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add bcn model #339

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add bcn model #339

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e55303b
add bcn model
daidaiershidi Jan 17, 2022
cb23d22
add bcn model
daidaiershidi Jan 18, 2022
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5 changes: 3 additions & 2 deletions .pre-commit-config.yaml
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Original file line number Diff line number Diff line change
@@ -1,14 +1,15 @@
repos:
- repo: local
hooks:
- id: yapf
name: yapf
entry: yapf
entry: bash -c 'yapf "$@"; git add -u' --
language: system
args: [-i, --style .style.yapf]
files: \.py$

- repo: https://github.com/pre-commit/pre-commit-hooks
sha: a11d9314b22d8f8c7556443875b731ef05965464
rev: a11d9314b22d8f8c7556443875b731ef05965464
hooks:
- id: check-merge-conflict
- id: check-symlinks
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75 changes: 75 additions & 0 deletions configs/segmentation/bcn/bgm/50salads/full/split1.yaml
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MODEL: #MODEL field
framework: "BcnBgm"
backbone:
name: "BcnBgm"
dataset: "50salads"
use_full: True
loss:
name: "BcnBgmLoss"
head:
name: "BcnBgmHead"
dataset: "50salads"
use_full: True
test_mode: "more"
results_path: "./output/BCN/50salads/split1/BcnBgmFull/results"

DATASET: #DATASET field
batch_size: 1
valid_batch_size: 1
test_batch_size: 1
num_workers: 4
train:
format: 'BcnBgmDataset'
file_path: "./data/50salads/splits/train.split1.bundle"
use_full: True
bd_ratio: 0.05
valid:
format: 'BcnBgmDataset'
file_path: "./data/50salads/splits/test.split1.bundle"
use_full: True
bd_ratio: 0.05
test:
format: 'BcnBgmDataset'
file_path: "./data/50salads/splits/test.split1.bundle"
use_full: True
bd_ratio: 0.05

PIPELINE: #PIPELINE field
train:
decode:
name: "GetBcnBgmTrainLabel"

valid:
decode:
name: "GetBcnBgmTrainLabel"

test:
decode:
name: "GetBcnBgmTrainLabel"

OPTIMIZER: #OPTIMIZER field
name: 'Adam'
learning_rate:
name: 'CustomMultiStepDecay'
learning_rate: 0.001
milestones: [100, 200]
gamma: 0.3
weight_decay:
name: 'L2'
value: 0.0001

METRIC: #METRIC field
name: 'BcnBgmMetric'

INFERENCE:
name: 'BcnBgmFull_Inference_helper'
num_channels: 2048
sample_rate: 2
result_path: './inference/'

output_dir: "./output/BCN/50salads/split1/BcnBgmFull/"
log_interval: 2000
epochs: 300
log_level: "DEBUG"
save_interval: 2000
model_name: "BcnBgmFull"
75 changes: 75 additions & 0 deletions configs/segmentation/bcn/bgm/50salads/full/split2.yaml
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Original file line number Diff line number Diff line change
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MODEL: #MODEL field
framework: "BcnBgm"
backbone:
name: "BcnBgm"
dataset: "50salads"
use_full: True
loss:
name: "BcnBgmLoss"
head:
name: "BcnBgmHead"
dataset: "50salads"
use_full: True
test_mode: "more"
results_path: "./output/BCN/50salads/split2/BcnBgmFull/results"

DATASET: #DATASET field
batch_size: 1
valid_batch_size: 1
test_batch_size: 1
num_workers: 4
train:
format: 'BcnBgmDataset'
file_path: "./data/50salads/splits/train.split2.bundle"
use_full: True
bd_ratio: 0.05
valid:
format: 'BcnBgmDataset'
file_path: "./data/50salads/splits/test.split2.bundle"
use_full: True
bd_ratio: 0.05
test:
format: 'BcnBgmDataset'
file_path: "./data/50salads/splits/test.split2.bundle"
use_full: True
bd_ratio: 0.05

PIPELINE: #PIPELINE field
train:
decode:
name: "GetBcnBgmTrainLabel"

valid:
decode:
name: "GetBcnBgmTrainLabel"

test:
decode:
name: "GetBcnBgmTrainLabel"

OPTIMIZER: #OPTIMIZER field
name: 'Adam'
learning_rate:
name: 'CustomMultiStepDecay'
learning_rate: 0.001
milestones: [100, 200]
gamma: 0.3
weight_decay:
name: 'L2'
value: 0.0001

METRIC: #METRIC field
name: 'BcnBgmMetric'

INFERENCE:
name: 'BcnBgmFull_Inference_helper'
num_channels: 2048
sample_rate: 2
result_path: './inference/'

output_dir: "./output/BCN/50salads/split2/BcnBgmFull/"
log_interval: 2000
epochs: 300
log_level: "DEBUG"
save_interval: 2000
model_name: "BcnBgmFull"
75 changes: 75 additions & 0 deletions configs/segmentation/bcn/bgm/50salads/full/split3.yaml
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Original file line number Diff line number Diff line change
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MODEL: #MODEL field
framework: "BcnBgm"
backbone:
name: "BcnBgm"
dataset: "50salads"
use_full: True
loss:
name: "BcnBgmLoss"
head:
name: "BcnBgmHead"
dataset: "50salads"
use_full: True
test_mode: "more"
results_path: "./output/BCN/50salads/split3/BcnBgmFull/results"

