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【Hackathon 7th No.38】为Paddle代码转换工具新增API转换规则（第5组） #6885

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【Hackathon 7th No.38】为 Paddle 代码转换工具新增 API 转换规则（第5组）
inaomIIsfarell Sep 20, 2024
84fb9f7
Merge branch 'develop' of https://github.com/PaddlePaddle/docs into hkt1
inaomIIsfarell Sep 20, 2024
17e10a0
fix docs
inaomIIsfarell Sep 22, 2024
7697816
fix
inaomIIsfarell Sep 25, 2024
8c0edfb
Merge branch 'develop' of https://github.com/PaddlePaddle/docs into hkt1
inaomIIsfarell Sep 25, 2024
940ec07
fix
inaomIIsfarell Sep 25, 2024
1a76e87
update_param_exp
inaomIIsfarell Sep 25, 2024
571d1e8
fix
inaomIIsfarell Sep 25, 2024
23bb1bd
fix
inaomIIsfarell Sep 27, 2024
de8ac23
Merge branch 'develop' of https://github.com/PaddlePaddle/docs into hkt1
inaomIIsfarell Sep 27, 2024
eacf377
fix
inaomIIsfarell Sep 30, 2024
b66bfd3
Merge branch 'develop' of https://github.com/PaddlePaddle/docs into hkt1
inaomIIsfarell Sep 30, 2024
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4 changes: 2 additions & 2 deletions ..._convert/convert_from_pytorch/api_difference/Tensor/torch.Tensor.float_power.md
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Expand Up @@ -12,8 +12,8 @@ Paddle 无此 API，需要组合实现。

```python
# PyTorch 写法
y = x.float_power(2)
y = x.float_power(y)

# Paddle 写法
y = x.cast(paddle.float64).pow(2)
y = x.cast(paddle.float64).pow(y)
```
15 changes: 15 additions & 0 deletions ...del_convert/convert_from_pytorch/api_difference/Tensor/torch.Tensor.isneginf.md
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## [无参数]torch.Tensor.isneginf

### [torch.Tensor.isneginf ](https://pytorch.org/docs/stable/generated/torch.Tensor.isneginf.html#torch.Tensor.isneginf)

```python
torch.Tensor.isneginf()
```

### [paddle.Tensor.isneginf](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/api/paddle/Tensor_cn.html#isneginf-name-none)

```python
paddle.Tensor.isneginf(name=None)
```

两者功能一致，无参数。
15 changes: 15 additions & 0 deletions ...del_convert/convert_from_pytorch/api_difference/Tensor/torch.Tensor.isposinf.md
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## [无参数]torch.Tensor.isposinf

### [torch.Tensor.isposinf](https://pytorch.org/docs/stable/generated/torch.Tensor.isposinf.html#torch.Tensor.isposinf)

```python
torch.Tensor.isposinf()
```

### [paddle.Tensor.isposinf](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/api/paddle/Tensor_cn.html#isposinf-name-none)

```python
paddle.Tensor.isposinf(name=None)
```

两者功能一致，无参数。
15 changes: 15 additions & 0 deletions ...model_convert/convert_from_pytorch/api_difference/Tensor/torch.Tensor.isreal.md
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## [无参数]torch.Tensor.isreal

### [torch.Tensor.isreal](https://pytorch.org/docs/stable/generated/torch.Tensor.isreal.html#torch.Tensor.isreal)

```python
Tensor.isreal()
```

### [paddle.Tensor.isreal](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/api/paddle/Tensor_cn.html#isreal-name-none)

```python
paddle.Tensor.isreal(name=None)
```

两者功能一致，无参数。
27 changes: 27 additions & 0 deletions ...del_convert/convert_from_pytorch/api_difference/Tensor/torch.Tensor.positive.md
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## [组合替代实现]torch.Tensor.positive

[torch.Tensor.positive](https://pytorch.org/docs/stable/generated/torch.Tensor.positive.html#torch.Tensor.positive)

```python
torch.Tensor.positive()
```

