tenorflow. python .framework.errors_impl.InvalidArgumentError: недопустимый аргумент: утверждение не выполнено: - PullRequest
1 голос
/ 29 мая 2020

Во время обучения с использованием TensorFlow Object Detection API от Google Colab я получил следующую ошибку (в следующем подробном описании есть две похожие ошибки… одна из них в конце):

WARNING:tensorflow:Forced number of epochs for all eval validations to be 1.
W0528 21:13:21.113062 140292083513216 model_lib.py:717] Forced number of epochs for all eval validations to be 1.
INFO:tensorflow:Maybe overwriting train_steps: 200000
I0528 21:13:21.113316 140292083513216 config_util.py:523] Maybe overwriting train_steps: 200000
INFO:tensorflow:Maybe overwriting use_bfloat16: False
I0528 21:13:21.113430 140292083513216 config_util.py:523] Maybe overwriting use_bfloat16: False
INFO:tensorflow:Maybe overwriting sample_1_of_n_eval_examples: 1
I0528 21:13:21.113519 140292083513216 config_util.py:523] Maybe overwriting sample_1_of_n_eval_examples: 1
INFO:tensorflow:Maybe overwriting eval_num_epochs: 1
I0528 21:13:21.113614 140292083513216 config_util.py:523] Maybe overwriting eval_num_epochs: 1
INFO:tensorflow:Maybe overwriting load_pretrained: True
I0528 21:13:21.113696 140292083513216 config_util.py:523] Maybe overwriting load_pretrained: True
INFO:tensorflow:Ignoring config override key: load_pretrained
I0528 21:13:21.113776 140292083513216 config_util.py:533] Ignoring config override key: load_pretrained
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.
W0528 21:13:21.114626 140292083513216 model_lib.py:733] 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 False
I0528 21:13:21.114744 140292083513216 model_lib.py:768] create_estimator_and_inputs: use_tpu False, export_to_tpu False
INFO:tensorflow:Using config: {'_model_dir': 'training/', '_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 0x7f97ed4dd128>, '_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}
I0528 21:13:21.115245 140292083513216 estimator.py:212] Using config: {'_model_dir': 'training/', '_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 0x7f97ed4dd128>, '_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 0x7f97d328dbf8>) includes params argument, but params are not passed to Estimator.
W0528 21:13:21.115487 140292083513216 model_fn.py:630] Estimator's model_fn (<function create_model_fn.<locals>.model_fn at 0x7f97d328dbf8>) includes params argument, but params are not passed to Estimator.
INFO:tensorflow:Not using Distribute Coordinator.
I0528 21:13:21.116259 140292083513216 estimator_training.py:186] Not using Distribute Coordinator.
INFO:tensorflow:Running training and evaluation locally (non-distributed).
I0528 21:13:21.116456 140292083513216 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.
I0528 21:13:21.116694 140292083513216 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 /usr/local/lib/python3.6/dist-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.
W0528 21:13:21.124795 140292083513216 deprecation.py:323] From /usr/local/lib/python3.6/dist-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.
WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards.
W0528 21:13:21.162153 140292083513216 dataset_builder.py:84] num_readers has been reduced to 1 to match input file shards.
WARNING:tensorflow:From /content/models/research/object_detection/builders/dataset_builder.py:101: parallel_interleave (from tensorflow.contrib.data.python.ops.interleave_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.data.experimental.parallel_interleave(...)`.
W0528 21:13:21.167545 140292083513216 deprecation.py:323] From /content/models/research/object_detection/builders/dataset_builder.py:101: parallel_interleave (from tensorflow.contrib.data.python.ops.interleave_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.data.experimental.parallel_interleave(...)`.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow_core/contrib/data/python/ops/interleave_ops.py:77: 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`.
W0528 21:13:21.167754 140292083513216 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow_core/contrib/data/python/ops/interleave_ops.py:77: 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`.
2020-05-28 21:13:22.910301: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2020-05-28 21:13:22.953259: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-28 21:13:22.953875: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: 
name: Tesla T4 major: 7 minor: 5 memoryClockRate(GHz): 1.59
pciBusID: 0000:00:04.0
2020-05-28 21:13:22.960996: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2020-05-28 21:13:22.967688: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2020-05-28 21:13:22.977811: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0
