experimental_experiment.torch_interpreter._aten_methods¶
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_bool(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str) str[source]¶
cast
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_clone(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str) str[source]¶
identity
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_contiguous(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str) str[source]¶
identity
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_cos(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str) str[source]¶
cos
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_cpu(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str) str[source]¶
identity
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_eq(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, y: str) str[source]¶
equal
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_expand(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, *dims: List[int]) str[source]¶
expand
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_float(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str) str[source]¶
cast
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_masked_fill(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, mask: str, value: Any) str[source]¶
constantofshape
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_masked_fill_(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, mask: str, value: Any) str[source]¶
masked
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_mean(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, dim: str, keepdim: bool = False) str[source]¶
reducemean
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_pow(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, exponent: str) str[source]¶
pow
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_repeat(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, *repeats: List[int]) str[source]¶
repeat
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_reshape(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], input_name: str, *shape: List[int], name: str = 'reshape') str[source]¶
reshape
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_sin(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str) str[source]¶
sin
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_size(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, dim: int | None = None, name: str = '.size') str[source]¶
size
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_t(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str) str[source]¶
transpose
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_to(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], input_name: str, *args: List[Any], **kwargs: Dict[str, Any]) str[source]¶
cast
- experimental_experiment.torch_interpreter._aten_methods.aten_meth_transpose(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], input_name: str, dim0: int, dim1: int) str[source]¶
transpose