判断 `input` 是否是 bool 类型的 Tensor，如果是则抛出 RuntimeError 异常，否则返回 `input` 。

Paddle 无此 API，需要组合实现。

### 转写示例

```python
# PyTorch 写法
x.positive()

# Paddle 写法
def positive(x):
if x.dtype != paddle.bool:
return x
else:
raise RuntimeError("boolean tensors is not supported.")

positive(x)
```
26 changes: 26 additions & 0 deletions ...nvert/convert_from_pytorch/api_difference/Tensor/torch.Tensor.scatter_reduce.md
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## [paddle 参数更多]torch.Tensor.scatter_reduce

### [torch.Tensor.scatter_reduce](https://pytorch.org/docs/stable/generated/torch.Tensor.scatter_reduce.html#torch-tensor-scatter-reduce)

```python
torch.Tensor.scatter_reduce(dim, index, src, reduce, *, include_self=True)
```

### [paddle.Tensor.put_along_axis](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/api/paddle/Tensor_cn.html#put-along-axis-indices-value-axis-reduce-assign-include-self-true-broadcast-true)

```python
paddle.Tensor.put_along_axis(indices, values, axis, reduce="assign", include_self=True, broadcast=True)
```

其中 Paddle 相比 PyTorch 支持更多其他参数，具体如下：

### 参数映射

| PyTorch | PaddlePaddle | 备注 |
| ------------ | ------------ | ------------------------------------------------------------ |
| dim | axis | 表示 scatter 的维度，仅参数名不一致。 |
| index | indices | 表示输入的索引张量，仅参数名不一致。 |
| src | values | 表示需要插入的值，仅参数名不一致。 |
| reduce | reduce | 表示插入 values 时的计算方式，参数默认值不一致。PyTorch 中该参数无默认值，需要输入，Paddle 中默认值为 `assign`，应设置为与 PyTorch 一致。其中 PyTorch 的 `sum` 对应 Paddle 中的 `add`，PyTorch 的 `prod` 对应 Paddle 中 `multiply`。 |
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此处 paddle 的 api 文档应该有误
params_in_docs
params_in_code

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此处 paddle 的 api 文档应该有误 params_in_docs params_in_code

以代码为准就行

| include_self | include_self | 表示插入 values 时是否包含输入元素中的值。 |
| - | broadcast | 表示是否需要广播索引张量矩阵，PyTorch 无此参数，Paddle 应设置为 `False` 才与 PyTorch 一致 |
33 changes: 33 additions & 0 deletions ...des/model_convert/convert_from_pytorch/api_difference/torch/torch.block_diag.md
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## [输入参数类型不一致]torch.block_diag

### [torch.block_diag](https://pytorch.org/docs/stable/generated/torch.block_diag.html#torch-block-diag)

```python
torch.block_diag(*tensors)
```

### [paddle.block_diag](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/api/paddle/block_diag_cn.html)

```python
paddle.block_diag(inputs, name=None)
```

二者功能一致但参数类型不一致，具体如下：

### 参数映射

| PyTorch | PaddlePaddle | 备注 |
| -------- | ------------ | ------------------------------------------------------------ |
| *tensors | inputs | 一组输入 Tensor，PyTorch 参数 tensors 为可变参数，Paddle 参数 inputs 为 list(Tensor) 或 tuple(Tensor) 的形式。 |

### 转写示例

#### *tensors：一组输入 Tensor

```python
# PyTorch 写法
torch.block_diag(x, y, z)

# Paddle 写法
paddle.block_diag([x, y, z])
```
194 changes: 194 additions & 0 deletions ...uides/model_convert/convert_from_pytorch/api_difference/torch/torch.can_cast.md
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## [组合替代实现]torch.can_cast

### [torch.can_cast](https://pytorch.org/docs/stable/generated/torch.can_cast.html#torch-can-cast)

```python
torch.can_cast(from_, to)
```

判断类型的转换在 PyTorch 的[casting 规则](https://pytorch.org/docs/stable/tensor_attributes.html#type-promotion-doc)中是否被允许。