2020-05-28 21:13:22.985131: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0
2020-05-28 21:13:22.995549: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0
2020-05-28 21:13:23.004617: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0
2020-05-28 21:13:23.025234: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2020-05-28 21:13:23.025382: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-28 21:13:23.026101: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-28 21:13:23.026693: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
WARNING:tensorflow:From /content/models/research/object_detection/inputs.py:77: 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.
W0528 21:13:33.109247 140292083513216 deprecation.py:323] From /content/models/research/object_detection/inputs.py:77: 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 /content/models/research/object_detection/utils/ops.py:493: 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
W0528 21:13:33.221111 140292083513216 deprecation.py:323] From /content/models/research/object_detection/utils/ops.py:493: 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 /usr/local/lib/python3.6/dist-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.
W0528 21:13:39.145547 140292083513216 api.py:332] From /usr/local/lib/python3.6/dist-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 /content/models/research/object_detection/inputs.py:259: 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.
W0528 21:13:42.865469 140292083513216 deprecation.py:323] From /content/models/research/object_detection/inputs.py:259: 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.
WARNING:tensorflow:From /content/models/research/object_detection/builders/dataset_builder.py:174: batch_and_drop_remainder (from tensorflow.contrib.data.python.ops.batching) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.data.Dataset.batch(..., drop_remainder=True)`.
W0528 21:13:46.217640 140292083513216 deprecation.py:323] From /content/models/research/object_detection/builders/dataset_builder.py:174: batch_and_drop_remainder (from tensorflow.contrib.data.python.ops.batching) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.data.Dataset.batch(..., drop_remainder=True)`.
INFO:tensorflow:Calling model_fn.
I0528 21:13:46.233859 140292083513216 estimator.py:1148] Calling model_fn.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tf_slim/layers/layers.py:1089: 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.
W0528 21:13:46.430602 140292083513216 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tf_slim/layers/layers.py:1089: 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
I0528 21:13:49.101978 140292083513216 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0
INFO:tensorflow:depth of additional conv before box predictor: 0
I0528 21:13:49.133970 140292083513216 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0
INFO:tensorflow:depth of additional conv before box predictor: 0
I0528 21:13:49.165436 140292083513216 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0
INFO:tensorflow:depth of additional conv before box predictor: 0
I0528 21:13:49.343221 140292083513216 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0
INFO:tensorflow:depth of additional conv before box predictor: 0
I0528 21:13:49.377842 140292083513216 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0
INFO:tensorflow:depth of additional conv before box predictor: 0
I0528 21:13:49.414346 140292083513216 convolutional_box_predictor.py:156] depth of additional conv before box predictor: 0
W0528 21:13:49.456603 140292083513216 variables_helper.py:161] Variable [FeatureExtractor/MobilenetV2/layer_19_2_Conv2d_2_3x3_s2_512/weights] is available in checkpoint, but has an incompatible shape with model variable. Checkpoint shape: [[1, 1, 256, 512]], model variable shape: [[3, 3, 256, 512]]. This variable will not be initialized from the checkpoint.
W0528 21:13:49.456816 140292083513216 variables_helper.py:161] Variable [FeatureExtractor/MobilenetV2/layer_19_2_Conv2d_3_3x3_s2_256/weights] is available in checkpoint, but has an incompatible shape with model variable. Checkpoint shape: [[1, 1, 128, 256]], model variable shape: [[3, 3, 128, 256]]. This variable will not be initialized from the checkpoint.
W0528 21:13:49.456997 140292083513216 variables_helper.py:161] Variable [FeatureExtractor/MobilenetV2/layer_19_2_Conv2d_4_3x3_s2_256/weights] is available in checkpoint, but has an incompatible shape with model variable. Checkpoint shape: [[1, 1, 128, 256]], model variable shape: [[3, 3, 128, 256]]. This variable will not be initialized from the checkpoint.
