Hi, I don't know if this issue has been already opened before, however, I am having an issue in training the tiny model. In particular I have downloaded the tiny weights and cfg from pjreddie site and have successfully converted the model into keras one.
Now, when I try to convert the model to tflite, it tells me that the fully quantized model has been converted, with the following output:
2020-09-09 18:36:58.637167: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/nvidia/lib:/usr/local/nvidia/lib64
2020-09-09 18:36:58.637217: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
WARNING:tensorflow:tf.keras.backend.set_learning_phase is deprecated and will be removed after 2020-10-11. To update it, simply pass a True/False value to the training argument of the __call__ method of your layer or model.
2020-09-09 18:37:00.669780: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2020-09-09 18:37:00.670767: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcuda.so.1
2020-09-09 18:37:00.673642: E tensorflow/stream_executor/cuda/cuda_driver.cc:328] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected
2020-09-09 18:37:00.673682: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (a7fb2c0c58ea): /proc/driver/nvidia/version does not exist
2020-09-09 18:37:00.674021: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2020-09-09 18:37:00.674188: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
WARNING:tensorflow:No training configuration found in the save file, so the model was not compiled. Compile it manually.
2020-09-09 18:37:01.104764: I tensorflow/core/grappler/devices.cc:69] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 0
2020-09-09 18:37:01.104999: I tensorflow/core/grappler/clusters/single_machine.cc:356] Starting new session
2020-09-09 18:37:01.105335: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2020-09-09 18:37:01.105626: I tensorflow/core/platform/profile_utils/cpu_utils.cc:108] CPU Frequency: 2200000000 Hz
2020-09-09 18:37:01.109356: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:872] Optimization results for grappler item: graph_to_optimize
function_optimizer: function_optimizer did nothing. time = 0.027ms.
function_optimizer: function_optimizer did nothing. time = 0ms.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/training/tracking/tracking.py:109: Model.state_updates (from tensorflow.python.keras.engine.training) is deprecated and will be removed in a future version.
Instructions for updating:
This property should not be used in TensorFlow 2.0, as updates are applied automatically.
2020-09-09 18:37:04.393755: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/training/tracking/tracking.py:109: Layer.updates (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version.
Instructions for updating:
This property should not be used in TensorFlow 2.0, as updates are applied automatically.
2020-09-09 18:37:07.257855: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/lite/python/convert_saved_model.py:60: load (from tensorflow.python.saved_model.loader_impl) is deprecated and will be removed in a future version.
Instructions for updating:
This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.loader.load or tf.compat.v1.saved_model.load. There will be a new function for importing SavedModels in Tensorflow 2.0.
2020-09-09 18:37:07.478564: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:196] None of the MLIR optimization passes are enabled (registered 0 passes)
2020-09-09 18:37:07.637655: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2020-09-09 18:37:08.125680: I tensorflow/core/grappler/devices.cc:69] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 0
2020-09-09 18:37:08.125892: I tensorflow/core/grappler/clusters/single_machine.cc:356] Starting new session
2020-09-09 18:37:08.126235: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2020-09-09 18:37:08.229160: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:872] Optimization results for grappler item: graph_to_optimize
function_optimizer: Graph size after: 632 nodes (507), 1238 edges (998), time = 13.368ms.
function_optimizer: function_optimizer did nothing. time = 0.351ms.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/lite/python/util.py:326: convert_variables_to_constants (from tensorflow.python.framework.graph_util_impl) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.compat.v1.graph_util.convert_variables_to_constants
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/convert_to_constants.py:856: extract_sub_graph (from tensorflow.python.framework.graph_util_impl) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.compat.v1.graph_util.extract_sub_graph
2020-09-09 18:37:08.605841: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:315] Ignored output_format.
2020-09-09 18:37:08.605918: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:318] Ignored drop_control_dependency.
2020-09-09 18:37:08.678676: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
In the meanwhile, this happens when I install the compiler:
python-learner-zry
commented
3 years ago
Edit #3 (a tough day at the office)
Hi, I don't know if this issue has been already opened before, however, I am having an issue in training the tiny model. In particular I have downloaded the tiny weights and cfg from pjreddie site and have successfully converted the model into keras one.
