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How to use fix method in pytest-asyncio

Best Python code snippet using pytest-asyncio_python

test_coco.py

Source:test_coco.py

1#!/usr/bin/env python323import numpy as np4import matplotlib.pyplot as plt5import time6import cocotb7from cocotb.clock import Clock8from cocotb.triggers import RisingEdge9import time10from fxpmath import Fxp11from rig.type_casts import fix_to_float1213pi_fxp = Fxp(None, signed=True, n_word=12, n_frac=8)    14pi_fxp.rounding = 'around'   151617def fix_pt(val):                          18    return int(pi_fxp(val).bin())192021def fix2float(val):22    f2f= fix_to_float(True,12, 10)23    return f2f(val)242526cnn_data = np.load('cnn_1train_weights_aftest.npz')27new_x = np.zeros((5,5))28layer2 = np.zeros((13,13,20))293031np.set_printoptions(precision=8)32np.set_printoptions(threshold=np.inf)3334correct_predictions = 035363738def print_max_err(i, d, id):39    if i == 0:40        exp = cnn_data[id][0]41        print(f'{np.max(np.abs(exp - d)):.3f}')424344def pwl_activation(acti):45    condition1 = np.less(acti, -2)46    condition2 = np.multiply(np.greater_equal(acti, -2), np.less(acti, -0.6875))47    condition3 = np.multiply(np.greater_equal(acti, -0.6875), np.less(acti, 0.6875))48    condition4 = np.multiply(np.greater_equal(acti, 0.6875), np.less(acti, 2))49    condition5 = np.greater_equal(acti, 2)5051    a = np.multiply(condition1, -1)52    b = np.multiply(condition2, np.multiply((acti - 2), 0.25))53    c = np.multiply(condition3, acti)54    d = np.multiply(condition4, np.multiply((acti + 2), 0.25))55    e = np.multiply(condition5, 1)5657    return a + b + c + d + e5859606162first_conv_max = 063second_conv_max = 064first_conv_avg = 065second_conv_avg = 06667first_layer_kernels = 2068second_layer_kernels = 6069third_layer_kernels = 6070fourth_layer_kernels = 12071# assume square kernels72first_layer_kernel_size = 473second_layer_kernel_size = 374third_layer_kernel_size = 375fourth_layer_kernel_size = 37677# assume 64bit fix point78bytesize = 87980# for each input in the test set81for i, img in enumerate(cnn_data['x_test']):8283    # layer0: conv2d84    weights = cnn_data['l0weights']85    iter=086    count = 08788    while(iter<25):89        ii=090        count2 = 091        while(ii<25):92            new_x = img[ii:ii+5,iter:iter+5]93            # loop = asyncio.new_event_loop()94            # asyncio.set_event_loop(loop)95            # layer2 = loop.run_until_complete(tstbench.test_cnn_hw(new_x,weights,layer2,iter,ii,count,count2))96            979899100            101            102            103            @cocotb.test()104            async def test_cnn_hw(dut, ii=ii, iter=iter, count=count, count2=count2):105                clock = Clock(dut.clk, 10, units="ns")  # Create a 10ns period clock on port clk106                cocotb.fork(clock.start())  # Start the clock107108                reset = 0109                110                print("iter before is",iter)111                print("ii before is",ii)112113114                await RisingEdge(dut.clk)115                dut.reset <= reset116                dut.i_activation_0_0 <= fix_pt(new_x[0, 0])117                dut.i_activation_0_1 <= fix_pt(new_x[0, 1])118                dut.i_activation_0_2 <= fix_pt(new_x[0, 2])119                dut.i_activation_0_3 <= fix_pt(new_x[0, 3])120                dut.i_activation_0_4 <= fix_pt(new_x[0, 4])121                dut.i_activation_1_0 <= fix_pt(new_x[1, 0])122                dut.i_activation_1_1 <= fix_pt(new_x[1, 1])123                dut.i_activation_1_2 <= fix_pt(new_x[1, 2])124                dut.i_activation_1_3 <= fix_pt(new_x[1, 3])125                dut.i_activation_1_4 <= fix_pt(new_x[1, 4])126                dut.i_activation_2_0 <= fix_pt(new_x[2, 0])127                dut.i_activation_2_1 <= fix_pt(new_x[2, 1])128                dut.i_activation_2_2 <= fix_pt(new_x[2, 2])129                dut.i_activation_2_3 <= fix_pt(new_x[2, 3])130                dut.i_activation_2_4 <= fix_pt(new_x[2, 4])131                dut.i_activation_3_0 <= fix_pt(new_x[3, 0])132                dut.i_activation_3_1 <= fix_pt(new_x[3, 1])133                dut.i_activation_3_2 <= fix_pt(new_x[3, 2])134                dut.i_activation_3_3 <= fix_pt(new_x[3, 3])135                dut.i_activation_3_4 <= fix_pt(new_x[3, 4])136                dut.i_activation_4_0 <= fix_pt(new_x[4, 0])137                dut.i_activation_4_1 <= fix_pt(new_x[4, 1])138                dut.i_activation_4_2 <= fix_pt(new_x[4, 2])139                dut.i_activation_4_3 <= fix_pt(new_x[4, 3])140                dut.i_activation_4_4 <= fix_pt(new_x[4, 4])141142                dut.i_weight_0_0_0 <= fix_pt(weights[0, 0, 0])143                dut.i_weight_0_0_1 <= fix_pt(weights[0, 1, 0])144                dut.i_weight_0_0_2 <= fix_pt(weights[0, 2, 0])145                dut.i_weight_0_0_3 <= fix_pt(weights[0, 3, 0])146                dut.i_weight_0_1_0 <= fix_pt(weights[1, 0, 0])147                dut.i_weight_0_1_1 <= fix_pt(weights[1, 1, 0])148                dut.i_weight_0_1_2 <= fix_pt(weights[1, 2, 0])149                dut.i_weight_0_1_3 <= fix_pt(weights[1, 3, 0])150                dut.i_weight_0_2_0 <= fix_pt(weights[2, 0, 0])151                dut.i_weight_0_2_1 <= fix_pt(weights[2, 1, 0])152                dut.i_weight_0_2_2 <= fix_pt(weights[2, 2, 0])153                dut.i_weight_0_2_3 <= fix_pt(weights[2, 3, 0])154                dut.i_weight_0_3_0 <= fix_pt(weights[3, 0, 0])155                dut.i_weight_0_3_1 <= fix_pt(weights[3, 1, 0])156                dut.i_weight_0_3_2 <= fix_pt(weights[3, 2, 0])157                dut.i_weight_0_3_3 <= fix_pt(weights[3, 3, 0])158159                dut.i_weight_1_0_0 <= fix_pt(weights[0, 0, 1])160                dut.i_weight_1_0_1 <= fix_pt(weights[0, 1, 1])161                dut.i_weight_1_0_2 <= fix_pt(weights[0, 2, 1])162                dut.i_weight_1_0_3 <= fix_pt(weights[0, 3, 1])163                dut.i_weight_1_1_0 <= fix_pt(weights[1, 0, 1])164                dut.i_weight_1_1_1 <= fix_pt(weights[1, 1, 1])165                dut.i_weight_1_1_2 <= fix_pt(weights[1, 2, 1])166                dut.i_weight_1_1_3 <= fix_pt(weights[1, 3, 1])167                dut.i_weight_1_2_0 <= fix_pt(weights[2, 0, 1])168                dut.i_weight_1_2_1 <= fix_pt(weights[2, 1, 1])169                dut.i_weight_1_2_2 <= fix_pt(weights[2, 2, 1])170                dut.i_weight_1_2_3 <= fix_pt(weights[2, 3, 1])171                dut.i_weight_1_3_0 <= fix_pt(weights[3, 0, 1])172                dut.i_weight_1_3_1 <= fix_pt(weights[3, 1, 1])173                dut.i_weight_1_3_2 <= fix_pt(weights[3, 2, 1])174                dut.i_weight_1_3_3 <= fix_pt(weights[3, 3, 1])175176                dut.i_weight_2_0_0 <= fix_pt(weights[0, 0, 2])177                dut.i_weight_2_0_1 <= fix_pt(weights[0, 1, 2])178                dut.i_weight_2_0_2 <= fix_pt(weights[0, 2, 2])179                dut.i_weight_2_0_3 <= fix_pt(weights[0, 3, 2])180                dut.i_weight_2_1_0 <= fix_pt(weights[1, 0, 2])181                dut.i_weight_2_1_1 <= fix_pt(weights[1, 1, 2])182                dut.i_weight_2_1_2 <= fix_pt(weights[1, 2, 2])183                dut.i_weight_2_1_3 <= fix_pt(weights[1, 3, 2])184                dut.i_weight_2_2_0 <= fix_pt(weights[2, 0, 2])185                dut.i_weight_2_2_1 <= fix_pt(weights[2, 1, 2])186                dut.i_weight_2_2_2 <= fix_pt(weights[2, 2, 2])187                dut.i_weight_2_2_3 <= fix_pt(weights[2, 3, 2])188                dut.i_weight_2_3_0 <= fix_pt(weights[3, 0, 2])189                dut.i_weight_2_3_1 <= fix_pt(weights[3, 1, 2])190                dut.i_weight_2_3_2 <= fix_pt(weights[3, 2, 2])191                dut.i_weight_2_3_3 <= fix_pt(weights[3, 3, 2])192193                dut.i_weight_3_0_0 <= fix_pt(weights[0, 