W0528 21:13:49.457174 140292083513216 variables_helper.py:161] Variable [FeatureExtractor/MobilenetV2/layer_19_2_Conv2d_5_3x3_s2_128/weights] is available in checkpoint, but has an incompatible shape with model variable. Checkpoint shape: [[1, 1, 64, 128]], model variable shape: [[3, 3, 64, 128]]. This variable will not be initialized from the checkpoint.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-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
W0528 21:13:54.449208 140292083513216 deprecation.py:506] From /usr/local/lib/python3.6/dist-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.
I0528 21:14:00.871218 140292083513216 estimator.py:1150] Done calling model_fn.
INFO:tensorflow:Create CheckpointSaverHook.
I0528 21:14:00.872715 140292083513216 basic_session_run_hooks.py:541] Create CheckpointSaverHook.
INFO:tensorflow:Graph was finalized.
I0528 21:14:04.557027 140292083513216 monitored_session.py:240] Graph was finalized.
2020-05-28 21:14:04.557485: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 AVX512F FMA
2020-05-28 21:14:04.562729: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2000165000 Hz
2020-05-28 21:14:04.563012: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x1771800 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-05-28 21:14:04.563048: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2020-05-28 21:14:04.666903: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-28 21:14:04.667672: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x1770d80 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2020-05-28 21:14:04.667705: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Tesla T4, Compute Capability 7.5
2020-05-28 21:14:04.668018: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-28 21:14:04.668594: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: 
name: Tesla T4 major: 7 minor: 5 memoryClockRate(GHz): 1.59
pciBusID: 0000:00:04.0
2020-05-28 21:14:04.668682: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2020-05-28 21:14:04.668724: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2020-05-28 21:14:04.668747: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0
2020-05-28 21:14:04.668769: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0
2020-05-28 21:14:04.668796: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0
2020-05-28 21:14:04.668819: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0
2020-05-28 21:14:04.668842: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2020-05-28 21:14:04.668951: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-28 21:14:04.669555: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-28 21:14:04.670109: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2020-05-28 21:14:04.670229: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2020-05-28 21:14:04.671546: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-05-28 21:14:04.671575: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165]      0 
2020-05-28 21:14:04.671585: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0:   N 
2020-05-28 21:14:04.671747: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-28 21:14:04.672416: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-28 21:14:04.672994: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:39] Overriding allow_growth setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.
2020-05-28 21:14:04.673037: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 14221 MB memory) -> physical GPU (device: 0, name: Tesla T4, pci bus id: 0000:00:04.0, compute capability: 7.5)
INFO:tensorflow:Running local_init_op.
I0528 21:14:09.605103 140292083513216 session_manager.py:500] Running local_init_op.
INFO:tensorflow:Done running local_init_op.
I0528 21:14:09.941666 140292083513216 session_manager.py:502] Done running local_init_op.
INFO:tensorflow:Saving checkpoints for 0 into training/model.ckpt.
I0528 21:14:18.960145 140292083513216 basic_session_run_hooks.py:606] Saving checkpoints for 0 into training/model.ckpt.
2020-05-28 21:14:36.916392: I tensorflow/core/kernels/data/shuffle_dataset_op.cc:145] Filling up shuffle buffer (this may take a while): 1074 of 2048
2020-05-28 21:14:46.905139: I tensorflow/core/kernels/data/shuffle_dataset_op.cc:145] Filling up shuffle buffer (this may take a while): 2026 of 2048
2020-05-28 21:14:46.910085: I tensorflow/core/kernels/data/shuffle_dataset_op.cc:195] Shuffle buffer filled.
2020-05-28 21:14:47.284742: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2020-05-28 21:14:53.420068: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
INFO:tensorflow:loss = 12.133639, step = 0
I0528 21:14:56.692664 140292083513216 basic_session_run_hooks.py:262] loss = 12.133639, step = 0
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1365, in _do_call
    return fn(*args)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1350, in _run_fn
