| """ |
| Inception V3, suitable for images with around 299 x 299 |
| |
| Reference: |
| |
| Szegedy, Christian, et al. "Rethinking the Inception Architecture for Computer Vision." arXiv preprint arXiv:1512.00567 (2015). |
| """ |
| import mxnet as mx |
| |
| def Conv(data, num_filter, kernel=(1, 1), stride=(1, 1), pad=(0, 0), name=None, suffix=''): |
| conv = mx.sym.Convolution(data=data, num_filter=num_filter, kernel=kernel, stride=stride, pad=pad, no_bias=True, name='%s%s_conv2d' %(name, suffix)) |
| bn = mx.sym.BatchNorm(data=conv, name='%s%s_batchnorm' %(name, suffix), fix_gamma=True) |
| act = mx.sym.Activation(data=bn, act_type='relu', name='%s%s_relu' %(name, suffix)) |
| return act |
| |
| |
| def Inception7A(data, |
| num_1x1, |
| num_3x3_red, num_3x3_1, num_3x3_2, |
| num_5x5_red, num_5x5, |
| pool, proj, |
| name): |
| tower_1x1 = Conv(data, num_1x1, name=('%s_conv' % name)) |
| tower_5x5 = Conv(data, num_5x5_red, name=('%s_tower' % name), suffix='_conv') |
| tower_5x5 = Conv(tower_5x5, num_5x5, kernel=(5, 5), pad=(2, 2), name=('%s_tower' % name), suffix='_conv_1') |
| tower_3x3 = Conv(data, num_3x3_red, name=('%s_tower_1' % name), suffix='_conv') |
| tower_3x3 = Conv(tower_3x3, num_3x3_1, kernel=(3, 3), pad=(1, 1), name=('%s_tower_1' % name), suffix='_conv_1') |
| tower_3x3 = Conv(tower_3x3, num_3x3_2, kernel=(3, 3), pad=(1, 1), name=('%s_tower_1' % name), suffix='_conv_2') |
| pooling = mx.sym.Pooling(data=data, kernel=(3, 3), stride=(1, 1), pad=(1, 1), pool_type=pool, name=('%s_pool_%s_pool' % (pool, name))) |
| cproj = Conv(pooling, proj, name=('%s_tower_2' % name), suffix='_conv') |
| concat = mx.sym.Concat(*[tower_1x1, tower_5x5, tower_3x3, cproj], name='ch_concat_%s_chconcat' % name) |
| return concat |
| |
| # First Downsample |
| def Inception7B(data, |
| num_3x3, |
| num_d3x3_red, num_d3x3_1, num_d3x3_2, |
| pool, |
| name): |
| tower_3x3 = Conv(data, num_3x3, kernel=(3, 3), pad=(0, 0), stride=(2, 2), name=('%s_conv' % name)) |
| tower_d3x3 = Conv(data, num_d3x3_red, name=('%s_tower' % name), suffix='_conv') |
| tower_d3x3 = Conv(tower_d3x3, num_d3x3_1, kernel=(3, 3), pad=(1, 1), stride=(1, 1), name=('%s_tower' % name), suffix='_conv_1') |
| tower_d3x3 = Conv(tower_d3x3, num_d3x3_2, kernel=(3, 3), pad=(0, 0), stride=(2, 2), name=('%s_tower' % name), suffix='_conv_2') |
| pooling = mx.symbol.Pooling(data=data, kernel=(3, 3), stride=(2, 2), pad=(0,0), pool_type="max", name=('max_pool_%s_pool' % name)) |
| concat = mx.sym.Concat(*[tower_3x3, tower_d3x3, pooling], name='ch_concat_%s_chconcat' % name) |
| return concat |
| |
| def Inception7C(data, |
| num_1x1, |
| num_d7_red, num_d7_1, num_d7_2, |
| num_q7_red, num_q7_1, num_q7_2, num_q7_3, num_q7_4, |
| pool, proj, |
| name): |
| tower_1x1 = Conv(data=data, num_filter=num_1x1, kernel=(1, 1), name=('%s_conv' % name)) |
| tower_d7 = Conv(data=data, num_filter=num_d7_red, name=('%s_tower' % name), suffix='_conv') |
| tower_d7 = Conv(data=tower_d7, num_filter=num_d7_1, kernel=(1, 7), pad=(0, 3), name=('%s_tower' % name), suffix='_conv_1') |
| tower_d7 = Conv(data=tower_d7, num_filter=num_d7_2, kernel=(7, 1), pad=(3, 0), name=('%s_tower' % name), suffix='_conv_2') |
| tower_q7 = Conv(data=data, num_filter=num_q7_red, name=('%s_tower_1' % name), suffix='_conv') |
| tower_q7 = Conv(data=tower_q7, num_filter=num_q7_1, kernel=(7, 1), pad=(3, 0), name=('%s_tower_1' % name), suffix='_conv_1') |
| tower_q7 = Conv(data=tower_q7, num_filter=num_q7_2, kernel=(1, 7), pad=(0, 3), name=('%s_tower_1' % name), suffix='_conv_2') |
| tower_q7 = Conv(data=tower_q7, num_filter=num_q7_3, kernel=(7, 1), pad=(3, 0), name=('%s_tower_1' % name), suffix='_conv_3') |
| tower_q7 = Conv(data=tower_q7, num_filter=num_q7_4, kernel=(1, 7), pad=(0, 3), name=('%s_tower_1' % name), suffix='_conv_4') |
| pooling = mx.sym.Pooling(data=data, kernel=(3, 3), stride=(1, 1), pad=(1, 1), pool_type=pool, name=('%s_pool_%s_pool' % (pool, name))) |
| cproj = Conv(data=pooling, num_filter=proj, kernel=(1, 1), name=('%s_tower_2' % name), suffix='_conv') |
| # concat |
| concat = mx.sym.Concat(*[tower_1x1, tower_d7, tower_q7, cproj], name='ch_concat_%s_chconcat' % name) |
| return concat |
| |
| def Inception7D(data, |
| num_3x3_red, num_3x3, |
| num_d7_3x3_red, num_d7_1, num_d7_2, num_d7_3x3, |
| pool, |
| name): |
| tower_3x3 = Conv(data=data, num_filter=num_3x3_red, name=('%s_tower' % name), suffix='_conv') |
| tower_3x3 = Conv(data=tower_3x3, num_filter=num_3x3, kernel=(3, 3), pad=(0,0), stride=(2, 2), name=('%s_tower' % name), suffix='_conv_1') |
| tower_d7_3x3 = Conv(data=data, num_filter=num_d7_3x3_red, name=('%s_tower_1' % name), suffix='_conv') |
| tower_d7_3x3 = Conv(data=tower_d7_3x3, num_filter=num_d7_1, kernel=(1, 7), pad=(0, 3), name=('%s_tower_1' % name), suffix='_conv_1') |
| tower_d7_3x3 = Conv(data=tower_d7_3x3, num_filter=num_d7_2, kernel=(7, 1), pad=(3, 0), name=('%s_tower_1' % name), suffix='_conv_2') |
| tower_d7_3x3 = Conv(data=tower_d7_3x3, num_filter=num_d7_3x3, kernel=(3, 3), stride=(2, 2), name=('%s_tower_1' % name), suffix='_conv_3') |
| pooling = mx.sym.Pooling(data=data, kernel=(3, 3), stride=(2, 2), pool_type=pool, name=('%s_pool_%s_pool' % (pool, name))) |
| # concat |
| concat = mx.sym.Concat(*[tower_3x3, tower_d7_3x3, pooling], name='ch_concat_%s_chconcat' % name) |
| return concat |
| |
| def Inception7E(data, |
| num_1x1, |
| num_d3_red, num_d3_1, num_d3_2, |
| num_3x3_d3_red, num_3x3, num_3x3_d3_1, num_3x3_d3_2, |
| pool, proj, |
| name): |
| tower_1x1 = Conv(data=data, num_filter=num_1x1, kernel=(1, 1), name=('%s_conv' % name)) |
| tower_d3 = Conv(data=data, num_filter=num_d3_red, name=('%s_tower' % name), suffix='_conv') |
| tower_d3_a = Conv(data=tower_d3, num_filter=num_d3_1, kernel=(1, 3), pad=(0, 1), name=('%s_tower' % name), suffix='_mixed_conv') |
| tower_d3_b = Conv(data=tower_d3, num_filter=num_d3_2, kernel=(3, 1), pad=(1, 0), name=('%s_tower' % name), suffix='_mixed_conv_1') |
| tower_3x3_d3 = Conv(data=data, num_filter=num_3x3_d3_red, name=('%s_tower_1' % name), suffix='_conv') |
