FunctionBuilder

class madspace.FunctionBuilder(self: madspace._madspace_py.FunctionBuilder, input_types: madspace._madspace_py.NamedTypes, output_types: madspace._madspace_py.NamedTypes)

Bases: pybind11_object

Records instructions and freezes them into a Function.

Construct it with the input and output types, read the graph inputs with input, add nodes by calling the instruction methods (for example add, stack or two_body_decay_com, listed below), wire the results to the outputs with output, then call function to obtain the finished Function. The instruction methods are generated from madspace/instruction_set.yaml.

Start an empty builder with the given input and output types.

abs(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value) → madspace._madspace_py.Value

accept_norm(self: madspace._madspace_py.FunctionBuilder, accepted_batch: madspace._madspace_py.Value, full_batch: madspace._madspace_py.Value) → madspace._madspace_py.Value

add(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value, in2: madspace._madspace_py.Value) → madspace._madspace_py.Value

add_int(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value, in2: madspace._madspace_py.Value) → madspace._madspace_py.Value

apply_subchannel_weights(self: madspace._madspace_py.FunctionBuilder, channel_weights_in: madspace._madspace_py.Value, subchannel_weights: madspace._madspace_py.Value, channel_indices: madspace._madspace_py.Value, subchannel_indices: madspace._madspace_py.Value) → madspace._madspace_py.Value

argsort(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value) → madspace._madspace_py.Value

batch_cat(self: madspace._madspace_py.FunctionBuilder, args: collections.abc.Sequence[madspace._madspace_py.Value]) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

batch_gather(self: madspace._madspace_py.FunctionBuilder, indices: madspace._madspace_py.Value, values: madspace._madspace_py.Value) → madspace._madspace_py.Value

batch_merge_by_index(self: madspace._madspace_py.FunctionBuilder, args: collections.abc.Sequence[madspace._madspace_py.Value]) → madspace._madspace_py.Value

batch_reduce_mean(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → madspace._madspace_py.Value

batch_reduce_mean_keepdim(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → madspace._madspace_py.Value

batch_reduce_sum(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → madspace._madspace_py.Value

batch_scatter(self: madspace._madspace_py.FunctionBuilder, indices: madspace._madspace_py.Value, target: madspace._madspace_py.Value, source: madspace._madspace_py.Value) → madspace._madspace_py.Value

batch_size(self: madspace._madspace_py.FunctionBuilder, args: collections.abc.Sequence[madspace._madspace_py.Value]) → madspace._madspace_py.Value

batch_split(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value, counts: madspace._madspace_py.Value) → list[madspace._madspace_py.Value]

batch_split_by_index(self: madspace._madspace_py.FunctionBuilder, indices: madspace._madspace_py.Value, count: madspace._madspace_py.Value) → list[madspace._madspace_py.Value]

boost_beam(self: madspace._madspace_py.FunctionBuilder, p1: madspace._madspace_py.Value, masses: madspace._madspace_py.Value, x1: madspace._madspace_py.Value, x2: madspace._madspace_py.Value) → madspace._madspace_py.Value

boost_beam_inverse(self: madspace._madspace_py.FunctionBuilder, p1: madspace._madspace_py.Value, masses: madspace._madspace_py.Value, x1: madspace._madspace_py.Value, x2: madspace._madspace_py.Value) → madspace._madspace_py.Value

boost_to_frame(self: madspace._madspace_py.FunctionBuilder, p_ext: madspace._madspace_py.Value, frame_mask: madspace._madspace_py.Value) → madspace._madspace_py.Value

breit_wigner_invariant(self: madspace._madspace_py.FunctionBuilder, r: madspace._madspace_py.Value, mass: madspace._madspace_py.Value, width: madspace._madspace_py.Value, s_min: madspace._madspace_py.Value, s_max: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

breit_wigner_invariant_inverse(self: madspace._madspace_py.FunctionBuilder, s: madspace._madspace_py.Value, mass: madspace._madspace_py.Value, width: madspace._madspace_py.Value, s_min: madspace._madspace_py.Value, s_max: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

cat(self: madspace._madspace_py.FunctionBuilder, args: collections.abc.Sequence[madspace._madspace_py.Value]) → madspace._madspace_py.Value

chili_forward(self: madspace._madspace_py.FunctionBuilder, r: madspace._madspace_py.Value, e_cm: madspace._madspace_py.Value, m_out: madspace._madspace_py.Value, pt_min: madspace._madspace_py.Value, y_max: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

chili_inverse(self: madspace._madspace_py.FunctionBuilder, p_ext: madspace._madspace_py.Value, e_cm: madspace._madspace_py.Value, m_out: madspace._madspace_py.Value, pt_min: madspace._madspace_py.Value, y_max: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

collect_channel_weights(self: madspace._madspace_py.FunctionBuilder, amp2: madspace._madspace_py.Value, channel_indices: madspace._madspace_py.Value, channel_count: madspace._madspace_py.Value) → madspace._madspace_py.Value

com_cos_theta_window(self: madspace._madspace_py.FunctionBuilder, r_cos_theta: madspace._madspace_py.Value, m0: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, m2: madspace._madspace_py.Value, x1: madspace._madspace_py.Value, x2: madspace._madspace_py.Value, pt_min: madspace._madspace_py.Value, y_max1: madspace._madspace_py.Value, y_max2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

com_cos_theta_window_inverse(self: madspace._madspace_py.FunctionBuilder, r_out: madspace._madspace_py.Value, m0: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, m2: madspace._madspace_py.Value, x1: madspace._madspace_py.Value, x2: madspace._madspace_py.Value, pt_min: madspace._madspace_py.Value, y_max1: madspace._madspace_py.Value, y_max2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

com_p_in(self: madspace._madspace_py.FunctionBuilder, e_cm: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

compress_channel_weights(self: madspace._madspace_py.FunctionBuilder, channel_index: madspace._madspace_py.Value, channel_weights: madspace._madspace_py.Value, keep_count: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

current_stream(self: madspace._madspace_py.FunctionBuilder) → int

Index of the execution stream new instructions are added to.

cut_all(self: madspace._madspace_py.FunctionBuilder, obs: madspace._madspace_py.Value, min: madspace._madspace_py.Value, max: madspace._madspace_py.Value) → madspace._madspace_py.Value

cut_any(self: madspace._madspace_py.FunctionBuilder, obs: madspace._madspace_py.Value, min: madspace._madspace_py.Value, max: madspace._madspace_py.Value) → madspace._madspace_py.Value

cut_one(self: madspace._madspace_py.FunctionBuilder, obs: madspace._madspace_py.Value, min: madspace._madspace_py.Value, max: madspace._madspace_py.Value) → madspace._madspace_py.Value

cut_unphysical(self: madspace._madspace_py.FunctionBuilder, w_in: madspace._madspace_py.Value, p: madspace._madspace_py.Value, x1: madspace._madspace_py.Value, x2: madspace._madspace_py.Value) → madspace._madspace_py.Value

diff_cross_section(self: madspace._madspace_py.FunctionBuilder, x1: madspace._madspace_py.Value, x2: madspace._madspace_py.Value, pdf1: madspace._madspace_py.Value, pdf2: madspace._madspace_py.Value, matrix_element: madspace._madspace_py.Value, e_cm2: madspace._madspace_py.Value) → madspace._madspace_py.Value

discrete_histogram(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value, weights: madspace._madspace_py.Value, option_count: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

div(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value, in2: madspace._madspace_py.Value) → madspace._madspace_py.Value

double_t_scattering(self: madspace._madspace_py.FunctionBuilder, r_phi: madspace._madspace_py.Value, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value, t1_abs: madspace._madspace_py.Value, t2_abs: madspace._madspace_py.Value, m1: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

double_t_scattering_inverse(self: madspace._madspace_py.FunctionBuilder, p1: madspace._madspace_py.Value, p2: madspace._madspace_py.Value, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

elu(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → madspace._madspace_py.Value

fast_rambo_massive(self: madspace._madspace_py.FunctionBuilder, r: madspace._madspace_py.Value, e_cm: madspace._madspace_py.Value, masses: madspace._madspace_py.Value, p0: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

fast_rambo_massive_com(self: madspace._madspace_py.FunctionBuilder, r: madspace._madspace_py.Value, e_cm: madspace._madspace_py.Value, masses: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