Now, when I try to convert the model to tflite, it tells me that the fully quantized model has been converted, with the following output:
2020-09-09 18:36:58.637167: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/nvidia/lib:/usr/local/nvidia/lib64 2020-09-09 18:36:58.637217: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine. WARNING:tensorflow:
tf.keras.backend.set_learning_phaseis deprecated and will be removed after 2020-10-11. To update it, simply pass a True/False value to thetrainingargument of the__call__method of your layer or model. 2020-09-09 18:37:00.669780: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set 2020-09-09 18:37:00.670767: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcuda.so.1 2020-09-09 18:37:00.673642: E tensorflow/stream_executor/cuda/cuda_driver.cc:328] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected 2020-09-09 18:37:00.673682: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (a7fb2c0c58ea): /proc/driver/nvidia/version does not exist 2020-09-09 18:37:00.674021: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2020-09-09 18:37:00.674188: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set WARNING:tensorflow:No training configuration found in the save file, so the model was not compiled. Compile it manually. 2020-09-09 18:37:01.104764: I tensorflow/core/grappler/devices.cc:69] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 0 2020-09-09 18:37:01.104999: I tensorflow/core/grappler/clusters/single_machine.cc:356] Starting new session 2020-09-09 18:37:01.105335: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set 2020-09-09 18:37:01.105626: I tensorflow/core/platform/profile_utils/cpu_utils.cc:108] CPU Frequency: 2200000000 Hz 2020-09-09 18:37:01.109356: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:872] Optimization results for grappler item: graph_to_optimize function_optimizer: function_optimizer did nothing. time = 0.027ms. function_optimizer: function_optimizer did nothing. time = 0ms.WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/training/tracking/tracking.py:109: Model.state_updates (from tensorflow.python.keras.engine.training) is deprecated and will be removed in a future version. Instructions for updating: This property should not be used in TensorFlow 2.0, as updates are applied automatically. 2020-09-09 18:37:04.393755: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them. WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/training/tracking/tracking.py:109: Layer.updates (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version. Instructions for updating: This property should not be used in TensorFlow 2.0, as updates are applied automatically. 2020-09-09 18:37:07.257855: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/lite/python/convert_saved_model.py:60: load (from tensorflow.python.saved_model.loader_impl) is deprecated and will be removed in a future version. Instructions for updating: This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.loader.load or tf.compat.v1.saved_model.load. There will be a new function for importing SavedModels in Tensorflow 2.0. 2020-09-09 18:37:07.478564: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:196] None of the MLIR optimization passes are enabled (registered 0 passes) 2020-09-09 18:37:07.637655: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set 2020-09-09 18:37:08.125680: I tensorflow/core/grappler/devices.cc:69] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 0 2020-09-09 18:37:08.125892: I tensorflow/core/grappler/clusters/single_machine.cc:356] Starting new session 2020-09-09 18:37:08.126235: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set 2020-09-09 18:37:08.229160: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:872] Optimization results for grappler item: graph_to_optimize function_optimizer: Graph size after: 632 nodes (507), 1238 edges (998), time = 13.368ms. function_optimizer: function_optimizer did nothing. time = 0.351ms.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/lite/python/util.py:326: convert_variables_to_constants (from tensorflow.python.framework.graph_util_impl) is deprecated and will be removed in a future version. Instructions for updating: Use
tf.compat.v1.graph_util.convert_variables_to_constantsWARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/convert_to_constants.py:856: extract_sub_graph (from tensorflow.python.framework.graph_util_impl) is deprecated and will be removed in a future version. Instructions for updating: Usetf.compat.v1.graph_util.extract_sub_graph2020-09-09 18:37:08.605841: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:315] Ignored output_format. 2020-09-09 18:37:08.605918: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:318] Ignored drop_control_dependency. 2020-09-09 18:37:08.678676: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not setIn the meanwhile, this happens when I install the compiler:
% Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 653 100 653 0 0 24185 0 --:--:-- --:--:-- --:--:-- 25115 OK deb https://packages.cloud.google.com/apt coral-edgetpu-stable main Get:1 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu bionic InRelease [21.3 kB] Hit:2 http://archive.ubuntu.com/ubuntu bionic InRelease Get:3 http://archive.ubuntu.com/ubuntu bionic-updates InRelease [88.7 kB] Get:4 http://ppa.launchpad.net/marutter/c2d4u3.5/ubuntu bionic InRelease [15.4 kB] Get:5 https://cloud.r-project.org/bin/linux/ubuntu bionic-cran35/ InRelease [3,626 B] Get:6 http://archive.ubuntu.com/ubuntu bionic-backports InRelease [74.6 kB] Get:7 http://security.ubuntu.com/ubuntu bionic-security InRelease [88.7 kB] Get:8 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu bionic/main amd64 Packages [43.0 kB] Ign:9 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 InRelease Ign:10 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 InRelease Hit:11 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 Release Get:12 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 Release [564 B] Get:13 http://ppa.launchpad.net/marutter/c2d4u3.5/ubuntu bionic/main Sources [1,864 kB] Get:14 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 Release.gpg [833 B] Get:15 https://cloud.r-project.org/bin/linux/ubuntu bionic-cran35/ Packages [95.7 kB] Get:16 https://packages.cloud.google.com/apt coral-edgetpu-stable InRelease [6,332 B] Get:17 http://ppa.launchpad.net/marutter/c2d4u3.5/ubuntu bionic/main amd64 Packages [900 kB] Get:18 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 Packages [1,384 kB] Get:19 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 Packages [1,425 kB] Get:20 http://archive.ubuntu.com/ubuntu bionic-updates/multiverse amd64 Packages [27.7 kB] Get:21 http://archive.ubuntu.com/ubuntu bionic-updates/restricted amd64 Packages [132 kB] Get:23 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 Packages [47.5 kB] Get:24 http://security.ubuntu.com/ubuntu bionic-security/universe amd64 Packages [897 kB] Get:25 https://packages.cloud.google.com/apt coral-edgetpu-stable/main amd64 Packages [1,284 B] Get:26 http://security.ubuntu.com/ubuntu bionic-security/main amd64 Packages [1,089 kB] Get:27 http://security.ubuntu.com/ubuntu bionic-security/multiverse amd64 Packages [10.1 kB] Get:28 http://security.ubuntu.com/ubuntu bionic-security/restricted amd64 Packages [116 kB] Fetched 8,333 kB in 2s (4,365 kB/s) Reading package lists... Done Reading package lists... Done Building dependency tree
Reading state information... Done The following package was automatically installed and is no longer required: libnvidia-common-440 Use 'sudo apt autoremove' to remove it. The following additional packages will be installed: libedgetpu1-std The following NEW packages will be installed: edgetpu-compiler libedgetpu1-std 0 upgraded, 2 newly installed, 0 to remove and 74 not upgraded. Need to get 6,770 kB of archives. After this operation, 25.5 MB of additional disk space will be used. Get:1 https://packages.cloud.google.com/apt coral-edgetpu-stable/main amd64 libedgetpu1-std amd64 14.1 [311 kB] Get:2 https://packages.cloud.google.com/apt coral-edgetpu-stable/main amd64 edgetpu-compiler amd64 14.1 [6,458 kB] Fetched 6,770 kB in 1s (5,476 kB/s) debconf: unable to initialize frontend: Dialog debconf: (No usable dialog-like program is installed, so the dialog based frontend cannot be used. at /usr/share/perl5/Debconf/FrontEnd/Dialog.pm line 76, <> line 2.) debconf: falling back to frontend: Readline debconf: unable to initialize frontend: Readline debconf: (This frontend requires a controlling tty.) debconf: falling back to frontend: Teletype dpkg-preconfigure: unable to re-open stdin: Selecting previously unselected package libedgetpu1-std:amd64. (Reading database ... 144579 files and directories currently installed.) Preparing to unpack .../libedgetpu1-std_14.1_amd64.deb ... Unpacking libedgetpu1-std:amd64 (14.1) ... Selecting previously unselected package edgetpu-compiler. Preparing to unpack .../edgetpu-compiler_14.1_amd64.deb ... Unpacking edgetpu-compiler (14.1) ... Setting up libedgetpu1-std:amd64 (14.1) ... Setting up edgetpu-compiler (14.1) ... Processing triggers for libc-bin (2.27-3ubuntu1) ... /sbin/ldconfig.real: /usr/local/lib/python3.6/dist-packages/ideep4py/lib/libmkldnn.so.0 is not a symbolic link
Doing so, the tflite file comes out. However, when I try to compile it via edgetpu_compiler output-filename.tflite, it outputs
Edge TPU Compiler version 14.1.317412892 Invalid model: output-filename.tflite Model not quantized
Will wait for news from you, thanks in advance