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Smartly restore pretrained model weights #2426

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Merged
MMathisLab merged 1 commit into from
Oct 24, 2023
Merged

Smartly restore pretrained model weights #2426

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4 changes: 3 additions & 1 deletion deeplabcut/pose_estimation_tensorflow/core/train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,6 +31,7 @@
)
from deeplabcut.pose_estimation_tensorflow.nnets import PoseNetFactory
from deeplabcut.pose_estimation_tensorflow.util.logging import setup_logging
from deeplabcut.utils import auxfun_models


class LearningRate(object):
Expand Down Expand Up @@ -243,7 +244,8 @@ def train(
sess.run(tf.compat.v1.local_variables_initializer())

# Restore variables from disk.
restorer.restore(sess, cfg["init_weights"])
auxfun_models.smart_restore(restorer, sess, cfg["init_weights"], net_type)

if maxiters is None:
max_iter = int(cfg["multi_step"][-1][1])
else:
Expand Down
4 changes: 3 additions & 1 deletion deeplabcut/pose_estimation_tensorflow/core/train_multianimal.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,6 +28,7 @@
get_optimizer,
LearningRate,
)
from deeplabcut.utils import auxfun_models


def train(
Expand Down Expand Up @@ -157,7 +158,8 @@ def train(
sess.run(tf.compat.v1.global_variables_initializer())
sess.run(tf.compat.v1.local_variables_initializer())

restorer.restore(sess, cfg["init_weights"])
auxfun_models.smart_restore(restorer, sess, cfg["init_weights"], net_type)

if maxiters is None:
max_iter = int(cfg["multi_step"][-1][1])
else:
Expand Down
17 changes: 17 additions & 0 deletions deeplabcut/utils/auxfun_models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -168,6 +168,23 @@ def set_visible_devices(gputouse: int):
tf.config.set_visible_devices(physical_devices[gputouse], "GPU")


def smart_restore(restorer, sess, checkpoint_path, net_type):
"Restore pretrained weights, smartly redownloading them if missing."
try:
restorer.restore(sess, checkpoint_path)
except ValueError as e: # The path may be wrong, or the weights no longer exist
dlcparent_path = auxiliaryfunctions.get_deeplabcut_path()
correct_model_path = os.path.join(
dlcparent_path, MODELTYPE_FILEPATH_MAP[net_type],
)
if checkpoint_path == correct_model_path:
# The path is right, hence the weights are missing; we'll download them again.
_ = check_for_weights(net_type, Path(dlcparent_path))
restorer.restore(sess, checkpoint_path)
else:
raise ValueError(e)


# Aliases for backwards-compatibility
Check4Weights = check_for_weights
Downloadweights = download_weights
Expand Down