Add GRUCell support

AndroidDL v1.1.0

🚀 New Features

• Added GRUCell for recurrent neural network architectures.
• Supports configurable input size and hidden size.
• Supports optional biases, enabled by default.
• Implements update, reset, and candidate hidden-state gates.
• Integrates with AndroidDL's existing Module, Linear, and autograd system.

🧪 Testing

• Verified forward-pass output shapes and finite values.
• Verified gradients across all GRU parameter groups.
• Tested numerical gradients using finite differences.
• Trained on a small sequence-to-target task and observed a significant reduction in loss.

Example

import { GRUCell } from "androiddl";

const gru = new GRUCell(3, 4);

const nextHidden = gru.call(input, hidden);

input has shape [batchSize, inputSize], and hidden has shape [batchSize, hiddenSize].

Notes

This release introduces a GRU building block for sequence models and reinforcement-learning experiments.