fast_rambo_massive_inverse(self: madspace._madspace_py.FunctionBuilder, p_out: madspace._madspace_py.Value, e_cm: madspace._madspace_py.Value, masses: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

fast_rambo_massless(self: madspace._madspace_py.FunctionBuilder, r: madspace._madspace_py.Value, e_cm: madspace._madspace_py.Value, p0: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

fast_rambo_massless_com(self: madspace._madspace_py.FunctionBuilder, r: madspace._madspace_py.Value, e_cm: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

fast_rambo_massless_inverse(self: madspace._madspace_py.FunctionBuilder, p_out: madspace._madspace_py.Value, e_cm: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

flat_window_breit_wigner_invariant(self: madspace._madspace_py.FunctionBuilder, r: madspace._madspace_py.Value, mass: madspace._madspace_py.Value, width: madspace._madspace_py.Value, window: madspace._madspace_py.Value, s_min: madspace._madspace_py.Value, s_max: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

flat_window_breit_wigner_invariant_inverse(self: madspace._madspace_py.FunctionBuilder, s: madspace._madspace_py.Value, mass: madspace._madspace_py.Value, width: madspace._madspace_py.Value, window: madspace._madspace_py.Value, s_min: madspace._madspace_py.Value, s_max: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

full(self: madspace._madspace_py.FunctionBuilder, args: collections.abc.Sequence[madspace._madspace_py.Value]) → madspace._madspace_py.Value

function(self: madspace._madspace_py.FunctionBuilder) → madspace._madspace_py.Function

Freeze the recorded graph into an immutable Function.

gather(self: madspace._madspace_py.FunctionBuilder, index: madspace._madspace_py.Value, choices: madspace._madspace_py.Value) → madspace._madspace_py.Value

gather_int(self: madspace._madspace_py.FunctionBuilder, index: madspace._madspace_py.Value, choices: madspace._madspace_py.Value) → madspace._madspace_py.Value

gather_vector(self: madspace._madspace_py.FunctionBuilder, index: madspace._madspace_py.Value, choices: madspace._madspace_py.Value) → madspace._madspace_py.Value

gelu(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → madspace._madspace_py.Value

get_global(self: madspace._madspace_py.FunctionBuilder, name: str, dtype: madspace._madspace_py.DataType, shape: collections.abc.Sequence[SupportsInt]) → madspace._madspace_py.Value

Declare a named global tensor and return a value reading it.

Parameters:

• name – global name

• dtype – element data type

• shape – static shape, without the batch dimension

histogram(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value, weights: madspace._madspace_py.Value, min: madspace._madspace_py.Value, max: madspace._madspace_py.Value, bin_count: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

input(self: madspace._madspace_py.FunctionBuilder, index: SupportsInt) → madspace._madspace_py.Value

The graph input at position index.

input_range(self: madspace._madspace_py.FunctionBuilder, start_index: SupportsInt, end_index: SupportsInt) → list[madspace._madspace_py.Value]

The graph inputs in the half-open range [start_index, end_index).

interpolate_alpha_s(self: madspace._madspace_py.FunctionBuilder, q: madspace._madspace_py.Value, grid_logq2: madspace._madspace_py.Value, grid_coeffs: madspace._madspace_py.Value) → madspace._madspace_py.Value

interpolate_pdf(self: madspace._madspace_py.FunctionBuilder, x: madspace._madspace_py.Value, q: madspace._madspace_py.Value, pid_indices: madspace._madspace_py.Value, grid_logx: madspace._madspace_py.Value, grid_logq2: madspace._madspace_py.Value, grid_coeffs: madspace._madspace_py.Value) → madspace._madspace_py.Value

invariants_from_momenta(self: madspace._madspace_py.FunctionBuilder, p_ext: madspace._madspace_py.Value, factors: madspace._madspace_py.Value) → madspace._madspace_py.Value

leaky_relu(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → madspace._madspace_py.Value

madnis_abs_weight(self: madspace._madspace_py.FunctionBuilder, f: madspace._madspace_py.Value, q: madspace._madspace_py.Value) → madspace._madspace_py.Value

