Hi all, I’m trying to train a yolov3 model using TAO toolkit and my custom data.
I successfully created a KITTI version of my data and then converted it to tfrecords using the tao command.
But when I try to execute the training command I get this error log:
in particular I don’t know where to look to debug the AssertionError AssertionError: No files match pattern /root/datasets/ at the end of the log.
Does anyone have suggestions?
Using TensorFlow backend.
WARNING:tensorflow:Deprecation warnings have been disabled. Set TF_ENABLE_DEPRECATION_WARNINGS=1 to re-enable them.
WARNING:tensorflow:From /root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v3/scripts/train.py:40: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.
2022-05-06 14:43:58,071 [WARNING] tensorflow: From /root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v3/scripts/train.py:40: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.
WARNING:tensorflow:From /root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v3/scripts/train.py:43: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.
2022-05-06 14:43:58,073 [WARNING] tensorflow: From /root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v3/scripts/train.py:43: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:153: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.
2022-05-06 14:43:58,490 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:153: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:517: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.
2022-05-06 14:43:58,506 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:517: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:4138: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.
2022-05-06 14:43:58,508 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:4138: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:1834: The name tf.nn.fused_batch_norm is deprecated. Please use tf.compat.v1.nn.fused_batch_norm instead.
2022-05-06 14:43:58,531 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:1834: The name tf.nn.fused_batch_norm is deprecated. Please use tf.compat.v1.nn.fused_batch_norm instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:2018: The name tf.image.resize_nearest_neighbor is deprecated. Please use tf.compat.v1.image.resize_nearest_neighbor instead.
2022-05-06 14:43:59,227 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:2018: The name tf.image.resize_nearest_neighbor is deprecated. Please use tf.compat.v1.image.resize_nearest_neighbor instead.
Traceback (most recent call last):
File "/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v3/scripts/train.py", line 110, in <module>
File "/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/common/utils.py", line 528, in return_func
File "/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/common/utils.py", line 516, in return_func
File "/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v3/scripts/train.py", line 106, in main
File "/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v3/scripts/train.py", line 58, in run_experiment
File "/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v3/models/utils.py", line 30, in build_training_pipeline
File "/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v3/data_loader/data_loader.py", line 67, in __init__
File "/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v3/data_loader/yolo_v3_data_loader.py", line 790, in build_dataloader
File "/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v3/data_loader/yolo_v3_data_loader.py", line 750, in build_data_source_lists
File "/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/detectnet_v2/dataloader/build_dataloader.py", line 59, in _pattern_to_files
AssertionError: No files match pattern /root/datasets/.
• Hardware (T4/V100/Xavier/Nano/etc): RTX2080
• Network Type (Detectnet_v2/Faster_rcnn/Yolo_v4/LPRnet/Mask_rcnn/Classification/etc): Yolo_v3
• TLT Version (Please run “tlt info --verbose” and share “docker_tag” here)
Configuration of the TAO Toolkit Instance
dockers:
nvidia/tao/tao-toolkit-tf:
v3.21.11-tf1.15.5-py3:
docker_registry: nvcr.io
tasks:
1. augment
2. bpnet
3. classification
4. dssd
5. emotionnet
6. efficientdet
7. fpenet
8. gazenet
9. gesturenet
10. heartratenet
11. lprnet
12. mask_rcnn
13. multitask_classification
14. retinanet
15. ssd
16. unet
17. yolo_v3
18. yolo_v4
19. yolo_v4_tiny
20. converter
v3.21.11-tf1.15.4-py3:
docker_registry: nvcr.io
tasks:
1. detectnet_v2
2. faster_rcnn
nvidia/tao/tao-toolkit-pyt:
v3.21.11-py3:
docker_registry: nvcr.io
tasks:
1. speech_to_text
2. speech_to_text_citrinet
3. text_classification
4. question_answering
5. token_classification
6. intent_slot_classification
7. punctuation_and_capitalization
8. action_recognition
v3.22.02-py3:
docker_registry: nvcr.io
tasks:
1. spectro_gen
2. vocoder
nvidia/tao/tao-toolkit-lm:
v3.21.08-py3:
docker_registry: nvcr.io
tasks:
1. n_gram
format_version: 2.0
toolkit_version: 3.22.02
published_date: 02/28/2022
• Training spec file(If have, please share here)
random_seed: 42
yolov3_config {
big_anchor_shape: "[(514.17, 78.47), (220.24, 217.41), (642.07, 120.47)]"
mid_anchor_shape: "[(294.79, 47.24), (169.48, 112.35), (156.00, 184.47)]"
small_anchor_shape: "[(30.97, 30.12), (112.12, 67.47), (108.68, 127.88)]"
matching_neutral_box_iou: 0.7
arch: "resnet"
nlayers: 18
arch_conv_blocks: 2
loss_loc_weight: 0.8
loss_neg_obj_weights: 100.0
loss_class_weights: 1.0
freeze_bn: false
#freeze_blocks: 0
force_relu: false
}
training_config {
batch_size_per_gpu: 8
num_epochs: 80
enable_qat: false
checkpoint_interval: 10
learning_rate {
soft_start_annealing_schedule {
min_learning_rate: 1e-6
max_learning_rate: 1e-4
soft_start: 0.1
annealing: 0.5
}
}
regularizer {
type: L1
weight: 3e-5
}
optimizer {
adam {
epsilon: 1e-7
beta1: 0.9
beta2: 0.999
amsgrad: false
}
}
pretrain_model_path: "/workspace/tao-experiments/tao_yolo_v3_01/pretrained_resnet18/pretrained_object_detection_vresnet18/resnet_18.hdf5"
}
eval_config {
average_precision_mode: SAMPLE
batch_size: 8
matching_iou_threshold: 0.5
}
nms_config {
confidence_threshold: 0.001
clustering_iou_threshold: 0.5
top_k: 200
force_on_cpu: True
}
augmentation_config {
hue: 0.1
saturation: 1.5
exposure:1.5
vertical_flip:0
horizontal_flip: 0.5
jitter: 0.3
output_width: 1248
output_height: 384
output_channel: 3
randomize_input_shape_period: 0
}
dataset_config {
data_sources: {
tfrecords_path: "/workspace/tao-experiments/data/tfrecords/insulators_test_dataset/train/*"
image_directory_path: "/workspace/tao-experiments/data/insulators_test_dataset/train/images/"
}
include_difficult_in_training: true
image_extension: "JPG"
target_class_mapping {
key: "insulator"
value: "insulator"
}
validation_data_sources: {
label_directory_path: "/workspace/tao-experiments/data/insulators_test_dataset/test/labels/"
image_directory_path: "/workspace/tao-experiments/data/insulators_test_dataset/test/images/"
}
}
• How to reproduce the issue ? (This is for errors. Please share the command line and the detailed log here.)
!tao yolo_v3 train -e $TAO_SPECS_DIR/yolo_v3_train_resnet18_tfrecord.txt \
-r $TAO_EXPERIMENT_DIR/experiment_dir_unpruned \
-k $KEY \
--log_file $TAO_EXPERIMENT_DIR/experiment_dir_unpruned/train_log.txt \
--gpus 1