Function inception

benchmark/exprModels/GoogLeNetExpr.cpp:16–29

inception module, channels: [inputChannel, 1x1, 3x3_reduce, 3x3, 5x5_reduce, 5x5, pool_proj]

// inception module, channels: [inputChannel, 1x1, 3x3_reduce, 3x3, 5x5_reduce, 5x5, pool_proj]
static VARP inception(VARP x, int inputChannelSet, int channel_1x1,
                      int channel_3x3_reduce, int channel_3x3,
                      int channel_5x5_reduce, int channel_5x5,
                      int channel_pool) {
    auto inputChannel = x->getInfo()->dim[1];
    auto y1 = _Conv(0.0f, 0.0f, x, {inputChannel, channel_1x1}, {1, 1}, VALID, {1, 1}, {1, 1}, 1);
    auto y2 = _Conv(0.0f, 0.0f, x, {inputChannel, channel_3x3_reduce}, {1, 1}, VALID, {1, 1}, {1, 1}, 1);
    y2 = _Conv(0.0f, 0.0f, y2, {channel_3x3_reduce, channel_3x3}, {3, 3}, SAME, {1, 1}, {1, 1}, 1);
    auto y3 = _Conv(0.0f, 0.0f, x, {inputChannel, channel_5x5_reduce}, {1, 1}, VALID, {1, 1}, {1, 1}, 1);
    y3 = _Conv(0.0f, 0.0f, y3, {channel_5x5_reduce, channel_5x5}, {5, 5}, SAME, {1, 1}, {1, 1}, 1);
    auto y4 = _MaxPool(x, {3, 3}, {1, 1}, SAME);
    y4 = _Conv(0.0f, 0.0f, y4, {inputChannel, channel_pool}, {1, 1}, VALID, {1, 1}, {1, 1}, 1);
    return _Concat({y1, y2, y3, y4}, 1); // concat on channel axis (NCHW)
}

VARP googLeNetExpr(int numClass) {
    auto x = _Input({1, 3, 224, 224}, NC4HW4);