code stringlengths 3 6.57k |
|---|
_("No Version Found") |
api.depends("dependence_module_version_ids.dependency_module_ids") |
_compute_dependence_module_version_qty(self) |
api.depends("module_version_ids") |
_compute_module_version_qty(self) |
len(module.module_version_ids) |
api.depends("module_version_ids.author_ids") |
_compute_author(self) |
set(authors) |
join(sorted([x.name for x in authors]) |
api.depends("module_version_ids.organization_serie_id") |
_compute_organization_serie(self) |
set(organization_series) |
sorted(organization_series, key=lambda x: x.sequence) |
create_if_not_exist(self, technical_name) |
self.search([("technical_name", "=", technical_name) |
self.create({"technical_name": technical_name}) |
name_get(self) |
interpolate1d(x, values, tangents) |
torch.is_tensor(x) |
torch.is_tensor(values) |
torch.is_tensor(tangents) |
len(values.shape) |
len(tangents.shape) |
torch.floor(torch.clamp(x, torch.as_tensor(0) |
type(torch.int64) |
x_lo.type(float_dtype) |
torch.where(t > 1., value_after, value_mid) |
log_safe(x) |
torch.as_tensor(x) |
torch.log(torch.min(x, torch.tensor(33e37) |
to(x) |
load_spline_params() |
os.path.dirname(__file__) |
open(os.path.join(dirname, '../misc/partition_spline.npz') |
np.load(spline_file, allow_pickle=False) |
torch.tensor(f['x_scale']) |
torch.tensor(f['values']) |
torch.tensor(f['tangents']) |
get_partition_init(shape) |
torch.as_tensor(shape) |
torch.abs(shape - 2) |
log_safe(4 * shape - 15) |
torch.where(shape < 4, base1, base2) |
get_partition(shape) |
torch.as_tensor(shape) |
assert (shape >= 0) |
all() |
get_partition_init(shape) |
load_spline_params() |
interpolate1d(init * x_scale.to(init) |
values.to(init) |
tangents.to(init) |
general_adaptive_loss(x, shape, bowl=1.) |
torch.as_tensor(shape) |
to(x.device) |
torch.as_tensor(bowl) |
to(x.device) |
x.size(0) |
x.view(b, -1) |
len(shape.shape) |
shape.unsqueeze(dim=0) |
expand([b, ]) |
unsqueeze(dim=1) |
shape.view(b, -1) |
len(bowl.shape) |
bowl.unsqueeze(dim=0) |
expand([b, ]) |
unsqueeze(dim=1) |
bowl.view(b, -1) |
get_partition(shape) |
torch.abs(shape - 2) |
torch.pow((torch.square(x/bowl) |
torch.abs(shape - 2) |
log_safe(bowl) |
log_safe(partition) |
ans.view(input_shape) |
Foundation (ASF) |
_get_conv2d_workload(data, kernel, strides, padding, out_dtype, layout) |
_is_int8_hw_support(data_dtype, kernel_dtype) |
tvm.codegen.llvm_lookup_intrinsic_id(llvm_intrin_fast_int8) |
tvm.target.current_target() |
_create_tuning_space_int8(cfg, data, kernel, strides, padding, dilation, layout) |
get_const_tuple(data.shape) |
get_const_tuple(kernel.shape) |
re.compile(r'NCHW.+(\d+) |
pat.match(layout) |
tvm.target.current_target(allow_none=False) |
format(layout) |
isinstance(padding, (tuple, list) |
else (padding, padding) |
isinstance(strides, (tuple, list) |
else (strides, strides) |
cfg.define_split('tile_ic', ic, num_outputs=2, filter=lambda y: y.size[-1] % 4 == 0) |
cfg.define_split('tile_oc', oc, num_outputs=2, filter=lambda y: y.size[-1] % 16 == 0) |
cfg.define_split("tile_ow", ow, num_outputs=2, filter=lambda y: y.size[-1] <= 64) |
cfg.define_knob("tile_oh", [1, 2] if oh > 1 else [1]) |
cfg.define_knob("unroll_kw", [True, False]) |
autotvm.task.register("topi_x86_conv2d_NCHWc_int8") |
_topi_nn_conv2d_NCHWc_int8(*args, **kwargs) |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.