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Ubuntu16.04+cuda10.0+cudnn7.6配置tensorflow1.x环境
作者：AllinToyou | 2024-06-08 00:52:11
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cuda10.0+cudnn7.6
现阶段有多种深度学习框架，应用较多的主要是tensorflow、pytorch以及百度公司的paddlepaddle。个人刚开始使用的深度学习框架是基于pytorch的mmdetection，来自于商汤科技公司，学习和使用了接近一年，利用其跑工程，学习网络等，主要是目标检测方向的应用，整体有较好把握，收获较大。近期，老板事物不多，个人时间较充裕，于是开始学习使用tensorflow，进一步了解其他的深度学习框架。下面分享一下我的环境安装过程：
tensorflow的环境配置不比mmdetection简单，但是由于有了后者的配环境经验，所以摸索起来即使遇到了困难，也能凭经验一步一步解决。我的系统是Ubuntu16.04，之前就装好了cuda，cudatoolkit和cudnn都已经版本对应了，所以少了一些前期的准备工作。
但是实际安装tensorflow的时候还是遇到了很多困难，原先计划安装tensorflow2.x版本，也从tensorflow的官网去找一些官方的安装教程，想避免走一些弯路，但最后下来，我发现我按照官网的教程倒是走了不少弯路，而且还没有成功。按照官网的教程cuda10.0是可以安装2.x版本的，但个人实践经验后还是觉得不靠谱，也和自己不熟悉有关吧，比如docker、bazel构建tensorflow等，操作起来不方便，而且也没有必要，官网把这些放在一起是真的浪费我的时间。
我开始装的是2.0版本，开始按照官网教程来的，有些指令执行不了，换方式也没解决。最后放弃了官方教程，从网上找了一些和自己环境差不多的博客进行参考，指令倒是都顺利装完了，但是跑实例的时候跑不出来，试着修改问题，但找不到源码位置，所以这次的尝试又夭折了。我后面把出现的问题找了一下：
(tf2) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf2/tensorflow/workspace/traning_demo# python model_main_tf2.py --model_dir=models/my_ssd_mobilenet_v2 --pipeline_config_path=models/my_ssd_mobilenet_v2/pipeline.config WARNING:tensorflow:There are non-GPU devices in `tf.distribute.Strategy`, not using nccl allreduce. W0408 14:14:37.727346 140687491278656 cross_device_ops.py:1321] There are non-GPU devices in `tf.distribute.Strategy`, not using nccl allreduce. INFO:tensorflow:Using MirroredStrategy with devices ('/job:localhost/replica:0/task:0/device:CPU:0',) I0408 14:14:37.727849 140687491278656 mirrored_strategy.py:350] Using MirroredStrategy with devices ('/job:localhost/replica:0/task:0/device:CPU:0',) INFO:tensorflow:Maybe overwriting train_steps: None I0408 14:14:37.742078 140687491278656 config_util.py:552] Maybe overwriting train_steps: None INFO:tensorflow:Maybe overwriting use_bfloat16: False I0408 14:14:37.742265 140687491278656 config_util.py:552] Maybe overwriting use_bfloat16: False WARNING:tensorflow:From /root/anaconda3/envs/tf2/lib/python3.7/site-packages/object_detection/model_lib_v2.py:546: StrategyBase.experimental_distribute_datasets_from_function (from tensorflow.python.distribute.distribute_lib) is deprecated and will be removed in a future version. Instructions for updating: rename to distribute_datasets_from_function W0408 14:14:37.806042 140687491278656 deprecation.py:339] From /root/anaconda3/envs/tf2/lib/python3.7/site-packages/object_detection/model_lib_v2.py:546: StrategyBase.experimental_distribute_datasets_from_function (from tensorflow.python.distribute.distribute_lib) is deprecated and will be removed in a future version. Instructions for updating: rename to distribute_datasets_from_function INFO:tensorflow:Reading unweighted datasets: ['images/train.record'] I0408 14:14:37.813343 140687491278656 dataset_builder.py:163] Reading unweighted datasets: ['images/train.record'] INFO:tensorflow:Reading record datasets for input file: ['images/train.record'] I0408 14:14:37.814830 140687491278656 dataset_builder.py:80] Reading record datasets for input file: ['images/train.record'] INFO:tensorflow:Number of filenames to read: 1 I0408 14:14:37.814923 140687491278656 dataset_builder.py:81] Number of filenames to read: 1 WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards. W0408 14:14:37.814991 140687491278656 dataset_builder.py:88] num_readers has been reduced to 1 to match input file shards. WARNING:tensorflow:From /root/anaconda3/envs/tf2/lib/python3.7/site-packages/object_detection/builders/dataset_builder.py:105: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.experimental_deterministic`. W0408 14:14:37.817644 140687491278656 deprecation.py:339] From /root/anaconda3/envs/tf2/lib/python3.7/site-packages/object_detection/builders/dataset_builder.py:105: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.experimental_deterministic`. WARNING:tensorflow:From /root/anaconda3/envs/tf2/lib/python3.7/site-packages/object_detection/builders/dataset_builder.py:237: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.data.Dataset.map() W0408 14:14:37.847065 140687491278656 deprecation.py:339] From /root/anaconda3/envs/tf2/lib/python3.7/site-packages/object_detection/builders/dataset_builder.py:237: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.data.Dataset.map() WARNING:tensorflow:From /root/anaconda3/envs/tf2/lib/python3.7/site-packages/tensorflow/python/util/dispatch.py:201: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version. Instructions for updating: Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead. W0408 14:14:43.827106 140687491278656 deprecation.py:339] From /root/anaconda3/envs/tf2/lib/python3.7/site-packages/tensorflow/python/util/dispatch.py:201: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version. Instructions for updating: Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead. WARNING:tensorflow:From /root/anaconda3/envs/tf2/lib/python3.7/site-packages/tensorflow/python/util/dispatch.py:201: sample_distorted_bounding_box (from tensorflow.python.ops.image_ops_impl) is deprecated and will be removed in a future version. Instructions for updating: `seed2` arg is deprecated.Use sample_distorted_bounding_box_v2 instead. W0408 14:14:47.471886 140687491278656 deprecation.py:339] From /root/anaconda3/envs/tf2/lib/python3.7/site-packages/tensorflow/python/util/dispatch.py:201: sample_distorted_bounding_box (from tensorflow.python.ops.image_ops_impl) is deprecated and will be removed in a future version. Instructions for updating: `seed2` arg is deprecated.Use sample_distorted_bounding_box_v2 instead. WARNING:tensorflow:From /root/anaconda3/envs/tf2/lib/python3.7/site-packages/object_detection/inputs.py:282: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. W0408 14:14:49.574233 140687491278656 deprecation.py:339] From /root/anaconda3/envs/tf2/lib/python3.7/site-packages/object_detection/inputs.py:282: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. /root/anaconda3/envs/tf2/lib/python3.7/site-packages/tensorflow/python/keras/backend.py:434: UserWarning: `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. warnings.warn('`tf.keras.backend.set_learning_phase` is deprecated and ' INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 14:15:02.898844 140671520339712 convolutional_keras_box_predictor.py:154] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 14:15:02.899355 140671520339712 convolutional_keras_box_predictor.py:154] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 14:15:02.899594 140671520339712 convolutional_keras_box_predictor.py:154] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 14:15:02.899832 140671520339712 convolutional_keras_box_predictor.py:154] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 14:15:02.900039 140671520339712 convolutional_keras_box_predictor.py:154] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 14:15:02.900240 140671520339712 convolutional_keras_box_predictor.py:154] depth of additional conv before box predictor: 0 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._groundtruth_lists W0408 14:15:23.303248 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._groundtruth_lists WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor W0408 14:15:23.303692 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor WARNING:tensorflow:Unresolved object in checkpoint: (root).model._batched_prediction_tensor_names W0408 14:15:23.303777 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._batched_prediction_tensor_names WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads W0408 14:15:23.303838 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._sorted_head_names W0408 14:15:23.303881 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._sorted_head_names WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._shared_nets W0408 14:15:23.303931 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._shared_nets WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings W0408 14:15:23.303973 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background W0408 14:15:23.304014 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._shared_nets.0 W0408 14:15:23.304055 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._shared_nets.0 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._shared_nets.1 W0408 14:15:23.304095 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._shared_nets.1 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._shared_nets.2 W0408 14:15:23.304135 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._shared_nets.2 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._shared_nets.3 W0408 14:15:23.304175 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._shared_nets.3 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._shared_nets.4 W0408 14:15:23.304216 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._shared_nets.4 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._shared_nets.5 W0408 14:15:23.304257 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._shared_nets.5 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.0 W0408 14:15:23.304313 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.0 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.1 W0408 14:15:23.304363 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.1 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.2 W0408 14:15:23.304403 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.2 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.3 W0408 14:15:23.304442 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.3 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.4 W0408 14:15:23.304482 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.4 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.5 W0408 14:15:23.304522 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.5 