"seadiver" is a Python based DeepLearning Framework which maximized its accessibility for DL beginners.
You can start by creating a model in any desired structure with only 3 required arguments. Easily train, predict and visualize your model.
"seadiver" supports 'export' and 'import' function in 'json' format. pip install is available >> "pip install seadiver"
Simple example for usage is like below.
import seadiver
#build a model model = seadiver.model.ANN(input_shape=(1, 784), structure = (100, 100, 100, 10), output="softmax") model.describe() #prints how the model looks
#train model.train(y= TRAIN_BATCH, t= ANSWER_BATCH, learning_rate=0.001, iteration=1000)
#predict model.predict(x = INPUT)
#export model as a 'json' file to a local directory model.export(directory = "C:\Users....", file_name="myModel.json")
#import model from a local directory imported_model = seadiver.factory.make(file = "C:\Users.....\myModel.json")
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Updates on more types of model such as 'CNN', 'LSTM' is underway. Thanks, and please contact the author via e-mail for any comment.
Metadata
Release files for seadiver 0.3.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| seadiver-0.3.6.tar.gz | 9.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| seadiver-0.3.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 21.7 kB
Release files / seadiver-0.3.6.tar.gz
| Download URL | seadiver-0.3.6.tar.gz |
|---|---|
| Size | 9.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.0.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.7.0
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Release files / seadiver-0.3.6-py3-none-any.whl
| Download URL | seadiver-0.3.6-py3-none-any.whl |
|---|---|
| Size | 12.6 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.0.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.7.0
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