Paddle 无此 API，需要组合实现。

### 转写示例

```python
# PyTorch 写法
torch.can_cast(x, y)

# Paddle 写法
def can_cast(from_, to):
can_cast_dict = {
paddle.bfloat16: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: False,
paddle.int8: False,
paddle.int16: False,
paddle.int32: False,
paddle.int64: False,
paddle.bool: False
},
paddle.float16: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: False,
paddle.int8: False,
paddle.int16: False,
paddle.int32: False,
paddle.int64: False,
paddle.bool: False,
},
paddle.float32: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: False,
paddle.int8: False,
paddle.int16: False,
paddle.int32: False,
paddle.int64: False,
paddle.bool: False,
},
paddle.float64: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: False,
paddle.int8: False,
paddle.int16: False,
paddle.int32: False,
paddle.int64: False,
paddle.bool: False,
},
paddle.complex64: {
paddle.bfloat16: False,
paddle.float16: False,
paddle.float32: False,
paddle.float64: False,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: False,
paddle.int8: False,
paddle.int16: False,
paddle.int32: False,
paddle.int64: False,
paddle.bool: False,
},
paddle.complex128: {
paddle.bfloat16: False,
paddle.float16: False,
paddle.float32: False,
paddle.float64: False,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: False,
paddle.int8: False,
paddle.int16: False,
paddle.int32: False,
paddle.int64: False,
paddle.bool: False,
},
paddle.uint8: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: True,
paddle.int8: True,
paddle.int16: True,
paddle.int32: True,
paddle.int64: True,
paddle.bool: False,
},
paddle.int8: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: True,
paddle.int8: True,
paddle.int16: True,
paddle.int32: True,
paddle.int64: True,
paddle.bool: False,
},
paddle.int16: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: True,
paddle.int8: True,
paddle.int16: True,
paddle.int32: True,
paddle.int64: True,
paddle.bool: False,
},
paddle.int32: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: True,
paddle.int8: True,
paddle.int16: True,
paddle.int32: True,
paddle.int64: True,
paddle.bool: False,
},
paddle.int64: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: True,
paddle.int8: True,
paddle.int16: True,
paddle.int32: True,
paddle.int64: True,
paddle.bool: False,
},
paddle.bool: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: True,
paddle.int8: True,
paddle.int16: True,
paddle.int32: True,
paddle.int64: True,
paddle.bool: True,
}
}
return can_cast_dict[from_][to]

can_cast(x, y)
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这个情况比较多，需要核对下，是不是与Torch结果一致的

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我写了一个测试代码，把示例中 can_cast_dict 的 paddle 全部替换成 torch，和 torch.can_cast 的结果一致

import torch

can_cast_dict = {
    torch.bfloat16: {
        torch.bfloat16: True,
        torch.float16: True,
        torch.float32: True,
        torch.float64: True,
        torch.complex64: True,
        torch.complex128: True,
        torch.uint8: False,
        torch.int8: False,
        torch.int16: False,
        torch.int32: False,
        torch.int64: False,
        torch.bool: False
    },
    torch.float16: {
        torch.bfloat16: True,
        torch.float16: True,
        torch.float32: True,
        torch.float64: True,
        torch.complex64: True,
        torch.complex128: True,
        torch.uint8: False,
        torch.int8: False,
        torch.int16: False,
        torch.int32: False,
        torch.int64: False,
        torch.bool: False,
    },
    torch.float32: {
        torch.bfloat16: True,
        torch.float16: True,
        torch.float32: True,
        torch.float64: True,
        torch.complex64: True,
        torch.complex128: True,
        torch.uint8: False,
        torch.int8: False,
        torch.int16: False,
        torch.int32: False,
        torch.int64: False,
        torch.bool: False,
    },
    torch.float64: {
        torch.bfloat16: True,
        torch.float16: True,
        torch.float32: True,
        torch.float64: True,
        torch.complex64: True,
        torch.complex128: True,
        torch.uint8: False,
        torch.int8: False,
        torch.int16: False,
        torch.int32: False,
        torch.int64: False,
        torch.bool: False,
    },
