# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. import os import re import numpy as np import tvm from tvm import te import topi import topi.testing from topi.util import get_const_tuple def generate_quantized_np(shape, bits, out_dtype): np.random.seed(0) min_val = 0 max_val = 1 << bits return np.random.randint(min_val, max_val, size=shape).astype(out_dtype) # Verify that certain special instructions from the tensorize pass exist def verify_bitserial_conv2d_nhwc(batch, in_size, in_channel, num_filter, kernel, stride, padding, activation_bits, weight_bits, unipolar): in_height = in_width = in_size input_type = 'uint32' out_dtype = 'int16' device = 'llvm -device=arm_cpu -model=bcm2837 -target=armv7l-linux-gnueabihf -mattr=+neon' with tvm.target.create(device): A = te.placeholder((batch, in_height, in_width, in_channel), dtype=input_type, name='A') W = te.placeholder((kernel, kernel, in_channel, num_filter), dtype=input_type, name='W') B = topi.arm_cpu.bitserial_conv2d_nhwc(A, W, stride, padding, activation_bits, weight_bits, 'uint8', out_dtype, unipolar) s = topi.arm_cpu.schedule_bitserial_conv2d_nhwc([B]) func = tvm.build(s, [A, W, B], device) assembly = func.get_source('asm') matches = re.findall("vpadal", assembly) assert (len(matches) > 0) matches = re.findall("vcnt", assembly) assert (len(matches) > 0) matches = re.findall("vpadd", assembly) assert (len(matches) > 0) ctx = tvm.context(device, 0) if 'arm' not in os.uname()[4]: print ("Skipped running code, not an arm device") return print("Running on target: %s" % device) def get_ref_data(): a_np = generate_quantized_np(get_const_tuple(A.shape), activation_bits, input_type) w_np = generate_quantized_np(get_const_tuple(W.shape), weight_bits, input_type) if unipolar: w_ = np.copy(w_np).astype(out_dtype) for x in np.nditer(w_, op_flags=['readwrite']): x[...] = 1 if x == 1 else -1 b_np = topi.testing.conv2d_nhwc_python(a_np, w_, stride, padding).astype(out_dtype) else: b_np = topi.testing.conv2d_nhwc_python(a_np, w_np, stride, padding).astype(out_dtype) return a_np, w_np, b_np a_np, w_np, b_np = get_ref_data() a = tvm.nd.array(a_np, ctx) w = tvm.nd.array(w_np, ctx) b = tvm.nd.array(np.zeros(get_const_tuple(B.shape), dtype=B.dtype), ctx) func = tvm.build(s, [A, W, B], device) func(a, w, b) np.testing.assert_allclose(b.asnumpy(), b_np, rtol=1e-5) def test_bitserial_conv2d(): in_size = 56 ic, oc = 64, 64 k = 3 stride = 1 pad = 1 verify_bitserial_conv2d_nhwc(1, in_size, ic, oc, k, stride, pad, 1, 1, False) verify_bitserial_conv2d_nhwc(1, in_size, ic, oc, k, stride, pad, 2, 1, False) verify_bitserial_conv2d_nhwc(1, in_size, ic, oc, k, stride, pad, 1, 1, True) verify_bitserial_conv2d_nhwc(1, in_size, ic, oc, k, stride, pad, 2, 1, True) if __name__ == "__main__": test_bitserial_conv2d()