diff --git a/exporters/trt_exporter.py b/exporters/trt_exporter.py
index 2db74a2..660ddcb 100644
--- a/exporters/trt_exporter.py
+++ b/exporters/trt_exporter.py
@@ -63,15 +63,15 @@ def export_trt(pb_file, output_dir, num_classes=90, neuralet_adaptive_model=1):
         text=True,
         debug_mode=False)
     input_dims = (3, 300, 300)
-    with trt.Builder(TRT_LOGGER) as builder, builder.create_network() as network, trt.UffParser() as parser:
-        builder.max_workspace_size = 1 << 28
+    with trt.Builder(TRT_LOGGER) as builder, builder.create_network() as network, builder.create_builder_config() as builder_config, trt.UffParser() as parser:
+        builder_config.max_workspace_size = 1 << 28
         builder.max_batch_size = 1
-        builder.fp16_mode = True
+        builder_config.set_flag(trt.BuilderFlag.FP16)
 
         parser.register_input('Input', input_dims)
         parser.register_output('MarkOutput_0')
         parser.parse(uff_path, network)
-        engine = builder.build_cuda_engine(network)
+        engine = builder.build_engine(network, builder_config)
         
         buf = engine.serialize()
         engine_path = os.path.join(output_dir, model_file_name + ".bin")
diff --git a/jetson-nano.Dockerfile b/jetson-nano.Dockerfile
index 0083c1b..3bd1901 100644
--- a/jetson-nano.Dockerfile
+++ b/jetson-nano.Dockerfile
@@ -3,9 +3,7 @@
 # 1) build: docker build -f Dockerfile -t "neuralet/jetson-nano:tf-ssd-to-trt" .
 # 2) run: docker run -it --runtime nvidia --privileged --network host -v /PATH_TO_DOCKERFILE_DIRECTORY/:/repo neuralet/jetson-nano:tf-ssd-to-trt
 
-#FROM nvcr.io/nvidia/l4t-base:r32.4.4
-
-FROM nvcr.io/nvidia/l4t-tensorflow:r32.4.4-tf1.15-py3
+FROM nvcr.io/nvidia/l4t-tensorflow:r32.6.1-tf1.15-py3
 ENV TZ=US/Pacific
 RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone