"""Test code for local response normalization""" import numpy as np import tvm import topi from topi.util import get_const_tuple import topi.testing def verify_lrn(shape, size, axis, bias, alpha, beta): A = tvm.placeholder(shape, name='A') B = topi.nn.lrn(A, size, axis, alpha, beta, bias) dtype = A.dtype a_np = np.random.uniform(size=shape).astype(dtype) b_np = topi.testing.lrn_python(a_np, size, axis, bias, alpha, beta) def check_device(device): if not tvm.module.enabled(device): print("Skip because %s is not enabled" % device) return print("Running on target: %s" % device) with tvm.target.create(device): if device == 'llvm': s = topi.generic.schedule_lrn([B]) else: s = topi.cuda.schedule_lrn([B]) ctx = tvm.context(device, 0) a = tvm.nd.array(a_np, ctx) b = tvm.nd.array(np.zeros(get_const_tuple(B.shape), dtype=dtype), ctx) f = tvm.build(s, [A, B], device) f(a, b) np.testing.assert_allclose(b.asnumpy(), b_np, rtol=1e-5) for device in ['llvm', 'cuda', 'opencl', 'metal', 'rocm', 'vulkan']: check_device(device) def test_lrn(): verify_lrn((1, 3, 5, 5), 3, 1, 1.0, 1.0, 0.5) verify_lrn((1, 3, 5, 5), 3, 3, 1.0, 1.0, 0.5) verify_lrn((1, 3, 20, 20), 3, 1, 2.0, 1.0, 0.75) if __name__ == "__main__": test_lrn()