示例#1
0
def test():
    """
    Execute the tests
    Returns: (n_total, n_success)
    """

    logger = TestLogger(TESTNAME, show_title=False)

    for simd, parallel in [(False, False), (True, False), (True, True)]:

        # generate makefile
        mkf = Makefile()
        mkf.add_fc_test_source("test.c")
        mkf.add_cl_test_source("cluster.c")
        mkf.add_cl_prog_source("net/layer3.c")
        mkf.add_cl_prog_source("net/net.c")
        mkf.add_cl_prog_source("func/transform.c")
        mkf.add_cl_prog_source("func/conv.c")

        if not simd:
            mkf.add_define("NO_SIMD")

        if parallel:
            mkf.add_define("PARALLEL")

        mkf.write()

        random_input = False

        # generate the stimuli
        _, x_align, _, y_exp_align = gen_stimuli(random_input)

        # prepare header file
        header = HeaderFile("test_stimuli.h")
        header.add(HeaderArray("x_vec", "int8_t", x_align.ravel()))
        header.add(HeaderArray("y_exp_vec", "int8_t", y_exp_align.ravel()))
        header.write()

        # compile and run
        os.system("make clean all run > {}".format(RESULT_FILE))

        # parse output
        result = parse_output(RESULT_FILE)

        # log the result
        options = []
        if simd:
            options.append("simd")
        if parallel:
            options.append("parallel")

        subcase_name = "layer 3 "
        if options:
            subcase_name += " + ".join(options)
        else:
            subcase_name += "naive"
        logger.show_subcase_result(subcase_name, result)

    # return summary
    return logger.summary()
示例#2
0
def test():
    """
    Execute the tests
    Returns: (n_total, n_success)
    """

    logger = TestLogger(TESTNAME, show_title=False)

    for parallel in [False, True]:

        # generate makefile
        mkf = Makefile()
        mkf.add_fc_test_source("test.c")
        mkf.add_cl_test_source("cluster.c")
        mkf.add_cl_prog_source("net/layer1.c")
        mkf.add_cl_prog_source("net/net.c")
        mkf.add_cl_prog_source("func/flip.c")

        if parallel:
            mkf.add_define("PARALLEL")

        mkf.write()

        # generate the stimuli
        _, x_align, y_exp, y_exp_align = gen_stimuli()

        # prepare header file
        header = HeaderFile("test_stimuli.h")
        header.add(HeaderArray("x_vec", "int8_t", x_align.ravel(),
                               const=False))
        header.add(
            HeaderArray("y_exp", "int8_t", y_exp_align.ravel(), const=False))
        header.write()

        # compile and run
        os.system("make clean all run > {}".format(RESULT_FILE))

        # parse output
        result = parse_output(RESULT_FILE)

        # log the result
        subcase_name = "Layer 1 flip "

        if parallel:
            subcase_name += "parallel"
        else:
            subcase_name += "naive"

        logger.show_subcase_result(subcase_name, result)

    # return summary
    return logger.summary()
示例#3
0
def test():
    """
    Execute the tests
    Returns: (n_total, n_success)
    """

    logger = TestLogger(TESTNAME)

    for size_a, size_b in [(155, 16), (1188, 64), (4096, 128)]:
        for conv_version in [0, 1, 2, 3]:

            div_factor = 128 * size_b // 8
            offset = 10 * div_factor

            # generate makefile
            mkf = Makefile()
            mkf.add_fc_test_source("test.c")
            mkf.add_cl_test_source("cluster.c")
            mkf.add_cl_prog_source("func/conv.c")
            mkf.add_define("CONV_VERSION", conv_version)
            mkf.write()

            # generate the stimuli
            vecA, vecB, vecExp = gen_stimuli(size_a, size_b, div_factor,
                                             offset)

            # prepare header file
            header = HeaderFile("test_stimuli.h")
            header.add(HeaderConstant("LENGTH_A", size_a))
            header.add(HeaderConstant("LENGTH_B", size_b))
            header.add(HeaderConstant("LENGTH_RES", len(vecExp)))
            header.add(HeaderConstant("FACTOR", div_factor))
            header.add(HeaderConstant("OFFSET", offset))
            header.add(HeaderArray("vecA", "int8_t", vecA))
            header.add(HeaderArray("vecB", "int8_t", vecB))
            header.add(HeaderArray("vecExp", "int8_t", vecExp))
            header.write()

