Buckets:
| from unittest.mock import MagicMock | |
| import torch | |
| from comfy.cli_args import args as cli_args | |
| if not torch.cuda.is_available(): | |
| cli_args.cpu = True | |
| import comfy.nested_tensor # noqa: E402 | |
| import nodes # noqa: E402 | |
| def test_vae_decode_tiled_unwraps_nested_tensor(): | |
| video = torch.zeros(1, 4, 2, 8, 8) | |
| audio = torch.zeros(1, 2, 2, 40) | |
| samples = {"samples": comfy.nested_tensor.NestedTensor((video, audio))} | |
| vae = MagicMock() | |
| vae.temporal_compression_decode.return_value = None | |
| vae.spacial_compression_decode.return_value = 8 | |
| vae.decode_tiled.return_value = torch.zeros(1, 3, 2, 8, 8) | |
| nodes.VAEDecodeTiled().decode(vae, samples, tile_size=512) | |
| decoded_arg = vae.decode_tiled.call_args[0][0] | |
| assert decoded_arg is video | |
Xet Storage Details
- Size:
- 770 Bytes
- Xet hash:
- c3d2c247063d446ecf9f38505c9f797f5c6826d867951e47299ca0fcd7c03765
·
Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.