Comments (2)
grad_helper doesn't panic, but this may not be what you want.
Getting 0 is impossible currently.
from rust-autograd.
Fixed in the master head
from rust-autograd.
Related Issues (20)
- segfault when calling grad() in a loop HOT 19
- access_elem failed HOT 1
- Unexpected gradient shape HOT 3
- Not differentiable with the given tensors error when trying to train multi-input neural network HOT 1
- "ndarray" and "autograd::ndarray" HOT 2
- Support for lgamma function HOT 22
- Gradient error for tensor of different dimensions HOT 7
- Alternatives for `tf.where()` HOT 12
- Bug for `g.argmax` HOT 1
- Index out of bound in DivOp when dividing 2 scalars HOT 2
- Documentation about GradientContext::set_input_grads is misleading HOT 1
- Use of 'extern crate' in examples HOT 1
- Dead PDF link in source HOT 1
- dropout with train=false produces error HOT 1
- Wrong docstrings
- softmax_cross_entropy outputs shape [-1], when it should output shape [-1, 1]. HOT 1
- Newbie-friendly documentation would be a huge benefit HOT 3
- Upgrade to ndarray 0.15 HOT 2
- "unreachable code" panic on certain uses of `grad_with_default`
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from rust-autograd.