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print debug messages to stderr instead of stdout

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This commit is contained in:
vytskalt
2026-01-09 20:05:52 +02:00
parent 6ecc00a5d3
commit f2e203d5e2
2 changed files with 14 additions and 12 deletions
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13
src/voxcpm/core.py
View File

@ -1,4 +1,5 @@
import os
import sys
import re
import tempfile
import numpy as np
@ -30,7 +31,7 @@ class VoxCPM:
lora_weights_path: Path to pre-trained LoRA weights (.pth file or directory
containing lora_weights.ckpt). If provided, LoRA weights will be loaded.
"""
print(f"voxcpm_model_path: {voxcpm_model_path}, zipenhancer_model_path: {zipenhancer_model_path}, enable_denoiser: {enable_denoiser}")
print(f"voxcpm_model_path: {voxcpm_model_path}, zipenhancer_model_path: {zipenhancer_model_path}, enable_denoiser: {enable_denoiser}", file=sys.stderr)
# If lora_weights_path is provided but no lora_config, create a default one
if lora_weights_path is not None and lora_config is None:
@ -39,15 +40,15 @@ class VoxCPM:
enable_dit=True,
enable_proj=False,
)
print(f"Auto-created default LoRAConfig for loading weights from: {lora_weights_path}")
print(f"Auto-created default LoRAConfig for loading weights from: {lora_weights_path}", file=sys.stderr)
self.tts_model = VoxCPMModel.from_local(voxcpm_model_path, optimize=optimize, lora_config=lora_config)
# Load LoRA weights if path is provided
if lora_weights_path is not None:
print(f"Loading LoRA weights from: {lora_weights_path}")
print(f"Loading LoRA weights from: {lora_weights_path}", file=sys.stderr)
loaded_keys, skipped_keys = self.tts_model.load_lora_weights(lora_weights_path)
print(f"Loaded {len(loaded_keys)} LoRA parameters, skipped {len(skipped_keys)}")
print(f"Loaded {len(loaded_keys)} LoRA parameters, skipped {len(skipped_keys)}", file=sys.stderr)
self.text_normalizer = None
if enable_denoiser and zipenhancer_model_path is not None:
@ -56,7 +57,7 @@ class VoxCPM:
else:
self.denoiser = None
if optimize:
print("Warm up VoxCPMModel...")
print("Warm up VoxCPMModel...", file=sys.stderr)
self.tts_model.generate(
target_text="Hello, this is the first test sentence.",
max_len=10,
@ -278,4 +279,4 @@ class VoxCPM:
@property
def lora_enabled(self) -> bool:
"""Check if LoRA is currently configured."""
return self.tts_model.lora_config is not None
return self.tts_model.lora_config is not None

13
src/voxcpm/model/voxcpm.py
View File

@ -19,6 +19,7 @@ limitations under the License.
"""
import os
import sys
from typing import Tuple, Union, Generator, List, Optional
import torch
@ -120,7 +121,7 @@ class VoxCPMModel(nn.Module):
self.device = "mps"
else:
self.device = "cpu"
print(f"Running on device: {self.device}, dtype: {self.config.dtype}")
print(f"Running on device: {self.device}, dtype: {self.config.dtype}", file=sys.stderr)
# Text-Semantic LM
self.base_lm = MiniCPMModel(config.lm_config)
@ -228,7 +229,7 @@ class VoxCPMModel(nn.Module):
self.feat_encoder = torch.compile(self.feat_encoder, mode="reduce-overhead", fullgraph=True)
self.feat_decoder.estimator = torch.compile(self.feat_decoder.estimator, mode="reduce-overhead", fullgraph=True)
except Exception as e:
print(f"Warning: torch.compile disabled - {e}")
print(f"Warning: torch.compile disabled - {e}", file=sys.stderr)
return self
def forward(
@ -459,7 +460,7 @@ class VoxCPMModel(nn.Module):
latent_pred, pred_audio_feat = next(inference_result)
if retry_badcase:
if pred_audio_feat.shape[0] >= target_text_length * retry_badcase_ratio_threshold:
print(f" Badcase detected, audio_text_ratio={pred_audio_feat.shape[0] / target_text_length}, retrying...")
print(f" Badcase detected, audio_text_ratio={pred_audio_feat.shape[0] / target_text_length}, retrying...", file=sys.stderr)
retry_badcase_times += 1
continue
else:
@ -683,7 +684,7 @@ class VoxCPMModel(nn.Module):
latent_pred, pred_audio_feat = next(inference_result)
if retry_badcase:
if pred_audio_feat.shape[0] >= target_text_length * retry_badcase_ratio_threshold:
print(f" Badcase detected, audio_text_ratio={pred_audio_feat.shape[0] / target_text_length}, retrying...")
print(f" Badcase detected, audio_text_ratio={pred_audio_feat.shape[0] / target_text_length}, retrying...", file=sys.stderr)
retry_badcase_times += 1
continue
else:
@ -868,10 +869,10 @@ class VoxCPMModel(nn.Module):
pytorch_model_path = os.path.join(path, "pytorch_model.bin")
if os.path.exists(safetensors_path) and SAFETENSORS_AVAILABLE:
print(f"Loading model from safetensors: {safetensors_path}")
print(f"Loading model from safetensors: {safetensors_path}", file=sys.stderr)
model_state_dict = load_file(safetensors_path)
elif os.path.exists(pytorch_model_path):
print(f"Loading model from pytorch_model.bin: {pytorch_model_path}")
print(f"Loading model from pytorch_model.bin: {pytorch_model_path}", file=sys.stderr)
checkpoint = torch.load(
pytorch_model_path,
map_location="cpu",