Hi,
I am using the below specs for training unet in binary segmentation task.
random_seed: 42
model_config {
model_input_width: 1024
model_input_height: 1280
model_input_channels: 3
arch: “vanilla_unet”
use_batch_norm: true
training_precision {
backend_floatx: FLOAT32
}
}
training_config {
batch_size: 16
epochs: 10
log_summary_steps: 10
checkpoint_interval: 1
loss: “dice”
learning_rate:0.0001
regularizer {
type: L2
weight: 3.00000002618e-09
}
optimizer {
adam {
epsilon: 9.99999993923e-09
beta1: 0.899999976158
beta2: 0.999000012875
}
}
}
dataset_config {
dataset: “custom”
augment: True
input_image_type: “color”
train_images_path:“/workspace/tlt-experiments/data/endoData/images/train”
train_masks_path:“/workspace/tlt-experiments/data/endoData/masks/train”
val_images_path:“/workspace/tlt-experiments/data/endoData/images/val”
val_masks_path:“/workspace/tlt-experiments/data/endoData/masks/val”
test_images_path:“/workspace/tlt-experiments/data/endoData/images/test”
data_class_config {
target_classes {
name: “foreground”
mapping_class: “foreground”
label_id: 0
}
target_classes {
name: “background”
mapping_class: “background”
label_id: 1
}
}
}
I am getting the following error :
ValueError: A Concatenate
layer requires inputs with matching shapes except for the concat axis. Got inputs shapes: [(None, 256, 280, 216), (None, 256, 281, 217)]
Traceback (most recent call last):
** File “/usr/local/bin/unet”, line 8, in **
** sys.exit(main())**
** File “/home/vpraveen/.cache/dazel/_dazel_vpraveen/216c8b41e526c3295d3b802489ac2034/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/unet/entrypoint/unet.py”, line 12, in main**
** File “/home/vpraveen/.cache/dazel/_dazel_vpraveen/216c8b41e526c3295d3b802489ac2034/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/common/entrypoint/entrypoint.py”, line 296, in launch_job**
AssertionError: Process run failed.
2021-04-19 00:29:40,037 [INFO] tlt.components.docker_handler.docker_handler: Stopping container.
input image dimensions 1024 and 1280 are multiples of 16 which is the requirement for unet traning.
I don’t know where I was wrong. I even height and width as 320. It didn’t even work.
Would anyone please help me with this issue?
Thanks,
Harsha.