まずは、テストコード。
load_and_run_tvm_model.py。この中のResnetの例。
def test_resnet():
# Load the model
model_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
'resnet18')
classes = 1000
device = 'cpu'
model = DLRModel(model_path, device)
# Run the model
image = np.load(os.path.join(os.path.dirname(os.path.abspath(__file__)), 'dog.npy')).astype(np.float32)
#flatten within a input array
input_data = {'data': image}
probabilities = model.run(input_data) #need to be a list of input arrays matching input names
assert probabilities[0].argmax() == 111
昨日の
input_shape = {'data': [1, 3, 224, 224]} # A single RGB 224x224 image
output_shape = [1, 1000] # The probability for each one of the 1,000 classes
device = 'cpu' # Go, Raspberry Pi, go!
model = DLRModel('resnet50', input_shape, output_shape, device)
とは、微妙に違うね。モデルの指定が名前と、入力シェイプと出力シェイプからモデルファイルのパスに変更。DLRModelの定義部は、ここ
def __init__(self, tar_path, dev_type='cpu', dev_id=0):
if not os.path.exists(tar_path):
raise ValueError("tar_path %s doesn't exist" % tar_path)
self.handle = c_void_p()
libpath = os.path.join(os.path.dirname(
os.path.abspath(os.path.expanduser(__file__))), 'libdlr.so')
self.lib = cdll.LoadLibrary(libpath)
self.lib.DLRGetLastError.restype = ctypes.c_char_p
device_table = {
'cpu': 1,
'gpu': 2,
'opencl': 4,
}
self._check_call(self.lib.CreateDLRModel(byref(self.handle),
c_char_p(tar_path.encode()),
c_int(device_table[dev_type]),
c_int(dev_id)))
self.num_inputs = self._get_num_inputs()
self.input_names = []
for i in range(self.num_inputs):
self.input_names.append(self._get_input_name(i))
self.num_outputs = self._get_num_outputs()
self.output_shapes = []
self.output_size_dim = []
for i in range(self.num_outputs):
shape = self._get_output_shape(i)
self.output_shapes.append(shape)
self.lib.CreateDLRModelは、ここ(dlr.cc)
extern "C" int CreateDLRModel(DLRModelHandle* handle,
const char* model_path,
int dev_type, int dev_id) {
API_BEGIN();
const std::string model_path_string(model_path);
DLContext ctx;
ctx.device_type = static_cast<DLDeviceType>(dev_type);
ctx.device_id = dev_id;
DLRModel *model = new DLRModel(model_path_string,
ctx);
*handle = model;
API_END();
}
DLRModelクラスのインスタンスを生成しているだけですよね。
明日に続く。
