COCONet中使用一个deep CNN来实现$p_{\theta}$,一个binary mask来表示$C$。音乐被表示为$x\in{0,1}^{I\times T\times P}$,I/T/P分别指声部数量、时长和音符数量,CNN的输入是masked music和mask的拼接。对于采样重建的算法,COCONet使用blocked-Gibbs sampling替代了orderless NADE的ancestral sampling orderle...
Therefore, I decided to build a scene graph benchmark on top of the well-known maskrcnn-benchmark project and define relationship prediction as an additional roi_head. By the way, thanks to their elegant framework, this codebase is much more novice-friendly and easier to read/modify for ...
Figure1maps the evolution of silicon photonics1,2. Silicon-based photonic integrated circuits (PICs) were introduced in 19853and low-loss waveguides in a thick silicon on insulator (SOI) process demonstrated in 1991–924,5. Various optical devices were next demonstrated6, and soon, silicon photoni...
The well-known cut-back method was used to measure the propagation loss of every waveguide using a 29 cm long glass plate cut to a 12 cm long piece. The overall lowest loss type I waveguide (∼0.1 dB/cm at 1550 nm) was achieved using the DB technique with the following p...
Fix functional.grid_sample() loss of precision for torch.float16 inputs (#90427) Fix functional.interpolate() bicubic interpolation to properly preserve memory format (#90470) torch.func Fix cross to match unbatched behavior (#86926) Properly error on complex inputs or outputs in jacrev, jac...
For each generated image, we mask it by the token maps of each object and attach the masked output to a black background. Then, we compute the CLIP score using the region-specific prompt. For ex- ample, for the prompt "a lighthouse (Cyberpunk) among the turbulent waves (Ukiyo-...
We build this on the face image data of CelebAMask-HQ [24], which contains high-resolution facial images with semantic masks of facial attributes. For simplicity, we currently focus on front faces, without decorative accessories (e.g., glasses, face masks). To extract sparse lines from real...
format: str, eval_steps: int, raw_text_file: str, overlap_len: int, newline_favor_len: int, higher_rank_limit: bool, warmup_steps: int, optimizer: str, hard_cut_string: str, train_only_after: str, stop_at_loss: float, add_eos_token: bool, min_chars: int, report...
1. 可以通过chain rule提供exact的data likelihood[Math Processing Error]p(x)=∏i=1n2p(xi|x1,.....
gr.Markdown("[Tutorial](https://github.com/oobabooga/text-generation-webui/blob/main/docs/Training-LoRAs.md)") gr.Markdown("[Tutorial](https://github.com/oobabooga/text-generation-webui/wiki/05-%E2%80%90-Training-Tab)") with gr.Row(): copy_from = gr.Dropdown(label='Copy paramete...