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Merge branch 'multigpu_support' of https://github.com/kosinkadink/ComfyUI into multigpu_support

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This commit is contained in:
Jedrzej Kosinski
2025-01-20 04:34:39 -06:00
parent 328d4f16a9 bdbcb85b8d
commit ef137ac0b6
38 changed files with 49867 additions and 21187 deletions
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4
comfy/extra_samplers/uni_pc.py
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@@ -661,7 +661,7 @@ class UniPC:
if x_t is None:
if use_predictor:
pred_res = torch.einsum('k,bkchw->bchw', rhos_p, D1s)
pred_res = torch.tensordot(D1s, rhos_p, dims=([1], [0])) # torch.einsum('k,bkchw->bchw', rhos_p, D1s)
else:
pred_res = 0
x_t = x_t_ - expand_dims(alpha_t * B_h, dims) * pred_res
@@ -669,7 +669,7 @@ class UniPC:
if use_corrector:
model_t = self.model_fn(x_t, t)
if D1s is not None:
corr_res = torch.einsum('k,bkchw->bchw', rhos_c[:-1], D1s)
corr_res = torch.tensordot(D1s, rhos_c[:-1], dims=([1], [0])) # torch.einsum('k,bkchw->bchw', rhos_c[:-1], D1s)
else:
corr_res = 0
D1_t = (model_t - model_prev_0)

2
comfy/k_diffusion/sampling.py
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@@ -40,7 +40,7 @@ def get_sigmas_polyexponential(n, sigma_min, sigma_max, rho=1., device='cpu'):
def get_sigmas_vp(n, beta_d=19.9, beta_min=0.1, eps_s=1e-3, device='cpu'):
"""Constructs a continuous VP noise schedule."""
t = torch.linspace(1, eps_s, n, device=device)
sigmas = torch.sqrt(torch.exp(beta_d * t ** 2 / 2 + beta_min * t) - 1)
sigmas = torch.sqrt(torch.special.expm1(beta_d * t ** 2 / 2 + beta_min * t))
return append_zero(sigmas)

5
comfy/samplers.py
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@@ -12,7 +12,6 @@ import collections
from comfy import model_management
import math
import logging
import comfy.samplers
import comfy.sampler_helpers
import comfy.model_patcher
import comfy.patcher_extension
@@ -181,7 +180,7 @@ def finalize_default_conds(model: 'BaseModel', hooked_to_run: dict[comfy.hooks.H
cond = default_conds[i]
for x in cond:
# do get_area_and_mult to get all the expected values
p = comfy.samplers.get_area_and_mult(x, x_in, timestep)
p = get_area_and_mult(x, x_in, timestep)
if p is None:
continue
# replace p's mult with calculated mult
@@ -220,7 +219,7 @@ def _calc_cond_batch(model: 'BaseModel', conds: list[list[dict]], x_in: torch.Te
default_c.append(x)
has_default_conds = True
continue
p = comfy.samplers.get_area_and_mult(x, x_in, timestep)
p = get_area_and_mult(x, x_in, timestep)
if p is None:
continue
if p.hooks is not None:

3
comfy/utils.py
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@@ -43,7 +43,8 @@ if hasattr(torch.serialization, "add_safe_globals"): # TODO: this was added in
torch.serialization.add_safe_globals([ModelCheckpoint, scalar, dtype, Float64DType, encode])
ALWAYS_SAFE_LOAD = True
logging.info("Checkpoint files will always be loaded safely.")
else:
logging.info("Warning, you are using an old pytorch version and some ckpt/pt files might be loaded unsafely. Upgrading to 2.4 or above is recommended.")
def load_torch_file(ckpt, safe_load=False, device=None):
if device is None: