def _ds_by_pl(data, name, level, dilate):
assert level > 0
level_block = level_blocks[level]
if not level_block.downsample == 'p':
return data, dilate
pool_stride = stride = 2
inc_dilate = level_block.dilate
pad = -1
if inc_dilate:
pool_stride = 1
pad = dilate
print 'Pooling stride: {}, dilate: {}, pad: {}'.format(pool_stride, dilate, pad)
top = pool(data, name, stride=pool_stride, dilate=dilate, pad=pad, pool_type=pool_type)
if inc_dilate:
dilate *= stride
return top, dilate
def _ds_by_pl(data, name, level, dilate):
assert level > 0
ds = level_blocks[level].downsample
if not ds == 'p':
return data, dilate
stride = 2
inc_dilate = level_blocks[level].dilate
pad = -1
if inc_dilate:
stride = 1
pad = dilate
print 'Pooling stride: {}, dilate: {}, pad: {}'.format(stride, dilate, pad)
top = pool(data, name, stride=stride, dilate=dilate, pad=pad, pool_type=pool_type)
if inc_dilate:
dilate *= ds[1]
return top, dilate
def rn_top(feat, fc_name, classes):
pool7 = pool(feat, 'pool7', pool_type='avg', global_pool=True)
scores = fc(pool7, fc_name, classes)
return softmax_out(scores)
def rn_top(feat, fc_name, classes):
pool7 = pool(feat, 'pool7', pool_type='avg', global_pool=True)
scores = fc(pool7, fc_name, classes)
return softmax_out(scores)
def rn_top_1(feat, fc_name, classes):
poolc2 = pool(feat, 'poolc2', pool_type='avg', global_pool=True)
fc1 = fc(poolc2, fc_name, 512)
scoresF = fc(fc1, 'bCls1', classes)
return sigmoid_out(scoresF)