的问题。

当前仍有部分 CI 未完成/有红灯，请合入前继续确认最终结果。

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risemeup1111

已复查标题更新，当前标题已覆盖这次新增的 Categorical 兼容范围；代码 head 未变化，先前评审结论不变，未发现新的需要阻塞合入的问题。

当前仍有部分 CI 未完成/有红灯，请合入前继续确认最终结果。

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Manfredss · 2026-07-29T06:16:25Z

/re-run all-failed

Manfredss · 2026-07-29T09:08:57Z

@zhwesky20 review this PR, Thx

zhwesky2010 · 2026-08-05T10:37:11Z

+        return str(input.dtype)
+
+    device = None
+    if isinstance(dtype, type) and dtype.__name__ in _TENSOR_TYPE_DTYPES:


这里是否考虑了全部情况且能正确执行：

paddle.float32 np.float32 'float32' 'paddle.FloatTensor' 'torch.FloatTensor'

zhwesky2010 · 2026-08-05T10:45:32Z

-        compat_fn = getattr(compat_root, attr_name)
-        _PADDLE_NAMESPACE_SAVED[(paddle.Tensor, attr_name)] = native_method
+        _PADDLE_NAMESPACE_SAVED[(paddle.Tensor, attr_name)] = native_attr
+        if isinstance(compat_attr, property) or inspect.isdatadescriptor(


在这个地方做四分支判断，最大化提升性能

Manfredss · 2026-08-06T08:55:28Z

/re-run all-failed

… three_Tensor_and_PReLU

zhwesky2010

小问题，如果还需要提交则顺便改，如果无需再提交则不用管。

zhwesky2010 · 2026-08-06T10:51:37Z

    return proxy


+def dispatch_property(


这里有点奇怪，property->func、func->property、property->property 三个分支可以共享这一个dispatch吗？

如果能共享，那后面三个分支也可以合并了

zhwesky2010 · 2026-08-06T10:51:52Z

+                dispatcher = dispatch_property(native_attr, compat_attr)
+            else:
+                # native function -> compat property
+                dispatcher = dispatch_property(native_attr, compat_attr)


这里三个分支看起来可以合并？

确实是可以合并的

zhwesky2010 · 2026-08-06T10:55:16Z

@SigureMo 需要review下enable_compat的接口变动。由于paconvert测试会同时跑 torch+paddle代码来比较结果，原设计会出现很多地方无法跑的问题，因此对enable_compat的功能进行了解耦设计：

level=1：默认情况，原功能不变，重定位 torch.* -> paddle.*
level=2：重定位 paddle.*->paddle.compat.*
level=3：level=1+2的用法，重定位 torch.* -> paddle.* + 重定位 paddle.*->paddle.compat.*

zhwesky2010 · 2026-08-06T10:56:25Z

@Manfredss CI看下有没有问题

Manfredss · 2026-08-06T11:22:22Z

@Manfredss CI看下有没有问题

感觉像是卡了，我多试试

Manfredss · 2026-08-06T11:22:43Z

/re-run all-failed

SigureMo · 2026-08-06T11:11:04Z

+        level |= 1
+    if _PADDLE_NAMESPACE_SAVED:
+        level |= 2
+    return level


这里是按位运算的逻辑吧？那是否可以用 enum.Flag 来维护下？数字直接 |= 会让人感到困惑

import enum class CompatLevel(enum.Flag): MODULE_PROXY = 1 API_ALIAS = 2 LEVEL_MODULE_PROXY = CompatLevel.MODULE_PROXY LEVEL_API_ALIAS = CompatLevel.API_ALIAS LEVEL_ALL = CompatLevel.MODULE_PROXY | CompatLevel.API_ALIAS VALID_COMPAT_LEVELS = {LEVEL_MODULE_PROXY, LEVEL_API_ALIAS, LEVEL_ALL} def is_module_proxy_enabled(level: CompatLevel) -> bool: return bool(level & CompatLevel.MODULE_PROXY) def is_api_alias_enabled(level: CompatLevel) -> bool: return bool(level & CompatLevel.API_ALIAS) def is_valid_compat_level(level: CompatLevel) -> bool: return level in VALID_COMPAT_LEVELS

接口层不需要感知这些（仍然是数字），仅仅实现层是这样

SigureMo · 2026-08-06T11:25:43Z

-        if native_method is None:
+    tensor_apis = {
+        attr_name: getattr(compat_root, attr_name)
+        for attr_name in getattr(compat_root, "__all__", ())


paddle.compat.__all__ 里的所有函数都是 tensor 上的 API 么？总感觉不太对？

虽然下面有过滤，但是这里的命名 -> method 的对应关系总感觉不应该按照这个假设？

呃确实不是全部 __all__ 里的 seed 就不是 Tensor API，它靠 inspect.getattr_static(paddle.Tensor, name, None) is None 过滤掉；其余 10 个在 Tensor 上同名同义、首参对应描述符传入的 tensor，能对上

我改一下更鲁棒一点

SigureMo · 2026-08-06T11:28:40Z

+        if compat_is_property:
+            if native_is_property:
+                # native property -> compat property
+                dispatcher = dispatch_property(native_attr, compat_attr)
+            else:
+                # native function -> compat property
+                dispatcher = dispatch_property(native_attr, compat_attr)
+        elif native_is_property:
+            # native property -> compat function
+            dispatcher = dispatch_property(native_attr, compat_attr)


