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translateWeights2ESP_lib.py
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translateWeights2ESP_lib.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Nov 30 11:56:37 2019
@author: caleb
"""
import numpy as np
import os
#(n, k, h, w) <-- from caffe website
net = 'rnet'
path = '/home/caleb/Downloads/DataSets/mtcnn-head-detection-master/'
#newDir='oNewMISS2/'
cutConvSmall=False
allfiles=os.listdir(os.path.join(path+net+'Out/'))
with open (path+net+'Out/'+net+'Cut16Weights.h','w') as f:
for file in allfiles:
print("processing: "+file)
if '.npy' not in file:
print("SKIPPING: "+file)
continue
c = np.load(path+net+'Out/'+file) #load npy file created by readCaffeModel.py
print("orig Shape")
print(c.shape) #printout the shape
print('\n')
try:
#ESP LIB : N,H,W,C
# translate --> normal/tensorflow format: (H,W,C,N)
#====== CAFFE BLOB FORMAT: (N C H W)
#=======ESP deep learning: (N H W C)
#if 'caffe' in framework:
# t=np.moveaxis(c,1,3)
# t=np.moveaxis(t,1,2)
#USING TRANSPOSE...0
t=c.transpose(0,2,3,1)
#out: N H W C woohoo! done.... should be like (bigNum,same ,same, Channel)
'''
# out: ( n,w,c,h )
#next -> c,h (2,3)
t1 = np.moveaxis(t,2,3)
#out: (n,w,h,c)
#next --> w,h : 1,2
#t = np.moveaxis(t1,2,1)
# out --> n,h,w,c woohoo! translated
'''
print(t.shape)
#print('new shape\n')
shape=t.shape
all=np.reshape(t,-1)#single dimension for printout (C uses flat buffer array)
doHalf = sum(t.shape)
cutConv = False
if doHalf >80:
cutConvSmall = True
print('Cut Smaller')
if doHalf > 400:
print("GOTTA SPLIT THIS CONVOLUTION")
cutConv=True
cutConvSmall=False
#print(len(all))
except:
print("1D weight array")
shape=c.shape
all=np.reshape(c,-1)
cutConv = False
doHalf = sum(shape)
if doHalf >130:
cutConvSmall = True
print('Cut Smaller')
if doHalf > 400:
cutConv = True
cutConvSmall = False
print("GOTTA SPLIT THIS CONVOLUTION")
if not cutConv and not cutConvSmall:
f.writelines("void get"+net+"_"+file[:-4]+"(dl_matrix3d_t* out) { \n ")
f.writelines("// "+str(shape)+" "+file+" from caffemodel\n")
f.writelines("float temp[] = { ")
count = 0
for i in all:
f.writelines(str(i)+",")# put the translated weights into a file
if count %4 ==0:
f.writelines("\n")
count+=1
#so i dont have to type out the function every time...
f.writelines("}; ")
f.writelines("\nsize_t n = sizeof(temp) / sizeof(temp[0]);\n")
f.writelines(" for (int i=0;i<n;i++)\n {\n out->item[i]=temp[i];\n }")
f.writelines("\n}//endFunc\n")
print("#elems: ",count)
if cutConvSmall:
for x in range(2):
smallCuts=2
f.writelines("void get"+net+"_cut"+str(x)+"_"+file[:-4]+"(dl_matrix3d_t* out) { \n ")
f.writelines("// "+str(shape)+" "+file+" from caffemodel\n")
f.writelines("float temp[] = { ")
count = 0
if x == 0:
#do first half
temp = all[0:int(len(all)*1/smallCuts)]#.125)]
if x == 1:
#do second half
temp = all[int(len(all)*1/smallCuts):int(len(all)*2/smallCuts)]#.25)]
if x == 2:
'''
#do first half
temp = all[int(len(all)*2/tCuts):int(len(all)*3/tCuts)]
if x == 3:
#do second half
temp = all[int(len(all)*3/tCuts):int(len(all)*4/tCuts)]
if x == 4:
#do first half