    torch.complex64: {
        torch.bfloat16: False,
        torch.float16: False,
        torch.float32: False,
        torch.float64: False,
        torch.complex64: True,
        torch.complex128: True,
        torch.uint8: False,
        torch.int8: False,
        torch.int16: False,
        torch.int32: False,
        torch.int64: False,
        torch.bool: False,
    },
    torch.complex128: {
        torch.bfloat16: False,
        torch.float16: False,
        torch.float32: False,
        torch.float64: False,
        torch.complex64: True,
        torch.complex128: True,
        torch.uint8: False,
        torch.int8: False,
        torch.int16: False,
        torch.int32: False,
        torch.int64: False,
        torch.bool: False,
    },
    torch.uint8: {
        torch.bfloat16: True,
        torch.float16: True,
        torch.float32: True,
        torch.float64: True,
        torch.complex64: True,
        torch.complex128: True,
        torch.uint8: True,
        torch.int8: True,
        torch.int16: True,
        torch.int32: True,
        torch.int64: True,
        torch.bool: False,
    },
    torch.int8: {
        torch.bfloat16: True,
        torch.float16: True,
        torch.float32: True,
        torch.float64: True,
        torch.complex64: True,
        torch.complex128: True,
        torch.uint8: True,
        torch.int8: True,
        torch.int16: True,
        torch.int32: True,
        torch.int64: True,
        torch.bool: False,
    },
    torch.int16: {
        torch.bfloat16: True,
        torch.float16: True,
        torch.float32: True,
        torch.float64: True,
        torch.complex64: True,
        torch.complex128: True,
        torch.uint8: True,
        torch.int8: True,
        torch.int16: True,
        torch.int32: True,
        torch.int64: True,
        torch.bool: False,
    },
    torch.int32: {
        torch.bfloat16: True,
        torch.float16: True,
        torch.float32: True,
        torch.float64: True,
        torch.complex64: True,
        torch.complex128: True,
        torch.uint8: True,
        torch.int8: True,
        torch.int16: True,
        torch.int32: True,
        torch.int64: True,
        torch.bool: False,
    },
    torch.int64: {
        torch.bfloat16: True,
        torch.float16: True,
        torch.float32: True,
        torch.float64: True,
        torch.complex64: True,
        torch.complex128: True,
        torch.uint8: True,
        torch.int8: True,
        torch.int16: True,
        torch.int32: True,
        torch.int64: True,
        torch.bool: False,
    },
    torch.bool: {
        torch.bfloat16: True,
        torch.float16: True,
        torch.float32: True,
        torch.float64: True,
        torch.complex64: True,
        torch.complex128: True,
        torch.uint8: True,
        torch.int8: True,
        torch.int16: True,
        torch.int32: True,
        torch.int64: True,
        torch.bool: True,
    }
}
for _from_dtype in can_cast_dict.keys():
    for _to_dtype in can_cast_dict[_from_dtype].keys():
        assert torch.can_cast(_from_dtype, _to_dtype) == can_cast_dict[_from_dtype][_to_dtype], "can_cast error"
        print(f"_from_dtype={_from_dtype}, _to_dtype={_to_dtype}")

print("can_cast test pass")

```
33 changes: 33 additions & 0 deletions ...model_convert/convert_from_pytorch/api_difference/torch/torch.cartesian_prod.md
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## [输入参数类型不一致]torch.cartesian_prod

### [torch.cartesian_prod](https://pytorch.org/docs/stable/generated/torch.cartesian_prod.html#torch-cartesian-prod)

```python
torch.cartesian_prod(*tensors)
```

### [paddle.cartesian_prod](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/api/paddle/cartesian_prod_cn.html)

```python
paddle.cartesian_prod(x, name=None)
```

两者功能一致但参数类型不一致，具体如下：

### 参数映射

| PyTorch | PaddlePaddle | 备注 |
| -------- | ------------ | ------------------------------------------------------------ |
| *tensors | x | 一组输入 Tensor ， PyTorch 参数 tensors 为可变参, Paddle 参数 x 为 list(Tensor) 或 tuple(Tensor) 的形式。 |

### 转写示例

#### *tensors：一组输入 Tensor

```python
# PyTorch 写法
torch.cartesian_prod(a, b)

# Paddle 写法
paddle.cartesian_prod([a, b])
```
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