ODENet model for combustion
ODENetMoel example
from ODENet import ODENetModel
dim_input = x_train.shape[1]
dim_label = y_train.shape[1]
model = ODENetModel(
dim_input=dim_input,
dim_label=dim_label,
)
model.summary()
loss_type = "mse"
model.compile(loss=loss_type, optimizer="adam", metrics=["accuracy"])
model.fit(x_train,y_train)
1 maintainer
Release files for ODENet 0.0.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ODENet-0.0.5.tar.gz | 4.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ODENet-0.0.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.9 kB
Release files / ODENet-0.0.5.tar.gz
| Download URL | ODENet-0.0.5.tar.gz |
|---|---|
| Size | 4.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.1.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.3
|
Release files / ODENet-0.0.5-py3-none-any.whl
| Download URL | ODENet-0.0.5-py3-none-any.whl |
|---|---|
| Size | 6.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
f6c4d8d6ee8c553794af4616413333b9d85939412bd53996dd04832bdd3eccee
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BLAKE2b-256 checksum How to use checksums |
1cb7bcd5cc3099a414c60601703cf7e60993ca6adf24c01d26ac1e0ea4276b54
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.1.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.3
|
