tinytensor
tinytensor - A lightweight educational deep learning framework in Python and NumPy featuring a custom graph autograd engine, modular architecture, and built-in infrastructure (layers, loss functions, and optimizers).
파일 탐색기
- cuda_ops.cpython-310-x86_64-linux-gnu.so
- cuda_binding.o
- cuda_gpu.o
- pytinytensor-0.1.1-cp310-cp310-linux_x86_64.whl
- pytinytensor-0.1.1.tar.gz
- pytinytensor-0.1.2-cp313-cp313-linux_x86_64.whl
- pytinytensor-0.1.2.tar.gz
- pytinytensor-0.1.3-cp313-cp313-linux_x86_64.whl
- pytinytensor-0.1.3.tar.gz
- pytinytensor-0.1.4-cp313-cp313-linux_x86_64.whl
- pytinytensor-0.1.4.tar.gz
- pytinytensor-0.1.5-cp313-cp313-linux_x86_64.whl
- pytinytensor-0.1.5.tar.gz
- pytinytensor-0.1.6-cp313-cp313-linux_x86_64.whl
- pytinytensor-0.1.6.tar.gz
- pytinytensor-0.1.7-cp313-cp313-linux_x86_64.whl
- pytinytensor-0.1.7.tar.gz
- pytinytensor-0.2.0-cp313-cp313-linux_x86_64.whl
- pytinytensor-0.2.0.tar.gz
- pytinytensor-0.2.1-cp313-cp313-linux_x86_64.whl
- pytinytensor-0.2.1.tar.gz
- extra.css
- cuda.md
- data.md
- faq.md
- getting_started.md
- index.md
- model_saving.md
- models.md
- nn.md
- optim.md
- quantization.md
- requirements.txt
- tensor_and_autograd.md
- training.md
- utils.md
- t10k-images-idx3-ubyte.gz
- t10k-labels-idx1-ubyte.gz
- tinyshakespeare.txt
- train-images-idx3-ubyte.gz
- train-labels-idx1-ubyte.gz
- t10k-images-idx3-ubyte.gz
- t10k-labels-idx1-ubyte.gz
- train-images-idx3-ubyte.gz
- train-labels-idx1-ubyte.gz
- 01_linear_regression.py
- 02_mnist_mlp.py
- 03_synthetic_classification.py
- 04_spiral_classification.py
- all.py
- all_tests.py
- callbacks_example.py
- dataloader_check.py
- ensemble.tt
- ensemble_example.py
- ensemble_plot.png
- fast_cnn.py
- fit_example.py
- lenet_mnist.py
- profiling_example.py
- quant_example.py
- showcase_model.tt
- test_model.tt
- train_gpt.py
- vgg_augment.py
- test_autograd.py
- test_data.py
- test_losses.py
- test_nn.py
- test_optim.py
- test_tensor_math.py
- __init__.py
- cpu_numpy.py
- cuda_binding.cpp
- cuda_gpu.cu
- cuda_gpu.py
- cuda_ops.cpython-310-x86_64-linux-gnu.so
- cuda_binding.o
- cuda_gpu.o
- __init__.cpython-310.pyc
- __init__.cpython-313.pyc
- autograd.cpython-310.pyc
- autograd.cpython-313.pyc
- tensor.cpython-310.pyc
- tensor.cpython-313.pyc
- __init__.py
- autograd.py
- ops.py
- tensor.py
- __init__.cpython-313.pyc
- dataloader.cpython-313.pyc
- dataset.cpython-313.pyc
- __init__.py
- augment.py
- dataloader.py
- dataset.py
- pytinytensor-0.1.2-cp313-cp313-linux_x86_64.whl
- pytinytensor-0.1.2.tar.gz
- pytinytensor-0.1.3-cp313-cp313-linux_x86_64.whl
- pytinytensor-0.1.3.tar.gz
- pytinytensor-0.1.4-cp313-cp313-linux_x86_64.whl
- pytinytensor-0.1.4.tar.gz
- pytinytensor-0.1.5-cp313-cp313-linux_x86_64.whl
- pytinytensor-0.1.5.tar.gz
- pytinytensor-0.1.6-cp313-cp313-linux_x86_64.whl
- pytinytensor-0.1.6.tar.gz
- pytinytensor-0.1.7-cp313-cp313-linux_x86_64.whl
- pytinytensor-0.1.7.tar.gz
- pytinytensor-0.1.8-cp313-cp313-linux_x86_64.whl
