aten_prims

experimental_experiment.torch_interpreter._prims_functions.prims_add(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, y: str, name='prims_add') → str

add

experimental_experiment.torch_interpreter._prims_functions.prims_amax(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, dim: int | None = None, keepdim: bool = False, output_dtype: torch.dtype | None = None, name: str = 'prims_amax') → str

reducemax

experimental_experiment.torch_interpreter._prims_functions.prims_broadcast_in_dim(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], a: str, shape: List[int], broadcast_dimensions: List[int]) → str

broadcast

s = list(shape)
for broadcast_dimension in broadcast_dimensions:
    s[broadcast_dimension] = -1

v = a
for idx, x in enumerate(s):
    if x != -1:
        v = unsqueeze(v, idx)

return expand(v, shape)

experimental_experiment.torch_interpreter._prims_functions.prims_cat(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], tensors: Tuple[str, ...], dim: int = 0, name: str = 'prims_cat') → str

concat

experimental_experiment.torch_interpreter._prims_functions.prims_clone(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, memory_format: str | None = None) → str

identity

experimental_experiment.torch_interpreter._prims_functions.prims_collapse_view(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, start: int, end: int, name: str = 'prims_collapse_view') → str

reshape

experimental_experiment.torch_interpreter._prims_functions.prims_convert_element_type(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, dtype: torch.dtype, name: str = 'prims_convert_element_type') → str

cast

experimental_experiment.torch_interpreter._prims_functions.prims_cos(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, name: str = 'prims_cos') → str

cos

experimental_experiment.torch_interpreter._prims_functions.prims_div(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, y: str, name: str = 'prims_div') → str

div

experimental_experiment.torch_interpreter._prims_functions.prims_empty_strided(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], size: str, stride: str, dtype: torch.dtype | None = None, layout=None, device: torch.device | None = None, requires_grad: bool = False, name: str = 'prims_empty_strided') → str

constantofshape

experimental_experiment.torch_interpreter._prims_functions.prims_eq(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, y: str, name: str = 'prims_eq') → str

equal

experimental_experiment.torch_interpreter._prims_functions.prims_exp(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, name: str = 'prims_exp') → str

exp

experimental_experiment.torch_interpreter._prims_functions.prims_ge(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, y: str, name: str = 'prims_ge') → str

less

experimental_experiment.torch_interpreter._prims_functions.prims_gt(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, y: str, name: str = 'prims_gt') → str

greater

experimental_experiment.torch_interpreter._prims_functions.prims_iota(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], length: int, start: int = 0, step: int = 1, dtype: torch.dtype | None = None, device: torch.device | None = None, requires_grad: bool = False) → str

arange

experimental_experiment.torch_interpreter._prims_functions.prims_lt(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, y: str, name: str = 'prims_lt') → str

less

experimental_experiment.torch_interpreter._prims_functions.prims_mul(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, y: str, name: str = 'prims_mul') → str

mul

experimental_experiment.torch_interpreter._prims_functions.prims_neg(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, name='prims_neg') → str

neg

experimental_experiment.torch_interpreter._prims_functions.prims_pow(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, exponent: str, name: str = 'prims_pow') → str

pow

experimental_experiment.torch_interpreter._prims_functions.prims_rsqrt(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, name: str = 'prims_rsqrt') → str

rqsrt

experimental_experiment.torch_interpreter._prims_functions.prims_sin(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, name: str = 'prims_sin') → str

sim

experimental_experiment.torch_interpreter._prims_functions.prims_split_dim(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, dim: int, outer_length: int, name: str = 'prims_split_dim')

split

experimental_experiment.torch_interpreter._prims_functions.prims_sub(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, y: str, name: str = 'prims_sub') → str

sub

experimental_experiment.torch_interpreter._prims_functions.prims_sum(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str, dim: int | List[int] | None = None, keepdim: bool = False, output_dtype: torch.dtype | None = None) → str

reducesum

experimental_experiment.torch_interpreter._prims_functions.prims_transpose(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], input_name: str, perm: List[int], name: str = 'prims_transpose') → str

transpose

experimental_experiment.torch_interpreter._prims_functions.prims_view_of(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], x: str) → str

identity

experimental_experiment.torch_interpreter._prims_functions.prims_where(g: GraphBuilder, sts: Dict[str, Any] | None, outputs: List[str], condition: str, x: str, other: str) → str

where