nndeploy.inference.inference¶

Functions

`create_inference`(type)
`register_inference_creator`(type, creator)

Classes

`Inference`(type)
`InferenceCreator`()

class nndeploy.inference.inference.Inference(type)[源代码]¶

基类：Inference

__init__(self: nndeploy._nndeploy_internal.inference.Inference, arg0: nndeploy._nndeploy_internal.base.InferenceType) → None[源代码]¶

get_inference_type(self: nndeploy._nndeploy_internal.inference.Inference) → nndeploy._nndeploy_internal.base.InferenceType[源代码]¶

set_param(self: nndeploy._nndeploy_internal.inference.Inference, param: nndeploy._nndeploy_internal.base.Param) → nndeploy._nndeploy_internal.base.Status[源代码]¶

get_param(self: nndeploy._nndeploy_internal.inference.Inference) → nndeploy._nndeploy_internal.base.Param[源代码]¶

get_device_type(self: nndeploy._nndeploy_internal.inference.Inference) → nndeploy._nndeploy_internal.base.DeviceType[源代码]¶

set_stream(self: nndeploy._nndeploy_internal.inference.Inference, stream: nndeploy._nndeploy_internal.device.Stream) → None[源代码]¶

get_stream(self: nndeploy._nndeploy_internal.inference.Inference) → nndeploy._nndeploy_internal.device.Stream[源代码]¶

init(self: nndeploy._nndeploy_internal.inference.Inference) → nndeploy._nndeploy_internal.base.Status[源代码]¶

deinit(self: nndeploy._nndeploy_internal.inference.Inference) → nndeploy._nndeploy_internal.base.Status[源代码]¶

get_min_shape(self: nndeploy._nndeploy_internal.inference.Inference) → dict[str, list[int]][源代码]¶

get_opt_shape(self: nndeploy._nndeploy_internal.inference.Inference) → dict[str, list[int]][源代码]¶

get_max_shape(self: nndeploy._nndeploy_internal.inference.Inference) → dict[str, list[int]][源代码]¶

reshape(self: nndeploy._nndeploy_internal.inference.Inference, shape_map: dict[str, list[int]]) → nndeploy._nndeploy_internal.base.Status[源代码]¶

get_memory_size(self: nndeploy._nndeploy_internal.inference.Inference) → int[源代码]¶

set_memory(self: nndeploy._nndeploy_internal.inference.Inference, buffer: nndeploy._nndeploy_internal.device.Buffer) → nndeploy._nndeploy_internal.base.Status[源代码]¶

get_gflops(self: nndeploy._nndeploy_internal.inference.Inference) → float[源代码]¶

is_batch(self: nndeploy._nndeploy_internal.inference.Inference) → bool[源代码]¶

is_share_context(self: nndeploy._nndeploy_internal.inference.Inference) → bool[源代码]¶

is_share_stream(self: nndeploy._nndeploy_internal.inference.Inference) → bool[源代码]¶

is_input_dynamic(self: nndeploy._nndeploy_internal.inference.Inference) → bool[源代码]¶

is_output_dynamic(self: nndeploy._nndeploy_internal.inference.Inference) → bool[源代码]¶

can_op_input(self: nndeploy._nndeploy_internal.inference.Inference) → bool[源代码]¶

can_op_output(self: nndeploy._nndeploy_internal.inference.Inference) → bool[源代码]¶

get_num_of_input_tensor(self: nndeploy._nndeploy_internal.inference.Inference) → int[源代码]¶

get_num_of_output_tensor(self: nndeploy._nndeploy_internal.inference.Inference) → int[源代码]¶

get_input_name(self: nndeploy._nndeploy_internal.inference.Inference, i: int = 0) → str[源代码]¶

get_output_name(self: nndeploy._nndeploy_internal.inference.Inference, i: int = 0) → str[源代码]¶

get_all_input_tensor_name(self: nndeploy._nndeploy_internal.inference.Inference) → list[str][源代码]¶

get_all_output_tensor_name(self: nndeploy._nndeploy_internal.inference.Inference) → list[str][源代码]¶

get_input_shape(self: nndeploy._nndeploy_internal.inference.Inference, name: str) → list[int][源代码]¶

get_all_input_shape(self: nndeploy._nndeploy_internal.inference.Inference) → dict[str, list[int]][源代码]¶

get_input_tensor_desc(self: nndeploy._nndeploy_internal.inference.Inference, name: str) → nndeploy._nndeploy_internal.device.TensorDesc[源代码]¶

get_output_tensor_desc(self: nndeploy._nndeploy_internal.inference.Inference, name: str) → nndeploy._nndeploy_internal.device.TensorDesc[源代码]¶

get_input_tensor_align_desc(self: nndeploy._nndeploy_internal.inference.Inference, name: str) → nndeploy._nndeploy_internal.device.TensorDesc[源代码]¶

get_output_tensor_align_desc(self: nndeploy._nndeploy_internal.inference.Inference, name: str) → nndeploy._nndeploy_internal.device.TensorDesc[源代码]¶

get_all_input_tensor_map(self: nndeploy._nndeploy_internal.inference.Inference) → dict[str, nndeploy._nndeploy_internal.device.Tensor][源代码]¶

get_all_output_tensor_map(self: nndeploy._nndeploy_internal.inference.Inference) → dict[str, nndeploy._nndeploy_internal.device.Tensor][源代码]¶

get_all_input_tensor_vector(self: nndeploy._nndeploy_internal.inference.Inference) → list[nndeploy._nndeploy_internal.device.Tensor][源代码]¶

get_all_output_tensor_vector(self: nndeploy._nndeploy_internal.inference.Inference) → list[nndeploy._nndeploy_internal.device.Tensor][源代码]¶

get_input_tensor(self: nndeploy._nndeploy_internal.inference.Inference, name: str) → nndeploy._nndeploy_internal.device.Tensor[源代码]¶

get_output_tensor(self: nndeploy._nndeploy_internal.inference.Inference, name: str) → nndeploy._nndeploy_internal.device.Tensor[源代码]¶

set_input_tensor(self: nndeploy._nndeploy_internal.inference.Inference, name: str, input_tensor: nndeploy._nndeploy_internal.device.Tensor) → nndeploy._nndeploy_internal.base.Status[源代码]¶

run(self: nndeploy._nndeploy_internal.inference.Inference) → nndeploy._nndeploy_internal.base.Status[源代码]¶

get_output_tensor_after_run(self: nndeploy._nndeploy_internal.inference.Inference, name: str, device_type: nndeploy._nndeploy_internal.base.DeviceType, is_copy: bool, data_format: nndeploy._nndeploy_internal.base.DataFormat = <DataFormat.Auto: 12>) → nndeploy._nndeploy_internal.device.Tensor[源代码]¶

class nndeploy.inference.inference.InferenceCreator[源代码]¶

基类：InferenceCreator

__init__(self: nndeploy._nndeploy_internal.inference.InferenceCreator) → None[源代码]¶

create_inference(self: nndeploy._nndeploy_internal.inference.InferenceCreator, arg0: nndeploy._nndeploy_internal.base.InferenceType) → nndeploy._nndeploy_internal.inference.Inference[源代码]¶

nndeploy.inference.inference.register_inference_creator(type, creator)[源代码]¶

nndeploy.inference.inference.create_inference(type)[源代码]¶