madnis_multi_channel_variance(self: madspace._madspace_py.FunctionBuilder, vars: madspace._madspace_py.Value, abs_means: madspace._madspace_py.Value) → madspace._madspace_py.Value

madnis_single_channel_variance(self: madspace._madspace_py.FunctionBuilder, var: madspace._madspace_py.Value, abs_mean: madspace._madspace_py.Value) → madspace._madspace_py.Value

madnis_softclip(self: madspace._madspace_py.FunctionBuilder, f: madspace._madspace_py.Value, q: madspace._madspace_py.Value, norm: madspace._madspace_py.Value, threshold: madspace._madspace_py.Value) → madspace._madspace_py.Value

madnis_variance(self: madspace._madspace_py.FunctionBuilder, f: madspace._madspace_py.Value, g: madspace._madspace_py.Value, q: madspace._madspace_py.Value, mean: madspace._madspace_py.Value) → madspace._madspace_py.Value

matmul(self: madspace._madspace_py.FunctionBuilder, x: madspace._madspace_py.Value, weight: madspace._madspace_py.Value, bias: madspace._madspace_py.Value) → madspace._madspace_py.Value

matrix_element(self: madspace._madspace_py.FunctionBuilder, args: collections.abc.Sequence[madspace._madspace_py.Value]) → list[madspace._madspace_py.Value]

max(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value, in2: madspace._madspace_py.Value) → madspace._madspace_py.Value

min(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value, in2: madspace._madspace_py.Value) → madspace._madspace_py.Value

mirror_momenta(self: madspace._madspace_py.FunctionBuilder, p_ext: madspace._madspace_py.Value, mirror: madspace._madspace_py.Value) → madspace._madspace_py.Value

momenta_to_x1x2(self: madspace._madspace_py.FunctionBuilder, p_ext: madspace._madspace_py.Value, e_cm: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

mul(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value, in2: madspace._madspace_py.Value) → madspace._madspace_py.Value

nonzero(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_delta_eta(self: madspace._madspace_py.FunctionBuilder, p1: madspace._madspace_py.Value, p2: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_delta_phi(self: madspace._madspace_py.FunctionBuilder, p1: madspace._madspace_py.Value, p2: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_delta_r(self: madspace._madspace_py.FunctionBuilder, p1: madspace._madspace_py.Value, p2: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_e(self: madspace._madspace_py.FunctionBuilder, p: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_eta(self: madspace._madspace_py.FunctionBuilder, p: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_eta_abs(self: madspace._madspace_py.FunctionBuilder, p: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_mass(self: madspace._madspace_py.FunctionBuilder, p: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_p_mag(self: madspace._madspace_py.FunctionBuilder, p: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_pair_mass(self: madspace._madspace_py.FunctionBuilder, p1: madspace._madspace_py.Value, p2: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_phi(self: madspace._madspace_py.FunctionBuilder, p: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_pt(self: madspace._madspace_py.FunctionBuilder, p: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_px(self: madspace._madspace_py.FunctionBuilder, p: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_py(self: madspace._madspace_py.FunctionBuilder, p: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_pz(self: madspace._madspace_py.FunctionBuilder, p: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_sqrt_s(self: madspace._madspace_py.FunctionBuilder, p_ext: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_theta(self: madspace._madspace_py.FunctionBuilder, p: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_y(self: madspace._madspace_py.FunctionBuilder, p: madspace._madspace_py.Value) → madspace._madspace_py.Value

obs_y_abs(self: madspace._madspace_py.FunctionBuilder, p: madspace._madspace_py.Value) → madspace._madspace_py.Value

offset_indices(self: madspace._madspace_py.FunctionBuilder, batch_sizes_offset: madspace._madspace_py.Value, batch_sizes_out: madspace._madspace_py.Value) → madspace._madspace_py.Value

one_hot(self: madspace._madspace_py.FunctionBuilder, index: madspace._madspace_py.Value, option_count: madspace._madspace_py.Value) → madspace._madspace_py.Value

output(self: madspace._madspace_py.FunctionBuilder, index: SupportsInt, value: madspace._madspace_py.Value) → None

Wire value to the graph output at position index.

output_range(self: madspace._madspace_py.FunctionBuilder, start_index: SupportsInt, values: collections.abc.Sequence[madspace._madspace_py.Value]) → None

