e3nn-jax importe3nn_jaxase3nn# Create a random array made of a scalar (0e) and a vector (1o)array=e3nn.normal("0e + 1o",jax.random.PRNGKey(0))print(array)# 1x0e+1x1o [ 1.8160863 -0.75488514 0.33988908 -0.53483534]# Compute the normsnorms=e3nn.norm(array)print(norms)# 1x0...
This PR fixes the import for e3nn-jax FunctionalFullyConnectedTensorProduct mentioned in issue #268. fix e3nn import f067273 View details ekindogus merged commit daa128e into jax-md:main Jun 30, 2023 0 of 3 checks passed abhijeetgangan deleted the e3nn_fix branch June 30, 2023 16:43...
output+=jax.numpy.linalg.norm(jax.nn.relu(contain),ord=np.inf)### unsure if l inf norm or any norm is the correct approach Expand DownExpand Up@@ -743,8 +743,8 @@ def gen_starsets_post_sim(old_star: StarSet, sim: Callable, T: float = 7, ts: fl ...
- e3nn ``` @misc{e3nn_paper, doi = {10.48550/ARXIV.2207.09453}, url = {https://arxiv.org/abs/2207.09453}, author = {Geiger, Mario and Smidt, Tess}, keywords = {Machine Learning (cs.LG), Artificial Intelligence (cs.AI), Neural and Evolutionary Computing (cs.NE), FOS: Computer ...
import e3nn_jax as e3nn # Create a random array made of a scalar (0e) and a vector (1o) array = e3nn.normal("0e + 1o", jax.random.PRNGKey(0)) print(array) # 1x0e+1x1o [ 1.8160863 -0.75488514 0.33988908 -0.53483534] # Compute the norms norms = e3nn.norm(array) print(no...