TFSurgeon
Allows for dynamic tensorflow keras model edition.
You can install this package with pip and call it as from tfsurgeon import edit_model.
How to use
- remove layers based on layer type
- remove layers based on name or index
- replace layers from one type to another
- replace specific layer (name) by another layer (callable)
see docstring for examples in src/tfsurgeon/tfsurgeon.py.
import
from tfsurgeon import edit_model
import tensorflow as tf
model = tf.keras.applications.MobileNetV2(weights=None)
new_model = edit_model(
model=model,
replace_layers_by_types=[
[tf.keras.layers.BatchNormalization, tf.keras.layers.LayerNormalization]
],
verbose=True,
)
CLI
no supported yet
1 maintainer
Metadata
1 maintainer
Release files for tfsurgeon 0.0.8
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
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| tfsurgeon-0.0.8.tar.gz | 7.6 kB | Without provenance | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| tfsurgeon-0.0.8-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 20.5 kB
Release files / tfsurgeon-0.0.8.tar.gz
| Download URL | tfsurgeon-0.0.8.tar.gz |
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| Size | 7.6 kB |
| Tags | Source |
|
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Release files / tfsurgeon-0.0.8-py3-none-any.whl
| Download URL | tfsurgeon-0.0.8-py3-none-any.whl |
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| Size | 12.8 kB |
| Tags | Python 3 |
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