diff --git a/example.yaml b/example.yaml index 05a69a172842ab10fd1e0a26c680b45f4925f27e..c80a2414cab848bd6dfe8865f526911d70ada5f0 100644 --- a/example.yaml +++ b/example.yaml @@ -7,7 +7,9 @@ embed_model_data: 1 vlog_level: 0 models: preview_net: + platform: tensorflow model_file_path: path/to/model64.pb # also support http:// and https:// + model_sha256_checksum: 05d92625809dc9edd6484882335c48c043397aed450a168d75eb8b538e86881a input_node: input_node output_node: output_node input_shape: 1,64,64,3 @@ -15,12 +17,18 @@ models: runtime: gpu limit_opencl_kernel_time: 0 dsp_mode: 0 + obfuscate: 1 capture_net: - model_file_path: path/to/model256.pb + platform: caffe + model_file_path: path/to/model.prototxt + weight_file_path: path/to/weight.caffemodel + model_sha256_checksum: 05d92625809dc9edd6484882335c48c043397aed450a168d75eb8b538e86881a + weight_sha256_checksum: 05d92625809dc9edd6484882335c48c043397aed450a168d75eb8b538e86881a input_node: input_node output_node: output_node input_shape: 1,256,256,3 output_shape: 1,256,256,2 - runtime: gpu + runtime: cpu limit_opencl_kernel_time: 1 dsp_mode: 0 + obfuscate: 1 diff --git a/generate_model_code.sh b/generate_model_code.sh index d7721416b6c317b4b963f1d5e7697a11f73f0234..0a780eddd6b12f9ebb6afc028a500e7d70c0030d 100644 --- a/generate_model_code.sh +++ b/generate_model_code.sh @@ -3,29 +3,26 @@ CURRENT_DIR=`dirname $0` source ${CURRENT_DIR}/env.sh -bazel build //lib/python/tools:tf_converter || exit 1 +bazel build //lib/python/tools:converter || exit 1 rm -rf ${MODEL_CODEGEN_DIR} mkdir -p ${MODEL_CODEGEN_DIR} if [ ${DSP_MODE} ]; then - DSP_MODE_FLAG="--dsp_mode=${DSP_MODE}" + DSP_MODE_FLAG="--dsp_mode=${DSP_MODE}" fi -OBFUSCATE=True -if [ "${BENCHMARK_FLAG}" = "1" ]; then - OBFUSCATE=False -fi - -bazel-bin/lib/python/tools/tf_converter --input=${MODEL_FILE_PATH} \ - --model_checksum=${MODEL_SHA256_CHECKSUM} \ - --output=${MODEL_CODEGEN_DIR}/model.cc \ - --input_node=${INPUT_NODE} \ - --output_node=${OUTPUT_NODE} \ - --data_type=${DATA_TYPE} \ - --runtime=${RUNTIME} \ - --output_type=source \ - --template=${LIBMACE_SOURCE_DIR}/lib/python/tools/model.template \ - --model_tag=${MODEL_TAG} \ - --input_shape=${INPUT_SHAPE} \ - ${DSP_MODE_FLAG} \ - --embed_model_data=${EMBED_MODEL_DATA} \ - --obfuscate=${OBFUSCATE} || exit 1 +bazel-bin/lib/python/tools/converter --platform=${PLATFORM} \ + --model_file=${MODEL_FILE_PATH} \ + --weight_file=${WEIGHT_FILE_PATH} \ + --model_checksum=${MODEL_SHA256_CHECKSUM} \ + --output=${MODEL_CODEGEN_DIR}/model.cc \ + --input_node=${INPUT_NODE} \ + --output_node=${OUTPUT_NODE} \ + --data_type=${DATA_TYPE} \ + --runtime=${RUNTIME} \ + --output_type=source \ + --template=${LIBMACE_SOURCE_DIR}/lib/python/tools/model.template \ + --model_tag=${MODEL_TAG} \ + --input_shape=${INPUT_SHAPE} \ + ${DSP_MODE_FLAG} \ + --embed_model_data=${EMBED_MODEL_DATA} \ + --obfuscate=${OBFUSCATE} || exit 1 diff --git a/mace_tools.py b/mace_tools.py index 8ae47d0f8bb9109a056c2f0215726992dca93412..11143a607c5bb78fa1fa448dc147ee21409704cc 100644 --- a/mace_tools.py +++ b/mace_tools.py @@ -17,7 +17,6 @@ import yaml from ConfigParser import ConfigParser - def run_command(command): print("Run command: {}".format(command)) result = subprocess.Popen( @@ -226,6 +225,11 @@ def main(unused_args): os.environ["MODEL_FILE_PATH"] = model_output_dir + "/model.pb" urllib.urlretrieve(model_config["model_file_path"], os.environ["MODEL_FILE_PATH"]) + if model_config["platform"] == "caffe" and (model_config["weight_file_path"].startswith( + "http://") or model_config["weight_file_path"].startswith("https://")): + os.environ["WEIGHT_FILE_PATH"] = model_output_dir + "/model.caffemodel" + urllib.urlretrieve(model_config["weight_file_path"], os.environ["WEIGHT_FILE_PATH"]) + if FLAGS.mode == "build" or FLAGS.mode == "run" or FLAGS.mode == "validate" or FLAGS.mode == "all": generate_random_input(model_output_dir) diff --git a/validate.py b/validate.py index 5c66efe31dcf01ba8aad5cb90eb3b84a4da0adad..62401489a5172af9e44576bfbb855dd44ebb38a0 100644 --- a/validate.py +++ b/validate.py @@ -56,7 +56,7 @@ def valid_output(out_shape, mace_out_file, tf_out_value): def run_model(input_shape): if not gfile.Exists(FLAGS.model_file): print("Input graph file '" + FLAGS.model_file + "' does not exist!") - return -1 + sys.exit(-1) input_graph_def = tf.GraphDef() with gfile.Open(FLAGS.model_file, "rb") as f: diff --git a/validate_caffe.py b/validate_caffe.py new file mode 100644 index 0000000000000000000000000000000000000000..cc50242ffe76fdb2f5a20502f635d6bceb481d1a --- /dev/null +++ b/validate_caffe.py @@ -0,0 +1,152 @@ +import argparse +import sys +import os +import os.path +import numpy as np +from scipy import spatial + +os.environ['GLOG_minloglevel'] = '1' # suprress Caffe verbose prints +import caffe + +# Validation Flow: +# 1. Generate input data +# python validate.py --generate_data true \ +# --input_file input_file +# --input_shape 1,64,64,3 +# +# 2. Use mace_run to run model on phone. +# 3. adb pull the result. +# 4. Compare output data of mace and tf +# python validate.py --model_file tf_model_opt.pb \ +# --input_file input_file \ +# --mace_out_file output_file \ +# --input_node input_node \ +# --output_node output_node \ +# --input_shape 1,64,64,3 \ +# --output_shape 1,64,64,2 + +def generate_data(shape): + np.random.seed() + data = np.random.random(shape) * 2 - 1 + print FLAGS.input_file + data.astype(np.float32).tofile(FLAGS.input_file) + print "Generate input file done." + +def load_data(file): + if os.path.isfile(file): + return np.fromfile(file=file, dtype=np.float32) + else: + return np.empty([0]) + +def valid_output(out_shape, mace_out_file, out_value): + mace_out_value = load_data(mace_out_file) + if mace_out_value.size != 0: + mace_out_value = mace_out_value.reshape(out_shape) + out_shape[1], out_shape[2], out_shape[3] = out_shape[3], out_shape[1], out_shape[2] + out_value = out_value.reshape(out_shape).transpose((0, 2, 3, 1)) + similarity = (1 - spatial.distance.cosine(out_value.flat, mace_out_value.flat)) + print 'MACE VS Caffe similarity: ', similarity + if (FLAGS.mace_runtime == "cpu" and similarity > 0.999) or \ + (FLAGS.mace_runtime == "gpu" and similarity > 0.995) or \ + (FLAGS.mace_runtime == "dsp" and similarity > 0.930): + print '=======================Similarity Test Passed======================' + else: + print '=======================Similarity Test Failed======================' + else: + print '=======================Skip empty node===================' + + +def run_model(input_shape): + if not os.path.isfile(FLAGS.model_file): + print("Input graph file '" + FLAGS.model_file + "' does not exist!") + sys.exit(-1) + if not os.path.isfile(FLAGS.weight_file): + print("Input weight file '" + FLAGS.weight_file + "' does not exist!") + sys.exit(-1) + + caffe.set_mode_cpu() + + net = caffe.Net(FLAGS.model_file, caffe.TEST, weights=FLAGS.weight_file) + + input_value = load_data(FLAGS.input_file) + input_value = input_value.reshape(input_shape).transpose((0, 3, 1, 2)) + net.blobs[FLAGS.input_node].data[0] = input_value + net.forward(start=FLAGS.input_node, end=FLAGS.output_node) + + result = net.blobs[FLAGS.output_node].data[0] + + return result + + +def main(unused_args): + input_shape = [int(x) for x in FLAGS.input_shape.split(',')] + output_shape = [int(x) for x in FLAGS.output_shape.split(',')] + if FLAGS.generate_data: + generate_data(input_shape) + else: + output_value = run_model(input_shape) + valid_output(output_shape, FLAGS.mace_out_file, output_value) + + +def parse_args(): + """Parses command line arguments.""" + parser = argparse.ArgumentParser() + parser.register("type", "bool", lambda v: v.lower() == "true") + parser.add_argument( + "--model_file", + type=str, + default="", + help="caffe prototxt file to load.") + parser.add_argument( + "--weight_file", + type=str, + default="", + help="caffe model file to load.") + parser.add_argument( + "--input_file", + type=str, + default="", + help="input file.") + parser.add_argument( + "--mace_out_file", + type=str, + default="", + help="mace output file to load.") + parser.add_argument( + "--mace_runtime", + type=str, + default="gpu", + help="mace runtime device.") + parser.add_argument( + "--input_shape", + type=str, + default="1,64,64,3", + help="input shape.") + parser.add_argument( + "--output_shape", + type=str, + default="1,64,64,2", + help="output shape.") + parser.add_argument( + "--input_node", + type=str, + default="input_node", + help="input node") + parser.add_argument( + "--output_node", + type=str, + default="output_node", + help="output node") + parser.add_argument( + "--generate_data", + type='bool', + default="false", + help="Generate data or not.") + + return parser.parse_known_args() + + +if __name__ == '__main__': + FLAGS, unparsed = parse_args() + main(unused_args=[sys.argv[0]] + unparsed) + diff --git a/validate_tools.sh b/validate_tools.sh index 17b30a60f245e37d1cee2390b51c09811d474b38..90e8f2eb0f2dd573a41f47fe2b32cf5a1c319085 100644 --- a/validate_tools.sh +++ b/validate_tools.sh @@ -15,12 +15,17 @@ source ${CURRENT_DIR}/env.sh MODEL_OUTPUT_DIR=$1 GENERATE_DATA_OR_NOT=$2 +echo $MODEL_OUTPUT_DIR if [ "$GENERATE_DATA_OR_NOT" = 1 ]; then rm -rf ${MODEL_OUTPUT_DIR}/${INPUT_FILE_NAME} python tools/validate.py --generate_data true \ --input_file=${MODEL_OUTPUT_DIR}/${INPUT_FILE_NAME} \ - --input_shape="${INPUT_SHAPE}" || exit 1 -else + --input_shape="${INPUT_SHAPE}" || exit 1 + exit 0 +fi + +if [ "$PLATFORM" == "tensorflow" ];then + rm -rf ${MODEL_OUTPUT_DIR}/${OUTPUT_FILE_NAME} adb /dev/null)" == "" ]]; then + echo "Build caffe docker" + docker build -t ${IMAGE_NAME} docker/caffe || exit 1 + fi + + if [ ! "$(docker ps -qa -f name=${CONTAINER_NAME})" ]; then + echo "Run caffe container" + docker run -d -it --name ${CONTAINER_NAME} ${IMAGE_NAME} /bin/bash || exit 1 + fi + + if [ "$(docker inspect -f {{.State.Running}} ${CONTAINER_NAME})" == "false" ];then + echo "Start caffe container" + docker start ${CONTAINER_NAME} + fi + + rm -rf ${MODEL_OUTPUT_DIR}/${OUTPUT_FILE_NAME} + adb