Update readme

README.md

@@ -292,15 +292,19 @@ The polynomial last layer is the same as that used in the convolution.
 |9 | 0.990 | 0.989
 |10| 0.990 | 0.990
 
-## MNIST Block 3D polynomial
+## MNIST Block 3D polynomial / block piecewise polynomial
 Basics implemented, needs to be made more efficient and model needs to change a bit. Currently uses a single NxNxN polynomial
 with 3 inputs (grayscale color, x, y) and 10 outputs to solve mnist. Not performant, but will work on it.
 ```
 python3 examples/block_mnist.py accelerator='cuda' batch_size=64 optimizer.lr=1e-3
 ```
 and
 ```
-python examples/block_mnist.py optimizer=lion optimizer.lr=1e-3 batch_size=16 max_epochs=100 n=28
+python examples/block_mnist.py optimizer=lion optimizer.lr=1e-3 batch_size=16 max_epochs=100 n=28 layer_type=polynomial_3d
+```
+and then for block piecewise polynomial
+```
+python examples/block_mnist.py optimizer=lion optimizer.lr=1e-3 batch_size=16 max_epochs=100 n=3 segments=10 layer_type=continuous_nd
 ```
 ## CIFAR100 (convolutional)