Failed to build TensorRTengine #193
Description
Description
Hi，I have used the following code to transform my saved model with TensorRT in TensorFlow 1.14:
from tensorflow.python.compiler.tensorrt import trt_convert as trt
converter = trt.TrtGraphConverter(input_saved_model_dir=input_saved_model_dir)
converter.convert()
converter.save(output_saved_model_dir)
after finished it, I used the following code to inference:
with tf.Session() as sess:
# First load the SavedModel into the session
tf.saved_model.loader.load(
sess, [tf.saved_model.tag_constants.SERVING], output_saved_model_dir)
output = sess.run([output_tensor], feed_dict={input_tensor: input_data})
Although I get the right output, I received the following warning message:
2019-11-01 19:11:24.404448: W tensorflow/compiler/tf2tensorrt/kernels/trt_engine_op.cc:647] Engine creation for TRTEngineOp_22 failed. The native segment will be used instead. Reason: Internal: Failed to build TensorRT engine
2019-11-01 19:11:24.406408: I tensorflow/compiler/tf2tensorrt/kernels/trt_engine_op.cc:632] Building a new TensorRT engine for TRTEngineOp_21 input shapes: [[1,128], [1,128]]
2019-11-01 19:11:24.406463: I tensorflow/compiler/tf2tensorrt/kernels/trt_engine_op.cc:632] Building a new TensorRT engine for TRTEngineOp_23 input shapes: [[1,128], [1,128]]
2019-11-01 19:11:24.408900: W tensorflow/compiler/tf2tensorrt/convert/convert_nodes.cc:1467] Quantization range was not found for (Unnamed Layer* 2) [Fully Connected]_output. This is okay if TensorRT does not need the range (e.g. due to node fusion).
2019-11-01 19:11:24.408921: W tensorflow/compiler/tf2tensorrt/convert/convert_nodes.cc:1467] Quantization range was not found for (Unnamed Layer* 5) [Scale]_output. This is okay if TensorRT does not need the range (e.g. due to node fusion).
2019-11-01 19:11:24.408930: W tensorflow/compiler/tf2tensorrt/convert/convert_nodes.cc:1467] Quantization range was not found for model/inference/post_cbhg/bidirectional_rnn/bw/bw/while/gru_cell/BiasAdd_1. This is okay if TensorRT does not need the range (e.g. due to node fusion).
2019-11-01 19:11:24.408938: W tensorflow/compiler/tf2tensorrt/convert/convert_nodes.cc:1467] Quantization range was not found for (Unnamed Layer* 1) [Shuffle]_output. This is okay if TensorRT does not need the range (e.g. due to node fusion).
2019-11-01 19:11:24.408946: W tensorflow/compiler/tf2tensorrt/convert/convert_nodes.cc:1467] Quantization range was not found for (Unnamed Layer* 4) [Shuffle]_output. This is okay if TensorRT does not need the range (e.g. due to node fusion).
And the cost time is the same as the origin model. I wonder if TensorRT really worked?
Besides, I also tried FP32 FP16 model, the cost time do not changed.
Environment
TensorRT Version: 5.1.5.0
GPU Type: Tesla T4
Nvidia Driver Version: 418.87.01
CUDA Version: 10.1.243
CUDNN Version: 7.6.3
Python Version (if applicable): 3.7.4
TensorFlow Version (if applicable):1.14.1
PyTorch Version (if applicable):
Operating System + Version: Ubuntu 16.04.6 LTS (GNU/Linux 4.4.0-142-generic x86_64)
Baremetal or Container (if container which image + tag):