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.0 W0408 14:15:23.304562 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.0 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.1 W0408 14:15:23.304601 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.1 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.2 W0408 14:15:23.304653 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.2 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.3 W0408 14:15:23.304707 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.3 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.4 W0408 14:15:23.304747 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.4 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.5 W0408 14:15:23.304787 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.5 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.0._box_encoder_layers W0408 14:15:23.304844 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.0._box_encoder_layers WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.1._box_encoder_layers W0408 14:15:23.304888 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.1._box_encoder_layers WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.2._box_encoder_layers W0408 14:15:23.304928 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.2._box_encoder_layers WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.3._box_encoder_layers W0408 14:15:23.304969 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.3._box_encoder_layers WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.4._box_encoder_layers W0408 14:15:23.305009 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.4._box_encoder_layers WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.5._box_encoder_layers W0408 14:15:23.305050 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.5._box_encoder_layers WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.0._class_predictor_layers W0408 14:15:23.305090 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.0._class_predictor_layers WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.1._class_predictor_layers W0408 14:15:23.305131 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.1._class_predictor_layers WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.2._class_predictor_layers W0408 14:15:23.305172 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.2._class_predictor_layers WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.3._class_predictor_layers W0408 14:15:23.305213 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.3._class_predictor_layers WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.4._class_predictor_layers W0408 14:15:23.305254 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.4._class_predictor_layers WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.5._class_predictor_layers W0408 14:15:23.305295 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.5._class_predictor_layers WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.0._box_encoder_layers.0 W0408 14:15:23.305337 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.0._box_encoder_layers.0 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.1._box_encoder_layers.0 W0408 14:15:23.305378 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.1._box_encoder_layers.0 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.2._box_encoder_layers.0 W0408 14:15:23.305418 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.2._box_encoder_layers.0 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.3._box_encoder_layers.0 W0408 14:15:23.305459 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.3._box_encoder_layers.0 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.4._box_encoder_layers.0 W0408 14:15:23.305498 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.4._box_encoder_layers.0 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.5._box_encoder_layers.0 W0408 14:15:23.305538 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.5._box_encoder_layers.0 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.0._class_predictor_layers.0 W0408 14:15:23.305578 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.0._class_predictor_layers.0 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.1._class_predictor_layers.0 W0408 14:15:23.305619 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.1._class_predictor_layers.0 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.2._class_predictor_layers.0 W0408 14:15:23.305659 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.2._class_predictor_layers.0 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.3._class_predictor_layers.0 W0408 14:15:23.305704 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.3._class_predictor_layers.0 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.4._class_predictor_layers.0 W0408 14:15:23.305745 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.4._class_predictor_layers.0 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.5._class_predictor_layers.0 W0408 14:15:23.305785 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.5._class_predictor_layers.0 WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.0._box_encoder_layers.0.kernel W0408 14:15:23.305828 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.0._box_encoder_layers.0.kernel WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.0._box_encoder_layers.0.bias W0408 14:15:23.305869 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.0._box_encoder_layers.0.bias WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.1._box_encoder_layers.0.kernel W0408 14:15:23.305909 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.1._box_encoder_layers.0.kernel WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.1._box_encoder_layers.0.bias W0408 14:15:23.305949 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.1._box_encoder_layers.0.bias WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.2._box_encoder_layers.0.kernel W0408 14:15:23.305990 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.2._box_encoder_layers.0.kernel WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.2._box_encoder_layers.0.bias W0408 14:15:23.306030 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.2._box_encoder_layers.0.bias WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.3._box_encoder_layers.0.kernel W0408 14:15:23.306070 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.3._box_encoder_layers.0.kernel WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.3._box_encoder_layers.0.bias W0408 14:15:23.306112 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.3._box_encoder_layers.0.bias WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.4._box_encoder_layers.0.kernel W0408 14:15:23.306151 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.4._box_encoder_layers.0.kernel WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.4._box_encoder_layers.0.bias W0408 14:15:23.306191 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.4._box_encoder_layers.0.bias WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.5._box_encoder_layers.0.kernel W0408 14:15:23.306232 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.5._box_encoder_layers.0.kernel WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.5._box_encoder_layers.0.bias W0408 14:15:23.306275 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.box_encodings.5._box_encoder_layers.0.bias WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.0._class_predictor_layers.0.kernel W0408 14:15:23.306315 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.0._class_predictor_layers.0.kernel WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.0._class_predictor_layers.0.bias W0408 14:15:23.306356 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.0._class_predictor_layers.0.bias WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.1._class_predictor_layers.0.kernel W0408 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(root).model._box_predictor._prediction_heads.class_predictions_with_background.2._class_predictor_layers.0.bias W0408 14:15:23.306519 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.2._class_predictor_layers.0.bias WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.3._class_predictor_layers.0.kernel W0408 14:15:23.306560 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.3._class_predictor_layers.0.kernel WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.3._class_predictor_layers.0.bias W0408 14:15:23.306600 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.3._class_predictor_layers.0.bias WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.4._class_predictor_layers.0.kernel W0408 14:15:23.306641 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.4._class_predictor_layers.0.kernel WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.4._class_predictor_layers.0.bias W0408 14:15:23.306685 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.4._class_predictor_layers.0.bias WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.5._class_predictor_layers.0.kernel W0408 14:15:23.306726 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.5._class_predictor_layers.0.kernel WARNING:tensorflow:Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.5._class_predictor_layers.0.bias W0408 14:15:23.306768 140687491278656 util.py:161] Unresolved object in checkpoint: (root).model._box_predictor._prediction_heads.class_predictions_with_background.5._class_predictor_layers.0.bias WARNING:tensorflow:A checkpoint was restored (e.g. tf.train.Checkpoint.restore or tf.keras.Model.load_weights) but not all checkpointed values were used. See above for specific issues. Use expect_partial() on the load status object, e.g. tf.train.Checkpoint.restore(...).expect_partial(), to silence these warnings, or use assert_consumed() to make the check explicit. See https://www.tensorflow.org/guide/checkpoint#loading_mechanics for details. W0408 14:15:23.306821 140687491278656 util.py:169] A checkpoint was restored (e.g. tf.train.Checkpoint.restore or tf.keras.Model.load_weights) but not all checkpointed values were used. See above for specific issues. Use expect_partial() on the load status object, e.g. tf.train.Checkpoint.restore(...).expect_partial(), to silence these warnings, or use assert_consumed() to make the check explicit. See https://www.tensorflow.org/guide/checkpoint#loading_mechanics for details. WARNING:tensorflow:From /root/anaconda3/envs/tf2/lib/python3.7/site-packages/tensorflow/python/util/deprecation.py:605: calling map_fn_v2 (from tensorflow.python.ops.map_fn) with dtype is deprecated and will be removed in a future version. Instructions for updating: Use fn_output_signature instead W0408 14:15:32.760873 140644878092032 deprecation.py:537] From /root/anaconda3/envs/tf2/lib/python3.7/site-packages/tensorflow/python/util/deprecation.py:605: calling map_fn_v2 (from tensorflow.python.ops.map_fn) with dtype is deprecated and will be removed in a future version. Instructions for updating: Use fn_output_signature instead
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最后就这么卡住了，看开始报的问题，还无法调用GPU,后面我查看工程文件，还是增加了一些训练的内容，也就是环境是搭上了，但并不对。我也怀疑是版本的问题，于是下一步改为装1.x版本。
针对无法调用gpu这个问题，我上网搜了我报错的地方，发现没什么有效的解决方法，我在执行完安装tensorflow的命令后验证是否可以使用GPU上找到了一点思路，我不按官网说的linux版本使用pip install tensorflow来安装，我直接装我这个版本可以安装的tensorflow-gpu，再去执行验证指令，发现可以调用GPU，我再下一步安装对应版本的其他配置文件。这是我使用的验证指令：
import tensorflow as tf
tf.test.is_gpu_available()
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发现返回的是true 说明可以调用GPU了
装完之后，我的环境是这样的：
(tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/workspace/training_demo# conda list # packages in environment at /root/anaconda3/envs/tf1: # # Name Version Build Channel _libgcc_mutex 0.1 main _tflow_select 2.1.0 gpu absl-py 0.12.0 py36h06a4308_0 astor 0.8.1 py36h06a4308_0 blas 1.0 mkl c-ares 1.17.1 h27cfd23_0 ca-certificates 2021.1.19 h06a4308_1 certifi 2020.12.5 py36h06a4308_0 contextlib2 0.6.0.post1 pypi_0 pypi coverage 5.5 py36h27cfd23_2 cudatoolkit 10.0.130 0 cudnn 7.6.5 cuda10.0_0 cupti 10.0.130 0 cycler 0.10.0 pypi_0 pypi cython 0.29.22 py36h2531618_0 gast 0.2.2 py36_0 google-pasta 0.2.0 py_0 grpcio 1.36.1 py36h2157cd5_1 h5py 2.10.0 py36hd6299e0_1 hdf5 1.10.6 hb1b8bf9_0 importlib-metadata 3.7.3 py36h06a4308_1 intel-openmp 2020.2 254 keras-applications 1.0.8 py_1 keras-preprocessing 1.1.2 pyhd3eb1b0_0 kiwisolver 1.3.1 pypi_0 pypi ld_impl_linux-64 2.33.1 h53a641e_7 libffi 3.3 he6710b0_2 libgcc-ng 9.1.0 hdf63c60_0 libgfortran-ng 7.3.0 hdf63c60_0 libprotobuf 3.14.0 h8c45485_0 libstdcxx-ng 9.1.0 hdf63c60_0 lvis 0.5.3 pypi_0 pypi lxml 4.6.3 pypi_0 pypi markdown 3.3.4 py36h06a4308_0 matplotlib 3.3.4 pypi_0 pypi mkl 2020.2 256 mkl-service 2.3.0 py36he8ac12f_0 mkl_fft 1.3.0 py36h54f3939_0 mkl_random 1.1.1 py36h0573a6f_0 ncurses 6.2 he6710b0_1 numpy 1.19.2 py36h54aff64_0 numpy-base 1.19.2 py36hfa32c7d_0 object-detection 0.1 pypi_0 pypi opencv-python 4.5.1.48 pypi_0 pypi openssl 1.1.1k h27cfd23_0 opt_einsum 3.1.0 py_0 pandas 1.1.5 pypi_0 pypi pillow 8.2.0 pypi_0 pypi pip 21.0.1 py36h06a4308_0 protobuf 3.14.0 py36h2531618_1 pycocotools 2.0.2 pypi_0 pypi pyparsing 2.4.7 pypi_0 pypi python 3.6.13 hdb3f193_0 python-dateutil 2.8.1 pypi_0 pypi pytz 2021.1 pypi_0 pypi readline 8.1 h27cfd23_0 scipy 1.5.2 py36h0b6359f_0 setuptools 52.0.0 py36h06a4308_0 six 1.15.0 py36h06a4308_0 sqlite 3.35.4 hdfb4753_0 tensorboard 1.15.0 pyhb230dea_0 tensorflow 1.15.0 gpu_py36h5a509aa_0 tensorflow-base 1.15.0 gpu_py36h9dcbed7_0 tensorflow-estimator 1.15.1 pyh2649769_0 tensorflow-gpu 1.15.0 h0d30ee6_0 termcolor 1.1.0 py36h06a4308_1 tf-slim 1.1.0 pypi_0 pypi tk 8.6.10 hbc83047_0 typing_extensions 3.7.4.3 pyha847dfd_0 webencodings 0.5.1 py36_1 werkzeug 0.16.1 py_0 wheel 0.36.2 pyhd3eb1b0_0 wrapt 1.12.1 py36h7b6447c_1 xz 5.2.5 h7b6447c_0 zipp 3.4.1 pyhd3eb1b0_0 zlib 1.2.11 h7b6447c_3
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我也把我的安装过程大致整理了一下：
(tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1# conda install protobuf Collecting package metadata (current_repodata.json): done Solving environment: done # All requested packages already installed. (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1# cd tensorflow/ (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow# mkdir workspace (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow# cd workspace/ (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/workspace# mkdir training_demo (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/workspace# cd training_demo/ (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/workspace/training_demo# chmod -R a=rwx ./ (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/workspace/training_demo# mkdir annotations (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/workspace/training_demo# mkdir exported-models (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/workspace/training_demo# mkdir images (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/workspace/training_demo# mkdir models (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/workspace/training_demo# mkdir pretrained-models (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/workspace/training_demo# chmod -R a=rwx ./ (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/workspace/training_demo# cd ../.. (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow# cd models/research/ (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research# protoc object_detection/protos/*.proto --python_out=. (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research# git clone https://github.com/cocodataset/cocoapi.git Cloning into 'cocoapi'... remote: Enumerating objects: 975, done. remote: Total 975 (delta 0), reused 0 (delta 0), pack-reused 975 Receiving objects: 100% (975/975), 11.72 MiB | 5.96 MiB/s, done. Resolving deltas: 100% (576/576), done. (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research# cd cocoapi/PythonAPI/ (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research/cocoapi/PythonAPI# make python setup.py build_ext --inplace running build_ext cythoning pycocotools/_mask.pyx to pycocotools/_mask.c /root/anaconda3/envs/tf1/lib/python3.6/site-packages/Cython/Compiler/Main.py:369: FutureWarning: Cython directive 'language_level' not set, using 2 for now (Py2). This will change in a later release! File: /nfs/private/junnxie/tf1/tensorflow/models/research/cocoapi/PythonAPI/pycocotools/_mask.pyx tree = Parsing.p_module(s, pxd, full_module_name) building 'pycocotools._mask' extension creating build creating build/common creating build/temp.linux-x86_64-3.6 creating build/temp.linux-x86_64-3.6/pycocotools gcc -pthread -B /root/anaconda3/envs/tf1/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/root/.local/lib/python3.6/site-packages/numpy/core/include -I../common -I/root/anaconda3/envs/tf1/include/python3.6m -c ../common/maskApi.c -o build/temp.linux-x86_64-3.6/../common/maskApi.o -Wno-cpp -Wno-unused-function -std=c99 ../common/maskApi.c: In function ‘rleDecode’: ../common/maskApi.c:46:7: warning: this ‘for’ clause does not guard... [-Wmisleading-indentation] for( k=0; k<R[i].cnts[j]; k++ ) *(M++)=v; v=!v; }} ^~~ ../common/maskApi.c:46:49: note: ...this statement, but the latter is misleadingly indented as if it were guarded by the ‘for’ for( k=0; k<R[i].cnts[j]; k++ ) *(M++)=v; v=!v; }} ^ ../common/maskApi.c: In function ‘rleFrPoly’: ../common/maskApi.c:166:3: warning: this ‘for’ clause does not guard... [-Wmisleading-indentation] for(j=0; j<k; j++) x[j]=(int)(scale*xy[j*2+0]+.5); x[k]=x[0]; ^~~ ../common/maskApi.c:166:54: note: ...this statement, but the latter is misleadingly indented as if it were guarded by the ‘for’ for(j=0; j<k; j++) x[j]=(int)(scale*xy[j*2+0]+.5); x[k]=x[0]; ^ ../common/maskApi.c:167:3: warning: this ‘for’ clause does not guard... [-Wmisleading-indentation] for(j=0; j<k; j++) y[j]=(int)(scale*xy[j*2+1]+.5); y[k]=y[0]; ^~~ ../common/maskApi.c:167:54: note: ...this statement, but the latter is misleadingly indented as if it were guarded by the ‘for’ for(j=0; j<k; j++) y[j]=(int)(scale*xy[j*2+1]+.5); y[k]=y[0]; ^ ../common/maskApi.c: In function ‘rleToString’: ../common/maskApi.c:212:7: warning: this ‘if’ clause does not guard... [-Wmisleading-indentation] if(more) c |= 0x20; c+=48; s[p++]=c; ^~ ../common/maskApi.c:212:27: note: ...this statement, but the latter is misleadingly indented as if it were guarded by the ‘if’ if(more) c |= 0x20; c+=48; s[p++]=c; ^ ../common/maskApi.c: In function ‘rleFrString’: ../common/maskApi.c:220:3: warning: this ‘while’ clause does not guard... [-Wmisleading-indentation] while( s[m] ) m++; cnts=malloc(sizeof(uint)*m); m=0; ^~~~~ ../common/maskApi.c:220:22: note: ...this statement, but the latter is misleadingly indented as if it were guarded by the ‘while’ while( s[m] ) m++; cnts=malloc(sizeof(uint)*m); m=0; ^~~~ ../common/maskApi.c:228:5: warning: this ‘if’ clause does not guard... [-Wmisleading-indentation] if(m>2) x+=(long) cnts[m-2]; cnts[m++]=(uint) x; ^~ ../common/maskApi.c:228:34: note: ...this statement, but the latter is misleadingly indented as if it were guarded by the ‘if’ if(m>2) x+=(long) cnts[m-2]; cnts[m++]=(uint) x; ^~~~ ../common/maskApi.c: In function ‘rleToBbox’: ../common/maskApi.c:141:31: warning: ‘xp’ may be used uninitialized in this function [-Wmaybe-uninitialized] if(j%2==0) xp=x; else if(xp<x) { ys=0; ye=h-1; } ^ gcc -pthread -B /root/anaconda3/envs/tf1/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/root/.local/lib/python3.6/site-packages/numpy/core/include -I../common -I/root/anaconda3/envs/tf1/include/python3.6m -c pycocotools/_mask.c -o build/temp.linux-x86_64-3.6/pycocotools/_mask.o -Wno-cpp -Wno-unused-function -std=c99 creating build/lib.linux-x86_64-3.6 creating build/lib.linux-x86_64-3.6/pycocotools gcc -pthread -shared -B /root/anaconda3/envs/tf1/compiler_compat -L/root/anaconda3/envs/tf1/lib -Wl,-rpath=/root/anaconda3/envs/tf1/lib -Wl,--no-as-needed -Wl,--sysroot=/ build/temp.linux-x86_64-3.6/../common/maskApi.o build/temp.linux-x86_64-3.6/pycocotools/_mask.o -o build/lib.linux-x86_64-3.6/pycocotools/_mask.cpython-36m-x86_64-linux-gnu.so copying build/lib.linux-x86_64-3.6/pycocotools/_mask.cpython-36m-x86_64-linux-gnu.so -> pycocotools rm -rf build (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research/cocoapi/PythonAPI# cp -r pycocotools /nfs/private/junnxie/tf1/tensorflow/models/research/ (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research/cocoapi/PythonAPI# cd ../.. (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research# cp object_detection/packages/tf1/setup.py . (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research# python Python 3.6.13 |Anaconda, Inc.