            # compile and run
            os.system("make clean all run > {}".format(RESULT_FILE))

            # parse output
            result = parse_output(RESULT_FILE)

            casename = "V{}, {}x{}".format(conv_version, size_a, size_b)

            # log the result
            logger.show_subcase_result(casename, result)

    # return summary
    return logger.summary()
示例#4
0
def test():
    """
    Execute the tests
    Returns: (n_total, n_success)
    """

    logger = TestLogger(TESTNAME, show_title=False)

    for simd in [False, True]:

        # generate makefile
        mkf = Makefile()
        mkf.add_fc_test_source("test.c")
        mkf.add_cl_test_source("cluster.c")
        mkf.add_cl_prog_source("net/layer5.c")
        mkf.add_cl_prog_source("net/net.c")
        mkf.add_cl_prog_source("func/transform.c")
        mkf.add_cl_prog_source("func/dotp.c")
        mkf.write()

        if not simd:
            mkf.add_define("NO_SIMD")

        random_input = False

        # generate the stimuli
        _, x_align, _, y_exp_align = gen_stimuli(random_input)

        # prepare header file
        header = HeaderFile("test_stimuli.h")
        header.add(HeaderArray("x_vec", "int8_t", x_align.ravel()))
        header.add(HeaderArray("y_exp_vec", "int8_t", y_exp_align.ravel()))
        header.write()

        # compile and run
        os.system("make clean all run > {}".format(RESULT_FILE))

        # parse output
        result = parse_output(RESULT_FILE)

        # log the result
        subcase_name = "Layer 5 "
        if simd:
            subcase_name += "simd"
        else:
            subcase_name += "naive"
        logger.show_subcase_result(subcase_name, result)

    # return summary
    return logger.summary()
示例#5
0
def test():
    """
    Execute the tests
    Returns: (n_total, n_success)
    """

    logger = TestLogger(TESTNAME)

    for no_intermediate_scale, duplicate_featuremap in [(False, False),
                                                        (True, False),
                                                        (True, True)]:

        # generate makefile
        # mkf = Makefile(opt_level=2 if duplicate_featuremap else 3)
        mkf = Makefile(opt_level=3)
        mkf.add_fc_test_source("test.c")
        mkf.add_cl_test_source("cluster.c")
        mkf.add_cl_prog_source("net/fused_layer_1_2.c")
        mkf.add_cl_prog_source("net/net.c")
        mkf.add_cl_prog_source("func/conv.c")
        mkf.add_cl_prog_source("func/xcorr.c")
        mkf.add_cl_prog_source("func/dotp.c")
        mkf.add_cl_prog_source("func/transform.c")

        mkf.add_define("PARALLEL")
        mkf.add_define("INTRINSIC_SCALE")
        mkf.add_define("CROSS_CORRELATE")
        mkf.add_define("FUSE_LAYERS")
        mkf.add_define("DEFAULT_DIM")

        if no_intermediate_scale:
            mkf.add_define("NO_INTERMEDIATE_SCALE")

        if duplicate_featuremap:
            mkf.add_define("DUPLICATE_FEATUREMAP")

        mkf.write()

        random_input = False

        # generate the stimuli
        _, x_align, _, y_exp_align = gen_stimuli(random_input,
                                                 no_intermediate_scale,
                                                 duplicate_featuremap)

        # prepare header file
        header = HeaderFile("test_stimuli.h")
        header.add(HeaderArray("x_vec", "int8_t", x_align.ravel()))
        header.add(HeaderArray("y_exp_vec", "int8_t", y_exp_align.ravel()))
        header.write()

        # compile and run
        os.system("make clean all run > {}".format(RESULT_FILE))

        # parse output
        result = parse_output(RESULT_FILE)

        # log the result
        options = []
        if no_intermediate_scale:
            options.append("no scale")
        if duplicate_featuremap:
            options.append("dup inp")

        subcase_name = "Fused Layer 1+2 "
        if options:
            subcase_name += "; ".join(options)

        logger.show_subcase_result(subcase_name, result)