Wire values to the graph outputs starting at start_index.

permute_momenta(self: madspace._madspace_py.FunctionBuilder, momenta: madspace._madspace_py.Value, permutations: madspace._madspace_py.Value, index: madspace._madspace_py.Value) → madspace._madspace_py.Value

pop(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

product(self: madspace._madspace_py.FunctionBuilder, values: collections.abc.Sequence[madspace._madspace_py.Value]) → madspace._madspace_py.Value

Product of values, element by element.

pt_eta_phi_x(self: madspace._madspace_py.FunctionBuilder, p_ext: madspace._madspace_py.Value, x1: madspace._madspace_py.Value, x2: madspace._madspace_py.Value) → madspace._madspace_py.Value

quantile(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value, q: madspace._madspace_py.Value) → madspace._madspace_py.Value

r_to_x1x2(self: madspace._madspace_py.FunctionBuilder, r: madspace._madspace_py.Value, s_hat: madspace._madspace_py.Value, s_lab: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

r_to_x1x2_window(self: madspace._madspace_py.FunctionBuilder, r: madspace._madspace_py.Value, s_hat: madspace._madspace_py.Value, s_lab: madspace._madspace_py.Value, y_max: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

random(self: madspace._madspace_py.FunctionBuilder, batch_size: madspace._madspace_py.Value, count: madspace._madspace_py.Value) → madspace._madspace_py.Value

random_int(self: madspace._madspace_py.FunctionBuilder, batch_size: madspace._madspace_py.Value, max: madspace._madspace_py.Value) → madspace._madspace_py.Value

reduce_product(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → madspace._madspace_py.Value

reduce_sum(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → madspace._madspace_py.Value

reduce_sum_vector(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → madspace._madspace_py.Value

relu(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → madspace._madspace_py.Value

restore_channel_weights(self: madspace._madspace_py.FunctionBuilder, chan_weight_values: madspace._madspace_py.Value, chan_weight_indices: madspace._madspace_py.Value, full_count: madspace._madspace_py.Value) → madspace._madspace_py.Value

rqs_find_bin(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value, in_sizes: madspace._madspace_py.Value, out_sizes: madspace._madspace_py.Value, derivatives: madspace._madspace_py.Value) → madspace._madspace_py.Value

rqs_forward(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value, condition: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

rqs_inverse(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value, condition: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

rqs_reshape(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value, bin_count: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

s23_arcsine_sample(self: madspace._madspace_py.FunctionBuilder, r: madspace._madspace_py.Value, s_min: madspace._madspace_py.Value, s_max: madspace._madspace_py.Value, s_phys_min: madspace._madspace_py.Value, s_phys_max: madspace._madspace_py.Value, power: madspace._madspace_py.Value, mass: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

s23_arcsine_sample_inverse(self: madspace._madspace_py.FunctionBuilder, u: madspace._madspace_py.Value, u_c: madspace._madspace_py.Value, s_min: madspace._madspace_py.Value, s_max: madspace._madspace_py.Value, s_phys_min: madspace._madspace_py.Value, s_phys_max: madspace._madspace_py.Value, power: madspace._madspace_py.Value, mass: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

s23_min_max(self: madspace._madspace_py.FunctionBuilder, pa: madspace._madspace_py.Value, p12: madspace._madspace_py.Value, p3: madspace._madspace_py.Value, t1_abs: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, m2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

s23_min_max_cut(self: madspace._madspace_py.FunctionBuilder, pa: madspace._madspace_py.Value, p12: madspace._madspace_py.Value, p3: madspace._madspace_py.Value, t1_abs: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, m2: madspace._madspace_py.Value, etmin_1: madspace._madspace_py.Value, etmin_2: madspace._madspace_py.Value, drcut: madspace._madspace_py.Value, s23_min_cut: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

s23_position(self: madspace._madspace_py.FunctionBuilder, s23: madspace._madspace_py.Value, s_phys_min: madspace._madspace_py.Value, s_phys_max: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

s23_value_and_min_max(self: madspace._madspace_py.FunctionBuilder, pa: madspace._madspace_py.Value, p3: madspace._madspace_py.Value, t1_abs: madspace._madspace_py.Value, p1: madspace._madspace_py.Value, p2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

s23_value_and_min_max_cut(self: madspace._madspace_py.FunctionBuilder, pa: madspace._madspace_py.Value, p3: madspace._madspace_py.Value, t1_abs: madspace._madspace_py.Value, p1: madspace._madspace_py.Value, p2: madspace._madspace_py.Value, etmin_1: madspace._madspace_py.Value, etmin_2: madspace._madspace_py.Value, drcut: madspace._madspace_py.Value, s23_min_cut: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

sample_discrete(self: madspace._madspace_py.FunctionBuilder, r: madspace._madspace_py.Value, option_count: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

sample_discrete_inverse(self: madspace._madspace_py.FunctionBuilder, index: madspace._madspace_py.Value, option_count: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

sample_discrete_probs(self: madspace._madspace_py.FunctionBuilder, r: madspace._madspace_py.Value, probs: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

sample_discrete_probs_inverse(self: madspace._madspace_py.FunctionBuilder, index: madspace._madspace_py.Value, probs: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

scale_half_transverse_mass(self: madspace._madspace_py.FunctionBuilder, momenta: madspace._madspace_py.Value) → madspace._madspace_py.Value

scale_partonic_energy(self: madspace._madspace_py.FunctionBuilder, momenta: madspace._madspace_py.Value) → madspace._madspace_py.Value

scale_transverse_energy(self: madspace._madspace_py.FunctionBuilder, momenta: madspace._madspace_py.Value) → madspace._madspace_py.Value

scale_transverse_mass(self: madspace._madspace_py.FunctionBuilder, momenta: madspace._madspace_py.Value) → madspace._madspace_py.Value

scaled_tanh(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → madspace._madspace_py.Value

sde2_channel_weights(self: madspace._madspace_py.FunctionBuilder, invariants: madspace._madspace_py.Value, masses: madspace._madspace_py.Value, widths: madspace._madspace_py.Value, indices: madspace._madspace_py.Value) → madspace._madspace_py.Value

select(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value, indices: madspace._madspace_py.Value) → madspace._madspace_py.Value

select_int(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value, indices: madspace._madspace_py.Value) → madspace._madspace_py.Value

select_vector(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value, indices: madspace._madspace_py.Value) → madspace._madspace_py.Value

set_current_stream(self: madspace._madspace_py.FunctionBuilder, arg0: SupportsInt) → None

Select the execution stream new instructions are added to.

sigmoid(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → madspace._madspace_py.Value

softmax(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value) → madspace._madspace_py.Value

softmax_prior(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value, prior: madspace._madspace_py.Value) → madspace._madspace_py.Value

softplus(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → madspace._madspace_py.Value

sqrt(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → madspace._madspace_py.Value

square(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → madspace._madspace_py.Value

squeeze(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value) → madspace._madspace_py.Value

stable_invariant(self: madspace._madspace_py.FunctionBuilder, r: madspace._madspace_py.Value, mass: madspace._madspace_py.Value, s_min: madspace._madspace_py.Value, s_max: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

stable_invariant_inverse(self: madspace._madspace_py.FunctionBuilder, s: madspace._madspace_py.Value, mass: madspace._madspace_py.Value, s_min: madspace._madspace_py.Value, s_max: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

stable_invariant_nu(self: madspace._madspace_py.FunctionBuilder, r: madspace._madspace_py.Value, mass: madspace._madspace_py.Value, nu: madspace._madspace_py.Value, s_min: madspace._madspace_py.Value, s_max: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

stable_invariant_nu_inverse(self: madspace._madspace_py.FunctionBuilder, s: madspace._madspace_py.Value, mass: madspace._madspace_py.Value, nu: madspace._madspace_py.Value, s_min: madspace._madspace_py.Value, s_max: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

stack(self: madspace._madspace_py.FunctionBuilder, args: collections.abc.Sequence[madspace._madspace_py.Value]) → madspace._madspace_py.Value

stack_sizes(self: madspace._madspace_py.FunctionBuilder, args: collections.abc.Sequence[madspace._madspace_py.Value]) → madspace._madspace_py.Value

sub(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value, in2: madspace._madspace_py.Value) → madspace._madspace_py.Value

subchannel_weights(self: madspace._madspace_py.FunctionBuilder, invariants: madspace._madspace_py.Value, masses: madspace._madspace_py.Value, widths: madspace._madspace_py.Value, indices: madspace._madspace_py.Value, on_shell: madspace._madspace_py.Value, group_sizes: madspace._madspace_py.Value) → madspace._madspace_py.Value

t1_inv_min_max_doublet(self: madspace._madspace_py.FunctionBuilder, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, mir_min: madspace._madspace_py.Value, etmin_i: madspace._madspace_py.Value, etmin_ir: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

t1_inv_value_and_min_max_doublet(self: madspace._madspace_py.FunctionBuilder, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value, p1: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, mir_min: madspace._madspace_py.Value, etmin_i: madspace._madspace_py.Value, etmin_ir: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

t1_rapidity_clamp_doublet(self: madspace._madspace_py.FunctionBuilder, t1_min: madspace._madspace_py.Value, t1_max: madspace._madspace_py.Value, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, mir_min: madspace._madspace_py.Value, etmin_1: madspace._madspace_py.Value, etmin_2: madspace._madspace_py.Value, x1: madspace._madspace_py.Value, x2: madspace._madspace_py.Value, beam_sign: madspace._madspace_py.Value, y_max1: madspace._madspace_py.Value, y_max2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

t2_inv_min_max_doublet(self: madspace._madspace_py.FunctionBuilder, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, mir_min: madspace._madspace_py.Value, t1_abs: madspace._madspace_py.Value, etmin_i: madspace._madspace_py.Value, etmin_ir: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

t2_inv_value_and_min_max_doublet(self: madspace._madspace_py.FunctionBuilder, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value, p1: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, mir_min: madspace._madspace_py.Value, t1_abs: madspace._madspace_py.Value, etmin_i: madspace._madspace_py.Value, etmin_ir: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

t2_rapidity_clamp_doublet(self: madspace._madspace_py.FunctionBuilder, t2_min: madspace._madspace_py.Value, t2_max: madspace._madspace_py.Value, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, t1_abs: madspace._madspace_py.Value, x1: madspace._madspace_py.Value, x2: madspace._madspace_py.Value, beam_sign: madspace._madspace_py.Value, y_max1: madspace._madspace_py.Value, y_max2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

t_inv_min_max(self: madspace._madspace_py.FunctionBuilder, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, m2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

t_inv_min_max_cut(self: madspace._madspace_py.FunctionBuilder, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, m2: madspace._madspace_py.Value, etmin_1: madspace._madspace_py.Value, etmin_2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

t_inv_value_and_min_max(self: madspace._madspace_py.FunctionBuilder, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value, p1: madspace._madspace_py.Value, p2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

t_inv_value_and_min_max_cut(self: madspace._madspace_py.FunctionBuilder, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value, p1: madspace._madspace_py.Value, p2: madspace._madspace_py.Value, etmin_1: madspace._madspace_py.Value, etmin_2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

t_rapidity_clamp(self: madspace._madspace_py.FunctionBuilder, t_min: madspace._madspace_py.Value, t_max: madspace._madspace_py.Value, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, m2: madspace._madspace_py.Value, x1: madspace._madspace_py.Value, x2: madspace._madspace_py.Value, beam_sign: madspace._madspace_py.Value, y_max1: madspace._madspace_py.Value, y_max2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

three_body_decay(self: madspace._madspace_py.FunctionBuilder, r_e1: madspace._madspace_py.Value, r_e2: madspace._madspace_py.Value, r_phi: madspace._madspace_py.Value, r_cos_theta: madspace._madspace_py.Value, r_beta: madspace._madspace_py.Value, m0: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, m2: madspace._madspace_py.Value, m3: madspace._madspace_py.Value, p0: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(4)']

three_body_decay_com(self: madspace._madspace_py.FunctionBuilder, r_e1: madspace._madspace_py.Value, r_e2: madspace._madspace_py.Value, r_phi: madspace._madspace_py.Value, r_cos_theta: madspace._madspace_py.Value, r_beta: madspace._madspace_py.Value, m0: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, m2: madspace._madspace_py.Value, m3: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(4)']

three_body_decay_com_inverse(self: madspace._madspace_py.FunctionBuilder, p1: madspace._madspace_py.Value, p2: madspace._madspace_py.Value, p3: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(10)']

three_body_decay_inverse(self: madspace._madspace_py.FunctionBuilder, p1: madspace._madspace_py.Value, p2: madspace._madspace_py.Value, p3: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(11)']

two_body_decay(self: madspace._madspace_py.FunctionBuilder, r_phi: madspace._madspace_py.Value, r_cos_theta: madspace._madspace_py.Value, m0: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, m2: madspace._madspace_py.Value, p0: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

two_body_decay_com(self: madspace._madspace_py.FunctionBuilder, r_phi: madspace._madspace_py.Value, r_cos_theta: madspace._madspace_py.Value, m0: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, m2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

two_body_decay_com_inverse(self: madspace._madspace_py.FunctionBuilder, p1: madspace._madspace_py.Value, p2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(6)']

two_body_decay_inverse(self: madspace._madspace_py.FunctionBuilder, p1: madspace._madspace_py.Value, p2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(7)']

two_to_three_particle_scattering(self: madspace._madspace_py.FunctionBuilder, phi_choice: madspace._madspace_py.Value, pa: madspace._madspace_py.Value, p12: madspace._madspace_py.Value, p3: madspace._madspace_py.Value, u: madspace._madspace_py.Value, u_c: madspace._madspace_py.Value, t1_abs: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, m2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

two_to_three_particle_scattering_inverse(self: madspace._madspace_py.FunctionBuilder, p1: madspace._madspace_py.Value, p2: madspace._madspace_py.Value, p3: madspace._madspace_py.Value, pa: madspace._madspace_py.Value, p12: madspace._madspace_py.Value, t1_abs: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(6)']

two_to_two_particle_scattering(self: madspace._madspace_py.FunctionBuilder, r_phi: madspace._madspace_py.Value, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value, t_abs: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, m2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

two_to_two_particle_scattering_com(self: madspace._madspace_py.FunctionBuilder, r_phi: madspace._madspace_py.Value, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value, t_abs: madspace._madspace_py.Value, m1: madspace._madspace_py.Value, m2: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(3)']

two_to_two_particle_scattering_com_inverse(self: madspace._madspace_py.FunctionBuilder, p1: madspace._madspace_py.Value, p2: madspace._madspace_py.Value, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(4)']

two_to_two_particle_scattering_inverse(self: madspace._madspace_py.FunctionBuilder, p1: madspace._madspace_py.Value, p2: madspace._madspace_py.Value, pa: madspace._madspace_py.Value, pb: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(4)']

uniform_invariant(self: madspace._madspace_py.FunctionBuilder, r: madspace._madspace_py.Value, s_min: madspace._madspace_py.Value, s_max: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

uniform_invariant_inverse(self: madspace._madspace_py.FunctionBuilder, s: madspace._madspace_py.Value, s_min: madspace._madspace_py.Value, s_max: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

unsqueeze(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value) → madspace._madspace_py.Value

unstack(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → list[madspace._madspace_py.Value]

unstack_sizes(self: madspace._madspace_py.FunctionBuilder, in1: madspace._madspace_py.Value) → list[madspace._madspace_py.Value]

unweight(self: madspace._madspace_py.FunctionBuilder, weights: madspace._madspace_py.Value, max_weight: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

vegas_forward(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value, grid: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

vegas_histogram(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value, weights: madspace._madspace_py.Value, bin_count: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

vegas_inverse(self: madspace._madspace_py.FunctionBuilder, input: madspace._madspace_py.Value, grid: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

x1x2_to_r(self: madspace._madspace_py.FunctionBuilder, x1: madspace._madspace_py.Value, x2: madspace._madspace_py.Value, s_lab: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']

x1x2_to_r_window(self: madspace._madspace_py.FunctionBuilder, x1: madspace._madspace_py.Value, x2: madspace._madspace_py.Value, s_lab: madspace._madspace_py.Value, y_max: madspace._madspace_py.Value) → Annotated[list[madspace._madspace_py.Value], 'FixedSize(2)']