| (default, Feb 23 2021, 21:15:04) [GCC 7.3.0] on linux Type "help", "copyright", "credits" or "license" for more information. >>> import tensorflow as tf >>> tf.__version__ '1.15.0' >>> (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research# python -m pip install . Processing /nfs/private/junnxie/tf1/tensorflow/models/research Collecting pillow Downloading Pillow-8.2.0-cp36-cp36m-manylinux1_x86_64.whl (3.0 MB) |????????????????????????????????| 3.0 MB 1.9 MB/s Collecting lxml Downloading lxml-4.6.3-cp36-cp36m-manylinux1_x86_64.whl (5.5 MB) |????????????????????????????????| 5.5 MB 18.7 MB/s Collecting matplotlib Using cached matplotlib-3.3.4-cp36-cp36m-manylinux1_x86_64.whl (11.5 MB) Requirement already satisfied: Cython in /root/anaconda3/envs/tf1/lib/python3.6/site-packages (from object-detection==0.1) (0.29.22) Collecting contextlib2 Using cached contextlib2-0.6.0.post1-py2.py3-none-any.whl (9.8 kB) Collecting tf-slim Using cached tf_slim-1.1.0-py2.py3-none-any.whl (352 kB) Requirement already satisfied: six in /root/anaconda3/envs/tf1/lib/python3.6/site-packages (from object-detection==0.1) (1.15.0) Collecting pycocotools Using cached pycocotools-2.0.2.tar.gz (23 kB) Collecting lvis Using cached lvis-0.5.3-py3-none-any.whl (14 kB) Requirement already satisfied: scipy in /root/anaconda3/envs/tf1/lib/python3.6/site-packages (from object-detection==0.1) (1.5.2) Collecting pandas Downloading pandas-1.1.5-cp36-cp36m-manylinux1_x86_64.whl (9.5 MB) |????????????????????????????????| 9.5 MB 25.6 MB/s Collecting cycler>=0.10.0 Using cached cycler-0.10.0-py2.py3-none-any.whl (6.5 kB) Collecting pyparsing>=2.4.0 Using cached pyparsing-2.4.7-py2.py3-none-any.whl (67 kB) Collecting opencv-python>=4.1.0.25 Using cached opencv_python-4.5.1.48-cp36-cp36m-manylinux2014_x86_64.whl (50.4 MB) Requirement already satisfied: numpy>=1.18.2 in /root/.local/lib/python3.6/site-packages (from lvis->object-detection==0.1) (1.19.5) Collecting kiwisolver>=1.1.0 Using cached kiwisolver-1.3.1-cp36-cp36m-manylinux1_x86_64.whl (1.1 MB) Collecting python-dateutil>=2.8.0 Using cached python_dateutil-2.8.1-py2.py3-none-any.whl (227 kB) Collecting pytz>=2017.2 Using cached pytz-2021.1-py2.py3-none-any.whl (510 kB) Requirement already satisfied: setuptools>=18.0 in /root/anaconda3/envs/tf1/lib/python3.6/site-packages (from pycocotools->object-detection==0.1) (52.0.0.post20210125) Requirement already satisfied: absl-py>=0.2.2 in /root/anaconda3/envs/tf1/lib/python3.6/site-packages (from tf-slim->object-detection==0.1) (0.12.0) Building wheels for collected packages: object-detection, pycocotools Building wheel for object-detection (setup.py) ... done Created wheel for object-detection: filename=object_detection-0.1-py3-none-any.whl size=1643984 sha256=89a5fc6e88577caab4206a9a4a200eb8dba4a7e5c2b970ff9637ad300854d029 Stored in directory: /tmp/pip-ephem-wheel-cache-zp4g9lh_/wheels/22/22/a1/fc116dd4526d44ac96cbfb85fb89f0a9c5cb88b825a6c25020 Building wheel for pycocotools (setup.py) ... done Created wheel for pycocotools: filename=pycocotools-2.0.2-cp36-cp36m-linux_x86_64.whl size=273408 sha256=b9eb3f09d6addcd01d7c90fde11e61852ca1dd913c31022c5d2ec1f016a600aa Stored in directory: /root/.cache/pip/wheels/d8/c2/ba/8f5306f921c2e79ad7b09effdfed6bd966cfcf8c6fe55422d6 Successfully built object-detection pycocotools Installing collected packages: python-dateutil, pyparsing, pillow, kiwisolver, cycler, pytz, opencv-python, matplotlib, tf-slim, pycocotools, pandas, lxml, lvis, contextlib2, object-detection Successfully installed contextlib2-0.6.0.post1 cycler-0.10.0 kiwisolver-1.3.1 lvis-0.5.3 lxml-4.6.3 matplotlib-3.3.4 object-detection-0.1 opencv-python-4.5.1.48 pandas-1.1.5 pillow-8.2.0 pycocotools-2.0.2 pyparsing-2.4.7 python-dateutil-2.8.1 pytz-2021.1 tf-slim-1.1.0 (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research# python object_detection/builders/model_builder_tf1_test.py Running tests under Python 3.6.13: /root/anaconda3/envs/tf1/bin/python [ RUN ] ModelBuilderTF1Test.test_create_context_rcnn_from_config_with_params0 (True) [ OK ] ModelBuilderTF1Test.test_create_context_rcnn_from_config_with_params0 (True) [ RUN ] ModelBuilderTF1Test.test_create_context_rcnn_from_config_with_params1 (False) [ OK ] ModelBuilderTF1Test.test_create_context_rcnn_from_config_with_params1 (False) [ RUN ] ModelBuilderTF1Test.test_create_experimental_model [ OK ] ModelBuilderTF1Test.test_create_experimental_model [ RUN ] ModelBuilderTF1Test.test_create_faster_rcnn_from_config_with_crop_feature0 (True) [ OK ] ModelBuilderTF1Test.test_create_faster_rcnn_from_config_with_crop_feature0 (True) [ RUN ] ModelBuilderTF1Test.test_create_faster_rcnn_from_config_with_crop_feature1 (False) [ OK ] ModelBuilderTF1Test.test_create_faster_rcnn_from_config_with_crop_feature1 (False) [ RUN ] ModelBuilderTF1Test.test_create_faster_rcnn_model_from_config_with_example_miner [ OK ] ModelBuilderTF1Test.test_create_faster_rcnn_model_from_config_with_example_miner [ RUN ] ModelBuilderTF1Test.test_create_faster_rcnn_models_from_config_faster_rcnn_with_matmul [ OK ] ModelBuilderTF1Test.test_create_faster_rcnn_models_from_config_faster_rcnn_with_matmul [ RUN ] ModelBuilderTF1Test.test_create_faster_rcnn_models_from_config_faster_rcnn_without_matmul [ OK ] ModelBuilderTF1Test.test_create_faster_rcnn_models_from_config_faster_rcnn_without_matmul [ RUN ] ModelBuilderTF1Test.test_create_faster_rcnn_models_from_config_mask_rcnn_with_matmul [ OK ] ModelBuilderTF1Test.test_create_faster_rcnn_models_from_config_mask_rcnn_with_matmul [ RUN ] ModelBuilderTF1Test.test_create_faster_rcnn_models_from_config_mask_rcnn_without_matmul [ OK ] ModelBuilderTF1Test.test_create_faster_rcnn_models_from_config_mask_rcnn_without_matmul [ RUN ] ModelBuilderTF1Test.test_create_rfcn_model_from_config [ OK ] ModelBuilderTF1Test.test_create_rfcn_model_from_config [ RUN ] ModelBuilderTF1Test.test_create_ssd_fpn_model_from_config [ OK ] ModelBuilderTF1Test.test_create_ssd_fpn_model_from_config [ RUN ] ModelBuilderTF1Test.test_create_ssd_models_from_config [ OK ] ModelBuilderTF1Test.test_create_ssd_models_from_config [ RUN ] ModelBuilderTF1Test.test_invalid_faster_rcnn_batchnorm_update [ OK ] ModelBuilderTF1Test.test_invalid_faster_rcnn_batchnorm_update [ RUN ] ModelBuilderTF1Test.test_invalid_first_stage_nms_iou_threshold [ OK ] ModelBuilderTF1Test.test_invalid_first_stage_nms_iou_threshold [ RUN ] ModelBuilderTF1Test.test_invalid_model_config_proto [ OK ] ModelBuilderTF1Test.test_invalid_model_config_proto [ RUN ] ModelBuilderTF1Test.test_invalid_second_stage_batch_size [ OK ] ModelBuilderTF1Test.test_invalid_second_stage_batch_size [ RUN ] ModelBuilderTF1Test.test_session [ SKIPPED ] ModelBuilderTF1Test.test_session [ RUN ] ModelBuilderTF1Test.test_unknown_faster_rcnn_feature_extractor [ OK ] ModelBuilderTF1Test.test_unknown_faster_rcnn_feature_extractor [ RUN ] ModelBuilderTF1Test.test_unknown_meta_architecture [ OK ] ModelBuilderTF1Test.test_unknown_meta_architecture [ RUN ] ModelBuilderTF1Test.test_unknown_ssd_feature_extractor [ OK ] ModelBuilderTF1Test.test_unknown_ssd_feature_extractor ---------------------------------------------------------------------- Ran 21 tests in 0.245s OK (skipped=1)
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我把指令进一步提炼一下,主要是省去了一些中间过程和结果：
conda create -n tf1 python=3.6 conda activate tf1 conda install tensorflow-gpu=1.15.0 conda install cudatoolkit=10.0 conda install cudnn=7.6 (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1# conda install protobuf (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow# cd models/research/ (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research# protoc object_detection/protos/*.proto --python_out=. (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research# git clone https://github.com/cocodataset/cocoapi.git (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research# cd cocoapi/PythonAPI/ (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research/cocoapi/PythonAPI# make (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research/cocoapi/PythonAPI# cp -r pycocotools /nfs/private/junnxie/tf1/tensorflow/models/research/ (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research/cocoapi/PythonAPI# cd ../.. (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research# cp object_detection/packages/tf1/setup.py . (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research# python Python 3.6.13 |Anaconda, Inc.| (default, Feb 23 2021, 21:15:04) [GCC 7.3.0] on linux Type "help", "copyright", "credits" or "license" for more information. >>> import tensorflow as tf >>> tf.__version__ '1.15.0' >>> (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research# python -m pip install . (tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/models/research# python object_detection/builders/model_builder_tf1_test.py
