How to use the taichi.root function in taichi
To help you get started, we’ve selected a few taichi examples, based on popular ways it is used in public projects.
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yuanming-hu / taichi / tests / python / test_kernel_template_mapper.py View on Github 
def layout():
ti.root.place(x, y)def layout():
ti.root.place(x, y)def layout():
ti.root.place(x)def layout():
ti.root.place(x, y)def place():
ti.root.dense(ti.i, n).pointer().dense(ti.i, n).place(x)
ti.root.place(s)def values():
ti.root.dense(ti.ij, (n, m)).place(val)def p(x):
for i in x.entries:
ti.root.dense(ti.l, max_steps).dense(ti.k, n_particles).place(i)
ti.root.dense(ti.l, max_steps).dense(ti.k, n_particles).place(i.grad)def place():
ti.root.dense(ti.i, max_timesteps).place(x, v)
ti.root.place(a, damping, loss)
ti.root.lazy_grad()def place():
ti.root.dense(ti.ij, (n_actuators, n_sin_waves)).place(weights)
ti.root.dense(ti.i, n_actuators).place(bias)
ti.root.dense(ti.ij, (max_steps, n_actuators)).place(actuation)
ti.root.dense(ti.i, n_particles).place(actuator_id, particle_type)
ti.root.dense(ti.l, max_steps).dense(ti.k, n_particles).place(x, v, C, F)
ti.root.dense(ti.ij, n_grid).place(grid_v_in, grid_m_in, grid_v_out)
ti.root.place(loss, x_avg)
ti.root.lazy_grad()def place():
ti.root.dense(ti.l, max_steps).dense(ti.ij, n_grid).place(p)
ti.root.dense(ti.l, max_steps).dense(ti.ij, n_grid).place(p.grad)
ti.root.dense(ti.ij, n_grid).place(target)
ti.root.dense(ti.ij, n_grid).place(target.grad)
ti.root.dense(ti.ij, n_grid).place(initial)
ti.root.dense(ti.ij, n_grid).place(initial.grad)
ti.root.place(loss)
ti.root.place(loss.grad)
