def Cut(prototxt, output_dir="work"):
cutter = xfdnnCutter(
cutAfter="data", # Prototxt expected to have layer named "data"
trainproto=
prototxt, # train_val prototxt used to extract accuracy layers
inproto=output_dir + "/deploy.prototxt",
outproto=output_dir + "/xfdnn_auto_cut_deploy.prototxt",
outtrainproto=output_dir + "/xfdnn_auto_cut_train_val.prototxt",
xclbin="/opt/xilinx/overlaybins/xdnnv3",
netcfg=output_dir + "/compiler.json",
quantizecfg=output_dir + "/quantizer.json",
weights=output_dir + "/deploy.caffemodel_data.h5")
cutter.cut()
def Cut(prototxt):
cutter = xfdnnCutter(
inproto="quantize_results/deploy.prototxt",
trainproto=prototxt,
outproto="xfdnn_auto_cut_deploy.prototxt",
outtrainproto="xfdnn_auto_cut_train_val.prototxt",
cutAfter="data",
xclbin="/opt/xilinx/overlaybins/xdnnv3",
netcfg="work/compiler.json",
quantizecfg="work/quantizer.json",
weights="work/weights.h5",
#profile=True
)
cutter.cut()
def Cut(prototxt):
cutter = xfdnnCutter(
inproto="quantize_results/deploy.prototxt",
trainproto=prototxt,
outproto="xfdnn_auto_cut_deploy.prototxt",
outtrainproto="xfdnn_auto_cut_train_val.prototxt",
cutAfter="data",
xclbin=os.getenv("VAI_ALVEO_ROOT") + "/overlaybins/" + "xdnnv3",
netcfg="work/compiler.json",
quantizecfg="work/quantizer.json",
weights="work/deploy.caffemodel_data.h5",
#profile=True
)
cutter.cut()