Quiet non-actionable startup warnings & status in progress bar

modules/modelSampler/AnimaSampler.py

@@ -12,13 +12,13 @@
 from modules.util.enum.ModelType import ModelType
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
+from modules.util.tqdm_util import tqdm
 
 import torch
 
 from diffusers import VaeImageProcessor
 
 import numpy as np
-from tqdm import tqdm
 
 
 @factory.register(BaseModelSampler, ModelType.ANIMA)

modules/modelSampler/ChromaSampler.py

@@ -12,11 +12,10 @@
 from modules.util.enum.ModelType import ModelType
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
+from modules.util.tqdm_util import tqdm
 
 import torch
 
-from tqdm import tqdm
-
 
 @factory.register(BaseModelSampler, ModelType.CHROMA_1)
 class ChromaSampler(BaseModelSampler):

modules/modelSampler/ErnieSampler.py

@@ -11,12 +11,12 @@
 from modules.util.enum.ModelType import ModelType
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
+from modules.util.tqdm_util import tqdm
 
 import torch
 
 import numpy as np
 from PIL import Image as PILImage
-from tqdm import tqdm
 
 
 @factory.register(BaseModelSampler, ModelType.ERNIE)

modules/modelSampler/Flux2Sampler.py

@@ -12,13 +12,13 @@
 from modules.util.enum.ModelType import ModelType
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
+from modules.util.tqdm_util import tqdm
 
 import torch
 
 from diffusers.pipelines.flux2.pipeline_flux2 import compute_empirical_mu
 
 import numpy as np
-from tqdm import tqdm
 
 
 @factory.register(BaseModelSampler, ModelType.FLUX_2)

modules/modelSampler/FluxSampler.py

@@ -14,13 +14,12 @@
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
 from modules.util.image_util import load_image
+from modules.util.tqdm_util import tqdm
 
 import torch
 from torch import nn
 from torchvision.transforms import transforms
 
-from tqdm import tqdm
-
 
 @factory.register(BaseModelSampler, ModelType.FLUX_DEV_1)
 @factory.register(BaseModelSampler, ModelType.FLUX_FILL_DEV_1)

modules/modelSampler/HiDreamSampler.py

@@ -12,11 +12,10 @@
 from modules.util.enum.ModelType import ModelType
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
+from modules.util.tqdm_util import tqdm
 
 import torch
 
-from tqdm import tqdm
-
 
 @factory.register(BaseModelSampler, ModelType.HI_DREAM_FULL)
 class HiDreamSampler(BaseModelSampler):

modules/modelSampler/HunyuanVideoSampler.py

@@ -12,11 +12,11 @@
 from modules.util.enum.ModelType import ModelType
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
+from modules.util.tqdm_util import tqdm
 
 import torch
 
 from PIL import Image
-from tqdm import tqdm
 
 
 @factory.register(BaseModelSampler, ModelType.HUNYUAN_VIDEO)

modules/modelSampler/IdeogramSampler.py

@@ -11,14 +11,14 @@
 from modules.util.enum.ModelType import ModelType
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
+from modules.util.tqdm_util import tqdm
 
 import torch
 
 from diffusers.pipelines.ideogram4.pipeline_ideogram4 import _logit_normal_sigmas, _resolution_aware_mu
 
 import numpy as np
 from PIL import Image as PILImage
-from tqdm import tqdm
 
 
 @factory.register(BaseModelSampler, ModelType.IDEOGRAM_4)

modules/modelSampler/Krea2Sampler.py

@@ -13,13 +13,12 @@
 from modules.util.enum.ModelType import ModelType
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
+from modules.util.tqdm_util import tqdm
 
 import torch
 
 from diffusers import Krea2Pipeline
 
-from tqdm import tqdm
-
 
 @factory.register(BaseModelSampler, ModelType.KREA_2)
 class Krea2Sampler(BaseModelSampler):

modules/modelSampler/PixArtAlphaSampler.py

@@ -11,11 +11,10 @@
 from modules.util.enum.ModelType import ModelType
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
+from modules.util.tqdm_util import tqdm
 
 import torch
 
-from tqdm import tqdm
-
 
 @factory.register(BaseModelSampler, ModelType.PIXART_ALPHA)
 @factory.register(BaseModelSampler, ModelType.PIXART_SIGMA)