0, 3])194                dut.i_weight_3_0_1 <= fix_pt(weights[0, 1, 3])195                dut.i_weight_3_0_2 <= fix_pt(weights[0, 2, 3])196                dut.i_weight_3_0_3 <= fix_pt(weights[0, 3, 3])197                dut.i_weight_3_1_0 <= fix_pt(weights[1, 0, 3])198                dut.i_weight_3_1_1 <= fix_pt(weights[1, 1, 3])199                dut.i_weight_3_1_2 <= fix_pt(weights[1, 2, 3])200                dut.i_weight_3_1_3 <= fix_pt(weights[1, 3, 3])201                dut.i_weight_3_2_0 <= fix_pt(weights[2, 0, 3])202                dut.i_weight_3_2_1 <= fix_pt(weights[2, 1, 3])203                dut.i_weight_3_2_2 <= fix_pt(weights[2, 2, 3])204                dut.i_weight_3_2_3 <= fix_pt(weights[2, 3, 3])205                dut.i_weight_3_3_0 <= fix_pt(weights[3, 0, 3])206                dut.i_weight_3_3_1 <= fix_pt(weights[3, 1, 3])207                dut.i_weight_3_3_2 <= fix_pt(weights[3, 2, 3])208                dut.i_weight_3_3_3 <= fix_pt(weights[3, 3, 3])209210                dut.i_weight_4_0_0 <= fix_pt(weights[0, 0, 4])211                dut.i_weight_4_0_1 <= fix_pt(weights[0, 1, 4])212                dut.i_weight_4_0_2 <= fix_pt(weights[0, 2, 4])213                dut.i_weight_4_0_3 <= fix_pt(weights[0, 3, 4])214                dut.i_weight_4_1_0 <= fix_pt(weights[1, 0, 4])215                dut.i_weight_4_1_1 <= fix_pt(weights[1, 1, 4])216                dut.i_weight_4_1_2 <= fix_pt(weights[1, 2, 4])217                dut.i_weight_4_1_3 <= fix_pt(weights[1, 3, 4])218                dut.i_weight_4_2_0 <= fix_pt(weights[2, 0, 4])219                dut.i_weight_4_2_1 <= fix_pt(weights[2, 1, 4])220                dut.i_weight_4_2_2 <= fix_pt(weights[2, 2, 4])221                dut.i_weight_4_2_3 <= fix_pt(weights[2, 3, 4])222                dut.i_weight_4_3_0 <= fix_pt(weights[3, 0, 4])223                dut.i_weight_4_3_1 <= fix_pt(weights[3, 1, 4])224                dut.i_weight_4_3_2 <= fix_pt(weights[3, 2, 4])225                dut.i_weight_4_3_3 <= fix_pt(weights[3, 3, 4])226227                dut.i_weight_5_0_0 <= fix_pt(weights[0, 0, 5])228                dut.i_weight_5_0_1 <= fix_pt(weights[0, 1, 5])229                dut.i_weight_5_0_2 <= fix_pt(weights[0, 2, 5])230                dut.i_weight_5_0_3 <= fix_pt(weights[0, 3, 5])231                dut.i_weight_5_1_0 <= fix_pt(weights[1, 0, 5])232                dut.i_weight_5_1_1 <= fix_pt(weights[1, 1, 5])233                dut.i_weight_5_1_2 <= fix_pt(weights[1, 2, 5])234                dut.i_weight_5_1_3 <= fix_pt(weights[1, 3, 5])235                dut.i_weight_5_2_0 <= fix_pt(weights[2, 0, 5])236                dut.i_weight_5_2_1 <= fix_pt(weights[2, 1, 5])237                dut.i_weight_5_2_2 <= fix_pt(weights[2, 2, 5])238                dut.i_weight_5_2_3 <= fix_pt(weights[2, 3, 5])239                dut.i_weight_5_3_0 <= fix_pt(weights[3, 0, 5])240                dut.i_weight_5_3_1 <= fix_pt(weights[3, 1, 5])241                dut.i_weight_5_3_2 <= fix_pt(weights[3, 2, 5])242                dut.i_weight_5_3_3 <= fix_pt(weights[3, 3, 5])243244                dut.i_weight_6_0_0 <= fix_pt(weights[0, 0, 6])245                dut.i_weight_6_0_1 <= fix_pt(weights[0, 1, 6])246                dut.i_weight_6_0_2 <= fix_pt(weights[0, 2, 6])247                dut.i_weight_6_0_3 <= fix_pt(weights[0, 3, 6])248                dut.i_weight_6_1_0 <= fix_pt(weights[1, 0, 6])249                dut.i_weight_6_1_1 <= fix_pt(weights[1, 1, 6])250                dut.i_weight_6_1_2 <= fix_pt(weights[1, 2, 6])251                dut.i_weight_6_1_3 <= fix_pt(weights[1, 3, 6])252                dut.i_weight_6_2_0 <= fix_pt(weights[2, 0, 6])253                dut.i_weight_6_2_1 <= fix_pt(weights[2, 1, 6])254                dut.i_weight_6_2_2 <= fix_pt(weights[2, 2, 6])255                dut.i_weight_6_2_3 <= fix_pt(weights[2, 3, 6])256                dut.i_weight_6_3_0 <= fix_pt(weights[3, 0, 6])257                dut.i_weight_6_3_1 <= fix_pt(weights[3, 1, 6])258                dut.i_weight_6_3_2 <= fix_pt(weights[3, 2, 6])259                dut.i_weight_6_3_3 <= fix_pt(weights[3, 3, 6])260261                dut.i_weight_7_0_0 <= fix_pt(weights[0, 0, 7])262                dut.i_weight_7_0_1 <= fix_pt(weights[0, 1, 7])263                dut.i_weight_7_0_2 <= fix_pt(weights[0, 2, 7])264                dut.i_weight_7_0_3 <= fix_pt(weights[0, 3, 7])265                dut.i_weight_7_1_0 <= fix_pt(weights[1, 0, 7])266                dut.i_weight_7_1_1 <= fix_pt(weights[1, 1, 7])267                dut.i_weight_7_1_2 <= fix_pt(weights[1, 2, 7])268                dut.i_weight_7_1_3 <= fix_pt(weights[1, 3, 7])269                dut.i_weight_7_2_0 <= fix_pt(weights[2, 0, 7])270                dut.i_weight_7_2_1 <= fix_pt(weights[2, 1, 7])271                dut.i_weight_7_2_2 <= fix_pt(weights[2, 2, 7])272                dut.i_weight_7_2_3 <= fix_pt(weights[2, 3, 7])273                dut.i_weight_7_3_0 <= fix_pt(weights[3, 0, 7])274                dut.i_weight_7_3_1 <= fix_pt(weights[3, 1, 7])275                dut.i_weight_7_3_2 <= fix_pt(weights[3, 2, 7])276                dut.i_weight_7_3_3 <= fix_pt(weights[3, 3, 7])277278                dut.i_weight_8_0_0 <= fix_pt(weights[0, 0, 8])279                dut.i_weight_8_0_1 <= fix_pt(weights[0, 1, 8])280                dut.i_weight_8_0_2 <= fix_pt(weights[0, 2, 8])281                dut.i_weight_8_0_3 <= fix_pt(weights[0, 3, 8])282                dut.i_weight_8_1_0 <= fix_pt(weights[1, 0, 8])283                dut.i_weight_8_1_1 <= fix_pt(weights[1, 1, 8])284                dut.i_weight_8_1_2 <= fix_pt(weights[1, 2, 8])285                dut.i_weight_8_1_3 <= fix_pt(weights[1, 3, 8])286                dut.i_weight_8_2_0 <= fix_pt(weights[2, 0, 8])287                dut.i_weight_8_2_1 <= fix_pt(weights[2, 1, 8])288                dut.i_weight_8_2_2 <= fix_pt(weights[2, 2, 8])289                dut.i_weight_8_2_3 <= fix_pt(weights[2, 3, 8])290                dut.i_weight_8_3_0 <= fix_pt(weights[3, 0, 8])291                dut.i_weight_8_3_1 <= fix_pt(weights[3, 1, 8])292                dut.i_weight_8_3_2 <= fix_pt(weights[3, 2, 8])293                dut.i_weight_8_3_3 <= fix_pt(weights[3, 3, 8])294295                dut.i_weight_9_0_0 <= fix_pt(weights[0, 0, 9])296                dut.i_weight_9_0_1 <= fix_pt(weights[0, 1, 9])297                dut.i_weight_9_0_2 <= fix_pt(weights[0, 2, 9])298                dut.i_weight_9_0_3 <= fix_pt(weights[0, 3, 9])299                dut.i_weight_9_1_0 <= fix_pt(weights[1, 0, 9])300                dut.i_weight_9_1_1 <= fix_pt(weights[1, 1, 9])301                dut.i_weight_9_1_2 <= fix_pt(weights[1, 2, 9])302                dut.i_weight_9_1_3 <= fix_pt(weights[1, 3, 9])303                dut.i_weight_9_2_0 <= fix_pt(weights[2, 0, 9])304                dut.i_weight_9_2_1 <= fix_pt(weights[2, 1, 9])305                dut.i_weight_9_2_2 <= fix_pt(weights[2, 2, 9])306                dut.i_weight_9_2_3 <= fix_pt(weights[2, 3, 9])307                dut.i_weight_9_3_0 <= fix_pt(weights[3, 0, 9])308                dut.i_weight_9_3_1 <= fix_pt(weights[3, 1, 9])309                dut.i_weight_9_3_2 <= fix_pt(weights[3, 2, 9])310                dut.i_weight_9_3_3 <= fix_pt(weights[3, 3, 9])311312                dut.i_weight_10_0_0 <= fix_pt(weights[0, 0, 10])313                dut.i_weight_10_0_1 <= fix_pt(weights[0, 1, 10])314                dut.i_weight_10_0_2 <= fix_pt(weights[0, 2, 10])315                dut.i_weight_10_0_3 <= fix_pt(weights[0, 3, 10])316                dut.i_weight_10_1_0 <= fix_pt(weights[1, 0, 10])317                dut.i_weight_10_1_1 <= fix_pt(weights[1, 1, 10])318                dut.i_weight_10_1_2 <= fix_pt(weights[1, 2, 10])319                dut.i_weight_10_1_3 <= fix_pt(weights[1, 3, 10])320                dut.i_weight_10_2_0 <= fix_pt(weights[2, 0, 10])321                