Open SokolyMoravia opened 7 months ago
Are you using the latest version of UVR? This model is only compatible with the latest version.
Yes, I'm using the latest version of UVR. It still occurs.
Nevermind, the error no longer appears and I can use the models once again. After I uninstalled it and then reinstalled it again.
This happens every time I choose the UVR-BVE-4B_SN-44100-1 model to extract lead vocals from the background vocals. Every time I do it, this message keeps popping up before it even starts to process. I also copied the full text and attached a screenshot of the error to makes things clearer.
**Last Error Received:
Process: VR Architecture
If this error persists, please contact the developers with the error details.
Raw Error Details:
RuntimeError: "Error(s) in loading state_dict for CascadedNet: size mismatch for stg1_low_band_net.0.lstm_dec2.lstm.weight_ih_l0: copying a param with shape torch.Size([256, 168]) from checkpoint, the shape in current model is torch.Size([256, 320]). size mismatch for stg1_low_band_net.0.lstm_dec2.lstm.weight_ih_l0_reverse: copying a param with shape torch.Size([256, 168]) from checkpoint, the shape in current model is torch.Size([256, 320]). size mismatch for stg1_low_band_net.0.lstm_dec2.dense.0.weight: copying a param with shape torch.Size([168, 128]) from checkpoint, the shape in current model is torch.Size([320, 128]). size mismatch for stg1_low_band_net.0.lstm_dec2.dense.0.bias: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg1_low_band_net.0.lstm_dec2.dense.1.weight: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg1_low_band_net.0.lstm_dec2.dense.1.bias: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg1_low_band_net.0.lstm_dec2.dense.1.running_mean: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg1_low_band_net.0.lstm_dec2.dense.1.running_var: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg1_high_band_net.lstm_dec2.lstm.weight_ih_l0: copying a param with shape torch.Size([128, 168]) from checkpoint, the shape in current model is torch.Size([128, 320]). size mismatch for stg1_high_band_net.lstm_dec2.lstm.weight_ih_l0_reverse: copying a param with shape torch.Size([128, 168]) from checkpoint, the shape in current model is torch.Size([128, 320]). size mismatch for stg1_high_band_net.lstm_dec2.dense.0.weight: copying a param with shape torch.Size([168, 64]) from checkpoint, the shape in current model is torch.Size([320, 64]). size mismatch for stg1_high_band_net.lstm_dec2.dense.0.bias: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg1_high_band_net.lstm_dec2.dense.1.weight: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg1_high_band_net.lstm_dec2.dense.1.bias: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg1_high_band_net.lstm_dec2.dense.1.running_mean: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg1_high_band_net.lstm_dec2.dense.1.running_var: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg2_low_band_net.0.lstm_dec2.lstm.weight_ih_l0: copying a param with shape torch.Size([256, 168]) from checkpoint, the shape in current model is torch.Size([256, 320]). size mismatch for stg2_low_band_net.0.lstm_dec2.lstm.weight_ih_l0_reverse: copying a param with shape torch.Size([256, 168]) from checkpoint, the shape in current model is torch.Size([256, 320]). size mismatch for stg2_low_band_net.0.lstm_dec2.dense.0.weight: copying a param with shape torch.Size([168, 128]) from checkpoint, the shape in current model is torch.Size([320, 128]). size mismatch for stg2_low_band_net.0.lstm_dec2.dense.0.bias: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg2_low_band_net.0.lstm_dec2.dense.1.weight: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg2_low_band_net.0.lstm_dec2.dense.1.bias: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg2_low_band_net.0.lstm_dec2.dense.1.running_mean: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg2_low_band_net.0.lstm_dec2.dense.1.running_var: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg2_high_band_net.lstm_dec2.lstm.weight_ih_l0: copying a param with shape torch.Size([128, 168]) from checkpoint, the shape in current model is torch.Size([128, 320]). size mismatch for stg2_high_band_net.lstm_dec2.lstm.weight_ih_l0_reverse: copying a param with shape torch.Size([128, 168]) from checkpoint, the shape in current model is torch.Size([128, 320]). size mismatch for stg2_high_band_net.lstm_dec2.dense.0.weight: copying a param with shape torch.Size([168, 64]) from checkpoint, the shape in current model is torch.Size([320, 64]). size mismatch for stg2_high_band_net.lstm_dec2.dense.0.bias: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg2_high_band_net.lstm_dec2.dense.1.weight: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg2_high_band_net.lstm_dec2.dense.1.bias: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg2_high_band_net.lstm_dec2.dense.1.running_mean: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg2_high_band_net.lstm_dec2.dense.1.running_var: copying a param with shape torch.Size([168]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for stg3_full_band_net.lstm_dec2.lstm.weight_ih_l0: copying a param with shape torch.Size([256, 336]) from checkpoint, the shape in current model is torch.Size([256, 640]). size mismatch for stg3_full_band_net.lstm_dec2.lstm.weight_ih_l0_reverse: copying a param with shape torch.Size([256, 336]) from checkpoint, the shape in current model is torch.Size([256, 640]). size mismatch for stg3_full_band_net.lstm_dec2.dense.0.weight: copying a param with shape torch.Size([336, 128]) from checkpoint, the shape in current model is torch.Size([640, 128]). size mismatch for stg3_full_band_net.lstm_dec2.dense.0.bias: copying a param with shape torch.Size([336]) from checkpoint, the shape in current model is torch.Size([640]). size mismatch for stg3_full_band_net.lstm_dec2.dense.1.weight: copying a param with shape torch.Size([336]) from checkpoint, the shape in current model is torch.Size([640]). size mismatch for stg3_full_band_net.lstm_dec2.dense.1.bias: copying a param with shape torch.Size([336]) from checkpoint, the shape in current model is torch.Size([640]). size mismatch for stg3_full_band_net.lstm_dec2.dense.1.running_mean: copying a param with shape torch.Size([336]) from checkpoint, the shape in current model is torch.Size([640]). size mismatch for stg3_full_band_net.lstm_dec2.dense.1.running_var: copying a param with shape torch.Size([336]) from checkpoint, the shape in current model is torch.Size([640])." Traceback Error: " File "UVR.py", line 4716, in process_start File "separate.py", line 667, in seperate File "torch\nn\modules\module.py", line 1671, in load_state_dict "
Error Time Stamp [2024-02-17 01:29:21]
Full Application Settings:
vr_model: UVR-BVE-4B_SN-44100-1 aggression_setting: 10 window_size: 320 batch_size: Default crop_size: 256 is_tta: False is_output_image: False is_post_process: False is_high_end_process: False post_process_threshold: 0.2 vr_voc_inst_secondary_model: No Model Selected vr_other_secondary_model: No Model Selected vr_bass_secondary_model: No Model Selected vr_drums_secondary_model: No Model Selected vr_is_secondary_model_activate: False vr_voc_inst_secondary_model_scale: 0.9 vr_other_secondary_model_scale: 0.7 vr_bass_secondary_model_scale: 0.5 vr_drums_secondary_model_scale: 0.5 demucs_model: Choose Model segment: Default overlap: 0.25 shifts: 2 chunks_demucs: Auto margin_demucs: 44100 is_chunk_demucs: False is_chunk_mdxnet: False is_primary_stem_only_Demucs: False is_secondary_stem_only_Demucs: False is_split_mode: True is_demucs_combine_stems: True demucs_voc_inst_secondary_model: No Model Selected demucs_other_secondary_model: No Model Selected demucs_bass_secondary_model: No Model Selected demucs_drums_secondary_model: No Model Selected demucs_is_secondary_model_activate: False demucs_voc_inst_secondary_model_scale: 0.9 demucs_other_secondary_model_scale: 0.7 demucs_bass_secondary_model_scale: 0.5 demucs_drums_secondary_model_scale: 0.5 demucs_pre_proc_model: No Model Selected is_demucs_pre_proc_model_activate: False is_demucs_pre_proc_model_inst_mix: False mdx_net_model: Choose Model chunks: Auto margin: 44100 compensate: Auto is_denoise: False is_invert_spec: False is_mixer_mode: False mdx_batch_size: Default mdx_voc_inst_secondary_model: No Model Selected mdx_other_secondary_model: No Model Selected mdx_bass_secondary_model: No Model Selected mdx_drums_secondary_model: No Model Selected mdx_is_secondary_model_activate: False mdx_voc_inst_secondary_model_scale: 0.9 mdx_other_secondary_model_scale: 0.7 mdx_bass_secondary_model_scale: 0.5 mdx_drums_secondary_model_scale: 0.5 is_save_all_outputs_ensemble: True is_append_ensemble_name: False chosen_audio_tool: Manual Ensemble choose_algorithm: Min Spec time_stretch_rate: 2.0 pitch_rate: 2.0 is_gpu_conversion: False is_primary_stem_only: False is_secondary_stem_only: False is_testing_audio: False is_add_model_name: False is_accept_any_input: False is_task_complete: False is_normalization: False is_create_model_folder: False mp3_bit_set: 320k save_format: WAV wav_type_set: PCM_16 help_hints_var: False model_sample_mode: False model_sample_mode_duration: 30 demucs_stems: All Stems**