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Project description
DeepTensor
- DeepTensor: A minimal deep learning library focused on custom autograd and efficient tensor operations.
Installation
pip install deeptensor
Checkout Demo
Check Docs
Basic Usage
from deeptensor import (
# model
Model,
# Layers
FeedForwardLayer,
# activation layers
GeLu,
LeakyReLu,
ReLu,
Sigmoid,
SoftMax,
Tanh,
# core objects
Tensor,
Value,
# optimizers
SGD,
Momentum,
AdaGrad,
RMSprop,
Adam,
# losses
mean_squared_error,
cross_entropy,
)
model = Model(
[
FeedForwardLayer(2, 16),
ReLu(),
FeedForwardLayer(16, 16),
LeakyReLu(0.1),
FeedForwardLayer(16, 1),
Sigmoid(),
],
False, # using_cuda
)
opt = Adam(model, 0.01) # learning rate
print(model)
tensor_input = Tensor([2])
tensor_input.set(0, Value(2.4))
tensor_input.set(1, Value(5.2))
out = model(tensor_input)
loss = mean_squared_error(out, YOUR_EXPECTED_OUTPUT)
# backprop
loss.backward()
opt.step()
opt.zero_grad()
WIP
- Save & Load model
- Train MNIST model
- Train a character-level transformer model
- Add support for DDP
- Add support for CUDA execution
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a9786b52f4cdb982ea6b6d2bc99e06df5042caf4b99d83f7a29ebf3a1b644bc5
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| MD5 |
3bfa8a25604a425bee0ed7c939c1e459
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| BLAKE2b-256 |
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File details
Details for the file deeptensor-0.3.0-cp39-cp39-macosx_10_9_x86_64.whl.
File metadata
- Download URL: deeptensor-0.3.0-cp39-cp39-macosx_10_9_x86_64.whl
- Upload date:
- Size: 684.4 kB
- Tags: CPython 3.9, macOS 10.9+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
418fb9e416ce0d6e9b5599abd361209cfa9a03529307a7952948f3adab9d996f
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| MD5 |
2cd53e56f394b41fa93ff23089c5ae93
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| BLAKE2b-256 |
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