dut.i_weight_10_2_1 <= fix_pt(weights[2, 1, 10])322                dut.i_weight_10_2_2 <= fix_pt(weights[2, 2, 10])323                dut.i_weight_10_2_3 <= fix_pt(weights[2, 3, 10])324                dut.i_weight_10_3_0 <= fix_pt(weights[3, 0, 10])325                dut.i_weight_10_3_1 <= fix_pt(weights[3, 1, 10])326                dut.i_weight_10_3_2 <= fix_pt(weights[3, 2, 10])327                dut.i_weight_10_3_3 <= fix_pt(weights[3, 3, 10])328329                dut.i_weight_11_0_0 <= fix_pt(weights[0, 0, 11])330                dut.i_weight_11_0_1 <= fix_pt(weights[0, 1, 11])331                dut.i_weight_11_0_2 <= fix_pt(weights[0, 2, 11])332                dut.i_weight_11_0_3 <= fix_pt(weights[0, 3, 11])333                dut.i_weight_11_1_0 <= fix_pt(weights[1, 0, 11])334                dut.i_weight_11_1_1 <= fix_pt(weights[1, 1, 11])335                dut.i_weight_11_1_2 <= fix_pt(weights[1, 2, 11])336                dut.i_weight_11_1_3 <= fix_pt(weights[1, 3, 11])337                dut.i_weight_11_2_0 <= fix_pt(weights[2, 0, 11])338                dut.i_weight_11_2_1 <= fix_pt(weights[2, 1, 11])339                dut.i_weight_11_2_2 <= fix_pt(weights[2, 2, 11])340                dut.i_weight_11_2_3 <= fix_pt(weights[2, 3, 11])341                dut.i_weight_11_3_0 <= fix_pt(weights[3, 0, 11])342                dut.i_weight_11_3_1 <= fix_pt(weights[3, 1, 11])343                dut.i_weight_11_3_2 <= fix_pt(weights[3, 2, 11])344                dut.i_weight_11_3_3 <= fix_pt(weights[3, 3, 11])345346                dut.i_weight_12_0_0 <= fix_pt(weights[0, 0, 12])347                dut.i_weight_12_0_1 <= fix_pt(weights[0, 1, 12])348                dut.i_weight_12_0_2 <= fix_pt(weights[0, 2, 12])349                dut.i_weight_12_0_3 <= fix_pt(weights[0, 3, 12])350                dut.i_weight_12_1_0 <= fix_pt(weights[1, 0, 12])351                dut.i_weight_12_1_1 <= fix_pt(weights[1, 1, 12])352                dut.i_weight_12_1_2 <= fix_pt(weights[1, 2, 12])353                dut.i_weight_12_1_3 <= fix_pt(weights[1, 3, 12])354                dut.i_weight_12_2_0 <= fix_pt(weights[2, 0, 12])355                dut.i_weight_12_2_1 <= fix_pt(weights[2, 1, 12])356                dut.i_weight_12_2_2 <= fix_pt(weights[2, 2, 12])357                dut.i_weight_12_2_3 <= fix_pt(weights[2, 3, 12])358                dut.i_weight_12_3_0 <= fix_pt(weights[3, 0, 12])359                dut.i_weight_12_3_1 <= fix_pt(weights[3, 1, 12])360                dut.i_weight_12_3_2 <= fix_pt(weights[3, 2, 12])361                dut.i_weight_12_3_3 <= fix_pt(weights[3, 3, 12])362363                dut.i_weight_13_0_0 <= fix_pt(weights[0, 0, 13])364                dut.i_weight_13_0_1 <= fix_pt(weights[0, 1, 13])365                dut.i_weight_13_0_2 <= fix_pt(weights[0, 2, 13])366                dut.i_weight_13_0_3 <= fix_pt(weights[0, 3, 13])367                dut.i_weight_13_1_0 <= fix_pt(weights[1, 0, 13])368                dut.i_weight_13_1_1 <= fix_pt(weights[1, 1, 13])369                dut.i_weight_13_1_2 <= fix_pt(weights[1, 2, 13])370                dut.i_weight_13_1_3 <= fix_pt(weights[1, 3, 13])371                dut.i_weight_13_2_0 <= fix_pt(weights[2, 0, 13])372                dut.i_weight_13_2_1 <= fix_pt(weights[2, 1, 13])373                dut.i_weight_13_2_2 <= fix_pt(weights[2, 2, 13])374                dut.i_weight_13_2_3 <= fix_pt(weights[2, 3, 13])375                dut.i_weight_13_3_0 <= fix_pt(weights[3, 0, 13])376                dut.i_weight_13_3_1 <= fix_pt(weights[3, 1, 13])377                dut.i_weight_13_3_2 <= fix_pt(weights[3, 2, 13])378                dut.i_weight_13_3_3 <= fix_pt(weights[3, 3, 13])379380                dut.i_weight_14_0_0 <= fix_pt(weights[0, 0, 14])381                dut.i_weight_14_0_1 <= fix_pt(weights[0, 1, 14])382                dut.i_weight_14_0_2 <= fix_pt(weights[0, 2, 14])383                dut.i_weight_14_0_3 <= fix_pt(weights[0, 3, 14])384                dut.i_weight_14_1_0 <= fix_pt(weights[1, 0, 14])385                dut.i_weight_14_1_1 <= fix_pt(weights[1, 1, 14])386                dut.i_weight_14_1_2 <= fix_pt(weights[1, 2, 14])387                dut.i_weight_14_1_3 <= fix_pt(weights[1, 3, 14])388                dut.i_weight_14_2_0 <= fix_pt(weights[2, 0, 14])389                dut.i_weight_14_2_1 <= fix_pt(weights[2, 1, 14])390                dut.i_weight_14_2_2 <= fix_pt(weights[2, 2, 14])391                dut.i_weight_14_2_3 <= fix_pt(weights[2, 3, 14])392                dut.i_weight_14_3_0 <= fix_pt(weights[3, 0, 14])393                dut.i_weight_14_3_1 <= fix_pt(weights[3, 1, 14])394                dut.i_weight_14_3_2 <= fix_pt(weights[3, 2, 14])395                dut.i_weight_14_3_3 <= fix_pt(weights[3, 3, 14])396397                dut.i_weight_15_0_0 <= fix_pt(weights[0, 0, 15])398                dut.i_weight_15_0_1 <= fix_pt(weights[0, 1, 15])399                dut.i_weight_15_0_2 <= fix_pt(weights[0, 2, 15])400                dut.i_weight_15_0_3 <= fix_pt(weights[0, 3, 15])401                dut.i_weight_15_1_0 <= fix_pt(weights[1, 0, 15])402                dut.i_weight_15_1_1 <= fix_pt(weights[1, 1, 15])403                dut.i_weight_15_1_2 <= fix_pt(weights[1, 2, 15])404                dut.i_weight_15_1_3 <= fix_pt(weights[1, 3, 15])405                dut.i_weight_15_2_0 <= fix_pt(weights[2, 0, 15])406                dut.i_weight_15_2_1 <= fix_pt(weights[2, 1, 15])407                dut.i_weight_15_2_2 <= fix_pt(weights[2, 2, 15])408                dut.i_weight_15_2_3 <= fix_pt(weights[2, 3, 15])409                dut.i_weight_15_3_0 <= fix_pt(weights[3, 0, 15])410                dut.i_weight_15_3_1 <= fix_pt(weights[3, 1, 15])411                dut.i_weight_15_3_2 <= fix_pt(weights[3, 2, 15])412                dut.i_weight_15_3_3 <= fix_pt(weights[3, 3, 15])413414                dut.i_weight_16_0_0 <= fix_pt(weights[0, 0, 16])415                dut.i_weight_16_0_1 <= fix_pt(weights[0, 1, 16])416                dut.i_weight_16_0_2 <= fix_pt(weights[0, 2, 16])417                dut.i_weight_16_0_3 <= fix_pt(weights[0, 3, 16])418                dut.i_weight_16_1_0 <= fix_pt(weights[1, 0, 16])419                dut.i_weight_16_1_1 <= fix_pt(weights[1, 1, 16])420                dut.i_weight_16_1_2 <= fix_pt(weights[1, 2, 16])421                dut.i_weight_16_1_3 <= fix_pt(weights[1, 3, 16])422                dut.i_weight_16_2_0 <= fix_pt(weights[2, 0, 16])423                dut.i_weight_16_2_1 <= fix_pt(weights[2, 1, 16])424                dut.i_weight_16_2_2 <= fix_pt(weights[2, 2, 16])425                dut.i_weight_16_2_3 <= fix_pt(weights[2, 3, 16])426                dut.i_weight_16_3_0 <= fix_pt(weights[3, 0, 16])427                dut.i_weight_16_3_1 <= fix_pt(weights[3, 1, 16])428                dut.i_weight_16_3_2 <= fix_pt(weights[3, 2, 16])429                dut.i_weight_16_3_3 <= fix_pt(weights[3, 3, 16])430431                dut.i_weight_17_0_0 <= fix_pt(weights[0, 0, 17])432                dut.i_weight_17_0_1 <= fix_pt(weights[0, 1, 17])433                dut.i_weight_17_0_2 <= fix_pt(weights[0, 2, 17])434                dut.i_weight_17_0_3 <= fix_pt(weights[0, 3, 17])435                dut.i_weight_17_1_0 <= fix_pt(weights[1, 0, 17])436                dut.i_weight_17_1_1 <= fix_pt(weights[1, 1, 17])437                dut.i_weight_17_1_2 <= fix_pt(weights[1, 2, 17])438                dut.i_weight_17_1_3 <= fix_pt(weights[1, 3, 17])439                dut.i_weight_17_2_0 <= fix_pt(weights[2, 0, 17])440                dut.i_weight_17_2_1 <= fix_pt(weights[2, 1, 17])441                dut.i_weight_17_2_2 <= fix_pt(weights[2, 2, 17])442                dut.i_weight_17_2_3 <= fix_pt(weights[2, 3, 17])443                dut.i_weight_17_3_0 <= fix_pt(weights[3, 0, 17])444                dut.i_weight_17_3_1 <= fix_pt(weights[3, 1, 17])445                