这几个分支不都是 dispatcher = dispatch_property(native_attr, compat_attr) 吗？为啥要这么多 if？

SigureMo · 2026-08-06T11:43:20Z

+                attr = native_attr
+            else:
+                attr = compat_attr
+            return attr.__get__(instance, owner)


这里能保证 attr 是 function 么？不然应该不能 .__get__ 吧

不用一定是 function，只要是描述符就可以了吧

dispatch_property 只有在 _patch_tensor_methods 里才用到，native 这边来自 inspect.getattr_static(paddle.Tensor, name)，compat 这边来自 paddle.compat.__all__（func）或 _TENSOR_API_OVERRIDES（func 或 property）。

现在只有两个 API 会走到这里：type（native 是 getset_descriptor，compat 是 func）、is_sparse（native 是 method_descriptor，compat 是 property）。这几个类型都实现了 __get__，所以我认为应该是没有问题的

是 descriptor 还是 function 不重要，关键是能不能 bind object（__get__）

算了，反正大概率也没人会在这两处注册 int 之类的 normal object，大概率也没啥问题，有问题再说吧

另外，其实 dispatch_property 已经能取代 dispatch_function 了吧？当然两者本质上有一点区别是，前者在 bind object 时候或者说 getattr 时候就已经确定 dispatch 的结果，而后者则是在实际函数调用时候才确定，但在实际调用过程中我觉得应该感知不到这点细微差异；还有一点差异就是之前可以用 paddle.Tensor.fn(obj) 而 descriptor 就不能 paddle.Tensor.des(obj) 了哈哈，但我觉得这倒没什么不至于有人这么去用，不过不重要了

Manfredss · 2026-08-06T16:33:16Z

/re-run all-failed

Manfredss · 2026-08-07T01:53:44Z

/re-run all-failed

zhwesky2010 · 2026-08-07T03:37:09Z

+    device = None
+    if isinstance(dtype, type) and dtype.__name__ in _TENSOR_TYPE_DTYPES:
+        tensor_type = dtype.__name__
+        dtype = _TENSOR_TYPE_DTYPES[tensor_type]


np.float32触发这个分支吗？看起来有点问题

直接判断np.dtype、paddle.dtype吧，鲁棒些。

这个isinstance(dtype, type) 比较奇怪

zhwesky2010 · 2026-08-07T03:40:47Z

+            )
+        elif tensor_type in _TENSOR_TYPE_DTYPES.values():
+            dtype = tensor_type
+            if dtype_string.startswith(("torch.cuda.", "paddle.cuda.")):


这个是什么case？有 'torch.cuda.float32' 吗

确实没有我删一下

zhwesky2010 · 2026-08-07T03:42:38Z

+        else:
+            raise ValueError(f"invalid type: {dtype_string!r}")
+
+    dtype_name = str(input.dtype).removeprefix("paddle.")


直接判断：str(input.dtype) == dtype 就可以了吧

dtype本身就是字符串

dtype 走到这里不一定是字符串好像，像t.type(paddle.float32)、t.type(np.float32)、t.type(np.dtype('float32')) 这些都不进上面两个分支，会直接传下来，而且即使是字符串，前面也已经把 'torch.DoubleTensor'、'paddle.float64' 这些统一成了 'float64'，和带前缀的 str(input.dtype)（'paddle.float64'）比的话是不一致的我还是想保留现在的写法

zhwesky2010 · 2026-08-07T03:44:33Z

+    return input.is_sparse_coo()
+
+
+_TENSOR_API_OVERRIDES = {


我建议这个是不是和上面的字典合并起来，统一成一个字典：

_TENSOR_API_OVERRIDES = ( 'allclose': allclose, 'equal': equal 'numel': _tensor_numel, )

risemeup1111

当前 head 仍未修复前次指出的两处 P1：paddle.nn.PReLU 仍会把字符串位置参数当作 device 重解释，enable_compat() / use_compat_guard(enable=False) 的 finder 恢复也还没有改成幂等插入或完整恢复。因此我仍然请求修改。

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align 3 Tensor api and PReLU

91b9144

paddle-bot Bot added the contributor External developers label Jul 27, 2026

Manfredss marked this pull request as draft July 27, 2026 07:56

risemeup1111 suggested changes Jul 27, 2026

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Merge branch 'develop' of https://github.com/paddlepaddle/paddle into…

3451263

… three_Tensor_and_PReLU

fix PReLU, fix enable_compat restore after using guard

d5154f3

Manfredss requested a review from risemeup1111 July 27, 2026 13:07

Manfredss marked this pull request as ready for review July 28, 2026 02:11

add test coverage

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fix per bot feedback

8aa81ef

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fix typo

7f2684a

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also fix paddle.distributions.categorical.Categorical

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Comment thread python/paddle/compat/distributions/categorical.py

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fix

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Manfredss requested a review from zhwesky2010 August 6, 2026 09:42

Merge branch 'develop' of https://github.com/paddlepaddle/paddle into…

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… three_Tensor_and_PReLU

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improve code per review suggestions

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fix

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refine

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	if isinstance(dtype, type):
	if isinstance(dtype, type) and dtype.__name__ in _TENSOR_TYPE_DTYPES:

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PR Category

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是否引起精度变化

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paddle-bot Bot commented Jul 27, 2026

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Manfredss commented Jul 27, 2026

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Manfredss commented Jul 28, 2026

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Manfredss commented Jul 29, 2026

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Manfredss commented Aug 6, 2026

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