def broadcast_pow(input1, input2, name='broadcast_pow'):
input1_mod, input2_mod, switch = broadcast_set(input1, input2)
if (switch):
return hcl.compute(
input1_mod.shape,
lambda *x: hcl.power(input1_mod[x], input2_mod[_broadcast(
input2_mod.shape, x)]),
name=name)
else:
return hcl.compute(
input2_mod.shape,
lambda *x: hcl.power(input1_mod[_broadcast(input1_mod.shape, x)],
input2_mod[x]),
name=name)
def test_int():
hcl.init(hcl.Float())
a = hcl.placeholder((10, ))
b = hcl.compute(a.shape, lambda x: hcl.power(2, a[x]))
s = hcl.create_schedule([a, b])
f = hcl.build(s)
np_a = np.random.rand(10)
np_b = np.zeros(10)
hcl_a = hcl.asarray(np_a)
hcl_b = hcl.asarray(np_b)
f(hcl_a, hcl_b)
np_golden = np.power(2, np_a)
assert np.allclose(np_golden, hcl_b.asnumpy())
def test_large_int():
hcl.init(hcl.Int())
a = hcl.placeholder((10, ))
b = hcl.placeholder((10, ))
c = hcl.compute(a.shape, lambda x: hcl.power(a[x], b[x]))
s = hcl.create_schedule([a, b, c])
f = hcl.build(s)
np_a = np.random.randint(1, 10, (10, ))
np_b = np.random.randint(1, 10, (10, ))
np_c = np.zeros(10, dtype="int")
hcl_a = hcl.asarray(np_a)
hcl_b = hcl.asarray(np_b)
hcl_c = hcl.asarray(np_c)
f(hcl_a, hcl_b, hcl_c)
np_golden = np.power(np_a, np_b)
assert np.allclose(np_golden, hcl_c.asnumpy())
def elemwise_pow(input1, input2, name='elemwise_pow'):
return hcl.compute(input1.shape,
lambda *x: hcl.power(input1[x], input2[x]),
name=name)
def top(input, ):
final_total_extent_1 = (hcl.cast(dtype = hcl.Int(bits = 64), expr = final_extent_1) * hcl.cast(dtype = hcl.Int(bits = 64), expr = final_extent_0))
final_total_extent_2 = (final_total_extent_1 * hcl.cast(dtype = hcl.Int(bits = 64), expr = final_extent_2))
linear = hcl.compute(((final_extent_0 + 2), (final_extent_1 + 2), final_extent_2), lambda x, y, z: 0, name = "linear", dtype = hcl.Float(bits = 32))
with hcl.Stage("linear"):
with hcl.for_(final_min_2, final_extent_2, name = "linear_s0_c") as linear_s0_c:
with hcl.for_(final_min_1, (final_extent_1 + 2), name = "linear_s0_y") as linear_s0_y:
with hcl.for_(final_min_0, (final_extent_0 + 2), name = "linear_s0_x") as linear_s0_x:
t4 = input[linear_s0_x, linear_s0_y, linear_s0_c]
linear[linear_s0_x, linear_s0_y, linear_s0_c] = hcl.select((hcl.cast(dtype = hcl.Float(bits = 32), expr = 0.040450) < t4), hcl.power(((t4 * hcl.cast(dtype = hcl.Float(bits = 32), expr = 0.947867)) + hcl.cast(dtype = hcl.Float(bits = 32), expr = 0.052133)), hcl.cast(dtype = hcl.Float(bits = 32), expr = 2.400000)), (t4 * hcl.cast(dtype = hcl.Float(bits = 32), expr = 0.077399)))
blur_x = hcl.compute((final_extent_0, (final_extent_1 + 2), final_extent_2), lambda x, y, z: 0, name = "blur_x", dtype = hcl.Float(bits = 32))
with hcl.Stage("blur_x"):
with hcl.for_(final_min_2, final_extent_2, name = "blur_x_s0_c") as blur_x_s0_c:
with hcl.for_(final_min_1, (final_extent_1 + 2), name = "blur_x_s0_y") as blur_x_s0_y:
with hcl.for_(final_min_0, final_extent_0, name = "blur_x_s0_x") as blur_x_s0_x:
blur_x[blur_x_s0_x, blur_x_s0_y, blur_x_s0_c] = ((linear[(blur_x_s0_x + 2), blur_x_s0_y, blur_x_s0_c] + (linear[blur_x_s0_x, blur_x_s0_y, blur_x_s0_c] + linear[(blur_x_s0_x + 1), blur_x_s0_y, blur_x_s0_c])) * hcl.cast(dtype = hcl.Float(bits = 32), expr = 0.333333))
blur_y = hcl.compute((final_extent_0, final_extent_1, final_extent_2), lambda x, y, z: 0, name = "blur_y", dtype = hcl.Float(bits = 32))
with hcl.Stage("blur_y"):
with hcl.for_(final_min_2, final_extent_2, name = "blur_y_s0_c") as blur_y_s0_c:
with hcl.for_(final_min_1, final_extent_1, name = "blur_y_s0_y") as blur_y_s0_y:
with hcl.for_(final_min_0, final_extent_0, name = "blur_y_s0_x") as blur_y_s0_x:
blur_y[blur_y_s0_x, blur_y_s0_y, blur_y_s0_c] = ((blur_x[blur_y_s0_x, (blur_y_s0_y + 2), blur_y_s0_c] + (blur_x[blur_y_s0_x, blur_y_s0_y, blur_y_s0_c] + blur_x[blur_y_s0_x, (blur_y_s0_y + 1), blur_y_s0_c])) * hcl.cast(dtype = hcl.Float(bits = 32), expr = 0.333333))
srgb = hcl.compute((final_extent_0, final_extent_1, final_extent_2), lambda x, y, z: 0, name = "srgb", dtype = hcl.Float(bits = 32))
with hcl.Stage("srgb"):
with hcl.for_(final_min_2, final_extent_2, name = "srgb_s0_c") as srgb_s0_c:
with hcl.for_(final_min_1, final_extent_1, name = "srgb_s0_y") as srgb_s0_y:
with hcl.for_(final_min_0, final_extent_0, name = "srgb_s0_x") as srgb_s0_x:
t5 = blur_y[srgb_s0_x, srgb_s0_y, srgb_s0_c]
srgb[srgb_s0_x, srgb_s0_y, srgb_s0_c] = hcl.select((hcl.cast(dtype = hcl.Float(bits = 32), expr = 0.003131) < t5), ((hcl.power(t5, hcl.cast(dtype = hcl.Float(bits = 32), expr = 0.416667)) * hcl.cast(dtype = hcl.Float(bits = 32), expr = 1.055000)) + hcl.cast(dtype = hcl.Float(bits = 32), expr = -0.055000)), (t5 * hcl.cast(dtype = hcl.Float(bits = 32), expr = 12.920000)))
final = hcl.compute((766, 1278, 3), lambda x, y, z: 0, name = "final", dtype = hcl.Float(bits = 32))
with hcl.Stage("final"):
with hcl.for_(final_min_2, final_extent_2, name = "final_s0_c") as final_s0_c:
with hcl.for_(final_min_1, final_extent_1, name = "final_s0_y") as final_s0_y:
with hcl.for_(final_min_0, final_extent_0, name = "final_s0_x") as final_s0_x:
final[final_s0_x, final_s0_y, final_s0_c] = srgb[final_s0_x, final_s0_y, final_s0_c]
return final