dut.i_weight_17_3_2 <= fix_pt(weights[3, 2, 17])446                dut.i_weight_17_3_3 <= fix_pt(weights[3, 3, 17])447448                dut.i_weight_18_0_0 <= fix_pt(weights[0, 0, 18])449                dut.i_weight_18_0_1 <= fix_pt(weights[0, 1, 18])450                dut.i_weight_18_0_2 <= fix_pt(weights[0, 2, 18])451                dut.i_weight_18_0_3 <= fix_pt(weights[0, 3, 18])452                dut.i_weight_18_1_0 <= fix_pt(weights[1, 0, 18])453                dut.i_weight_18_1_1 <= fix_pt(weights[1, 1, 18])454                dut.i_weight_18_1_2 <= fix_pt(weights[1, 2, 18])455                dut.i_weight_18_1_3 <= fix_pt(weights[1, 3, 18])456                dut.i_weight_18_2_0 <= fix_pt(weights[2, 0, 18])457                dut.i_weight_18_2_1 <= fix_pt(weights[2, 1, 18])458                dut.i_weight_18_2_2 <= fix_pt(weights[2, 2, 18])459                dut.i_weight_18_2_3 <= fix_pt(weights[2, 3, 18])460                dut.i_weight_18_3_0 <= fix_pt(weights[3, 0, 18])461                dut.i_weight_18_3_1 <= fix_pt(weights[3, 1, 18])462                dut.i_weight_18_3_2 <= fix_pt(weights[3, 2, 18])463                dut.i_weight_18_3_3 <= fix_pt(weights[3, 3, 18])464465                dut.i_weight_19_0_0 <= fix_pt(weights[0, 0, 19])466                dut.i_weight_19_0_1 <= fix_pt(weights[0, 1, 19])467                dut.i_weight_19_0_2 <= fix_pt(weights[0, 2, 19])468                dut.i_weight_19_0_3 <= fix_pt(weights[0, 3, 19])469                dut.i_weight_19_1_0 <= fix_pt(weights[1, 0, 19])470                dut.i_weight_19_1_1 <= fix_pt(weights[1, 1, 19])471                dut.i_weight_19_1_2 <= fix_pt(weights[1, 2, 19])472                dut.i_weight_19_1_3 <= fix_pt(weights[1, 3, 19])473                dut.i_weight_19_2_0 <= fix_pt(weights[2, 0, 19])474                dut.i_weight_19_2_1 <= fix_pt(weights[2, 1, 19])475                dut.i_weight_19_2_2 <= fix_pt(weights[2, 2, 19])476                dut.i_weight_19_2_3 <= fix_pt(weights[2, 3, 19])477                dut.i_weight_19_3_0 <= fix_pt(weights[3, 0, 19])478                dut.i_weight_19_3_1 <= fix_pt(weights[3, 1, 19])479                dut.i_weight_19_3_2 <= fix_pt(weights[3, 2, 19])480                dut.i_weight_19_3_3 <= fix_pt(weights[3, 3, 19])481482                time.sleep(10)483                484                485                #print("count is:",count)486                #print("count2 is:",count2)487                print("iter",iter)488                print("ii",ii)489490                layer2[count, count2, 0] = fix2float(dut.o_output_0)491                layer2[count, count2, 1] = fix2float(dut.o_output_1)492                layer2[count, count2, 2] = fix2float(dut.o_output_2)493                layer2[count, count2, 3] = fix2float(dut.o_output_3)494                layer2[count, count2, 4] = fix2float(dut.o_output_4)495                layer2[count, count2, 5] = fix2float(dut.o_output_5)496                layer2[count, count2, 6] = fix2float(dut.o_output_6)497                layer2[count, count2, 7] = fix2float(dut.o_output_7)498                layer2[count, count2, 8]  = fix2float(dut.o_output_8)499                layer2[count, count2, 9] = fix2float(dut.o_output_9)500                layer2[count, count2, 10] = fix2float(dut.o_output_10)501                layer2[count, count2, 11] = fix2float(dut.o_output_11)502                layer2[count, count2, 12] = fix2float(dut.o_output_12)503                layer2[count, count2, 13] = fix2float(dut.o_output_13)504                layer2[count, count2, 14] = fix2float(dut.o_output_14)505                layer2[count, count2, 15] = fix2float(dut.o_output_15)506                layer2[count, count2, 16] = fix2float(dut.o_output_16)507                layer2[count, count2, 17] = fix2float(dut.o_output_17)508                layer2[count, count2, 18] = fix2float(dut.o_output_18)509                layer2[count, count2, 19] = fix2float(dut.o_output_19)510                511                512513514            515            ii = ii + 2516            count2 = count2+1517        iter = iter + 2518        519        count=count+1520521522    # if i == 0:523        # print('saving data')524        # np.save('exact_fm.npy', layer2)525526    # # layer3: conv2d527    # weights = cnn_data['l3weights']528    # shape = (first_layer_kernels, second_layer_kernel_size, second_layer_kernel_size, layer2.shape[0] - second_layer_kernel_size + 1,529             # layer2.shape[1] - second_layer_kernel_size + 1)530    # # stride values: bytesize = size of one data value531    # stride = (bytesize, first_layer_kernels * layer2.shape[0] * bytesize, first_layer_kernels * bytesize, layer2.shape[1] * first_layer_kernels * bytesize,532              # first_layer_kernels * bytesize)533    # subs = np.lib.stride_tricks.as_strided(layer2, shape, stride)534    # layer3 = np.einsum('ijhm,hijkl->klm', weights, subs) + [[cnn_data['l3biases']]]535    # #print_max_err(i, layer3, 'test0l3')536537    # # layer4: activation function538    # layer4 = np.maximum(layer3, 0)539540    # # layer5: conv2d541    # weights = cnn_data['l5weights']542    # shape = (second_layer_kernels, third_layer_kernel_size, third_layer_kernel_size, layer4.shape[0] - third_layer_kernel_size + 1,543             # layer4.shape[1] - third_layer_kernel_size + 1)544    # # stride values: bytesize = size of one data value545    # stride = (bytesize, second_layer_kernels * layer4.shape[0] * bytesize, second_layer_kernels * bytesize, layer4.shape[1] * second_layer_kernels * bytesize,546              # second_layer_kernels * bytesize)547    # subs = np.lib.stride_tricks.as_strided(layer4, shape, stride)548    # layer5 = np.einsum('ijhm,hijkl->klm', weights, subs) + [[cnn_data['l5biases']]]549    # #print_max_err(i, layer5, 'test0l5')550551    # # layer6: activation function552    # layer6 = np.maximum(layer5, 0)553    # #print_max_err(i, layer6, 'test0l6')554555    # # layer7: max pooling with 'same' padding556    # layer6_padded = np.zeros(tuple([sum(x) for x in zip(layer6.shape, (1, 1, 0))]))557    # layer6_padded[:9, :9, :] = layer6558    # layer6_padded[9, :9, :] = layer6[8, :, :]559    # layer6_padded[:9, 9, :] = layer6[:, 8, :]560    # layer7 = layer6_padded.reshape(int(layer6_padded.shape[0] / 2), 2, int(layer6_padded.shape[1] / 2), 2, -1).max(axis=(1, 3))561    # #print_max_err(i, layer7, 'test0l7')562563    # # layer8: conv2d564    # weights = cnn_data['l8weights']565    # shape = (third_layer_kernels, fourth_layer_kernel_size, fourth_layer_kernel_size, layer7.shape[0] - fourth_layer_kernel_size + 1,566             # layer7.shape[1] - fourth_layer_kernel_size + 1)567    # # stride values: bytesize = size of one data value568    # stride = (bytesize, third_layer_kernels * layer7.shape[0] * bytesize, third_layer_kernels * bytesize, layer7.shape[1] * third_layer_kernels * bytesize,569              # third_layer_kernels * bytesize)570    # subs = np.lib.stride_tricks.as_strided(layer7, shape, stride)571    # layer8 = np.einsum('ijhm,hijkl->klm', weights, subs) + [[cnn_data['l8biases']]]572    # #print_max_err(i, layer8, 'test0l8')573574    # # layer9: activation function575    # layer9 = np.maximum(layer8, 0)576577    # # layer10: flatten578    # layer10 = layer9.flatten()579580    # # layer11: dense581    # layer11 = np.dot(layer10, cnn_data['l11weights']) + cnn_data['l11biases']582    # #print_max_err(i, layer11, 'test0l11')583584    # # layer12: dense585    # layer12 = np.dot(layer11, cnn_data['l12weights']) + cnn_data['l12biases']586    # #print_max_err(i, layer12, 'test0l12')587588    # # layer13: softmax589    # exp = np.exp(layer12)590    # layer13 = exp / np.sum(exp)591592    # if (np.argmax(layer12) == np.argmax(cnn_data['y_test'][i])):593        # correct_predictions += 1594595    # print(f'Test {i + 1} of 500. Accuracy: {correct_predictions / (i + 1):.3f}')
...

adding.py

Source:adding.py

1async def test_cnn_hw(dut, ii=ii, iter=iter, count=count, count2=count2):2    clock = Clock(dut.clk, 10, units="ns")  # Create a 10ns period clock on port clk3    cocotb.fork(clock.start())  # Start the clock4    reset = 05    print("iter before is", iter)6    print("ii before is", ii)7    await RisingEdge(dut.clk)8    dut.reset <= reset9    dut.i_activation_0_0 <= fix_pt(new_x[0, 0])10    dut.i_activation_0_1 <= fix_pt(new_x[0, 1])11    dut.i_activation_0_2 <= fix_pt(new_x[0, 2])12    dut.i_activation_0_3 <= fix_pt(new_x[0, 3])13    dut.i_activation_0_4 <= fix_pt(new_x[0, 4])14    dut.i_activation_1_0 <= fix_pt(new_x[1, 0])15    dut.i_activation_1_1 <= fix_pt(new_x[1, 1])16    dut.i_activation_1_2 <= fix_pt(new_x[1, 2])17    dut.i_activation_1_3 <= fix_pt(new_x[1, 3])18    dut.i_activation_1_4 <= fix_pt(new_x[1, 4])19    dut.i_activation_2_0 <= fix_pt(new_x[2, 0])20    dut.i_activation_2_1 <= fix_pt(new_x[2, 1])21    dut.i_activation_2_2 <= fix_pt(new_x[2, 2])22    dut.i_activation_2_3 <= fix_pt(new_x[2, 3])23    dut.i_activation_2_4 <= fix_pt(new_x[2, 4])24    dut.i_activation_3_0 <= fix_pt(new_x[3, 0])25    dut.i_activation_3_1 <= fix_pt(new_x[3, 1])26    dut.i_activation_3_2 <= fix_pt(new_x[3, 2])27    dut.i_activation_3_3 <= fix_pt(new_x[3, 3])28    dut.i_activation_3_4 <= fix_pt(new_x[3, 4])29    dut.i_activation_4_0 <= fix_pt(new_x[4, 0])30    dut.i_activation_4_1 <= fix_pt(new_x[4, 1])31    dut.i_activation_4_2 <= fix_pt(new_x[4, 2])32    dut.i_activation_4_3 <= fix_pt(new_x[4, 3])33    dut.i_activation_4_4 <= fix_pt(new_x[4, 4])34    dut.i_weight_0_0_0 <= fix_pt(weights[0, 0, 0])35    dut.i_weight_0_0_1 <= fix_pt(weights[0, 1, 0])36    dut.i_weight_0_0_2 <= fix_pt(weights[0, 2, 0])37    dut.i_weight_0_0_3 <= fix_pt(weights[0, 3, 0])38    dut.i_weight_0_1_0 <= fix_pt(weights[1, 0, 0])39    dut.i_weight_0_1_1 <= fix_pt(weights[1, 1, 0])40    dut.i_weight_0_1_2 <= fix_pt(weights[1, 2, 0])41    dut.i_weight_0_1_3 <= fix_pt(weights[1, 3, 0])42    dut.i_weight_0_2_0 <= fix_pt(weights[2, 0, 0])43    dut.i_weight_0_2_1 <= fix_pt(weights[2, 1, 0])44    dut.i_weight_0_2_2 <= fix_pt(weights[2, 2, 0])45    dut.i_weight_0_2_3 <= fix_pt(weights[2, 3, 0])46    dut.i_weight_0_3_0 <= fix_pt(weights[3, 0, 0])47    dut.i_weight_0_3_1 <= fix_pt(weights[3, 1, 0])48    dut.i_weight_0_3_2 <= fix_pt(weights[3, 2, 0])49    dut.i_weight_0_3_3 <= fix_pt(weights[3, 3, 0])50    dut.i_weight_1_0_0 <= fix_pt(weights[0, 0, 1])51    dut.i_weight_1_0_1 <= fix_pt(weights[0, 1, 1])52    dut.i_weight_1_0_2 <= fix_pt(weights[0, 2, 1])53    dut.i_weight_1_0_3 <= fix_pt(weights[0, 3, 1])54    dut.i_weight_1_1_0 <= fix_pt(weights[1, 0, 1])55    dut.i_weight_1_1_1 <= fix_pt(weights[1, 1, 1])56    dut.i_weight_1_1_2 <= fix_pt(weights[1, 2, 1])57    dut.i_weight_1_1_3 <= fix_pt(weights[1, 3, 1])58    dut.i_weight_1_2_0 <= fix_pt(weights[2, 0, 1])59    dut.i_weight_1_2_1 <= fix_pt(weights[2, 1, 1])60    dut.i_weight_1_2_2 <= fix_pt(weights[2, 2, 1])61    dut.i_weight_1_2_3 <= fix_pt(weights[2, 3, 1])62    dut.i_weight_1_3_0 <= fix_pt(weights[3, 0, 1])63    dut.i_weight_1_3_1 <= fix_pt(weights[3, 1, 1])64    dut.i_weight_1_3_2 <= fix_pt(weights[3, 2, 1])65    dut.i_weight_1_3_3 <= fix_pt(weights[3, 3, 1])66    dut.i_weight_2_0_0 <= fix_pt(weights[0, 0, 2])67    dut.i_weight_2_0_1 <= fix_pt(weights[0, 1, 2])68    dut.i_weight_2_0_2 <= fix_pt(weights[0, 2, 2])69    dut.i_weight_2_0_3 <= fix_pt(weights[0, 3, 2])70    dut.i_weight_2_1_0 <= fix_pt(weights[1, 0, 2])71    dut.i_weight_2_1_1 <= fix_pt(weights[1, 1, 2])72    dut.i_weight_2_1_2 <= fix_pt(weights[1, 2, 2])73    dut.i_weight_2_1_3 <= fix_pt(weights[1, 3, 2])74    dut.i_weight_2_2_0 <= fix_pt(weights[2, 0, 2])75    dut.i_weight_2_2_1 <= fix_pt(weights[2, 1, 2])76    dut.i_weight_2_2_2 <= fix_pt(weights[2, 2, 2])77    dut.i_weight_2_2_3 <= fix_pt(weights[2, 3, 2])78    dut.i_weight_2_3_0 <= fix_pt(weights[3, 0, 2])79    dut.i_weight_2_3_1 <= fix_pt(weights[3, 1, 2])80    dut.i_weight_2_3_2 <= fix_pt(weights[3, 2, 2])81    dut.i_weight_2_3_3 <= fix_pt(weights[3, 3, 2])82    dut.i_weight_3_0_0 <= fix_pt(weights[0, 0, 3])83    dut.i_weight_3_0_1 <= fix_pt(weights[0, 1, 3])84    dut.i_weight_3_0_2 <= fix_pt(weights[0, 2, 3])85    dut.i_weight_3_0_3 <= fix_pt(weights[0, 3, 3])86    dut.i_weight_3_1_0 <= fix_pt(weights[1, 0, 3])87    dut.i_weight_3_1_1 <= fix_pt(weights[1, 1, 3])88    dut.i_weight_3_1_2 <= fix_pt(weights[1, 2, 3])89    dut.i_weight_3_1_3 <= fix_pt(weights[1, 3, 3])90    dut.i_weight_3_2_0 <= fix_pt(weights[2, 0, 3])91    dut.i_weight_3_2_1 <= fix_pt(weights[2, 1, 3])92    dut.i_weight_3_2_2 <= fix_pt(weights[2, 2, 3])93    dut.i_weight_3_2_3 <= fix_pt(weights[2, 3, 3])94    dut.i_weight_3_3_0 <= fix_pt(weights[3, 0, 3])95    dut.i_weight_3_3_1 <= fix_pt(weights[3, 1, 3])96    dut.i_weight_3_3_2 <= fix_pt(weights[3, 2, 3])97    dut.i_weight_3_3_3 <= fix_pt(weights[3, 3, 3])98    dut.i_weight_4_0_0 <= fix_pt(weights[0, 0, 4])99    dut.i_weight_4_0_1 <= fix_pt(weights[0, 1, 4])100    dut.i_weight_4_0_2 <= fix_pt(weights[0, 2, 4])101    dut.i_weight_4_0_3 <= fix_pt(weights[0, 3, 4])102    dut.i_weight_4_1_0 <= fix_pt(weights[1, 0, 4])103    dut.i_weight_4_1_1 <= fix_pt(weights[1, 1, 4])104    dut.i_weight_4_1_2 <= fix_pt(weights[1, 2, 4])105    dut.i_weight_4_1_3 <= fix_pt(weights[1, 3, 4])106    dut.i_weight_4_2_0 <= fix_pt(weights[2, 0, 4])107    dut.i_weight_4_2_1 <= fix_pt(weights[2, 1, 4])108    dut.i_weight_4_2_2 <= fix_pt(weights[2, 2, 4])109    dut.i_weight_4_2_3 <= fix_pt(weights[2, 3, 4])110    dut.i_weight_4_3_0 <= fix_pt(weights[3, 0, 4])111    dut.i_weight_4_3_1 <= fix_pt(weights[3, 1, 4])112    dut.i_weight_4_3_2 <= fix_pt(weights[3, 2, 4])113    dut.i_weight_4_3_3 <= fix_pt(weights[3, 3, 4])114    dut.i_weight_5_0_0 <= fix_pt(weights[0, 0, 5])115    dut.i_weight_5_0_1 <= fix_pt(weights[0, 1, 5])116    dut.i_weight_5_0_2 <= fix_pt(weights[0, 2, 5])117    dut.i_weight_5_0_3 <= fix_pt(weights[0, 3, 5])118    dut.i_weight_5_1_0 <= fix_pt(weights[1, 0, 5])119    dut.i_weight_5_1_1 <= fix_pt(weights[1, 1, 5])120    dut.i_weight_5_1_2 <= fix_pt(weights[1, 2, 5])121    dut.i_weight_5_1_3 <= fix_pt(weights[1, 3, 5])122    dut.i_weight_5_2_0 <= fix_pt(weights[2, 0, 5])123    dut.i_weight_5_2_1 <= fix_pt(weights[2, 1, 5])124    dut.i_weight_5_2_2 <= fix_pt(weights[2, 2, 5])125    dut.i_weight_5_2_3 <= fix_pt(weights[2, 3, 5])126    dut.i_weight_5_3_0 <= fix_pt(weights[3, 0, 5])127    dut.i_weight_5_3_1 <= fix_pt(weights[3, 1, 5])128    dut.i_weight_5_3_2 <= fix_pt(weights[3, 2, 5])129    dut.i_weight_5_3_3 <= fix_pt(weights[3, 3, 5])130    dut.i_weight_6_0_0 <= fix_pt(weights[0, 0, 6])131    dut.i_weight_6_0_1 <= fix_pt(weights[0, 1, 6])132    dut.i_weight_6_0_2 <= fix_pt(weights[0, 2, 6])133    dut.i_weight_6_0_3 <= fix_pt(weights[0, 3, 6])134    dut.i_weight_6_1_0 <= fix_pt(weights[1, 0, 6])135    dut.i_weight_6_1_1 <= fix_pt(weights[1, 1, 6])136    dut.i_weight_6_1_2 <= fix_pt(weights[1, 2, 6])137    dut.i_weight_6_1_3 <= fix_pt(weights[1, 3, 6])138    dut.i_weight_6_2_0 <= fix_pt(weights[2, 0, 6])139    dut.i_weight_6_2_1 <= fix_pt(weights[2, 1, 6])140    dut.i_weight_6_2_2 <= fix_pt(weights[2, 2, 6])141    dut.i_weight_6_2_3 <= fix_pt(weights[2, 3, 6])142    dut.i_weight_6_3_0 <= fix_pt(weights[3, 0, 6])143    dut.i_weight_6_3_1 <= fix_pt(weights[3, 1, 6])144    dut.i_weight_6_3_2 <= fix_pt(weights[3, 2, 6])145    dut.i_weight_6_3_3 <= fix_pt(weights[3, 3, 6])146    dut.i_weight_7_0_0 <= fix_pt(weights[0, 0, 7])147    dut.i_weight_7_0_1 <= fix_pt(weights[0, 1, 7])148    dut.i_weight_7_0_2 <= fix_pt(weights[0, 2, 7])149    dut.i_weight_7_0_3 <= fix_pt(weights[0, 3, 7])150    dut.i_weight_7_1_0 <= fix_pt(weights[1, 0, 7])151    dut.i_weight_7_1_1 <= fix_pt(weights[1, 1, 7])152    dut.i_weight_7_1_2 <= fix_pt(weights[1, 2, 7])153    dut.i_weight_7_1_3 <= fix_pt(weights[1, 3, 7])154    dut.i_weight_7_2_0 <= fix_pt(weights[2, 0, 7])155    dut.i_weight_7_2_1 <= fix_pt(weights[2, 1, 7])156    dut.i_weight_7_2_2 <= fix_pt(weights[2, 2, 7])157    dut.i_weight_7_2_3 <= fix_pt(weights[2, 3, 7])158    dut.i_weight_7_3_0 <= fix_pt(weights[3, 0, 7])159    dut.i_weight_7_3_1 <= fix_pt(weights[3, 1, 7])160    dut.i_weight_7_3_2 <= fix_pt(weights[3, 2, 7])161    dut.i_weight_7_3_3 <= fix_pt(weights[3, 3, 7])162    dut.i_weight_8_0_0 <= fix_pt(weights[0, 0, 8])163    dut.i_weight_8_0_1 <= fix_pt(weights[0, 1, 8])164    dut.i_weight_8_0_2 <= fix_pt(weights[0, 2, 8])165    dut.i_weight_8_0_3 <= fix_pt(weights[0, 3, 8])166    dut.i_weight_8_1_0 <= fix_pt(weights[1, 0, 8])167    dut.i_weight_8_1_1 <= fix_pt(weights[1, 1, 8])168    dut.i_weight_8_1_2 <= fix_pt(weights[1, 2, 8])169    dut.i_weight_8_1_3 <= fix_pt(weights[1, 3, 8])170    dut.i_weight_8_2_0 <= fix_pt(weights[2, 0, 8])171    dut.i_weight_8_2_1 <= fix_pt(weights[2, 1, 8])172    dut.i_weight_8_2_2 <= fix_pt(weights[2, 2, 8])173    dut.i_weight_8_2_3 <= fix_pt(weights[2, 3, 8])174    dut.i_weight_8_3_0 <= fix_pt(weights[3, 0, 8])175    dut.i_weight_8_3_1 <= fix_pt(weights[3, 1, 8])176    dut.i_weight_8_3_2 <= fix_pt(weights[3, 2, 8])177    dut.i_weight_8_3_3 <= fix_pt(weights[3, 3, 8])178    dut.i_weight_9_0_0 <= fix_pt(weights[0, 0, 9])179    dut.i_weight_9_0_1 <= fix_pt(weights[0, 1, 9])180    dut.i_weight_9_0_2 <= fix_pt(weights[0, 2, 9])181    dut.i_weight_9_0_3 <= fix_pt(weights[0, 3, 9])182    dut.i_weight_9_1_0 <= fix_pt(weights[1, 0, 9])183    dut.i_weight_9_1_1 <= fix_pt(weights[1, 1, 9])184    dut.i_weight_9_1_2 <= fix_pt(weights[1, 2, 9])185    dut.i_weight_9_1_3 <= fix_pt(weights[1, 3, 9])186    dut.i_weight_9_2_0 <= fix_pt(weights[2, 0, 9])187    dut.i_weight_9_2_1 <= fix_pt(weights[2, 1, 9])188    dut.i_weight_9_2_2 <= fix_pt(weights[2, 2, 9])189    dut.i_weight_9_2_3 <= fix_pt(weights[2, 3, 9])190    dut.i_weight_9_3_0 <= fix_pt(weights[3, 0, 9])191    dut.i_weight_9_3_1 <= fix_pt(weights[3, 1, 9])192    dut.i_weight_9_3_2 <= fix_pt(weights[3, 2, 9])193    dut.i_weight_9_3_3 <= fix_pt(weights[3, 3, 9])194    dut.i_weight_10_0_0 <= fix_pt(weights[0, 0, 10])195    dut.i_weight_10_0_1 <= fix_pt(weights[0, 1, 10])196    dut.i_weight_10_0_2 <= fix_pt(weights[0, 2, 10])197    dut.i_weight_10_0_3 <= fix_pt(weights[0, 3, 10])198    dut.i_weight_10_1_0 <= fix_pt(weights[1, 0, 10])199    dut.i_weight_10_1_1 <= fix_pt(weights[1, 1, 10])200    dut.i_weight_10_1_2 <= fix_pt(weights[1, 2, 10])201    dut.i_weight_10_1_3 <= fix_pt(weights[1, 3, 10])202    dut.i_weight_10_2_0 <= fix_pt(weights[2, 0, 10])203    dut.i_weight_10_2_1 <= fix_pt(weights[2, 1, 10])204    dut.i_weight_10_2_2 <= fix_pt(weights[2, 2, 10])205    dut.i_weight_10_2_3 <= fix_pt(weights[2, 3, 10])206    dut.i_weight_10_3_0 <= fix_pt(weights[3, 0, 10])207    dut.i_weight_10_3_1 <= fix_pt(weights[3, 1, 10])208    dut.i_weight_10_3_2 <= fix_pt(weights[3, 2, 10])209    dut.i_weight_10_3_3 <= fix_pt(weights[3, 3, 10])210    dut.i_weight_11_0_0 <= fix_pt(weights[0, 0, 11])211    dut.i_weight_11_0_1 <= fix_pt(weights[0, 1, 11])212    dut.i_weight_11_0_2 <= fix_pt(weights[0, 2, 11])213    dut.i_weight_11_0_3 <= fix_pt(weights[0, 3, 11])214    dut.i_weight_11_1_0 <= fix_pt(weights[1, 0, 11])215    dut.i_weight_11_1_1 <= fix_pt(weights[1, 1, 11])216    dut.i_weight_11_1_2 <= fix_pt(weights[1, 2, 11])217    dut.i_weight_11_1_3 <= fix_pt(weights[1, 3, 11])218    dut.i_weight_11_2_0 <= fix_pt(weights[2, 0, 11])219    dut.i_weight_11_2_1 <= fix_pt(weights[2, 1, 11])220    dut.i_weight_11_2_2 <= fix_pt(weights[2, 2, 11])221    dut.i_weight_11_2_3 <= fix_pt(weights[2, 3, 11])222    dut.i_weight_11_3_0 <= fix_pt(weights[3, 0, 11])223    dut.i_weight_11_3_1 <= fix_pt(weights[3, 1, 11])224    dut.i_weight_11_3_2 <= fix_pt(weights[3, 2, 11])225    dut.i_weight_11_3_3 <= fix_pt(weights[3, 3, 11])226    dut.i_weight_12_0_0 <= fix_pt(weights[0, 0, 12])227    dut.i_weight_12_0_1 <= fix_pt(weights[0, 1, 12])228    dut.i_weight_12_0_2 <= fix_pt(weights[0, 2, 12])229    dut.i_weight_12_0_3 <= fix_pt(weights[0, 3, 12])230    dut.i_weight_12_1_0 <= fix_pt(weights[1, 0, 12])231    dut.i_weight_12_1_1 <= fix_pt(weights[1, 1, 12])232    dut.i_weight_12_1_2 <= fix_pt(weights[1, 2, 12])233    dut.i_weight_12_1_3 <= fix_pt(weights[1, 3, 12])234    dut.i_weight_12_2_0 <= fix_pt(weights[2, 0, 12])235    dut.i_weight_12_2_1 <= fix_pt(weights[2, 1, 12])236    dut.i_weight_12_2_2 <= fix_pt(weights[2, 2, 12])237    dut.i_weight_12_2_3 <= fix_pt(weights[2, 3, 12])238    dut.i_weight_12_3_0 <= fix_pt(weights[3, 0, 12])239    dut.i_weight_12_3_1 <= fix_pt(weights[3, 1, 12])240    dut.i_weight_12_3_2 <= fix_pt(weights[3, 2, 12])241    dut.i_weight_12_3_3 <= fix_pt(weights[3, 3, 12])242    dut.i_weight_13_0_0 <= fix_pt(weights[0, 0, 13])243    dut.i_weight_13_0_1 <= fix_pt(weights[0, 1, 13])244    dut.i_weight_13_0_2 <= fix_pt(weights[0, 2, 13])245    dut.i_weight_13_0_3 <= fix_pt(weights[0, 3, 13])246    dut.i_weight_13_1_0 <= fix_pt(weights[1, 0, 13])247    dut.i_weight_13_1_1 <= fix_pt(weights[1, 1, 13])248    dut.i_weight_13_1_2 <= fix_pt(weights[1, 2, 13])249    dut.i_weight_13_1_3 <= fix_pt(weights[1, 3, 13])250    dut.i_weight_13_2_0 <= fix_pt(weights[2, 0, 13])251    dut.i_weight_13_2_1 <= fix_pt(weights[2, 1, 13])252    dut.i_weight_13_2_2 <= fix_pt(weights[2, 2, 13])253    dut.i_weight_13_2_3 <= fix_pt(weights[2, 3, 13])254    dut.i_weight_13_3_0 <= fix_pt(weights[3, 0, 13])255    dut.i_weight_13_3_1 <= fix_pt(weights[3, 1, 13])256    dut.i_weight_13_3_2 <= fix_pt(weights[3, 2, 13])257    dut.i_weight_13_3_3 <= fix_pt(weights[3, 3, 13])258    dut.i_weight_14_0_0 <= fix_pt(weights[0, 0, 14])259    dut.i_weight_14_0_1 <= fix_pt(weights[0, 1, 14])260    dut.i_weight_14_0_2 <= fix_pt(weights[0, 2, 14])261    dut.i_weight_14_0_3 <= fix_pt(weights[0, 3, 14])262    dut.i_weight_14_1_0 <= fix_pt(weights[1, 0, 14])263    dut.i_weight_14_1_1 <= fix_pt(weights[1, 1, 14])264    dut.i_weight_14_1_2 <= fix_pt(weights[1, 2, 14])265    dut.i_weight_14_1_3 <= fix_pt(weights[1, 3, 14])266    dut.i_weight_14_2_0 <= fix_pt(weights[2, 0, 14])267    dut.i_weight_14_2_1 <= fix_pt(weights[2, 1, 14])268    dut.i_weight_14_2_2 <= fix_pt(weights[2, 2, 14])269    dut.i_weight_14_2_3 <= fix_pt(weights[2, 3, 14])270    dut.i_weight_14_3_0 <= fix_pt(weights[3, 0, 14])271    dut.i_weight_14_3_1 <= fix_pt(weights[3, 1, 14])272    dut.i_weight_14_3_2 <= fix_pt(weights[3, 2, 14])273    dut.i_weight_14_3_3 <= fix_pt(weights[3, 3, 14])274    dut.i_weight_15_0_0 <= fix_pt(weights[0, 0, 15])275    dut.i_weight_15_0_1 <= fix_pt(weights[0, 1, 15])276    dut.i_weight_15_0_2 <= fix_pt(weights[0, 2, 15])277    dut.i_weight_15_0_3 <= fix_pt(weights[0, 3, 15])278    dut.i_weight_15_1_0 <= fix_pt(weights[1, 0, 15])279    dut.i_weight_15_1_1 <= fix_pt(weights[1, 1, 15])280    dut.i_weight_15_1_2 <= fix_pt(weights[1, 2, 15])281    dut.i_weight_15_1_3 <= fix_pt(weights[1, 3, 15])282    dut.i_weight_15_2_0 <= fix_pt(weights[2, 0, 15])283    dut.i_weight_15_2_1 <= fix_pt(weights[2, 1, 15])284    dut.i_weight_15_2_2 <= fix_pt(weights[2, 2, 15])285    dut.i_weight_15_2_3 <= fix_pt(weights[2, 3, 15])286    dut.i_weight_15_3_0 <= fix_pt(weights[3, 0, 15])287    dut.i_weight_15_3_1 <= fix_pt(weights[3, 1, 15])288    dut.i_weight_15_3_2 <= fix_pt(weights[3, 2, 15])289    dut.i_weight_15_3_3 <= fix_pt(weights[3, 3, 15])290    dut.i_weight_16_0_0 <= fix_pt(weights[0, 0, 16])291    dut.i_weight_16_0_1 <= fix_pt(weights[0, 1, 16])292    dut.i_weight_16_0_2 <= fix_pt(weights[0, 2, 16])293    dut.i_weight_16_0_3 <= fix_pt(weights[0, 3, 16])294    dut.i_weight_16_1_0 <= fix_pt(weights[1, 0, 16])295    dut.i_weight_16_1_1 <= fix_pt(weights[1, 1, 16])296    dut.i_weight_16_1_2 <= fix_pt(weights[1, 2, 16])297    dut.i_weight_16_1_3 <= fix_pt(weights[1, 3, 16])298    dut.i_weight_16_2_0 <= fix_pt(weights[2, 0, 16])299    dut.i_weight_16_2_1 <= fix_pt(weights[2, 1, 16])300    dut.i_weight_16_2_2 <= fix_pt(weights[2, 2, 16])301    dut.i_weight_16_2_3 <= fix_pt(weights[2, 3, 16])302    dut.i_weight_16_3_0 <= fix_pt(weights[3, 0, 16])303    dut.i_weight_16_3_1 <= fix_pt(weights[3, 1, 16])304    dut.i_weight_16_3_2 <= fix_pt(weights[3, 2, 16])305    dut.i_weight_16_3_3 <= fix_pt(weights[3, 3, 16])306    dut.i_weight_17_0_0 <= fix_pt(weights[0, 0, 17])307    dut.i_weight_17_0_1 <= fix_pt(weights[0, 1, 17])308    dut.i_weight_17_0_2 <= fix_pt(weights[0, 2, 17])309    dut.i_weight_17_0_3 <= fix_pt(weights[0, 3, 17])310    dut.i_weight_17_1_0 <= fix_pt(weights[1, 0, 17])311    dut.i_weight_17_1_1 <= fix_pt(weights[1, 1, 17])312    dut.i_weight_17_1_2 <= fix_pt(weights[1, 2, 17])313    dut.i_weight_17_1_3 <= fix_pt(weights[1, 3, 17])314    dut.i_weight_17_2_0 <= fix_pt(weights[2, 0, 17])315    dut.i_weight_17_2_1 <= fix_pt(weights[2, 1, 17])316    dut.i_weight_17_2_2 <= fix_pt(weights[2, 2, 17])317    dut.i_weight_17_2_3 <= fix_pt(weights[2, 3, 17])318    dut.i_weight_17_3_0 <= fix_pt(weights[3, 0, 17])319    dut.i_weight_17_3_1 <= fix_pt(weights[3, 1, 17])320    dut.i_weight_17_3_2 <= fix_pt(weights[3, 2, 17])321    dut.i_weight_17_3_3 <= fix_pt(weights[3, 3, 17])322    dut.i_weight_18_0_0 <= fix_pt(weights[0, 0, 18])323    dut.i_weight_18_0_1 <= fix_pt(weights[0, 1, 18])324    dut.i_weight_18_0_2 <= fix_pt(weights[0, 2, 18])325    dut.i_weight_18_0_3 <= fix_pt(weights[0, 3, 18])326    dut.i_weight_18_1_0 <= fix_pt(weights[1, 0, 18])327    dut.i_weight_18_1_1 <= fix_pt(weights[1, 1, 18])328    dut.i_weight_18_1_2 <= fix_pt(weights[1, 2, 18])329    dut.i_weight_18_1_3 <= fix_pt(weights[1, 3, 18])330    dut.i_weight_18_2_0 <= fix_pt(weights[2, 0, 18])331    dut.i_weight_18_2_1 <= fix_pt(weights[2, 1, 18])332    dut.i_weight_18_2_2 <= fix_pt(weights[2, 2, 18])333    dut.i_weight_18_2_3 <= fix_pt(weights[2, 3, 18])334    dut.i_weight_18_3_0 <= fix_pt(weights[3, 0, 18])335    dut.i_weight_18_3_1 <= fix_pt(weights[3, 1, 18])336    dut.i_weight_18_3_2 <= fix_pt(weights[3, 2, 18])337    dut.i_weight_18_3_3 <= fix_pt(weights[3, 3, 18])338    dut.i_weight_19_0_0 <= fix_pt(weights[0, 0, 19])339    dut.i_weight_19_0_1 <= fix_pt(weights[0, 1, 19])340    dut.i_weight_19_0_2 <= fix_pt(weights[0, 2, 19])341    dut.i_weight_19_0_3 <= fix_pt(weights[0, 3, 19])342    dut.i_weight_19_1_0 <= fix_pt(weights[1, 0, 19])343    dut.i_weight_19_1_1 <= fix_pt(weights[1, 1, 19])344    dut.i_weight_19_1_2 <= fix_pt(weights[1, 2, 19])345    dut.i_weight_19_1_3 <= fix_pt(weights[1, 3, 19])346    dut.i_weight_19_2_0 <= fix_pt(weights[2, 0, 19])347    dut.i_weight_19_2_1 <= fix_pt(weights[2, 1, 19])348    dut.i_weight_19_2_2 <= fix_pt(weights[2, 2, 19])349    dut.i_weight_19_2_3 <= fix_pt(weights[2, 3, 19])350    dut.i_weight_19_3_0 <= fix_pt(weights[3, 0, 19])351    dut.i_weight_19_3_1 <= fix_pt(weights[3, 1, 19])352    dut.i_weight_19_3_2 <= fix_pt(weights[3, 2, 19])353    dut.i_weight_19_3_3 <= fix_pt(weights[3, 3, 19])354    time.sleep(10)355    # print("count is:",count)356    # print("count2 is:",count2)357    print("iter", iter)358    print("ii", ii)359    layer2[count, count2, 0] = fix2float(dut.o_output_0)360    layer2[count, count2, 1] = fix2float(dut.o_output_1)361    layer2[count, count2, 2] = fix2float(dut.o_output_2)362    layer2[count, count2, 3] = fix2float(dut.o_output_3)363    layer2[count, count2, 4] = fix2float(dut.o_output_4)364    layer2[count, count2, 5] = fix2float(dut.o_output_5)365    layer2[count, count2, 6] = fix2float(dut.o_output_6)366    layer2[count, count2, 7] = fix2float(dut.o_output_7)367    layer2[count, count2, 8] = fix2float(dut.o_output_8)368    layer2[count, count2, 9] = fix2float(dut.o_output_9)369    layer2[count, count2, 10] = fix2float(dut.o_output_10)370    layer2[count, count2, 11] = fix2float(dut.o_output_11)371    layer2[count, count2, 12] = fix2float(dut.o_output_12)372    layer2[count, count2, 13] = fix2float(dut.o_output_13)373    layer2[count, count2, 14] = fix2float(dut.o_output_14)374    layer2[count, count2, 15] = fix2float(dut.o_output_15)375    layer2[count, count2, 16] = fix2float(dut.o_output_16)376    layer2[count, count2, 17] = fix2float(dut.o_output_17)377    layer2[count, count2, 18] = fix2float(dut.o_output_18)...

