Details
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Epic
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Status: In Progress
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Major
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Resolution: Unresolved
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None
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None
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None
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Deep Learning DML Library
Description
This issue tracks the creation of a layers-based deep learning library in pure DML.
The library contains layers with simple forward (function evaluation) and backward (gradient computation) functions for affine, convolution (start with 2D), max-pooling, non-linearities (relu, sigmoid, softmax, etc.), dropout, loss functions, other layers, optimizers, and gradient checks.
Examples: Please see example scripts and notebooks in the examples folder: https://github.com/apache/systemml/tree/master/scripts/nn/examples.
SystemML-NN: https://github.com/apache/systemml/tree/master/scripts/nn
- Layers:
- Core:
- Affine
- Batch Normalization 1D
- Batch Normalization 2D ("Spatial Batch Normalization")
- Convolution 2D ("Spatial Convolution")
- LSTM
- Max Pooling 2D ("Spatial Max Pooling")
- RNN
- Nonlinearities:
- ReLU
- Sigmoid
- Softmax
- Softmax 2D
- Tanh
- Loss:
- Cross-entropy loss
- Cross-entropy loss 2D
- L1 loss
- L2 loss
- Log ("Logistic") loss
- Regularization:
- Dropout
- L1 reg
- L2 reg
- Core:
- Optimizers:
- Adagrad
- Adam
- RMSprop
- SGD
- SGD w/ Momentum
- SGD w/ Nesterov Momentum
- Tests:
- Gradient Checks
- Unit Tests
Attachments
Issue Links
- is depended upon by
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SYSTEMDS-1185 SystemML Breast Cancer Project
- Resolved
- is part of
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SYSTEMDS-540 Deep Learning
- In Progress
- is related to
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SYSTEMDS-409 Extended update in-place support
- Open
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SYSTEMDS-669 Improve PyDML Language
- Closed
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SYSTEMDS-1566 Possible regression from 0.13 -> 0.14 for MNIST LeNet script
- Closed
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SYSTEMDS-1621 `max(0, X)` fails with type mismatch
- Closed
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SYSTEMDS-1686 Transpose Conv2d has incorrect filter shape and incorrect input size argument
- Closed
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SYSTEMDS-633 Improve Left-Indexing Performance with (Nested) Parfor Loops in UDFs
- Closed
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SYSTEMDS-845 Compare Performance of LeNet Scripts With & Without Using SystemML-NN
- Closed
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SYSTEMDS-1561 Improve constant folding during compilation
- Closed
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SYSTEMDS-1000 Allow users to pass non-1 bias filler in conv_builtin.dml
- Closed
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SYSTEMDS-1479 Make Caffe2DML feature-complete
- Open
- relates to
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SYSTEMDS-716 Consumability of SystemML for Deep Learning
- Open