- pytinytensor-0.1.8.tar.gz
- cuda.md
- data.md
- faq.md
- getting_started.md
- model_saving.md
- models.md
- nn.md
- optim.md
- quantization.md
- tensor_and_autograd.md
- training.md
- utils.md
- 01_linear_regression.py
- 02_mnist_mlp.py
- 03_synthetic_classification.py
- 04_spiral_classification.py
- all.py
- all_tests.py
- benchmark_vs_pytorch.py
- benchmark_vs_pytorch_gpu.py
- callbacks_example.py
- dataloader_check.py
- ensemble_example.py
- fast_cnn.py
- fit_example.py
- lenet_mnist.py
- profiling_example.py
- quant_example.py
- test_model.tt
- train_gpt.py
- vgg_augment.py
- __init__.py
- ensemble.py
- lenet.py
- resnet.py
- vgg.py
- __init__.cpython-313.pyc
- activations.cpython-313.pyc
- attention.cpython-313.pyc
- batchnorm.cpython-313.pyc
- conv.cpython-313.pyc
- dropout.cpython-313.pyc
- embedding.cpython-313.pyc
- flatten.cpython-313.pyc
- functional.cpython-313.pyc
- layernorm.cpython-313.pyc
- linear.cpython-313.pyc
- losses.cpython-313.pyc
- modules.cpython-313.pyc
- pooling.cpython-313.pyc
- rnn.cpython-313.pyc
- utils.cpython-313.pyc
- __init__.py
- activations.py
- attention.py
- batchnorm.py
- callbacks.py
- conv.py
- dropout.py
- embedding.py
- flatten.py
- functional.py
- history.py
- layernorm.py
- linear.py
- losses.py
- modules.py
- pooling.py
- residual.py
- rnn.py
- sequential.py
- utils.py
- __init__.cpython-313.pyc
- lr_scheduler.cpython-313.pyc
- optimizer.cpython-313.pyc
- __init__.py
- lr_scheduler.py
- optimizer.py
- test_autograd.py
- test_data.py
- test_losses.py
- test_nn.py
- test_optim.py
- test_tensor_math.py
- __init__.py
- cpu_numpy.py
- cuda_binding.cpp
- cuda_gpu.cu
- cuda_gpu.py
- __init__.py
- autograd.py
- ops.py
- tensor.py
- __init__.py
- augment.py
- dataloader.py
- dataset.py
- __init__.py
- ensemble.py
- lenet.py
- resnet.py
- vgg.py
- __init__.py
- activations.py
- attention.py
- batchnorm.py
- callbacks.py
- conv.py
- dropout.py
- embedding.py
- flatten.py
- functional.py
- history.py
- layernorm.py
- linear.py
- losses.py
- modules.py
- pooling.py
- residual.py
- rnn.py
- sequential.py
- utils.py
- __init__.py
- lr_scheduler.py
- optimizer.py
- __init__.py
- bar.py
- early_stopping.py
- profiling.py
- summary.py
- __init__.py
- config.py
- cuda_ops.cpython-310-x86_64-linux-gnu.so
- cuda_ops.cpython-313-x86_64-linux-gnu.so
- lib.rs
- Cargo.lock
- Cargo.toml
- pyproject.toml
- README.md
- test_correctness.py
- __init__.cpython-313.pyc
- bar.cpython-313.pyc
- early_stopping.cpython-313.pyc
- summary.cpython-313.pyc
- __init__.py
- bar.py
- early_stopping.py
- profiling.py
- summary.py
- __init__.py
- config.py
- cuda_ops.cpython-310-x86_64-linux-gnu.so
- cuda_ops.cpython-313-x86_64-linux-gnu.so
- LICENSE
- pyproject.toml
- README.md
- requirements.txt
- setup.py
- .gitignore
- LICENSE
- mkdocs.yml
- pyproject.toml
- README.md
- requirements.txt
- setup.py
- test_model.tt
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