Spaces:
Runtime error
Runtime error
File size: 1,951 Bytes
7ccc423 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 |
# TODO: Adapted from cli
from typing import Callable, List, Optional
import numpy as np
def ordered_halving(val):
bin_str = f"{val:064b}"
bin_flip = bin_str[::-1]
as_int = int(bin_flip, 2)
return as_int / (1 << 64)
def uniform(
step: int = ...,
num_steps: Optional[int] = None,
num_frames: int = ...,
context_size: Optional[int] = None,
context_stride: int = 3,
context_overlap: int = 4,
closed_loop: bool = True,
):
if num_frames <= context_size:
yield list(range(num_frames))
return
context_stride = min(
context_stride, int(np.ceil(np.log2(num_frames / context_size))) + 1
)
for context_step in 1 << np.arange(context_stride):
pad = int(round(num_frames * ordered_halving(step)))
for j in range(
int(ordered_halving(step) * context_step) + pad,
num_frames + pad + (0 if closed_loop else -context_overlap),
(context_size * context_step - context_overlap),
):
yield [
e % num_frames
for e in range(j, j + context_size * context_step, context_step)
]
def get_context_scheduler(name: str) -> Callable:
if name == "uniform":
return uniform
else:
raise ValueError(f"Unknown context_overlap policy {name}")
def get_total_steps(
scheduler,
timesteps: List[int],
num_steps: Optional[int] = None,
num_frames: int = ...,
context_size: Optional[int] = None,
context_stride: int = 3,
context_overlap: int = 4,
closed_loop: bool = True,
):
return sum(
len(
list(
scheduler(
i,
num_steps,
num_frames,
context_size,
context_stride,
context_overlap,
)
)
)
for i in range(len(timesteps))
)
|