Add utility scripts that we use to repository.
Signed-off-by: Denis Maksimenko <d.maksimenko@partner.samsung.com>
--- /dev/null
+These scripts can be useful for developing/testing nnc. Usage and purpose of the scripts can be found in comments in their source code.
+
+Note that these scripts are just development artifacts and are not supposed to go into production in any form.
+
+infer_testcases.py: run inference with `nnkit` on testcases
+res2bin.py: used by infer_testcases.py to convert resulting hdf5 to binary format
+
+'testcases' folder structure:
+At the moment we use the following structure: a folder for a model contains 'models' and 'testcases' subfolders. The 'models' subfolder contains model that we run inference on, 'testcases' subfolder contains a 'testcase*' folder for each different testcase. Each of those folders in turn contain 'input' with a '.JPEG' file (and '.hdf5' and '.dat' files after running `jpeg2hdf5` script), and 'output' folder where inference results are stored.
\ No newline at end of file
--- /dev/null
+from __future__ import print_function
+import sys
+import glob
+import subprocess
+import res2bin
+import datetime
+
+# This script uses nnkit to run inference for given model on a given data
+# Messages are printed to stderr
+# Usage:
+# -b - specifies path to nnkit build folder, inside which tools/nni is located
+# -f - specifies framework ('tfl' for tflite or 'caf' for caffe) that the model belogs to
+# -t - specifies path to testcase folder (see it's structure in readme)
+# -p - allow some sort of parallelism by processing only a subset of files,
+# you need to specify number of processes and run as much of them
+# manually with diferent numbers
+# -r - infer all testcases regardless of whether the result files are present
+# last argument(s) is the model to infer
+#
+# Example of usage:
+# python3 infer_testcases.py -f tfl -b /mnt/nncc_ci/nncc_new/build/contrib/nnkit -t /mnt/nncc_ci/images/inc_slim/testcases/ -p 10 1 -r /mnt/nncc_ci/images/inc_slim/models/inception_v3_2018.tflite
+#
+
+helpstr = "Expected arguments: -b <path_to_nnkit>" + \
+ "-f (tfl | caf) " + \
+ "-t <testcases_dir> " + \
+ "[-p <nporc> <proc_num>] " + \
+ "[-r] " + \
+ "(<tflite_model_file> | <caffe_prototxt_model> <caffe_caffemodel_file>)"
+
+def eprint(*args, **kwargs):
+ print(*args, file=sys.stderr, **kwargs)
+
+
+nproc = 1
+proc_num = 1
+min_argc = 8
+
+args = {}
+args['-p'] = (1, 1)
+args['-r'] = False
+
+argc = len(sys.argv)
+for i in range(argc):
+ arg = sys.argv[i]
+ if arg =='-r':
+ args[arg] = True
+ elif arg == '-b' or arg == '-f' or arg == '-t':
+ if i + 1 >= argc:
+ eprint(arg, " is missing it's value")
+ eprint(helpstr)
+ exit()
+ args[arg] = sys.argv[i + 1]
+ elif arg == '-p':
+ min_argc += 3
+ if i + 2 >= argc:
+ eprint(arg, " is missing some of it's values")
+ eprint(helpstr)
+ exit()
+ args[arg] = (int(sys.argv[i + 1]), int(sys.argv[i + 2]))
+ elif arg[0] == '-':
+ print('Unsupported argument: ', arg)
+ exit()
+
+if not ('-b' in args and '-f' in args and '-t' in args):
+ eprint('Some arguments are not provided')
+ eprint(helpstr)
+ exit()
+
+fw = args['-f']
+build_path = args['-b']
+testcases_dir = args['-t']
+nproc, proc_num = args['-p']
+remove_existing = args['-r']
+
+if fw == 'tfl':
+ model = sys.argv[-1]
+ print('Model: ', model)
+elif fw == 'caf':
+ model_proto = sys.argv[-2]
+ model_caffe = sys.argv[-1]
+ print('Models: ', model_proto, model_caffe)
+else:
+ eprint('Unsupported framework:', fw)
+ exit()
+
+eprint('started at', datetime.datetime.now())
+print('Framework: ', fw)
+print('Path to nnkit: ', build_path)
+print('Testcases folder: ', testcases_dir)
+
+hdf_suffix = '.hdf5'
+bin_suffix = '.dat'
+
+def get_command_caf(infilename, outfilename, proto, caffemodel):
+ return [build_path + "/tools/nni/nni",