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最后，我运行了一个目标检测工程，数据是网上找的，使用tensorflow提供的代码制作标准的数据集用于训练。
训练过程如下：
(tf1) root@k8s-deploy-jcjbxf-1609678570414-7fffc8595-hkrph:/nfs/private/junnxie/tf1/tensorflow/workspace/training_demo# python model_main.py --model_dir=models/my_ssd_inception_v2 --pipeline_config_path=models/my_ssd_inception_v2/pipeline.config WARNING:tensorflow:Forced number of epochs for all eval validations to be 1. W0408 19:36:14.746835 140553343391552 model_lib.py:813] Forced number of epochs for all eval validations to be 1. INFO:tensorflow:Maybe overwriting train_steps: None I0408 19:36:14.747101 140553343391552 config_util.py:552] Maybe overwriting train_steps: None INFO:tensorflow:Maybe overwriting use_bfloat16: False I0408 19:36:14.747195 140553343391552 config_util.py:552] Maybe overwriting use_bfloat16: False INFO:tensorflow:Maybe overwriting sample_1_of_n_eval_examples: 1 I0408 19:36:14.747280 140553343391552 config_util.py:552] Maybe overwriting sample_1_of_n_eval_examples: 1 INFO:tensorflow:Maybe overwriting eval_num_epochs: 1 I0408 19:36:14.747370 140553343391552 config_util.py:552] Maybe overwriting eval_num_epochs: 1 WARNING:tensorflow:Expected number of evaluation epochs is 1, but instead encountered `eval_on_train_input_config.num_epochs` = 0. Overwriting `num_epochs` to 1. W0408 19:36:14.747480 140553343391552 model_lib.py:829] Expected number of evaluation epochs is 1, but instead encountered `eval_on_train_input_config.num_epochs` = 0. Overwriting `num_epochs` to 1. INFO:tensorflow:create_estimator_and_inputs: use_tpu False, export_to_tpu None I0408 19:36:14.747575 140553343391552 model_lib.py:866] create_estimator_and_inputs: use_tpu False, export_to_tpu None INFO:tensorflow:Using config: {'_model_dir': 'models/my_ssd_inception_v2', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': allow_soft_placement: true graph_options { rewrite_options { meta_optimizer_iterations: ONE } } , '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_train_distribute': None, '_device_fn': None, '_protocol': None, '_eval_distribute': None, '_experimental_distribute': None, '_experimental_max_worker_delay_secs': None, '_session_creation_timeout_secs': 7200, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7fd4ed457e10>, '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1} I0408 19:36:14.748096 140553343391552 estimator.py:212] Using config: {'_model_dir': 'models/my_ssd_inception_v2', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': allow_soft_placement: true graph_options { rewrite_options { meta_optimizer_iterations: ONE } } , '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_train_distribute': None, '_device_fn': None, '_protocol': None, '_eval_distribute': None, '_experimental_distribute': None, '_experimental_max_worker_delay_secs': None, '_session_creation_timeout_secs': 7200, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7fd4ed457e10>, '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1} WARNING:tensorflow:Estimator's model_fn (<function create_model_fn.<locals>.model_fn at 0x7fd4ed462378>) includes params argument, but params are not passed to Estimator. W0408 19:36:14.749072 140553343391552 model_fn.py:630] Estimator's model_fn (<function create_model_fn.<locals>.model_fn at 0x7fd4ed462378>) includes params argument, but params are not passed to Estimator. INFO:tensorflow:Not using Distribute Coordinator. I0408 19:36:14.749960 140553343391552 estimator_training.py:186] Not using Distribute Coordinator. INFO:tensorflow:Running training and evaluation locally (non-distributed). I0408 19:36:14.750178 140553343391552 training.py:612] Running training and evaluation locally (non-distributed). INFO:tensorflow:Start train and evaluate loop. The evaluate will happen after every checkpoint. Checkpoint frequency is determined based on RunConfig arguments: save_checkpoints_steps None or save_checkpoints_secs 600. I0408 19:36:14.750450 140553343391552 training.py:700] Start train and evaluate loop. The evaluate will happen after every checkpoint. Checkpoint frequency is determined based on RunConfig arguments: save_checkpoints_steps None or save_checkpoints_secs 600. WARNING:tensorflow:From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/tensorflow_core/python/training/training_util.py:236: Variable.initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version. Instructions for updating: Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts. W0408 19:36:14.780125 140553343391552 deprecation.py:323] From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/tensorflow_core/python/training/training_util.py:236: Variable.initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version. Instructions for updating: Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts. INFO:tensorflow:Reading unweighted datasets: ['annotations/train.record'] I0408 19:36:14.899453 140553343391552 dataset_builder.py:163] Reading unweighted datasets: ['annotations/train.record'] INFO:tensorflow:Reading record datasets for input file: ['annotations/train.record'] I0408 19:36:14.906244 140553343391552 dataset_builder.py:80] Reading record datasets for input file: ['annotations/train.record'] INFO:tensorflow:Number of filenames to read: 1 I0408 19:36:14.906542 140553343391552 dataset_builder.py:81] Number of filenames to read: 1 WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards. W0408 19:36:14.906724 140553343391552 dataset_builder.py:88] num_readers has been reduced to 1 to match input file shards. WARNING:tensorflow:From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/object_detection/builders/dataset_builder.py:105: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.experimental.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.experimental_determinstic`. W0408 19:36:14.920520 140553343391552 deprecation.py:323] From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/object_detection/builders/dataset_builder.py:105: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.experimental.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.experimental_determinstic`. WARNING:tensorflow:From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/object_detection/builders/dataset_builder.py:237: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.data.Dataset.map() W0408 19:36:14.985749 140553343391552 deprecation.py:323] From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/object_detection/builders/dataset_builder.py:237: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.data.Dataset.map() WARNING:tensorflow:From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/object_detection/inputs.py:110: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version. Instructions for updating: Use tf.where in 2.0, which has the same broadcast rule as np.where W0408 19:36:27.862425 140553343391552 deprecation.py:323] From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/object_detection/inputs.py:110: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version. Instructions for updating: Use tf.where in 2.0, which has the same broadcast rule as np.where WARNING:tensorflow:From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/object_detection/inputs.py:94: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version. Instructions for updating: Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead. W0408 19:36:28.015421 140553343391552 deprecation.py:323] From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/object_detection/inputs.py:94: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version. Instructions for updating: Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead. WARNING:tensorflow:From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/tensorflow_core/python/autograph/operators/control_flow.py:1004: sample_distorted_bounding_box (from tensorflow.python.ops.image_ops_impl) is deprecated and will be removed in a future version. Instructions for updating: `seed2` arg is deprecated.Use sample_distorted_bounding_box_v2 instead. W0408 19:36:34.523849 140553343391552 api.py:332] From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/tensorflow_core/python/autograph/operators/control_flow.py:1004: sample_distorted_bounding_box (from tensorflow.python.ops.image_ops_impl) is deprecated and will be removed in a future version. Instructions for updating: `seed2` arg is deprecated.Use sample_distorted_bounding_box_v2 instead. WARNING:tensorflow:From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/object_detection/inputs.py:282: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. W0408 19:36:37.794182 140553343391552 deprecation.py:323] From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/object_detection/inputs.py:282: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. INFO:tensorflow:Calling model_fn. I0408 19:36:41.447258 140553343391552 estimator.py:1148] Calling model_fn. WARNING:tensorflow:From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/tf_slim/layers/layers.py:2802: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version. Instructions for updating: Please use `layer.__call__` method instead. W0408 19:36:41.740483 140553343391552 deprecation.py:323] From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/tf_slim/layers/layers.py:2802: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version. Instructions for updating: Please use `layer.__call__` method instead. INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:36:44.422615 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:36:44.448537 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:36:44.473237 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:36:44.497899 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:36:44.522875 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:36:44.547588 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 WARNING:tensorflow:From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/tensorflow_core/python/training/rmsprop.py:119: calling Ones.