MegEngine/dnn/scripts/gen_cuda_batch_conv_bias_kern_impls.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

import os
import argparse
import itertools

PREFIXES = {"dp4a": [("batch_conv_bias_int8_implicit_gemm_precomp_ncdiv4hw4", True), ("batch_conv_bias_int8_gemm_ncdiv4hw4", False), ("batch_conv_bias_int8_gemm_ncdiv4hw4_ldg_128", False)]}

ACTIVATIONS = {1: ("IDENTITY", "_id"), 
               2: ("RELU", "_relu"), 
               3: ("H_SWISH", "_hswish")}

BIASES = {1: ("PerElementBiasVisitor", "_per_elem"), 
          2: ("PerChannelBiasVisitor", "_per_chan")}

SUFFIXES = {"dp4a": [""], 
            "imma": [""]} 

def main():
    parser = argparse.ArgumentParser(
        description='generate cuda batch conv bias (dp4a/imma) kern impl files',
        formatter_class=argparse.ArgumentDefaultsHelpFormatter)
    parser.add_argument('--type', type=str, choices=['dp4a',
                                                     'imma'], 
                        default='dp4a', help='generate cuda conv bias kernel file')
    parser.add_argument('output', help='output directory')
    args = parser.parse_args()

    if not os.path.isdir(args.output):
        os.makedirs(args.output)

    
    inst = '''
template void megdnn::cuda::batch_conv_bias::do_PREFIXSUFFIX<BIAS, 
        IConvEpilogue<Activation<megdnn::param_enumv::BatchConvBias::NonlineMode::ACTIVATION>>>(
        const int8_t* d_src, 
        const int8_t* d_filter, WORKSPACE 
        BIAS bias, 
        IConvEpilogue<Activation<megdnn::param_enumv::BatchConvBias::NonlineMode::ACTIVATION>> epilogue, 
        const ConvParam& param, 
        float alpha, 
        float beta, 
        cudaStream_t stream);'''

    for prefix in PREFIXES[args.type]:
        for suffix in SUFFIXES[args.type]:
            for _, act in ACTIVATIONS.items():
                has_workspace = prefix[1]
                bias = BIASES[2]
                fname = "{}{}{}{}.cu".format(prefix[0], suffix, bias[1], act[1])
                fname = os.path.join(args.output, fname)
                with open(fname, "w") as fout:
                    w = lambda s: print(s, file=fout)
                    w('// generated by gen_batch_cuda_conv_bias_kern_impls.py')
                    cur_inst = inst.replace("PREFIX", prefix[0]).replace("SUFFIX", suffix).replace("BIAS", bias[0]).replace("ACTIVATION", act[0])
                    if has_workspace:
                        cur_inst = cur_inst.replace("WORKSPACE", "\nint* d_workspace, ")
                    else:
                        cur_inst = cur_inst.replace("WORKSPACE", "") 
                    w('#include "../{}{}.cuinl"'.format(prefix[0], suffix))
                    w(cur_inst)
            
                    print('generated {}'.format(fname))
    os.utime(args.output)

if __name__ == '__main__':
    main()