+ "--pre", build_path + "/actions/HDF5/libnnkit_HDF5_import_action.so",
+ "--pre-arg", infilename,
+ "--backend", build_path + "/backends/caffe/libnnkit_caffe_backend.so",
+ "--backend-arg", proto,
+ "--backend-arg", caffemodel,
+ "--post", build_path + "/actions/HDF5/libnnkit_HDF5_export_action.so",
+ "--post-arg", outfilename]
+
+def get_command_tfl(infilename, outfilename, model_file):
+ return [build_path + "/tools/nni/nni",
+ "--pre", build_path + "/actions/HDF5/libnnkit_HDF5_import_action.so",
+ "--pre-arg", infilename,
+ "--backend", build_path + "/backends/tflite/libnnkit_tflite_backend.so",
+ "--backend-arg", model_file,
+ "--post", build_path + "/actions/builtin/libnnkit_show_action.so",
+ "--post", build_path + "/actions/HDF5/libnnkit_HDF5_export_action.so",
+ "--post-arg", outfilename]
+
+testcase_num = 0
+testcases = glob.glob(testcases_dir + '/testcase*')
+
+#testcases = [t
+# for t in testcases
+# if remove_existing
+# or len(glob.glob(t + '/output/output' + hdf_suffix)) == 0
+# or len(glob.glob(t + '/output/output' + bin_suffix)) == 0]
+testcases = testcases[proc_num - 1::nproc]
+
+testcases.sort()
+for testcase in testcases:
+ testcase_num += 1
+ try:
+ infile = glob.glob(testcase + '/input/*' + hdf_suffix)
+ if len(infile) > 0:
+ infile = infile[0]
+ outfile = testcase + '/output/output' + hdf_suffix
+ outfile_bin = testcase + '/output/output' + bin_suffix
+ if len(glob.glob(outfile)) == 0 or remove_existing:
+ if fw == 'tfl':
+ command = get_command_tfl(infile, outfile, model)
+ elif fw == 'caf':
+ command = get_command_caf(infile, outfile, model_proto, model_caffe)
+ #subprocess.call(command, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+ subprocess.call(command)
+ if len(glob.glob(outfile_bin)) == 0 or remove_existing:
+ res2bin.res2bin(outfile, outfile_bin)
+ eprint(testcase_num, "/", len(testcases))
+ else:
+ eprint(testcase, ': input not found')
+ except:
+ eprint(testcase, 'failed')
+
+eprint('ended at', datetime.datetime.now())
+
--- /dev/null
+import numpy as np
+import h5py
+import struct
+import sys
+
+# This script takes hdf5 file and unfolds it in a vector of float values
+# which is then writen in binary format to a given file
+# This is used by infer_testcases.py
+
+def res2bin(infilename, outfilename):
+# print("Input filename: ", infilename)
+# print("Output filename: " , outfilename)
+
+ f = h5py.File(infilename)
+ dset = f[list(f.keys())[0]]
+
+ vals = np.zeros(np.shape(dset), dtype='float32')
+ for i in range(np.size(dset,0)):
+ vals[i,:] = np.asarray(dset[i], dtype='float32')
+ vals = list(np.reshape(vals, (vals.size)))
+
+ with open(outfilename, 'wb') as outfile:
+ outfile.write(struct.pack('f'*len(vals), *vals))
+
+if __name__ == '__main__':
+ argc = len(sys.argv)
+ if (argc > 2):
+ res2bin(sys.argv[1], sys.argv[2])
+ else:
+ print("Not enough arguments, expected: hdf5 filename, output filename")
+ exit()
+
--- /dev/null
+These scripts can be useful for developing/testing nnc. Usage and purpose of the scripts can be found in comments in their source code.
+
+Note that these scripts are just development artifacts and are not supposed to go into production in any form.
+
+jpeg2hdf5.py: prepare '.hdf5' files from '.JPEG' to be used by nnkit. Can also convert those '.JPEG's to binary format along the way.
+
+'testcases' folder structure:
+At the moment we use the following structure: a folder for a model contains 'models' and 'testcases' subfolders. The 'models' subfolder contains model that we run inference on, 'testcases' subfolder contains a 'testcase*' folder for each different testcase. Each of those folders in turn contain 'input' with a '.JPEG' file (and '.hdf5' and '.dat' files after running `jpeg2hdf5` script), and 'output' folder where inference results are stored.
