def make_qgraph(data, weight):
out = data * relay.const(32.0)
out = relay.round(out)
out = relay.clip(out, a_min=-127, a_max=127)
out = out.astype('int8')
out = relay.nn.conv2d(out, weight, kernel_size=(3, 3),
padding=(1, 1), channels=c, out_dtype='int32')
out = out.astype('float32')
out = relay.multiply(out, relay.const(0.00024414062))
out = relay.Function(relay.ir_pass.free_vars(out), out)
return out
def verify_round(dshape, dtype="float32"):
x = relay.var("x", relay.ty.TensorType(dshape, dtype))
y = relay.round(x)
func = relay.Function([x], y)
x_data = np.random.uniform(size=dshape).astype(dtype)
verify_results(func, [x_data], "test_round", rtol=1e-4, atol=1e-4)