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version. Instructions for updating: Call initializer instance with the dtype argument instead of passing it to the constructor W0408 19:36:50.300761 140553343391552 deprecation.py:506] From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/tensorflow_core/python/training/rmsprop.py:119: calling Ones.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version. Instructions for updating: Call initializer instance with the dtype argument instead of passing it to the constructor INFO:tensorflow:Done calling model_fn. I0408 19:36:56.719294 140553343391552 estimator.py:1150] Done calling model_fn. INFO:tensorflow:Create CheckpointSaverHook. I0408 19:36:56.720463 140553343391552 basic_session_run_hooks.py:541] Create CheckpointSaverHook. INFO:tensorflow:Graph was finalized. I0408 19:37:00.901003 140553343391552 monitored_session.py:240] Graph was finalized. 2021-04-08 19:37:00.901417: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 AVX512F FMA 2021-04-08 19:37:00.915375: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2300000000 Hz 2021-04-08 19:37:00.921384: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55aafa799d00 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2021-04-08 19:37:00.921444: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2021-04-08 19:37:00.923131: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2021-04-08 19:37:00.976282: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: name: TITAN Xp major: 6 minor: 1 memoryClockRate(GHz): 1.582 pciBusID: 0000:1e:00.0 2021-04-08 19:37:00.976922: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0 2021-04-08 19:37:00.980881: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0 2021-04-08 19:37:00.984547: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0 2021-04-08 19:37:00.985348: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0 2021-04-08 19:37:00.988312: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0 2021-04-08 19:37:00.990079: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0 2021-04-08 19:37:01.001160: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2021-04-08 19:37:01.012950: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0 2021-04-08 19:37:01.013081: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0 2021-04-08 19:37:01.291709: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix: 2021-04-08 19:37:01.291754: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0 2021-04-08 19:37:01.291785: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N 2021-04-08 19:37:01.300849: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 11299 MB memory) -> physical GPU (device: 0, name: TITAN Xp, pci bus id: 0000:1e:00.0, compute capability: 6.1) 2021-04-08 19:37:01.303098: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55ab0e7a4670 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2021-04-08 19:37:01.303132: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): TITAN Xp, Compute Capability 6.1 INFO:tensorflow:Running local_init_op. I0408 19:37:11.309897 140553343391552 session_manager.py:500] Running local_init_op. INFO:tensorflow:Done running local_init_op. I0408 19:37:12.092763 140553343391552 session_manager.py:502] Done running local_init_op. INFO:tensorflow:Saving checkpoints for 0 into models/my_ssd_inception_v2/model.ckpt. I0408 19:37:24.229167 140553343391552 basic_session_run_hooks.py:606] Saving checkpoints for 0 into models/my_ssd_inception_v2/model.ckpt. 2021-04-08 19:37:42.652158: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2021-04-08 19:37:48.131007: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0 INFO:tensorflow:loss = 26.353672, step = 0 I0408 19:37:50.209866 140553343391552 basic_session_run_hooks.py:262] loss = 26.353672, step = 0 INFO:tensorflow:global_step/sec: 2.45856 I0408 19:38:30.884657 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 2.45856 INFO:tensorflow:loss = 7.0979624, step = 100 (40.679 sec) I0408 19:38:30.887990 140553343391552 basic_session_run_hooks.py:260] loss = 7.0979624, step = 100 (40.679 sec) INFO:tensorflow:global_step/sec: 3.5244 I0408 19:38:59.256149 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.5244 INFO:tensorflow:loss = 6.423036, step = 200 (28.385 sec) I0408 19:38:59.272437 140553343391552 basic_session_run_hooks.py:260] loss = 6.423036, step = 200 (28.385 sec) INFO:tensorflow:global_step/sec: 3.44889 I0408 19:39:28.251045 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.44889 INFO:tensorflow:loss = 6.2270827, step = 300 (28.982 sec) I0408 19:39:28.253960 140553343391552 basic_session_run_hooks.py:260] loss = 6.2270827, step = 300 (28.982 sec) INFO:tensorflow:global_step/sec: 3.51676 I0408 19:39:56.686080 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.51676 INFO:tensorflow:loss = 6.3535028, step = 400 (28.434 sec) I0408 19:39:56.688244 140553343391552 basic_session_run_hooks.py:260] loss = 6.3535028, step = 400 (28.434 sec) INFO:tensorflow:global_step/sec: 3.53058 I0408 19:40:25.010002 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.53058 INFO:tensorflow:loss = 5.5039124, step = 500 (28.324 sec) I0408 19:40:25.011913 140553343391552 basic_session_run_hooks.py:260] loss = 5.5039124, step = 500 (28.324 sec) INFO:tensorflow:global_step/sec: 3.52694 I0408 19:40:53.363433 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.52694 INFO:tensorflow:loss = 5.1926427, step = 600 (28.354 sec) I0408 19:40:53.366256 140553343391552 basic_session_run_hooks.py:260] loss = 5.1926427, step = 600 (28.354 sec) INFO:tensorflow:global_step/sec: 3.50592 I0408 19:41:21.886609 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.50592 INFO:tensorflow:loss = 5.6967077, step = 700 (28.533 sec) I0408 19:41:21.899112 140553343391552 basic_session_run_hooks.py:260] loss = 5.6967077, step = 700 (28.533 sec) INFO:tensorflow:global_step/sec: 3.51716 I0408 19:41:50.318632 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.51716 INFO:tensorflow:loss = 4.9808583, step = 800 (28.422 sec) I0408 19:41:50.321131 140553343391552 basic_session_run_hooks.py:260] loss = 4.9808583, step = 800 (28.422 sec) INFO:tensorflow:global_step/sec: 3.55013 I0408 19:42:18.486627 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.55013 INFO:tensorflow:loss = 5.414756, step = 900 (28.168 sec) I0408 19:42:18.489443 140553343391552 basic_session_run_hooks.py:260] loss = 5.414756, step = 900 (28.168 sec) INFO:tensorflow:global_step/sec: 3.54571 I0408 19:42:46.689790 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.54571 INFO:tensorflow:loss = 4.1702933, step = 1000 (28.203 sec) I0408 19:42:46.692520 140553343391552 basic_session_run_hooks.py:260] loss = 4.1702933, step = 1000 (28.203 sec) INFO:tensorflow:global_step/sec: 3.56015 I0408 19:43:14.778345 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.56015 INFO:tensorflow:loss = 4.250403, step = 1100 (28.088 sec) I0408 19:43:14.780816 140553343391552 basic_session_run_hooks.py:260] loss = 4.250403, step = 1100 (28.088 sec) INFO:tensorflow:global_step/sec: 3.4538 I0408 19:43:43.732146 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.4538 INFO:tensorflow:loss = 4.8844323, step = 1200 (28.964 sec) I0408 19:43:43.744886 140553343391552 basic_session_run_hooks.py:260] loss = 4.8844323, step = 1200 (28.964 sec) INFO:tensorflow:global_step/sec: 3.50202 I0408 19:44:12.286877 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.50202 INFO:tensorflow:loss = 5.226234, step = 1300 (28.544 sec) I0408 19:44:12.289032 140553343391552 basic_session_run_hooks.py:260] loss = 5.226234, step = 1300 (28.544 sec) INFO:tensorflow:global_step/sec: 3.51738 I0408 19:44:40.717238 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.51738 INFO:tensorflow:loss = 4.5052533, step = 1400 (28.431 sec) I0408 19:44:40.719830 140553343391552 basic_session_run_hooks.py:260] loss = 4.5052533, step = 1400 (28.431 sec) INFO:tensorflow:global_step/sec: 3.55431 I0408 19:45:08.852223 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.55431 INFO:tensorflow:loss = 4.34357, step = 1500 (28.135 sec) I0408 19:45:08.855122 140553343391552 basic_session_run_hooks.py:260] loss = 4.34357, step = 1500 (28.135 sec) INFO:tensorflow:global_step/sec: 3.49746 I0408 19:45:37.444391 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.49746 INFO:tensorflow:loss = 4.2605658, step = 1600 (28.592 sec) I0408 19:45:37.447230 140553343391552 basic_session_run_hooks.py:260] loss = 4.2605658, step = 1600 (28.592 sec) INFO:tensorflow:global_step/sec: 3.53497 I0408 19:46:05.733187 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.53497 INFO:tensorflow:loss = 3.5676794, step = 1700 (28.295 sec) I0408 19:46:05.741827 140553343391552 basic_session_run_hooks.py:260] loss = 3.5676794, step = 1700 (28.295 sec) INFO:tensorflow:global_step/sec: 3.55267 I0408 19:46:33.881087 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.55267 INFO:tensorflow:loss = 4.289984, step = 1800 (28.142 sec) I0408 19:46:33.884087 140553343391552 basic_session_run_hooks.py:260] loss = 4.289984, step = 1800 (28.142 sec) INFO:tensorflow:global_step/sec: 3.53733 I0408 19:47:02.150989 140553343391552 basic_session_run_hooks.py:692] global_step/sec: 3.53733 INFO:tensorflow:loss = 3.744223, step = 1900 (28.270 sec) I0408 19:47:02.153777 140553343391552 basic_session_run_hooks.py:260] loss = 3.744223, step = 1900 (28.270 sec) INFO:tensorflow:Saving checkpoints for 1997 into models/my_ssd_inception_v2/model.ckpt. I0408 19:47:29.373254 140553343391552 basic_session_run_hooks.py:606] Saving checkpoints for 1997 into models/my_ssd_inception_v2/model.ckpt. INFO:tensorflow:Reading unweighted datasets: ['annotations/test.record'] I0408 19:47:43.834930 140553343391552 