\ No newline at end of file
--- /dev/null
+from PIL import Image
+import numpy as np
+import h5py
+import sys
+import glob
+import subprocess
+import struct
+import datetime
+
+# Generates hdf5 files (and optionally binary files) from JPEGs
+# -f - specifies framework to generate them for
+# -t - specifies testcases directory (see it's structure in readme)
+# -i - specifies input node name of the model that will use them (required by nnkit)
+# -r - if files already exist, rewrites them
+# -b - enable binary file generation
+# -p - allow some sort of parallelism by processing only a subset of files,
+# you need to specify number of processes and run as much of them
+# manually with diferent numbers
+#
+# Example:
+# python3 conv.py -f tfl -t inc_slim/testcases -i input -p 16 1
+#
+
+helpstr = 'Usage: -f (tfl | caf) ' + \
+ '-t <testcases_directory> ' + \
+ '[-i <input_layer_name>] ' + \
+ '[-r] [-b]' + \
+ '[-p <number_of_processes> <process number>]'
+
+supported_frameworks = ['tfl', 'caf']
+args = {}
+# Defaults
+args['-p'] = (1, 1)
+args['-r'] = False
+args['-b'] = False
+
+argc = len(sys.argv)
+for i in range(len(sys.argv)):
+ arg = sys.argv[i]
+ if arg == '-r' or arg == '-b':
+ args[arg] = True
+ elif arg == '-f' or arg == '-t' or arg == '-i':
+ if i + 1 >= argc or sys.argv[i + 1][0] == '-':
+ print(arg, " is missing it's value")
+ print(helpstr)
+ exit()
+ args[arg] = sys.argv[i + 1]
+ elif arg == '-p':
+ if i + 2 >= argc or sys.argv[i + 1][0] == '-' or sys.argv[i + 2][0] == '-':
+ print(arg, " is missing some of it's values")
+ print(helpstr)
+ exit()
+ args[arg] = (int(sys.argv[i + 1]), int(sys.argv[i + 2]))
+ elif arg[0] == '-':
+ print('Unsupported argument: ', arg)
+ exit()
+
+if not ('-f' in args and '-t' in args):
+ print('Some arguments are not provided')
+ print(helpstr)
+ exit()
+
+fw = args['-f']
+if not fw in supported_frameworks:
+ print('Unsupported framework: ', fw)
+ exit()
+
+indirname = args['-t']
+
+if not '-i' in args:
+ if fw == 'caf':
+ inputname = 'data'
+ elif fw =='tfl':
+ inputname = 'input'
+else:
+ inputname = args['-i']
+
+nproc, proc_num = args['-p']
+remove_existing = args['-r']
+gen_binary = args['-b']
+
+print('started at', datetime.datetime.now())
+testcases = glob.glob(indirname + '/testcase*/')
+testcases.sort()
+testcases = testcases[proc_num - 1::nproc]
+
+number = 0
+for testcase in testcases:
+ try:
+ infilename = glob.glob(testcase + 'input/*.JPEG')
+ if len(infilename) > 0:
+ number += 1
+ infilename = infilename[0]
+ outfilename = testcase + 'input/' + infilename.split('/')[-1] + '.hdf5'
+ binoutfilename = testcase + 'input/' + infilename.split('/')[-1] + '.dat'
+ found_hdf = len(glob.glob(outfilename)) != 0
+ found_bin = len(glob.glob(binoutfilename)) != 0
+ if not found_hdf or (not found_bin and gen_binary) or remove_existing:
+ with Image.open(infilename) as im:
+ #TODO: check if order is correct here and in other places
+ h = im.size[0]
+ w = im.size[1]
+ s = im.split()
+ if len(s) == 3:
+ r, g, b = s
+ else:
+ r = s[0]
+ g = s[0]
+ b = s[0]
+ rf = r.convert('F')
+ gf = g.convert('F')
+ bf = b.convert('F')
+ rfb = rf.tobytes()
+ gfb = gf.tobytes()
+ bfb = bf.tobytes()
+
+ made_hdf = False
+ if not found_hdf or remove_existing:
+ if fw == 'tfl':
+ reds = np.fromstring(rfb, count=(h * w), dtype='float32')
+ greens = np.fromstring(gfb, count=(h * w), dtype='float32')
+ blues = np.fromstring(bfb, count=(h * w), dtype='float32')
+
+ dset_shape = (1, h, w, 3)
+ narr = np.ndarray(shape=(0))
+ mixed_ch = []
+ for i in range(h * w):
+ mixed_ch += [reds[i] / 255.0, greens[i] / 255.0, blues[i] / 255.0]
+ narr = np.append(narr, mixed_ch)
+ elif fw == 'caf':
+ dset_shape = (1, 3, h, w)
+ narr = np.fromstring(rfb + gfb + bfb, count=(3 * h * w), dtype='float32')
+ for i in range(3 * h * w):
+ narr[i] /= 255.0
+ if remove_existing:
+ subprocess.call(['rm', '-f', outfilename])
+ with h5py.File(outfilename) as f:
+ # nnkit hdf5_import asserts to use IEEE_F32BE, which is >f4 in numpy
+ dset = f.require_dataset(inputname, dset_shape, dtype='>f4')
+ dset[0] = np.reshape(narr, dset_shape)
+ made_hdf = True
+
+ if gen_binary and (not found_bin or remove_existing):
+ if fw == 'tfl' and made_hdf:
+ l = narr.tolist()
+ else:
+ reds = np.fromstring(rfb, count=(h * w), dtype='float32')
+ greens = np.fromstring(gfb, count=(h * w), dtype='float32')
+ blues = np.fromstring(bfb, count=(h * w), dtype='float32')
+ l = np.ndarray(shape=(0))
+ mixed_ch = []
+ for i in range(h * w):
+ mixed_ch += [reds[i] / 255.0, greens[i] / 255.0, blues[i] / 255.0]
+ l = np.append(l, mixed_ch)
+ l = l.tolist()
+ with open(binoutfilename, 'wb') as out:
+ out.write(struct.pack('f'*len(l), *l))
+ print(number, ': ' + testcase + ' Done')
+ else:
+ print(testcase, ' nothing to do')
+ else:
+ print(testcase, ' JPEG not found')
+ except:
+ print(testcase, " FAILED")
+print('started at', ended.datetime.now())
+
projects / platform / core / ml / nnfw.git / commitdiff