    target_list, run_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1443, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: 2 root error(s) found.
  (0) Invalid argument: {{function_node __inference_Dataset_map_transform_and_pad_input_data_fn_3047}} assertion failed: [[0.748][0.758]] [[0.67][0.67]]
     [[{{node Assert/AssertGuard/else/_123/Assert}}]]
     [[IteratorGetNext]]
  (1) Invalid argument: {{function_node __inference_Dataset_map_transform_and_pad_input_data_fn_3047}} assertion failed: [[0.748][0.758]] [[0.67][0.67]]
     [[{{node Assert/AssertGuard/else/_123/Assert}}]]
     [[IteratorGetNext]]
     [[IteratorGetNext/_8451]]
0 successful operations.
0 derived errors ignored.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/content/models/research/object_detection/model_main.py", line 114, in <module>
    tf.app.run()
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/platform/app.py", line 40, in run
    _run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
  File "/usr/local/lib/python3.6/dist-packages/absl/app.py", line 299, in run
    _run_main(main, args)
  File "/usr/local/lib/python3.6/dist-packages/absl/app.py", line 250, in _run_main
    sys.exit(main(argv))
  File "/content/models/research/object_detection/model_main.py", line 110, in main
    tf.estimator.train_and_evaluate(estimator, train_spec, eval_specs[0])
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_estimator/python/estimator/training.py", line 473, in train_and_evaluate
    return executor.run()
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_estimator/python/estimator/training.py", line 613, in run
    return self.run_local()
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_estimator/python/estimator/training.py", line 714, in run_local
    saving_listeners=saving_listeners)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_estimator/python/estimator/estimator.py", line 370, in train
    loss = self._train_model(input_fn, hooks, saving_listeners)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_estimator/python/estimator/estimator.py", line 1161, in _train_model
    return self._train_model_default(input_fn, hooks, saving_listeners)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_estimator/python/estimator/estimator.py", line 1195, in _train_model_default
    saving_listeners)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_estimator/python/estimator/estimator.py", line 1494, in _train_with_estimator_spec
    _, loss = mon_sess.run([estimator_spec.train_op, estimator_spec.loss])
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/monitored_session.py", line 754, in run
    run_metadata=run_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/monitored_session.py", line 1259, in run
    run_metadata=run_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/monitored_session.py", line 1360, in run
    raise six.reraise(*original_exc_info)
  File "/usr/local/lib/python3.6/dist-packages/six.py", line 693, in reraise
    raise value
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/monitored_session.py", line 1345, in run
    return self._sess.run(*args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/monitored_session.py", line 1418, in run
    run_metadata=run_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/monitored_session.py", line 1176, in run
    return self._sess.run(*args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 956, in run
    run_metadata_ptr)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1180, in _run
    feed_dict_tensor, options, run_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1359, in _do_run
    run_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1384, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: 2 root error(s) found.
  (0) Invalid argument:  assertion failed: [[0.748][0.758]] [[0.67][0.67]]
     [[{{node Assert/AssertGuard/else/_123/Assert}}]]
     [[IteratorGetNext]]
  (1) Invalid argument:  assertion failed: [[0.748][0.758]] [[0.67][0.67]]
     [[{{node Assert/AssertGuard/else/_123/Assert}}]]
     [[IteratorGetNext]]
     [[IteratorGetNext/_8451]]
0 successful operations.
0 derived errors ignored.

Хотя я нашел похожие вопросы с похожим названием, но ошибки не совпадают . Здесь дополнительно упоминается, что я использую tensorflow-gpu==1.15.0, а модель, используемая для точной настройки, - ssd_mobilenet_v2_coco.

Есть какие-нибудь подсказки, почему возникает эта ошибка?

1 Ответ

1 голос
/ 07 июня 2020

У меня была точно такая же ошибка при создании моих собственных tfrecords для переобучения моей модели. Проблема заключалась в том, что высота одного из помеченных ящиков была отрицательной. Я бы рекомендовал проверить правильность ваших данных.

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