DATASET: #DATASET field
batch_size: 1
valid_batch_size: 1
test_batch_size: 1
num_workers: 4
train:
format: 'BcnBgmDataset'
file_path: "./data/50salads/splits/train.split3.bundle"
use_full: True
bd_ratio: 0.05
valid:
format: 'BcnBgmDataset'
file_path: "./data/50salads/splits/test.split3.bundle"
use_full: True
bd_ratio: 0.05
test:
format: 'BcnBgmDataset'
file_path: "./data/50salads/splits/test.split3.bundle"
use_full: True
bd_ratio: 0.05

PIPELINE: #PIPELINE field
train:
decode:
name: "GetBcnBgmTrainLabel"

valid:
decode:
name: "GetBcnBgmTrainLabel"

test:
decode:
name: "GetBcnBgmTrainLabel"

OPTIMIZER: #OPTIMIZER field
name: 'Adam'
learning_rate:
name: 'CustomMultiStepDecay'
learning_rate: 0.001
milestones: [100, 200]
gamma: 0.3
weight_decay:
name: 'L2'
value: 0.0001

METRIC: #METRIC field
name: 'BcnBgmMetric'

INFERENCE:
name: 'BcnBgmFull_Inference_helper'
num_channels: 2048
sample_rate: 2
result_path: './inference/'

output_dir: "./output/BCN/50salads/split3/BcnBgmFull/"
log_interval: 2000
epochs: 300
log_level: "DEBUG"
save_interval: 2000
model_name: "BcnBgmFull"
75 changes: 75 additions & 0 deletions configs/segmentation/bcn/bgm/50salads/full/split4.yaml
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Original file line number Diff line number Diff line change
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MODEL: #MODEL field
framework: "BcnBgm"
backbone:
name: "BcnBgm"
dataset: "50salads"
use_full: True
loss:
name: "BcnBgmLoss"
head:
name: "BcnBgmHead"
dataset: "50salads"
use_full: True
test_mode: "more"
results_path: "./output/BCN/50salads/split4/BcnBgmFull/results"

DATASET: #DATASET field
batch_size: 1
valid_batch_size: 1
test_batch_size: 1
num_workers: 4
train:
format: 'BcnBgmDataset'
file_path: "./data/50salads/splits/train.split4.bundle"
use_full: True
bd_ratio: 0.05
valid:
format: 'BcnBgmDataset'
file_path: "./data/50salads/splits/test.split4.bundle"
use_full: True
bd_ratio: 0.05
test:
format: 'BcnBgmDataset'
file_path: "./data/50salads/splits/test.split4.bundle"
use_full: True
bd_ratio: 0.05

PIPELINE: #PIPELINE field
train:
decode:
name: "GetBcnBgmTrainLabel"

valid:
decode:
name: "GetBcnBgmTrainLabel"

test:
decode:
name: "GetBcnBgmTrainLabel"

OPTIMIZER: #OPTIMIZER field
name: 'Adam'
learning_rate:
name: 'CustomMultiStepDecay'
learning_rate: 0.001
milestones: [100, 200]
gamma: 0.3
weight_decay:
name: 'L2'
value: 0.0001

METRIC: #METRIC field
name: 'BcnBgmMetric'

INFERENCE:
name: 'BcnBgmFull_Inference_helper'
num_channels: 2048
sample_rate: 2
result_path: './inference/'

output_dir: "./output/BCN/50salads/split4/BcnBgmFull/"
log_interval: 2000
epochs: 300
log_level: "DEBUG"
save_interval: 2000
model_name: "BcnBgmFull"
75 changes: 75 additions & 0 deletions configs/segmentation/bcn/bgm/50salads/full/split5.yaml
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Original file line number Diff line number Diff line change
@@ -0,0 +1,75 @@
MODEL: #MODEL field
framework: "BcnBgm"
backbone:
name: "BcnBgm"
dataset: "50salads"
use_full: True
loss:
name: "BcnBgmLoss"
head:
name: "BcnBgmHead"
dataset: "50salads"
use_full: True
test_mode: "more"
results_path: "./output/BCN/50salads/split5/BcnBgmFull/results"

DATASET: #DATASET field
batch_size: 1
valid_batch_size: 1
test_batch_size: 1
num_workers: 4
train:
format: 'BcnBgmDataset'
file_path: "./data/50salads/splits/train.split5.bundle"
use_full: True
bd_ratio: 0.05
valid:
format: 'BcnBgmDataset'
file_path: "./data/50salads/splits/test.split5.bundle"
use_full: True
bd_ratio: 0.05
test:
format: 'BcnBgmDataset'
file_path: "./data/50salads/splits/test.split5.bundle"
use_full: True
bd_ratio: 0.05

PIPELINE: #PIPELINE field
train:
decode:
name: "GetBcnBgmTrainLabel"

valid:
decode:
name: "GetBcnBgmTrainLabel"

test:
decode:
name: "GetBcnBgmTrainLabel"

OPTIMIZER: #OPTIMIZER field
name: 'Adam'
learning_rate:
name: 'CustomMultiStepDecay'
learning_rate: 0.001
milestones: [100, 200]
gamma: 0.3
weight_decay:
name: 'L2'
value: 0.0001

METRIC: #METRIC field
name: 'BcnBgmMetric'

INFERENCE:
name: 'BcnBgmFull_Inference_helper'
num_channels: 2048
sample_rate: 2
result_path: './inference/'

output_dir: "./output/BCN/50salads/split5/BcnBgmFull/"
log_interval: 2000
epochs: 300
log_level: "DEBUG"
save_interval: 2000
model_name: "BcnBgmFull"
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