def passReorderMaxPooling(pipeline):
"Move max pooling layers past thresholding layers."
inStages = pipeline
inStages.reverse()
numChanges = 0
ret = []
while len(inStages) > 1:
layerA = inStages.pop()
layerB = inStages.pop()
if lb.isMaxPoolingLayer(layerA) and lb.isThresholdLayer(layerB):
# need to check that the threholding preserves max to reoder
for t in range(len(layerB.thresholds) - 1):
if not (layerB.thresholds[t + 1] >=
layerB.thresholds[t]).all():
raise Exception("Threshold does not preserve max")
# re-insert layers in reversed order
ret += [layerB, layerA]
numChanges += 1
else:
ret += [layerA]
inStages.append(layerB)
# pop final element, if any left
if len(inStages) == 1:
ret += [inStages.pop()]
return (ret, numChanges)
def passAbsorbLinearIntoThreshold(pipeline):
"Absorb linear transformations into the following threshold layer."
inStages = pipeline
inStages.reverse()
numChanges = 0
ret = []
while len(inStages) > 1:
layerA = inStages.pop()
layerB = inStages.pop()
if lb.isLinearLayer(layerA) and lb.isThresholdLayer(layerB):
# absorb the linear transform Ax+B into the threshold layer
# by updating each threshold T as Tnew = (T-B)/A
A = layerA.A
B = layerA.B
T = layerB.thresholds
Tnew = np.asarray([(t - B) / A for t in T])
layerBThresClass = layerB.__class__
ret += [layerBThresClass(Tnew)]
numChanges += 1
else:
ret += [layerA]
inStages.append(layerB)
# pop final element, if any left
if len(inStages) == 1:
ret += [inStages.pop()]
return (ret, numChanges)
def passRoundUpIntThresholds(pipeline):
"Round up thresholds of ThresholdingLayers with integer inputs."
inStages = pipeline
ret = []
for L in inStages:
# TODO this is not a good way to check for integer input --
# fix this once we have i/o data types specified
if lb.isThresholdLayer(L) and L.ibits <= 16:
L.thresholds = np.ceil(L.thresholds).astype(np.int16)
ret += [L]
return (ret, 0)
def passConvertToCaffeLayers(pipeline, qnnengine):
"Convert layers to corresponding Caffe-equivalent implementation layers."
inStages = pipeline
ret = []
default_engine_maxbits = 4
gemmlowp_maxbits = 8
if qnnengine == "float":
# force all layers to be generated as vanilla Caffe layers
default_engine_maxbits = 0
gemmlowp_maxbits = 0
# note that layer, in and out buf names are empty -- we'll set those later
for L in inStages:
if lb.isFCLayer(L):
if (L.wbits * L.ibits) <= default_engine_maxbits:
ret += [lcaffe.CaffeIntegerInnerProductLayer("", L, qnnengine)]
elif L.wbits <= gemmlowp_maxbits:
ret += [
lcaffe.CaffeIntegerInnerProductLayer("", L, "gemmlowp")
]
else:
ret += [lcaffe.CaffeInnerProductLayer("", L)]
elif lb.isConvLayer(L):
if (L.wbits * L.ibits) <= default_engine_maxbits:
ret += [lcaffe.CaffeIntegerConvolutionLayer("", L, qnnengine)]
elif L.wbits <= gemmlowp_maxbits:
ret += [lcaffe.CaffeIntegerConvolutionLayer("", L, "gemmlowp")]
else:
ret += [lcaffe.CaffeConvolutionLayer("", L)]
elif lb.isPoolingLayer(L):
ret += [lcaffe.CaffePoolLayer("", L)]
elif lb.isThresholdLayer(L):
ret += [lcaffe.CaffeMultiThresholdLayer("", L)]
elif lb.isLinearLayer(L):
ret += [lcaffe.CaffeScaleLayer("", L)]
elif lb.isReLULayer(L):
ret += [lcaffe.CaffeReLULayer("")]
elif lb.isSoftmaxLayer(L):
ret += [lcaffe.CaffeSoftmaxLayer("")]
elif lcaffe.isCaffeLayer(L):
ret += [L]
else:
raise Exception("Unsupported layer type for Caffe backend: %s" %
L.get_type())
return (ret, 0)
def passFuseActivations(pipeline):
"Replace (Matrix, Threshold) layer pairs with fused equivalents."
inStages = pipeline
inStages.reverse()
numChanges = 0
ret = []
while len(inStages) > 1:
layerA = inStages.pop()
layerB = inStages.pop()
if lb.isMatrixLayer(layerA) and lb.isThresholdLayer(layerB):
ret += [lb.MatrixThresholdLayer("", layerA, layerB)]
numChanges += 1
else:
ret += [layerA]
inStages.append(layerB)
# pop final element, if any left
if len(inStages) == 1:
ret += [inStages.pop()]
return (ret, numChanges)