    # return summary
    return logger.summary()
示例#6
0
def test():
    """
    Execute the tests
    Returns: (n_total, n_success)
    """

    logger = TestLogger(TESTNAME)

    for intrinsic, simd, flip_layers, parallel, stream, xcorr, fuse, no_div, reorder, dup_inp in [
            (False, False, False, False, False, False, False, False, False, False),
            (True, False, False, False, False, False, False, False, False, False),
            (True, True, False, False, False, False, False, False, False, False),
            (True, True, True, False, False, False, False, False, False, False),
            (True, True, True, True, False, False, False, False, False, False),
            (True, True, True, True, True, False, False, False, False, False),
            (True, True, True, True, True, True, False, False, False, False),
            (True, True, True, True, True, True, True, False, False, False),
            (True, True, True, True, True, True, True, True, False, False),
            (True, True, True, True, True, True, True, True, True, False),
            (True, True, True, True, True, True, True, True, True, True)
    ]:

        # generate makefile
        mkf = Makefile()
        mkf.add_fc_test_source("test.c")
        mkf.add_cl_test_source("cluster.c")
        mkf.add_cl_prog_source("net/model.c")
        mkf.add_cl_prog_source("net/layer1.c")
        mkf.add_cl_prog_source("net/layer2.c")
        mkf.add_cl_prog_source("net/layer3.c")
        mkf.add_cl_prog_source("net/layer4.c")
        mkf.add_cl_prog_source("net/layer5.c")
        mkf.add_cl_prog_source("net/fused_layer_1_2.c")
        mkf.add_cl_prog_source("net/net.c")
        mkf.add_cl_prog_source("func/transform.c")
        mkf.add_cl_prog_source("func/dotp.c")
        mkf.add_cl_prog_source("func/conv.c")
        mkf.add_cl_prog_source("func/flip.c")
        mkf.add_cl_prog_source("func/xcorr.c")

        if not simd:
            mkf.add_define("NO_SIMD")
        if flip_layers:
            mkf.add_define("FLIP_LAYERS")
        if parallel:
            mkf.add_define("PARALLEL")
        if intrinsic:
            mkf.add_define("INTRINSIC_SCALE")
        if stream:
            mkf.add_define("DMA_STREAM")
        if xcorr:
            mkf.add_define("CROSS_CORRELATE")
        if fuse:
            mkf.add_define("FUSE_LAYERS")
        if no_div:
            mkf.add_define("NO_INTERMEDIATE_SCALE")
        if dup_inp:
            mkf.add_define("DUPLICATE_FEATUREMAP")
        if reorder:
            mkf.add_define("REORDER_BN")

        mkf.write()

        # generate the stimuli
        _, x_align, _, y_exp_align = gen_stimuli(no_div=no_div, pad_data=dup_inp, reorder_bn=reorder)

        # prepare header file
        header = HeaderFile("test_stimuli.h")
        header.add(HeaderArray("x_vec", "int8_t", x_align.ravel()))
        header.add(HeaderArray("y_exp_vec", "int8_t", y_exp_align.ravel()))
        header.write()

        # compile and run
        os.system("make clean all run > {}".format(RESULT_FILE))

        # parse output
        result = parse_output(RESULT_FILE)

        # skip the naive result
        if not flip_layers:
            result["1"]["result"] = None

        # prepare the case name
        subcase_name = "naive"
        if intrinsic:
            subcase_name = "+ intrinsic scale"
        if simd:
            subcase_name = "+ SIMD"
        if flip_layers:
            subcase_name = "+ flip"
        if parallel:
            subcase_name = "+ parallel"
        if stream:
            subcase_name = "+ double buffering"
        if xcorr:
            subcase_name = "+ cross correlations"
        if fuse:
            subcase_name = "+ fused layer 1+2"
        if no_div:
            subcase_name = "+ no division after layer 1"
        if reorder:
            subcase_name = "+ reorder BN"
        if dup_inp:
            subcase_name = "+ duplicate featuremap"

        # log the result
        logger.show_subcase_result(subcase_name, result)

    # return summary
    return logger.summary()
示例#7
0
def test():
    """
    Execute the tests
    Returns: (n_total, n_success)
    """

    logger = TestLogger(TESTNAME, show_title=False)

    for simd in [False, True]:
        for flip_layers in [False, True]:
            for parallel in [False, True]:
                for dma_stream in [False, True]:
                    for reorder in [False, True]:

                        if not simd and (flip_layers or parallel or dma_stream or reorder):
                            continue

                        if not flip_layers and (parallel or dma_stream):
                            # not implemented
                            continue

                        if not parallel and dma_stream:
                            # not implemented
                            continue

