Please provide the following information when requesting support.
• Hardware (NVIDIA RTX 3080Ti)
• Network Type (Mask_rcnn)
• TLT Version (Tensorflow backend TF_1)
• Training spec file
seed: 123
use_amp: False
warmup_steps: 0
checkpoint: “/workspace/tao-tf1/pretrained_models/resnet_50.hdf5”
learning_rate_steps: “[1, 2, 3]”
learning_rate_decay_levels: “[0.1, 0.02, 0.002]”
total_steps: 120000
num_epochs: 1
num_examples_per_epoch: 50
train_batch_size: 2
eval_batch_size: 2
num_steps_per_eval: 3
momentum: 0.9
l2_weight_decay: 0.0001
l1_weight_decay: 0.0
warmup_learning_rate: 0.0001
init_learning_rate: 0.02
pruned_model_path: “/workspace/tlt-experiments/maskrcnn/pruned_model/model.tlt”
data_config{
image_size: “(832, 1344)”
augment_input_data: True
eval_samples: 5
training_file_pattern: “/workspace/tao-tf1/nvidia_tao_tf1/cv/mask_rcnn/tfrecords/"
validation_file_pattern: "/workspace/tao-tf1/nvidia_tao_tf1/cv/mask_rcnn/tfrecords/”
val_json_file: “/workspace/tao-tf1/nvidia_tao_tf1/cv/dataset/coco/annotations/instances_val2017.json”
# dataset specific parameters
num_classes: 91
skip_crowd_during_training: True
max_num_instances: 200
}
maskrcnn_config {
nlayers: 50
arch: “resnet”
freeze_bn: True
freeze_blocks: “[0,1]”
gt_mask_size: 112
# Region Proposal Network
rpn_positive_overlap: 0.7
rpn_negative_overlap: 0.3
rpn_batch_size_per_im: 256
rpn_fg_fraction: 0.5
rpn_min_size: 0.
# Proposal layer.
batch_size_per_im: 512
fg_fraction: 0.25
fg_thresh: 0.5
bg_thresh_hi: 0.5
bg_thresh_lo: 0.
# Faster-RCNN heads.
fast_rcnn_mlp_head_dim: 1024
bbox_reg_weights: "(10., 10., 5., 5.)"
# Mask-RCNN heads.
include_mask: True
mrcnn_resolution: 28
# training
train_rpn_pre_nms_topn: 2000
train_rpn_post_nms_topn: 1000
train_rpn_nms_threshold: 0.7
# evaluation
test_detections_per_image: 100
test_nms: 0.5
test_rpn_pre_nms_topn: 1000
test_rpn_post_nms_topn: 1000
test_rpn_nms_thresh: 0.7
# model architecture
min_level: 2
max_level: 6
num_scales: 1
aspect_ratios: "[(1.0, 1.0), (1.4, 0.7), (0.7, 1.4)]"
anchor_scale: 8
# localization loss
rpn_box_loss_weight: 1.0
fast_rcnn_box_loss_weight: 1.0
mrcnn_weight_loss_mask: 1.0
}
• How to reproduce the issue ?
/workspace/tao-tf1/nvidia_tao_tf1/cv# python mask_rcnn/scripts/train.py -e mask_rcnn/experiment_specs/default.txt -d /workspace/tao-tf1/nvidia_tao_tf1/cv/mask_rcnn/results/exp4
i want to save the model in hdf5 format i am getting the model in .tlt format
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