temp = all[int(len(all)*4/tCuts):int(len(all)*5/tCuts)]
if x == 5:
#do second half
temp = all[int(len(all)*5/tCuts):int(len(all)*6/tCuts)]
if x == 6:
#do first half
temp = all[int(len(all)*6/tCuts):int(len(all)*7/tCuts)]
if x == 7:
#do second half
temp = all[int(len(all)*7/tCuts):int(len(all)*8/tCuts)]
if x == 8:
#do first half
temp = all[int(len(all)*8/tCuts):int(len(all)*9/tCuts)]
if x == 9:
#do second half
temp = all[int(len(all)*9/tCuts):int(len(all)*10/tCuts)]
if x == 10:
#do first half
temp = all[int(len(all)*10/tCuts):int(len(all)*11/tCuts)]
if x == 11:
#do second half
temp = all[int(len(all)*10/tCuts):int(len(all)*11/tCuts)]
if x == 12:
#do first half
temp = all[int(len(all)*11/tCuts):]#int(len(all)*11/tCuts)]
'''
for i in temp:
f.writelines(str(i)+",")# put the translated weights into a file
if count %4 ==0:
f.writelines("\n")
count+=1
f.writelines("}; ")
f.writelines("\nsize_t n = sizeof(temp) / sizeof(temp[0]);\n")
f.writelines(" for (int i=0;i<n;i++)\n {\n out->item[i]=temp[i];\n }")
f.writelines("\n}//endFunc\n")
print("#elems: ",count, "at:",x)
cutConvSmall=False
if cutConv:
for x in range(16):
tCuts=16
f.writelines("void get"+net+"_cut"+str(x)+"_"+file[:-4]+"(dl_matrix3d_t* out) { \n ")
f.writelines("// "+str(shape)+" "+file+" from caffemodel\n")
f.writelines("float temp[] = { ")
count = 0
if x == 0:
#do first half
temp = all[0:int(len(all)*1/tCuts)]#.125)]
if x == 1:
#do second half
temp = all[int(len(all)*1/tCuts):int(len(all)*2/tCuts)]#.25)]
if x == 2:
#do first half
temp = all[int(len(all)*2/tCuts):int(len(all)*3/tCuts)]
if x == 3:
#do second half
temp = all[int(len(all)*3/tCuts):int(len(all)*4/tCuts)]
if x == 4:
#do first half
temp = all[int(len(all)*4/tCuts):int(len(all)*5/tCuts)]
if x == 5:
#do second half
temp = all[int(len(all)*5/tCuts):int(len(all)*6/tCuts)]
if x == 6:
#do first half
temp = all[int(len(all)*6/tCuts):int(len(all)*7/tCuts)]
if x == 7:
#do second half
temp = all[int(len(all)*7/tCuts):int(len(all)*8/tCuts)]
if x == 8:
#do first half
temp = all[int(len(all)*8/tCuts):int(len(all)*9/tCuts)]
if x == 9:
#do second half
temp = all[int(len(all)*9/tCuts):int(len(all)*10/tCuts)]
if x == 10:
#do first half
temp = all[int(len(all)*10/tCuts):int(len(all)*11/tCuts)]
if x == 11:
#do second half
temp = all[int(len(all)*10/tCuts):int(len(all)*11/tCuts)]
if x == 12:
#do first half
temp = all[int(len(all)*11/tCuts):int(len(all)*12/tCuts)]#int(len(all)*11/tCuts)]
if x == 13:
#do first half
temp = all[int(len(all)*12/tCuts):int(len(all)*13/tCuts)]
if x == 14:
#do second half
temp = all[int(len(all)*13/tCuts):int(len(all)*14/tCuts)]
if x == 15:
#do first half
temp = all[int(len(all)*14/tCuts):int(len(all)*15/tCuts)]
if x == 16:
#do second half
temp = all[int(len(all)*15/tCuts):int(len(all)*16/tCuts)]
for i in temp:
f.writelines(str(i)+",")# put the translated weights into a file
if count %4 ==0:
f.writelines("\n")
count+=1
f.writelines("}; ")
f.writelines("\nsize_t n = sizeof(temp) / sizeof(temp[0]);\n")
f.writelines(" for (int i=0;i<n;i++)\n {\n out->item[i]=temp[i];\n }")
f.writelines("\n}//endFunc\n")
print("#elems: ",count, "at:",x)
f.close()