dataset_builder.py:163] Reading unweighted datasets: ['annotations/test.record'] INFO:tensorflow:Reading record datasets for input file: ['annotations/test.record'] I0408 19:47:43.839394 140553343391552 dataset_builder.py:80] Reading record datasets for input file: ['annotations/test.record'] INFO:tensorflow:Number of filenames to read: 1 I0408 19:47:43.839524 140553343391552 dataset_builder.py:81] Number of filenames to read: 1 INFO:tensorflow:Calling model_fn. I0408 19:47:45.471107 140553343391552 estimator.py:1148] Calling model_fn. INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:47:47.676634 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:47:47.701958 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:47:47.727361 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:47:47.752024 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:47:47.777025 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:47:47.801182 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 WARNING:tensorflow:From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/object_detection/eval_util.py:929: to_int64 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. W0408 19:47:48.630852 140553343391552 deprecation.py:323] From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/object_detection/eval_util.py:929: to_int64 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. WARNING:tensorflow:From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/object_detection/utils/visualization_utils.py:618: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version. Instructions for updating: tf.py_func is deprecated in TF V2. Instead, there are two options available in V2. - tf.py_function takes a python function which manipulates tf eager tensors instead of numpy arrays. It's easy to convert a tf eager tensor to an ndarray (just call tensor.numpy()) but having access to eager tensors means `tf.py_function`s can use accelerators such as GPUs as well as being differentiable using a gradient tape. - tf.numpy_function maintains the semantics of the deprecated tf.py_func (it is not differentiable, and manipulates numpy arrays). It drops the stateful argument making all functions stateful. W0408 19:47:48.957098 140553343391552 deprecation.py:323] From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/object_detection/utils/visualization_utils.py:618: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version. Instructions for updating: tf.py_func is deprecated in TF V2. Instead, there are two options available in V2. - tf.py_function takes a python function which manipulates tf eager tensors instead of numpy arrays. It's easy to convert a tf eager tensor to an ndarray (just call tensor.numpy()) but having access to eager tensors means `tf.py_function`s can use accelerators such as GPUs as well as being differentiable using a gradient tape. - tf.numpy_function maintains the semantics of the deprecated tf.py_func (it is not differentiable, and manipulates numpy arrays). It drops the stateful argument making all functions stateful. INFO:tensorflow:Done calling model_fn. I0408 19:47:49.616228 140553343391552 estimator.py:1150] Done calling model_fn. INFO:tensorflow:Starting evaluation at 2021-04-08T19:47:49Z I0408 19:47:49.635172 140553343391552 evaluation.py:255] Starting evaluation at 2021-04-08T19:47:49Z INFO:tensorflow:Graph was finalized. I0408 19:47:50.092404 140553343391552 monitored_session.py:240] Graph was finalized. 2021-04-08 19:47:50.101238: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: name: TITAN Xp major: 6 minor: 1 memoryClockRate(GHz): 1.582 pciBusID: 0000:1e:00.0 2021-04-08 19:47:50.101469: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0 2021-04-08 19:47:50.101504: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0 2021-04-08 19:47:50.101532: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0 2021-04-08 19:47:50.101561: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0 2021-04-08 19:47:50.101586: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0 2021-04-08 19:47:50.101615: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0 2021-04-08 19:47:50.101686: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2021-04-08 19:47:50.111780: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0 2021-04-08 19:47:50.111874: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix: 2021-04-08 19:47:50.111910: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0 2021-04-08 19:47:50.111944: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N 2021-04-08 19:47:50.116084: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 11299 MB memory) -> physical GPU (device: 0, name: TITAN Xp, pci bus id: 0000:1e:00.0, compute capability: 6.1) INFO:tensorflow:Restoring parameters from models/my_ssd_inception_v2/model.ckpt-1997 I0408 19:47:50.128154 140553343391552 saver.py:1284] Restoring parameters from models/my_ssd_inception_v2/model.ckpt-1997 INFO:tensorflow:Running local_init_op. I0408 19:47:52.254904 140553343391552 session_manager.py:500] Running local_init_op. INFO:tensorflow:Done running local_init_op. I0408 19:47:52.436636 140553343391552 session_manager.py:502] Done running local_init_op. INFO:tensorflow:Performing evaluation on 25 images. I0408 19:47:56.768712 140496349411072 coco_evaluation.py:293] Performing evaluation on 25 images. creating index... index created! INFO:tensorflow:Loading and preparing annotation results... I0408 19:47:56.769833 140496349411072 coco_tools.py:116] Loading and preparing annotation results... INFO:tensorflow:DONE (t=0.00s) I0408 19:47:56.772033 140496349411072 coco_tools.py:138] DONE (t=0.00s) creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* DONE (t=0.22s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.001 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.007 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.002 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.021 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.022 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.021 INFO:tensorflow:Finished evaluation at 2021-04-08-19:47:57 I0408 19:47:57.225715 140553343391552 evaluation.py:275] Finished evaluation at 2021-04-08-19:47:57 INFO:tensorflow:Saving dict for global step 1997: DetectionBoxes_Precision/mAP = 0.0001709473, DetectionBoxes_Precision/mAP (large) = 0.00013584658, DetectionBoxes_Precision/mAP (medium) = 0.0073927394, DetectionBoxes_Precision/mAP (small) = -1.0, DetectionBoxes_Precision/mAP@.50IOU = 0.00088169175, DetectionBoxes_Precision/mAP@.75IOU = 0.0, DetectionBoxes_Recall/AR@1 = 0.0, DetectionBoxes_Recall/AR@10 = 0.002352941, DetectionBoxes_Recall/AR@100 = 0.02117647, DetectionBoxes_Recall/AR@100 (large) = 0.020967742, DetectionBoxes_Recall/AR@100 (medium) = 0.02173913, DetectionBoxes_Recall/AR@100 (small) = -1.0, Loss/classification_loss = 8.233138, Loss/localization_loss = 4.0231056, Loss/regularization_loss = 0.48583883, Loss/total_loss = 12.742084, global_step = 1997, learning_rate = 0.004, loss = 12.742084 I0408 19:47:57.226226 140553343391552 estimator.py:2049] Saving dict for global step 1997: DetectionBoxes_Precision/mAP = 0.0001709473, DetectionBoxes_Precision/mAP (large) = 0.00013584658, DetectionBoxes_Precision/mAP (medium) = 0.0073927394, DetectionBoxes_Precision/mAP (small) = -1.0, DetectionBoxes_Precision/mAP@.50IOU = 0.00088169175, DetectionBoxes_Precision/mAP@.75IOU = 0.0, DetectionBoxes_Recall/AR@1 = 0.0, DetectionBoxes_Recall/AR@10 = 0.002352941, DetectionBoxes_Recall/AR@100 = 0.02117647, DetectionBoxes_Recall/AR@100 (large) = 0.020967742, DetectionBoxes_Recall/AR@100 (medium) = 0.02173913, DetectionBoxes_Recall/AR@100 (small) = -1.0, Loss/classification_loss = 8.233138, Loss/localization_loss = 4.0231056, Loss/regularization_loss = 0.48583883, Loss/total_loss = 12.742084, global_step = 1997, learning_rate = 0.004, loss = 12.742084 INFO:tensorflow:Saving 'checkpoint_path' summary for global step 1997: models/my_ssd_inception_v2/model.ckpt-1997 I0408 19:47:58.198050 140553343391552 estimator.py:2109] Saving 'checkpoint_path' summary for global step 1997: models/my_ssd_inception_v2/model.ckpt-1997 INFO:tensorflow:Saving checkpoints for 2000 into models/my_ssd_inception_v2/model.ckpt. I0408 19:47:59.095469 140553343391552 basic_session_run_hooks.py:606] Saving checkpoints for 2000 into models/my_ssd_inception_v2/model.ckpt. INFO:tensorflow:Skip the current checkpoint eval due to throttle secs (600 secs). I0408 19:48:01.902159 140553343391552 training.py:527] Skip the current checkpoint eval due to throttle secs (600 secs). INFO:tensorflow:Reading unweighted datasets: ['annotations/test.record'] I0408 19:48:01.939406 140553343391552 dataset_builder.py:163] Reading unweighted datasets: ['annotations/test.record'] INFO:tensorflow:Reading record datasets for input file: ['annotations/test.record'] I0408 19:48:01.946810 140553343391552 dataset_builder.py:80] Reading record datasets for input file: ['annotations/test.record'] INFO:tensorflow:Number of filenames to read: 1 I0408 19:48:01.946915 140553343391552 dataset_builder.py:81] Number of filenames to read: 1 INFO:tensorflow:Calling model_fn. I0408 19:48:02.928972 140553343391552 estimator.py:1148] Calling model_fn. INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:48:05.048127 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:48:05.074190 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:48:05.100624 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:48:05.125298 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:48:05.150101 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:48:05.175326 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:Done calling model_fn. I0408 19:48:06.351978 140553343391552 estimator.py:1150] Done calling model_fn. INFO:tensorflow:Starting evaluation at 2021-04-08T19:48:06Z I0408 19:48:06.365622 140553343391552 evaluation.py:255] Starting evaluation at 2021-04-08T19:48:06Z INFO:tensorflow:Graph was finalized. I0408 19:48:06.785058 140553343391552 monitored_session.py:240] Graph was finalized. 