"""Test code for binary neural network operators.""" import numpy as np import tvm import topi from topi.util import get_const_tuple from tvm.contrib.pickle_memoize import memoize def verify_binary_dense(batch, in_dim, out_dim): A = tvm.placeholder((batch, in_dim), name='A') B = tvm.placeholder((out_dim, in_dim), name='B') bnn_A = topi.cpp.nn.binarize_pack(A, 1) bnn_B = topi.cpp.nn.binarize_pack(B, 1) # binary dense bnn_A1 = tvm.placeholder(bnn_A.shape, dtype=bnn_A.dtype) bnn_B1 = tvm.placeholder(bnn_B.shape, dtype=bnn_B.dtype) bnn_C = topi.cpp.nn.binary_dense(bnn_A1, bnn_B1) # schedule target = topi.cpp.TEST_create_target("llvm") s1 = topi.cpp.x86.schedule_binarize_pack(target, [bnn_A]) s2 = topi.cpp.x86.schedule_binarize_pack(target, [bnn_B]) s3 = topi.cpp.x86.schedule_binary_dense(target, [bnn_C]) dtype = A.dtype @memoize("topi.tests.test_topi_binary_dense") def get_ref_data(): # generate random matrix of +1 or -1 value a_np = (np.random.randint(2, size=(batch, in_dim)) * 2 - 1).astype(dtype) b_np = (np.random.randint(2, size=(out_dim, in_dim)) * 2 - 1).astype(dtype) c_np = np.dot(a_np, b_np.T) return (a_np, b_np, c_np) a_np, b_np, c_np = get_ref_data() ctx = tvm.cpu(0) a = tvm.nd.array(a_np, ctx) b = tvm.nd.array(b_np, ctx) bnn_a = tvm.nd.array(np.zeros(get_const_tuple(bnn_A.shape), dtype=bnn_A.dtype), ctx) bnn_b = tvm.nd.array(np.zeros(get_const_tuple(bnn_B.shape), dtype=bnn_B.dtype), ctx) bnn_c = tvm.nd.array(np.zeros(get_const_tuple(bnn_C.shape), dtype=bnn_C.dtype), ctx) f1 = tvm.build(s1, [A, bnn_A], 'llvm') f2 = tvm.build(s2, [B, bnn_B], 'llvm') f3 = tvm.build(s3, [bnn_A1, bnn_B1, bnn_C], 'llvm') f1(a, bnn_a) f2(b, bnn_b) f3(bnn_a, bnn_b, bnn_c) np.testing.assert_allclose(bnn_c.asnumpy(), c_np, rtol=1e-5) def test_binary_dense(): verify_binary_dense(1, 4096, 1024) verify_binary_dense(1, 1024, 1000) if __name__ == "__main__": test_binary_dense()