RNNTestCore
scalation.modeling.autograd.RNNTestCore
object RNNTestCore
The RNNTestCore object defines a suite of @main entrypoints that exercise the autograd system using recurrent neural network components. These tests verify:
- forward computation consistency for RNNCell and GRUCell
- correct propagation of hidden states through
RNNBase - correctness of gradient backpropagation through time
- multilayer RNN/GRU behavior and parameter interaction
- construction and export of autograd computation graphs for debugging All tests use synthetic inputs and manually assigned weights/biases to ensure deterministic behavior to validate against PyTorch, enabling reliable gradient-checking via finite differences using
GradCheck.gradCheck.
Attributes
- Note
-
This file focuses exclusively on core autograd correctness and does not contain any real-data forecasting experiments.
- Graph
-
- Supertypes
-
class Objecttrait Matchableclass Any
- Self type
-
RNNTestCore.type
Members list
In this article