                        # generate makefile
                        mkf = Makefile()
                        mkf.add_fc_test_source("test.c")
                        mkf.add_cl_test_source("cluster.c")
                        mkf.add_cl_prog_source("net/layer2.c")
                        mkf.add_cl_prog_source("net/net.c")
                        mkf.add_cl_prog_source("func/transform.c")
                        mkf.add_cl_prog_source("func/dotp.c")

                        if not simd:
                            mkf.add_define("NO_SIMD")

                        if flip_layers:
                            mkf.add_define("FLIP_LAYERS")

                        if parallel:
                            mkf.add_define("PARALLEL")

                        if dma_stream:
                            mkf.add_define("DMA_STREAM")

                        if reorder:
                            mkf.add_define("REORDER_BN")

                        mkf.write()

                        random_input = False

                        # generate the stimuli
                        _, x_align, _, y_exp_align = gen_stimuli(random_input, flip_layers, reorder)

                        # prepare header file
                        header = HeaderFile("test_stimuli.h")
                        header.add(HeaderArray("x_vec", "int8_t", x_align.ravel()))
                        header.add(HeaderArray("y_exp_vec", "int8_t", y_exp_align.ravel()))
                        header.write()

                        # compile and run
                        os.system("make clean all run > {}".format(RESULT_FILE))

                        # parse output
                        result = parse_output(RESULT_FILE)

                        # log the result
                        subcase_name = "Layer 2 "

                        options = []
                        if simd:
                            options.append("simd")
                        if flip_layers:
                            options.append("flip")
                        if parallel:
                            options.append("par")
                        if dma_stream:
                            options.append("stream")
                        if reorder:
                            options.append("reorder")

                        if options:
                            subcase_name += "; ".join(options)
                        else:
                            subcase_name += "naive"

                        logger.show_subcase_result(subcase_name, result)

    # return summary
    return logger.summary()
示例#8
0
def test():
    """
    Execute the tests
    Returns: (n_total, n_success)
    """

    logger = TestLogger(TESTNAME)

    for intrinsic_conv_scale in [False, True]:
        for simd in [False, True]:
            for parallel in [False, True]:
                for cross_correlate in [False, True]:

                    if not simd and (parallel or cross_correlate):
                        continue

                    # parallel requires intrinsic conv scale
                    if parallel and not intrinsic_conv_scale:
                        continue

                    # not implemented
                    if cross_correlate and not parallel:
                        continue

                    # generate makefile
                    mkf = Makefile()
                    mkf.add_fc_test_source("test.c")
                    mkf.add_cl_test_source("cluster.c")
                    mkf.add_cl_prog_source("net/layer1.c")
                    mkf.add_cl_prog_source("net/net.c")
                    mkf.add_cl_prog_source("func/conv.c")
                    mkf.add_cl_prog_source("func/xcorr.c")
                    mkf.add_cl_prog_source("func/transform.c")

                    if parallel:
                        mkf.add_define("PARALLEL")
                    if intrinsic_conv_scale:
                        mkf.add_define("INTRINSIC_SCALE")
                    if cross_correlate:
                        mkf.add_define("CROSS_CORRELATE")
                    if not simd:
                        mkf.add_define("NO_SIMD")

                    mkf.write()

                    random_input = False

                    # generate the stimuli
                    x, y_exp = gen_stimuli(random_input)
                    x_align = align_array(x)
                    y_exp_align = align_array(y_exp)

                    # prepare header file
                    header = HeaderFile("test_stimuli.h")
                    header.add(HeaderArray("x_vec", "int8_t", x_align.ravel()))
                    header.add(
                        HeaderArray("y_exp_vec", "int8_t",
                                    y_exp_align.ravel()))
                    header.write()

                    # compile and run
                    os.system("make clean all run > {}".format(RESULT_FILE))

                    # parse output
                    result = parse_output(RESULT_FILE)

                    # log the result
                    options = []
                    if simd:
                        options.append("simd")
                    if parallel:
                        options.append("par")
                    if intrinsic_conv_scale:
                        options.append("intr.s.")
                    if cross_correlate:
                        options.append("xcorr")

                    subcase_name = "Layer 1 "
                    if options:
                        subcase_name += "; ".join(options)
                    else:
                        subcase_name += "naive"

                    logger.show_subcase_result(subcase_name, result)

    # return summary
    return logger.summary()