__init__.py

Source:__init__.py

1import sys2from lib2to3 import refactor3# The following fixers are "safe": they convert Python 2 code to more4# modern Python 2 code. They should be uncontroversial to apply to most5# projects that are happy to drop support for Py2.5 and below. Applying6# them first will reduce the size of the patch set for the real porting.7lib2to3_fix_names_stage1 = set([8    'lib2to3.fixes.fix_apply',9    'lib2to3.fixes.fix_except',10    'lib2to3.fixes.fix_exec',11    'lib2to3.fixes.fix_exitfunc',12    'lib2to3.fixes.fix_funcattrs',13    'lib2to3.fixes.fix_has_key',14    'lib2to3.fixes.fix_idioms',15    # 'lib2to3.fixes.fix_import',    # makes any implicit relative imports explicit. (Use with ``from __future__ import absolute_import)16    'lib2to3.fixes.fix_intern',17    'lib2to3.fixes.fix_isinstance',18    'lib2to3.fixes.fix_methodattrs',19    'lib2to3.fixes.fix_ne',20    # 'lib2to3.fixes.fix_next',         # would replace ``next`` method names21                                        # with ``__next__``.22    'lib2to3.fixes.fix_numliterals',    # turns 1L into 1, 0755 into 0o75523    'lib2to3.fixes.fix_paren',24    # 'lib2to3.fixes.fix_print',        # see the libfuturize fixer that also25                                        # adds ``from __future__ import print_function``26    # 'lib2to3.fixes.fix_raise',   # uses incompatible with_traceback() method on exceptions27    'lib2to3.fixes.fix_reduce',    # reduce is available in functools on Py2.6/Py2.728    'lib2to3.fixes.fix_renames',        # sys.maxint -> sys.maxsize29    # 'lib2to3.fixes.fix_set_literal',  # this is unnecessary and breaks Py2.6 support30    'lib2to3.fixes.fix_repr',31    'lib2to3.fixes.fix_standarderror',32    'lib2to3.fixes.fix_sys_exc',33    'lib2to3.fixes.fix_throw',34    'lib2to3.fixes.fix_tuple_params',35    'lib2to3.fixes.fix_types',36    'lib2to3.fixes.fix_ws_comma',       # can perhaps decrease readability: see issue #5837    'lib2to3.fixes.fix_xreadlines',38])39# The following fixers add a dependency on the ``future`` package on order to40# support Python 2:41lib2to3_fix_names_stage2 = set([42    # 'lib2to3.fixes.fix_buffer',    # perhaps not safe. Test this.43    # 'lib2to3.fixes.fix_callable',  # not needed in Py3.2+44    'lib2to3.fixes.fix_dict',        # TODO: add support for utils.viewitems() etc. and move to stage245    # 'lib2to3.fixes.fix_execfile',  # some problems: see issue #37.46                                     # We use a custom fixer instead (see below)47    # 'lib2to3.fixes.fix_future',    # we don't want to remove __future__ imports48    'lib2to3.fixes.fix_getcwdu',49    # 'lib2to3.fixes.fix_imports',   # called by libfuturize.fixes.fix_future_standard_library50    # 'lib2to3.fixes.fix_imports2',  # we don't handle this yet (dbm)51    # 'lib2to3.fixes.fix_input',     # Called conditionally by libfuturize.fixes.fix_input52    'lib2to3.fixes.fix_itertools',53    'lib2to3.fixes.fix_itertools_imports',54    'lib2to3.fixes.fix_filter',55    'lib2to3.fixes.fix_long',56    'lib2to3.fixes.fix_map',57    # 'lib2to3.fixes.fix_metaclass', # causes SyntaxError in Py2! Use the one from ``six`` instead58    'lib2to3.fixes.fix_next',59    'lib2to3.fixes.fix_nonzero',     # TODO: cause this to import ``object`` and/or add a decorator for mapping __bool__ to __nonzero__60    'lib2to3.fixes.fix_operator',    # we will need support for this by e.g. extending the Py2 operator module to provide those functions in Py361    'lib2to3.fixes.fix_raw_input',62    # 'lib2to3.fixes.fix_unicode',   # strips off the u'' prefix, which removes a potentially helpful source of information for disambiguating unicode/byte strings63    # 'lib2to3.fixes.fix_urllib',    # included in libfuturize.fix_future_standard_library_urllib64    # 'lib2to3.fixes.fix_xrange',    # custom one because of a bug with Py3.3's lib2to365    'lib2to3.fixes.fix_zip',66])67libfuturize_fix_names_stage1 = set([68    'libfuturize.fixes.fix_absolute_import',69    'libfuturize.fixes.fix_next_call',  # obj.next() -> next(obj). Unlike70                                        # lib2to3.fixes.fix_next, doesn't change71                                        # the ``next`` method to ``__next__``.72    'libfuturize.fixes.fix_print_with_import',73    'libfuturize.fixes.fix_raise',74    # 'libfuturize.fixes.fix_order___future__imports',  # TODO: consolidate to a single line to simplify testing75])76libfuturize_fix_names_stage2 = set([77    'libfuturize.fixes.fix_basestring',78    # 'libfuturize.fixes.fix_add__future__imports_except_unicode_literals',  # just in case79    'libfuturize.fixes.fix_cmp',80    'libfuturize.fixes.fix_division_safe',81    'libfuturize.fixes.fix_execfile',82    'libfuturize.fixes.fix_future_builtins',83    'libfuturize.fixes.fix_future_standard_library',84    'libfuturize.fixes.fix_future_standard_library_urllib',85    'libfuturize.fixes.fix_input',86    'libfuturize.fixes.fix_metaclass',87    'libpasteurize.fixes.fix_newstyle',88    'libfuturize.fixes.fix_object',89    # 'libfuturize.fixes.fix_order___future__imports',  # TODO: consolidate to a single line to simplify testing90    'libfuturize.fixes.fix_unicode_keep_u',91    # 'libfuturize.fixes.fix_unicode_literals_import',92    'libfuturize.fixes.fix_xrange_with_import',  # custom one because of a bug with Py3.3's lib2to3...

isacfix.gypi

Source:isacfix.gypi

1# Copyright (c) 2012 The WebRTC project authors. All Rights Reserved.2#3# Use of this source code is governed by a BSD-style license4# that can be found in the LICENSE file in the root of the source5# tree. An additional intellectual property rights grant can be found6# in the file PATENTS.  All contributing project authors may7# be found in the AUTHORS file in the root of the source tree.8{9  'includes': [10    '../../../../build/common.gypi',11  ],12  'targets': [13    {14      'target_name': 'isac_fix',15      'type': 'static_library',16      'dependencies': [17        '<(webrtc_root)/common_audio/common_audio.gyp:common_audio',18        '<(webrtc_root)/system_wrappers/system_wrappers.gyp:system_wrappers',19        'isac_common',20      ],21      'include_dirs': [22        'fix/include',23        '<(webrtc_root)'24      ],25      'direct_dependent_settings': {26        'include_dirs': [27          'fix/include',28          '<(webrtc_root)',29        ],30      },31      'sources': [32        'fix/include/audio_decoder_isacfix.h',33        'fix/include/audio_encoder_isacfix.h',34        'fix/include/isacfix.h',35        'fix/source/arith_routines.c',36        'fix/source/arith_routines_hist.c',37        'fix/source/arith_routines_logist.c',38        'fix/source/audio_decoder_isacfix.cc',39        'fix/source/audio_encoder_isacfix.cc',40        'fix/source/bandwidth_estimator.c',41        'fix/source/decode.c',42        'fix/source/decode_bwe.c',43        'fix/source/decode_plc.c',44        'fix/source/encode.c',45        'fix/source/entropy_coding.c',46        'fix/source/fft.c',47        'fix/source/filterbank_tables.c',48        'fix/source/filterbanks.c',49        'fix/source/filters.c',50        'fix/source/initialize.c',51        'fix/source/isac_fix_type.h',52        'fix/source/isacfix.c',53        'fix/source/lattice.c',54        'fix/source/lattice_c.c',55        'fix/source/lpc_masking_model.c',56        'fix/source/lpc_tables.c',57        'fix/source/pitch_estimator.c',58        'fix/source/pitch_estimator_c.c',59        'fix/source/pitch_filter.c',60        'fix/source/pitch_filter_c.c',61        'fix/source/pitch_gain_tables.c',62        'fix/source/pitch_lag_tables.c',63        'fix/source/spectrum_ar_model_tables.c',64        'fix/source/transform.c',65        'fix/source/transform_tables.c',66        'fix/source/arith_routins.h',67        'fix/source/bandwidth_estimator.h',68        'fix/source/codec.h',69        'fix/source/entropy_coding.h',70        'fix/source/fft.h',71        'fix/source/filterbank_tables.h',72        'fix/source/lpc_masking_model.h',73        'fix/source/lpc_tables.h',74        'fix/source/pitch_estimator.h',75        'fix/source/pitch_gain_tables.h',76        'fix/source/pitch_lag_tables.h',77        'fix/source/settings.h',78        'fix/source/spectrum_ar_model_tables.h',79        'fix/source/structs.h',80      ],81      'conditions': [82        ['target_arch=="arm" and arm_version>=7', {83          'sources': [84            'fix/source/lattice_armv7.S',85            'fix/source/pitch_filter_armv6.S',86          ],87          'sources!': [88            'fix/source/lattice_c.c',89            'fix/source/pitch_filter_c.c',90          ],91        }],92        ['build_with_neon==1', {93          'dependencies': ['isac_neon', ],94        }],95        ['target_arch=="mipsel" and mips_arch_variant!="r6"', {96          'sources': [97            'fix/source/entropy_coding_mips.c',98            'fix/source/filters_mips.c',99            'fix/source/lattice_mips.c',100            'fix/source/pitch_estimator_mips.c',101            'fix/source/transform_mips.c',102          ],103          'sources!': [104            'fix/source/lattice_c.c',105            'fix/source/pitch_estimator_c.c',106          ],107          'conditions': [108            ['mips_dsp_rev>0', {109              'sources': [110                'fix/source/filterbanks_mips.c',111              ],112            }],113            ['mips_dsp_rev>1', {114              'sources': [115                'fix/source/lpc_masking_model_mips.c',116                'fix/source/pitch_filter_mips.c',117              ],118              'sources!': [119                'fix/source/pitch_filter_c.c',120              ],121            }],122          ],123        }],124      ],125    },126  ],127  'conditions': [128    ['build_with_neon==1', {129      'targets': [130        {131          'target_name': 'isac_neon',132          'type': 'static_library',133          'includes': ['../../../../build/arm_neon.gypi',],134          'dependencies': [135            '<(webrtc_root)/common_audio/common_audio.gyp:common_audio',136          ],137          'sources': [138            'fix/source/entropy_coding_neon.c',139            'fix/source/filterbanks_neon.c',140            'fix/source/filters_neon.c',141            'fix/source/lattice_neon.c',142            'fix/source/transform_neon.c',143          ],144        },145      ],146    }],147  ],...

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