modules/modelSampler/QwenSampler.py

@@ -13,11 +13,10 @@
 from modules.util.enum.ModelType import ModelType
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
+from modules.util.tqdm_util import tqdm
 
 import torch
 
-from tqdm import tqdm
-
 
 @factory.register(BaseModelSampler, ModelType.QWEN)
 class QwenSampler(BaseModelSampler):

modules/modelSampler/SanaSampler.py

@@ -12,11 +12,10 @@
 from modules.util.enum.ModelType import ModelType
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
+from modules.util.tqdm_util import tqdm
 
 import torch
 
-from tqdm import tqdm
-
 
 @factory.register(BaseModelSampler, ModelType.SANA)
 class SanaSampler(BaseModelSampler):

modules/modelSampler/StableDiffusion3Sampler.py

@@ -12,11 +12,10 @@
 from modules.util.enum.ModelType import ModelType
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
+from modules.util.tqdm_util import tqdm
 
 import torch
 
-from tqdm import tqdm
-
 
 @factory.register(BaseModelSampler, ModelType.STABLE_DIFFUSION_3)
 @factory.register(BaseModelSampler, ModelType.STABLE_DIFFUSION_35)

modules/modelSampler/StableDiffusionSampler.py

@@ -12,13 +12,12 @@
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
 from modules.util.image_util import load_image
+from modules.util.tqdm_util import tqdm
 
 import torch
 from torch import nn
 from torchvision.transforms import transforms
 
-from tqdm import tqdm
-
 
 @factory.register(BaseModelSampler, ModelType.STABLE_DIFFUSION_15)
 @factory.register(BaseModelSampler, ModelType.STABLE_DIFFUSION_15_INPAINTING)

modules/modelSampler/StableDiffusionXLSampler.py

@@ -12,13 +12,12 @@
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
 from modules.util.image_util import load_image
+from modules.util.tqdm_util import tqdm
 
 import torch
 from torch import nn
 from torchvision.transforms import transforms
 
-from tqdm import tqdm
-
 
 @factory.register(BaseModelSampler, ModelType.STABLE_DIFFUSION_XL_10_BASE)
 @factory.register(BaseModelSampler, ModelType.STABLE_DIFFUSION_XL_10_BASE_INPAINTING)

modules/modelSampler/WuerstchenSampler.py

@@ -11,11 +11,11 @@
 from modules.util.enum.ModelType import ModelType
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
+from modules.util.tqdm_util import tqdm
 
 import torch
 
 from PIL import Image
-from tqdm import tqdm
 
 
 @factory.register(BaseModelSampler, ModelType.WUERSTCHEN_2)

modules/modelSampler/ZImageSampler.py

@@ -12,11 +12,10 @@
 from modules.util.enum.ModelType import ModelType
 from modules.util.enum.NoiseScheduler import NoiseScheduler
 from modules.util.enum.VideoFormat import VideoFormat
+from modules.util.tqdm_util import tqdm
 
 import torch
 
-from tqdm import tqdm
-
 
 @factory.register(BaseModelSampler, ModelType.Z_IMAGE)
 class ZImageSampler(BaseModelSampler):

modules/module/BaseImageCaptionModel.py

@@ -6,9 +6,9 @@
 
 from modules.util import path_util
 from modules.util.image_util import load_image
+from modules.util.tqdm_util import tqdm
 
 from PIL import Image
-from tqdm import tqdm
 
 
 class CaptionSample:

modules/module/BaseImageMaskModel.py

@@ -5,13 +5,13 @@
 
 from modules.util import path_util
 from modules.util.image_util import load_image
+from modules.util.tqdm_util import tqdm
 
 import torch
 from torch import Tensor
 from torchvision.transforms import transforms
 
 from PIL import Image
-from tqdm import tqdm
 
 
 class MaskSample:

modules/module/GenerateLossesModel.py

@@ -8,12 +8,11 @@
 from modules.util import create
 from modules.util.config.TrainConfig import QuantizationConfig, TrainConfig
 from modules.util.torch_util import torch_gc
+from modules.util.tqdm_util import tqdm
 from modules.util.TrainProgress import TrainProgress
 
 import torch
 
-from tqdm import tqdm
-
 
 class GenerateLossesModel:
     """Based on train args, writes a JSON instead of a model with filenames mapped to losses,

modules/trainer/BaseTrainer.py

@@ -97,7 +97,11 @@ def _start_tensorboard(self):
         if self.config.tensorboard_expose:
             tensorboard_args.append("--bind_all")
 
