241 lines
3.8 KiB
Markdown
241 lines
3.8 KiB
Markdown
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# Tensor 张量
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Tensor 是模型推理的输入输出类型，包含了数据信息，实现内容管理
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## \_\_init\_\_
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初始化 Tensor，并为 Tensor 分配内存
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**接口形式1**
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```python
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def __init__(self, handle: Handle, data: np.arrat, own_sys_data=True)
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```
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**参数说明1**
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- handle: sail.Handle
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设备标识 Handle
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- array_data: numpy.array
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利用 numpy.array 类型初始化 Tensor，其数据类型可以是 np.float32，np.int8，np.uint8
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- own_sys_data:bool
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指示该 Tensor 是否拥有 system memory，如果为 False，则直接将数据复制到 device memory
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**接口形式2**
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```python
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def __init__(self, handle: Handle, shape: tuple, dtype: Dtype, own_sys_data: bool, own_dev_data: bool)
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```
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**参数说明2**
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- handle: sail.Handle
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设备标识 Handle
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- shape: tuple
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设置 Tensor 的 shape
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- dtype: sail.Dtype
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Tensor 的数据类型
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- own_sys_data: bool
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指示 Tensor 是否拥有 system memory
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- own_dev_data: bool
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指示 Tensor 是否拥有 device memory
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## shape
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获取 Tensor 的 shape
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**接口形式:**
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```python
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def shape(self) -> list :
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```
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**返回值说明:**
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- tensor_shape : list
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返回Tensor的shape的列表。
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## asnumpy
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获取Tensor中系统内存的数据，返回numpy.array类型。
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**接口形式:**
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```python
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def asnumpy(self) -> numpy.array
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def asnumpy(self, shape: tuple) -> numpy.array
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```
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**参数说明:**
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- shape: tuple
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可对Tensor中的数据reshape，返回形状为shape的numpy.array
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**返回值说明**
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返回Tensor中系统内存的数据，返回类型为numpy.array。
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## update_data
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更新Tensor中系统内存的数据
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**接口形式:**
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```python
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def update_data(self, data: numpy.array) -> None
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```
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**参数说明:**
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- data: numpy.array
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更新的数据，数据size不能超过Tensor的size，Tensor的shape将保持不变。
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## scale_from
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先对data按比例缩放，再将数据更新到Tensor的系统内存。
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**接口形式:**
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```python
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def scale_from(self, data: numpy.array, scale: float32)->None
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```
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**参数说明:**
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- data: numpy.array
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对data进行scale，再将数据更新到Tensor的系统内存。
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- scale: float32
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等比例缩放时的尺度。
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## scale_to
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先对Tensor进行等比例缩放，再将数据返回到系统内存。
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**接口形式:**
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```python
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def scale_to(self, scale: float32)->numpy.array
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def scale_to(self, scale: float32, shape: tuple)->numpy.array
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```
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**参数说明:**
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- scale: float32
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等比例缩放时的尺度。
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- shape: tuple
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数据返回前可进行reshape，返回shape形状的数据。
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**返回值说明:**
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- data: numpy.array
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将处理后的数据返回至系统内存，返回numpy.array
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## reshape
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对Tensor进行reshape
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**接口形式:**
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```python
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def reshape(self, shape: list)->None
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```
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**参数说明:**
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- shape: list
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设置期望得到的新shape。
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# own_sys_data
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查询该Tensor是否拥有系统内存的数据指针。
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**接口形式:**
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```python
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def own_sys_data(self)->bool
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```
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**返回值说明:**
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- judge_ret: bool
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如果拥有系统内存的数据指针则返回True，否则False。
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## own_dev_data
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查询该Tensor是否拥有设备内存的数据
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**接口形式:**
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```python
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def own_dev_data(self)->bool
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```
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**返回值说明:**
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- judge_ret : bool
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如果拥有设备内存中的数据则返回True，否则False。
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## sync_s2d
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将Tensor中的数据从系统内存拷贝到设备内存。
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**接口形式:**
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```python
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def sync_s2d(self)->None
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def sync_s2d(self, size)->None
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```
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**参数说明:**
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- size: int
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将特定size字节的数据从系统内存拷贝到设备内存。
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## sync_d2s
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将Tensor中的数据从设备内存拷贝到系统内存。
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**接口形式:**
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```python
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def sync_d2s(self)->None
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def sync_d2s(self, size: int)->None
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```
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**参数说明:**
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- size: int
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将特定size字节的数据从设备内存拷贝到系统内存。
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