2021-04-08 19:48:06.787840: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: name: TITAN Xp major: 6 minor: 1 memoryClockRate(GHz): 1.582 pciBusID: 0000:1e:00.0 2021-04-08 19:48:06.788024: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0 2021-04-08 19:48:06.788048: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0 2021-04-08 19:48:06.788072: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0 2021-04-08 19:48:06.788094: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0 2021-04-08 19:48:06.788114: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0 2021-04-08 19:48:06.788137: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0 2021-04-08 19:48:06.788157: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2021-04-08 19:48:06.791190: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0 2021-04-08 19:48:06.791261: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix: 2021-04-08 19:48:06.791276: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0 2021-04-08 19:48:06.791332: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N 2021-04-08 19:48:06.794789: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 11299 MB memory) -> physical GPU (device: 0, name: TITAN Xp, pci bus id: 0000:1e:00.0, compute capability: 6.1) INFO:tensorflow:Restoring parameters from models/my_ssd_inception_v2/model.ckpt-2000 I0408 19:48:06.804881 140553343391552 saver.py:1284] Restoring parameters from models/my_ssd_inception_v2/model.ckpt-2000 INFO:tensorflow:Running local_init_op. I0408 19:48:08.983566 140553343391552 session_manager.py:500] Running local_init_op. INFO:tensorflow:Done running local_init_op. I0408 19:48:09.121775 140553343391552 session_manager.py:502] Done running local_init_op. INFO:tensorflow:Performing evaluation on 25 images. I0408 19:48:13.511092 140495493789440 coco_evaluation.py:293] Performing evaluation on 25 images. creating index... index created! INFO:tensorflow:Loading and preparing annotation results... I0408 19:48:13.512457 140495493789440 coco_tools.py:116] Loading and preparing annotation results... INFO:tensorflow:DONE (t=0.00s) I0408 19:48:13.514708 140495493789440 coco_tools.py:138] DONE (t=0.00s) creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* DONE (t=0.25s). Accumulating evaluation results... DONE (t=0.01s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.001 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.009 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.027 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.017 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.031 INFO:tensorflow:Finished evaluation at 2021-04-08-19:48:13 I0408 19:48:13.930575 140553343391552 evaluation.py:275] Finished evaluation at 2021-04-08-19:48:13 INFO:tensorflow:Saving dict for global step 2000: DetectionBoxes_Precision/mAP = 0.000258673, DetectionBoxes_Precision/mAP (large) = 0.00023983713, DetectionBoxes_Precision/mAP (medium) = 0.009405941, DetectionBoxes_Precision/mAP (small) = -1.0, DetectionBoxes_Precision/mAP@.50IOU = 0.001324426, DetectionBoxes_Precision/mAP@.75IOU = 0.0, DetectionBoxes_Recall/AR@1 = 0.0, DetectionBoxes_Recall/AR@10 = 0.0, DetectionBoxes_Recall/AR@100 = 0.027058823, DetectionBoxes_Recall/AR@100 (large) = 0.030645162, DetectionBoxes_Recall/AR@100 (medium) = 0.017391304, DetectionBoxes_Recall/AR@100 (small) = -1.0, Loss/classification_loss = 7.987997, Loss/localization_loss = 4.0830684, Loss/regularization_loss = 0.48584178, Loss/total_loss = 12.556907, global_step = 2000, learning_rate = 0.004, loss = 12.556907 I0408 19:48:13.931072 140553343391552 estimator.py:2049] Saving dict for global step 2000: DetectionBoxes_Precision/mAP = 0.000258673, DetectionBoxes_Precision/mAP (large) = 0.00023983713, DetectionBoxes_Precision/mAP (medium) = 0.009405941, DetectionBoxes_Precision/mAP (small) = -1.0, DetectionBoxes_Precision/mAP@.50IOU = 0.001324426, DetectionBoxes_Precision/mAP@.75IOU = 0.0, DetectionBoxes_Recall/AR@1 = 0.0, DetectionBoxes_Recall/AR@10 = 0.0, DetectionBoxes_Recall/AR@100 = 0.027058823, DetectionBoxes_Recall/AR@100 (large) = 0.030645162, DetectionBoxes_Recall/AR@100 (medium) = 0.017391304, DetectionBoxes_Recall/AR@100 (small) = -1.0, Loss/classification_loss = 7.987997, Loss/localization_loss = 4.0830684, Loss/regularization_loss = 0.48584178, Loss/total_loss = 12.556907, global_step = 2000, learning_rate = 0.004, loss = 12.556907 INFO:tensorflow:Saving 'checkpoint_path' summary for global step 2000: models/my_ssd_inception_v2/model.ckpt-2000 I0408 19:48:13.956167 140553343391552 estimator.py:2109] Saving 'checkpoint_path' summary for global step 2000: models/my_ssd_inception_v2/model.ckpt-2000 INFO:tensorflow:Performing the final export in the end of training. I0408 19:48:13.959100 140553343391552 exporter.py:410] Performing the final export in the end of training. INFO:tensorflow:Calling model_fn. I0408 19:48:14.372867 140553343391552 estimator.py:1148] Calling model_fn. INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:48:16.682502 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:48:16.708631 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:48:16.733302 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:48:16.758555 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:48:16.782882 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:depth of additional conv before box predictor: 0 I0408 19:48:16.807321 140553343391552 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0 INFO:tensorflow:Done calling model_fn. I0408 19:48:17.382560 140553343391552 estimator.py:1150] Done calling model_fn. WARNING:tensorflow:From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/tensorflow_core/python/saved_model/signature_def_utils_impl.py:201: build_tensor_info (from tensorflow.python.saved_model.utils_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.utils.build_tensor_info or tf.compat.v1.saved_model.build_tensor_info. W0408 19:48:17.382837 140553343391552 deprecation.py:323] From /root/anaconda3/envs/tf1/lib/python3.6/site-packages/tensorflow_core/python/saved_model/signature_def_utils_impl.py:201: build_tensor_info (from tensorflow.python.saved_model.utils_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.utils.build_tensor_info or tf.compat.v1.saved_model.build_tensor_info. INFO:tensorflow:Signatures INCLUDED in export for Classify: None I0408 19:48:17.383411 140553343391552 export_utils.py:170] Signatures INCLUDED in export for Classify: None INFO:tensorflow:Signatures INCLUDED in export for Regress: None I0408 19:48:17.383496 140553343391552 export_utils.py:170] Signatures INCLUDED in export for Regress: None INFO:tensorflow:Signatures INCLUDED in export for Predict: ['tensorflow/serving/predict', 'serving_default'] I0408 19:48:17.383557 140553343391552 export_utils.py:170] Signatures INCLUDED in export for Predict: ['tensorflow/serving/predict', 'serving_default'] INFO:tensorflow:Signatures INCLUDED in export for Train: None I0408 19:48:17.383643 140553343391552 export_utils.py:170] Signatures INCLUDED in export for Train: None INFO:tensorflow:Signatures INCLUDED in export for Eval: None I0408 19:48:17.383695 140553343391552 export_utils.py:170] Signatures INCLUDED in export for Eval: None 2021-04-08 19:48:17.385852: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: name: TITAN Xp major: 6 minor: 1 memoryClockRate(GHz): 1.582 pciBusID: 0000:1e:00.0 2021-04-08 19:48:17.385957: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0 2021-04-08 19:48:17.385978: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0 2021-04-08 19:48:17.385999: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0 2021-04-08 19:48:17.386017: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0 2021-04-08 19:48:17.386034: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0 2021-04-08 19:48:17.386053: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0 2021-04-08 19:48:17.386070: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2021-04-08 19:48:17.389097: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0 2021-04-08 19:48:17.389145: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix: 2021-04-08 19:48:17.389159: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0 2021-04-08 19:48:17.389171: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N 2021-04-08 19:48:17.392436: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 11299 MB memory) -> physical GPU (device: 0, name: TITAN Xp, pci bus id: 0000:1e:00.0, compute capability: 6.1) INFO:tensorflow:Restoring parameters from models/my_ssd_inception_v2/model.ckpt-2000 I0408 19:48:17.407397 140553343391552 saver.py:1284] Restoring parameters from models/my_ssd_inception_v2/model.ckpt-2000 INFO:tensorflow:Assets added to graph. I0408 19:48:18.091548 140553343391552 builder_impl.py:665] Assets added to graph. INFO:tensorflow:No assets to write. I0408 19:48:18.091738 140553343391552 builder_impl.py:460] No assets to write. INFO:tensorflow:SavedModel written to: models/my_ssd_inception_v2/export/Servo/temp-b'1617882493'/saved_model.pb I0408 19:48:20.169840 140553343391552 builder_impl.py:425] SavedModel written to: models/my_ssd_inception_v2/export/Servo/temp-b'1617882493'/saved_model.pb INFO:tensorflow:Loss for final step: 3.5268488. I0408 19:48:21.147778 140553343391552 estimator.py:371] Loss for final step: 3.5268488.
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跑完后的结果使用tensorfboard进行可视化，结果如下：
准确率曲线：
召回率曲线：
损失曲线：
迭代20W次后的验证集结果：
左右两张图是一致的，左图是模型测试结果，右图是真值（人为标的），进行对比可得准确率。模型准确率较低，主要原因是训练的数据太小，只有三四百张图片，而且标注的目标特征较复杂，学习起来难度较大，导致模型准确率低。从训练的准确率也可以看出，数据量小，迭代次数太多没有意义，反而会过拟合，导致准确率下降。
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