-        self.tensorboard_subprocess = subprocess.Popen(tensorboard_args)
+        # discard the child's banner and notices; the UI already shows the tensorboard URL.
+        # Popen still raises if the executable is missing.
+        self.tensorboard_subprocess = subprocess.Popen(
+            tensorboard_args, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL,
+        )
 
     def _stop_tensorboard(self):
         self.tensorboard_subprocess.kill()

modules/trainer/GenericTrainer.py

@@ -32,6 +32,7 @@
 from modules.util.profiling_util import PeakMemoryRecorder, TorchMemoryRecorder, TorchProfiler
 from modules.util.time_util import get_string_timestamp
 from modules.util.torch_util import torch_gc
+from modules.util.tqdm_util import tqdm
 from modules.util.TrainProgress import TrainProgress
 
 import torch
@@ -41,8 +42,6 @@
 from torch.utils.tensorboard import SummaryWriter
 from torchvision.transforms.functional import pil_to_tensor
 
-from tqdm import tqdm
-
 # OT_DEBUG_PROFILES=1 dumps a CUDA memory snapshot for the first two steps, where the allocator is still
 # growing, and a profiler trace at steps 10 and 40, past compilation and warmup.
 _DEBUG_PROFILES = os.environ.get("OT_DEBUG_PROFILES") == "1"

modules/ui/TrainUIController.py

@@ -108,8 +108,11 @@ def _start_always_on_tensorboard(self):
         if self.train_config.tensorboard_expose:
             tensorboard_args.append("--bind_all")
 
+        # discard the child's banner and notices; the UI already shows the tensorboard URL.
         try:
-            self.always_on_tensorboard_subprocess = subprocess.Popen(tensorboard_args)
+            self.always_on_tensorboard_subprocess = subprocess.Popen(
+                tensorboard_args, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL,
+            )
         except Exception:
             self.always_on_tensorboard_subprocess = None
 

modules/util/compile_util.py

@@ -1,9 +1,10 @@
+from modules.util.tqdm_util import tqdm
+
 import torch
 import torch._dynamo.callback
 import torch.utils._sympy.functions
 
 from sympy import S
-from tqdm import tqdm
 
 
 #code from https://github.com/pytorch/pytorch/blob/ed82d5fcfd80110565f69130f286c7bfec6db2dc/torch/utils/_sympy/functions.py#L481
@@ -95,7 +96,7 @@ def init_compile():
 def _on_compile_start(args: "torch._dynamo.callback.CallbackArgs") -> None:
     frame_id, _, frame_compile_id = args.compile_id.partition("/")
     direction = "backward" if args.callback_trigger == torch._dynamo.callback.CallbackTrigger.LAZY_BACKWARD else "forward"
-    tqdm.write(f"[torch.compile] compiling kernel {frame_id} {direction} (variant #{frame_compile_id or 0})...")
+    tqdm.show_status(f"compiling kernel {frame_id} {direction} (variant #{frame_compile_id or 0})...")
 
 
 torch._dynamo.callback.on_compile_start(_on_compile_start)

modules/util/multi_gpu_util.py

@@ -3,11 +3,10 @@
 from modules.util.bf16_stochastic_rounding import copy_stochastic_
 from modules.util.commands.TrainCommands import TrainCommands
 from modules.util.enum.GradientReducePrecision import GradientReducePrecision
+from modules.util.tqdm_util import tqdm
 
 import torch
 
-from tqdm import tqdm
-
 
 def is_enabled() -> bool:
     return torch.distributed.is_available() and torch.distributed.is_initialized()

modules/util/quantization_util.py

@@ -9,14 +9,14 @@
 from modules.util.config.TrainConfig import QuantizationConfig, TrainConfig
 from modules.util.enum.DataType import DataType
 from modules.util.ModuleFilter import ModuleFilter
+from modules.util.tqdm_util import tqdm
 
 import torch
 from torch import Tensor, nn
 
 from diffusers.quantizers.gguf.utils import GGUFLinear, dequantize_gguf_tensor
 
 import accelerate
-from tqdm import tqdm
 
 try:
     from modules.module.quantized.LinearNf4 import LinearNf4