我们正在尝试提交有关GCP的培训工作。我遵循了宠物教程，走了很远，但是现在我有点卡住了，希望有人能指出我正确的方向。
我们正在使用以下命令开始培训工作：
gcloud ml-engine jobs submit training `whoami`_object_detection_`date +%s` \
--job-dir=${YOUR_GCS_BUCKET}/train \
--packages dist/object_detection-0.1.tar.gz,slim/dist/slim-0.1.tar.gz,/tmp/pycocotools/pycocotools-2.0.tar.gz \
--module-name object_detection.model_main \
--runtime-version 1.11 \
--region europe-west1 \
--python-version 3.5
该作业已成功排队，并显示在ML Engine任务概述中。出现许多日志，看起来都很正确，直到实际开始培训工作为止。然后出现错误（下面的日志中的第3行）。我将日志的最后几行放在下面：
2019-02-26 16:03:42.994 CET master-replica-0 Running command: python3 -m object_detection.model_main --job-dir gs://tiotf_train_store/train
2019-02-26 16:04:01.119 CET master-replica-0 TF_CONFIG environment variable: {'environment': 'cloud', 'task': {'type': 'master', 'index': 0, 'cloud': 'sd5078b2935497c61-ml'}, 'job': {'runtime_version': '1.11', 'python_module': 'object_detection.model_main', 'package_uris': ['gs://tiotf_train_store/train/packages/4ce59656c997bb99dded0300dd801c07db79e589aee2d33fd2cc15b844d27c96/object_detection-0.1.tar.gz', 'gs://tiotf_train_store/train/packages/4ce59656c997bb99dded0300dd801c07db79e589aee2d33fd2cc15b844d27c96/slim-0.1.tar.gz', 'gs://tiotf_train_store/train/packages/4ce59656c997bb99dded0300dd801c07db79e589aee2d33fd2cc15b844d27c96/pycocotools-2.0.tar.gz'], 'region': 'europe-west1', 'job_dir': 'gs://tiotf_train_store/train', 'run_on_raw_vm': True, 'python_version': '3.5'}, 'cluster': {'master': ['127.0.0.1:2222']}}
2019-02-26 16:04:01.156 CET master-replica-0 Traceback (most recent call last): File "/usr/lib/python3.5/runpy.py", line 184, in _run_module_as_main "__main__", mod_spec) File "/usr/lib/python3.5/runpy.py", line 85, in _run_code exec(code, run_globals) File "/root/.local/lib/python3.5/site-packages/object_detection/model_main.py", line 109, in <module> tf.app.run() File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/platform/app.py", line 125, in run _sys.exit(main(argv)) File "/root/.local/lib/python3.5/site-packages/object_detection/model_main.py", line 71, in main FLAGS.sample_1_of_n_eval_on_train_examples)) File "/root/.local/lib/python3.5/site-packages/object_detection/model_lib.py", line 566, in create_estimator_and_inputs config_override=config_override) File "/root/.local/lib/python3.5/site-packages/object_detection/utils/config_util.py", line 95, in get_configs_from_pipeline_file proto_str = f.read() File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/lib/io/file_io.py", line 125, in read self._preread_check() File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/lib/io/file_io.py", line 85, in _preread_check compat.as_bytes(self.__name), 1024 * 512, status) File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/util/compat.py", line 61, in as_bytes (bytes_or_text,)) TypeError: Expected binary or unicode string, got None
2019-02-26 16:04:01.623 CET master-replica-0 Command '['python3', '-m', 'object_detection.model_main', '--job-dir', 'gs://tiotf_train_store/train']' returned non-zero exit status 1
有人可以指出我在哪里寻找可能的解决方案吗？所有数据都存在于上述子存储区的数据子文件夹中。 我还将配置文件放在存储桶中（名为faster_rcnn_resnet101_pets.config）
model {
faster_rcnn {
num_classes: 37
image_resizer {
keep_aspect_ratio_resizer {
min_dimension: 600
max_dimension: 1024
}
}
feature_extractor {
type: 'faster_rcnn_resnet101'
first_stage_features_stride: 16
}
first_stage_anchor_generator {
grid_anchor_generator {
scales: [0.25, 0.5, 1.0, 2.0]
aspect_ratios: [0.5, 1.0, 2.0]
height_stride: 16
width_stride: 16
}
}
first_stage_box_predictor_conv_hyperparams {
op: CONV
regularizer {
l2_regularizer {
weight: 0.0
}
}
initializer {
truncated_normal_initializer {
stddev: 0.01
}
}
}
first_stage_nms_score_threshold: 0.0
first_stage_nms_iou_threshold: 0.7
first_stage_max_proposals: 300
first_stage_localization_loss_weight: 2.0
first_stage_objectness_loss_weight: 1.0
initial_crop_size: 14
maxpool_kernel_size: 2
maxpool_stride: 2
second_stage_box_predictor {
mask_rcnn_box_predictor {
use_dropout: false
dropout_keep_probability: 1.0
fc_hyperparams {
op: FC
regularizer {
l2_regularizer {
weight: 0.0
}
}
initializer {
variance_scaling_initializer {
factor: 1.0
uniform: true
mode: FAN_AVG
}
}
}
}
}
second_stage_post_processing {
batch_non_max_suppression {
score_threshold: 0.0
iou_threshold: 0.6
max_detections_per_class: 100
max_total_detections: 300
}
score_converter: SOFTMAX
}
second_stage_localization_loss_weight: 2.0
second_stage_classification_loss_weight: 1.0
}
}
train_config: {
batch_size: 1
optimizer {
momentum_optimizer: {
learning_rate: {
manual_step_learning_rate {
initial_learning_rate: 0.0003
schedule {
step: 900000
learning_rate: .00003
}
schedule {
step: 1200000
learning_rate: .000003
}
}
}
momentum_optimizer_value: 0.9
}
use_moving_average: false
}
gradient_clipping_by_norm: 10.0
fine_tune_checkpoint: "gs://tiotf_train_store/data/model.ckpt"
from_detection_checkpoint: true
load_all_detection_checkpoint_vars: true
# Note: The below line limits the training process to 200K steps, which we
# empirically found to be sufficient enough to train the pets dataset. This
# effectively bypasses the learning rate schedule (the learning rate will
# never decay). Remove the below line to train indefinitely.
num_steps: 200000
data_augmentation_options {
random_horizontal_flip {
}
}
}
train_input_reader: {
tf_record_input_reader {
input_path: "gs://tiotf_train_store/data/pet_faces_train.record-?????-of-00010"
}
label_map_path: "gs://tiotf_train_store/data/pet_label_map.pbtxt"
}
eval_config: {
metrics_set: "coco_detection_metrics"
num_examples: 1101
}
eval_input_reader: {
tf_record_input_reader {
input_path: "gs://tiotf_train_store/data/pet_faces_val.record-?????-of-00010"
}
label_map_path: "gs://tiotf_train_store/data/pet_label_map.pbtxt"
shuffle: false
num_readers: 1
}
感谢您的帮助。
答案 0 :(得分：2)
经过数小时的尝试，我认为我找到了问题。在gcloud命令中添加了以下参数：
--
--pipeline_config_path=[path to .config file]
现在，培训工作可以正确开始了。