| tower_3x3_d3 = Conv(data=tower_3x3_d3, num_filter=num_3x3, kernel=(3, 3), pad=(1, 1), name=('%s_tower_1' % name), suffix='_conv_1') |
| tower_3x3_d3_a = Conv(data=tower_3x3_d3, num_filter=num_3x3_d3_1, kernel=(1, 3), pad=(0, 1), name=('%s_tower_1' % name), suffix='_mixed_conv') |
| tower_3x3_d3_b = Conv(data=tower_3x3_d3, num_filter=num_3x3_d3_2, kernel=(3, 1), pad=(1, 0), name=('%s_tower_1' % name), suffix='_mixed_conv_1') |
| pooling = mx.sym.Pooling(data=data, kernel=(3, 3), stride=(1, 1), pad=(1, 1), pool_type=pool, name=('%s_pool_%s_pool' % (pool, name))) |
| cproj = Conv(data=pooling, num_filter=proj, kernel=(1, 1), name=('%s_tower_2' % name), suffix='_conv') |
| # concat |
| concat = mx.sym.Concat(*[tower_1x1, tower_d3_a, tower_d3_b, tower_3x3_d3_a, tower_3x3_d3_b, cproj], name='ch_concat_%s_chconcat' % name) |
| return concat |
| |
| # In[49]: |
| |
| def get_symbol(num_classes=1000, **kwargs): |
| data = mx.symbol.Variable(name="data") |
| # stage 1 |
| conv = Conv(data, 32, kernel=(3, 3), stride=(2, 2), name="conv") |
| conv_1 = Conv(conv, 32, kernel=(3, 3), name="conv_1") |
| conv_2 = Conv(conv_1, 64, kernel=(3, 3), pad=(1, 1), name="conv_2") |
| pool = mx.sym.Pooling(data=conv_2, kernel=(3, 3), stride=(2, 2), pool_type="max", name="pool") |
| # stage 2 |
| conv_3 = Conv(pool, 80, kernel=(1, 1), name="conv_3") |
| conv_4 = Conv(conv_3, 192, kernel=(3, 3), name="conv_4") |
| pool1 = mx.sym.Pooling(data=conv_4, kernel=(3, 3), stride=(2, 2), pool_type="max", name="pool1") |
| # stage 3 |
| in3a = Inception7A(pool1, 64, |
| 64, 96, 96, |
| 48, 64, |
| "avg", 32, "mixed") |
| in3b = Inception7A(in3a, 64, |
| 64, 96, 96, |
| 48, 64, |
| "avg", 64, "mixed_1") |
| in3c = Inception7A(in3b, 64, |
| 64, 96, 96, |
| 48, 64, |
| "avg", 64, "mixed_2") |
| in3d = Inception7B(in3c, 384, |
| 64, 96, 96, |
| "max", "mixed_3") |
| # stage 4 |
| in4a = Inception7C(in3d, 192, |
| 128, 128, 192, |
| 128, 128, 128, 128, 192, |
| "avg", 192, "mixed_4") |
| in4b = Inception7C(in4a, 192, |
| 160, 160, 192, |
| 160, 160, 160, 160, 192, |
| "avg", 192, "mixed_5") |
| in4c = Inception7C(in4b, 192, |
| 160, 160, 192, |
| 160, 160, 160, 160, 192, |
| "avg", 192, "mixed_6") |
| in4d = Inception7C(in4c, 192, |
| 192, 192, 192, |
| 192, 192, 192, 192, 192, |
| "avg", 192, "mixed_7") |
| in4e = Inception7D(in4d, 192, 320, |
| 192, 192, 192, 192, |
| "max", "mixed_8") |
| # stage 5 |
| in5a = Inception7E(in4e, 320, |
| 384, 384, 384, |
| 448, 384, 384, 384, |
| "avg", 192, "mixed_9") |
| in5b = Inception7E(in5a, 320, |
| 384, 384, 384, |
| 448, 384, 384, 384, |
| "max", 192, "mixed_10") |
| # pool |
| pool = mx.sym.Pooling(data=in5b, kernel=(8, 8), stride=(1, 1), pool_type="avg", name="global_pool") |
| flatten = mx.sym.Flatten(data=pool, name="flatten") |
| fc1 = mx.symbol.FullyConnected(data=flatten, num_hidden=num_classes, name='fc1') |
| softmax = mx.symbol.SoftmaxOutput(data=fc1, name='softmax') |
| return softmax |
