Beiträge von atmde

Blöde Frage, stellt man im Windows den HDR Mode auf ein oder aus ?

Okay danke Dir Harald, jetzt weiß ich wenigstens woran es liegt.

CUDA hängt fast durchgehend bei 100% wenn SVP auf 62 fps transkodiert.

RIFE AI war bei der Anschaffung auch kein Thema, dann ist es jetzt halt so.

Hab gerade probiert "Die Eiskönigin" und dann "Coco" zu transkodieren, da hat es direkt Error gebracht

Zitat

20:33:01.207: ===== Starting mpv ======

20:33:01.207: Command line: C:\Program Files (x86)\SVP 4\mpv64\mpv.exe M:/Filme/Die Eiskönigin - Völlig unverfroren (2013)/Die Eiskönigin - Völlig unverfroren (2013) 1080p DTS.mkv --o=M:/Filme/Die Eiskönigin - Völlig unverfroren (2013)/Die Eiskönigin - Völlig unverfroren (2013) 1080p DTS.SVP.temporary.mkv --no-audio --no-sub --no-sub-auto --input-ipc-server=mpvencodepipe --input-media-keys=no --no-msg-color --vf=vapoursynth:[C:\Users\HTPC_User\AppData\Roaming\SVP4\scripts\ffff.py]:4:8 --of=matroska --ovc=hevc_nvenc --ovcopts=b=16332133,preset=slow,rc=vbr,maxrate=21231773,bufsize=32664266,time_base=1000/23976,threads=8

20:33:02.363: (+) Video --vid=1 (*) 'HD 1080p AVC' (h264 1920x856 23.976fps)

20:33:02.363: Audio --aid=1 --alang=ger (*) 'DTS 5.1 ' (dts 6ch 48000Hz)

20:33:02.363: Subs --sid=1 --slang=ger (*) 'complete' (dvd_subtitle)

20:33:03.427: vstrt: TensorRT version mismatch, built with 2135 but loaded with 2136; continue but fingers crossed...

20:33:03.487: [vapoursynth] Script evaluation failed:

20:33:03.487: [vapoursynth] Python exception: vsmlrt.RIFE: RIFE: multi must be at least 2

20:33:03.487: [vapoursynth]

20:33:03.487: [vapoursynth] Traceback (most recent call last):

20:33:03.487: [vapoursynth] File "src\cython\vapoursynth.pyx", line 2866, in vapoursynth._vpy_evaluate

20:33:03.487: [vapoursynth] File "src\cython\vapoursynth.pyx", line 2867, in vapoursynth._vpy_evaluate

20:33:03.487: [vapoursynth] File "C:\Users\HTPC_User\AppData\Roaming\SVP4\scripts\ffff.py", line 78, in <module>

20:33:03.487: [vapoursynth] smooth = interpolate(clip)

20:33:03.487: [vapoursynth] File "C:\Users\HTPC_User\AppData\Roaming\SVP4\scripts\ffff.py", line 57, in interpolate

20:33:03.487: [vapoursynth] smooth = RIFE(input_m,multi=rife_num,model=rife_mnum,backend=trt_backend)

20:33:03.487: [vapoursynth] File "C:\Program Files (x86)\SVP 4\rife\vsmlrt.py", line 981, in RIFE

20:33:03.487: [vapoursynth] raise ValueError(f'{func_name}: RIFE: multi must be at least 2')

20:33:03.487: [vapoursynth] ValueError: vsmlrt.RIFE: RIFE: multi must be at least 2

20:33:03.487: [vapoursynth]

20:33:03.542: (!!!) Intermediate file may be broken: M:\Filme\Die Eiskönigin - Völlig unverfroren (2013)\Die Eiskönigin - Völlig unverfroren (2013) 1080p DTS.SVP.temporary.mkv

20:33:03.542: ===== mpv exited with code 62097 =====

Alles anzeigen

Ich habe aber mittlerweile kapiert, das ich auf der ersten Seite (Videoprofile) die gewünschte Bildfrequenz vorab einstellen muss, dann läuft auch das Transkodieren an.

Bisheriger Höchstwert um die 67.1 fps

Ansonsten läuft er so mit 66 fps konstant (bei 50-60% GPU Last).

So Titel ist durchgelaufen, seperater File wurde gespeichert und der soapige Effekt ist voll da.

Läuft mit 60fps.

Kann mir jemand was zu dem Log sagen ? Passt das so, was da drin steht ?

Muss ich hier was ändern, oder ist das normal ?

Kann man den "Con Air - Extended Edition (1997) 1080p AC3.SVP.temporary.mkv" file bedenkenlos löschen ?

Zitat

21:49:35.338: [03/12/2023-21:49:35] [W] [TRT] CUDA lazy loading is not enabled. Enabli

21:49:35.354: ng it can significantly reduce device memory usage. See `CUDA_MODULE_LOADING` in https://docs.n

21:49:35.354: vidia.com/cuda/cuda-c-programming-guide/index.html#env-vars

Zitat

21:49:31.624: ===== Starting mpv ======

21:49:31.624: Command line: C:\Program Files (x86)\SVP 4\mpv64\mpv.exe M:/Filme/Con Air - Extended Edition (1997)/Con Air - Extended Edition (1997) 1080p AC3.mkv --o=M:/Filme/Con Air - Extended Edition (1997)/Con Air - Extended Edition (1997) 1080p AC3.SVP.temporary.mkv --no-audio --no-sub --no-sub-auto --input-ipc-server=mpvencodepipe --input-media-keys=no --no-msg-color --vf=vapoursynth:[C:\Users\HTPC_User\AppData\Roaming\SVP4\scripts\ffff.py]:4:8 --of=matroska --ovc=hevc_nvenc --ovcopts=b=15645268,preset=slow,rc=vbr,maxrate=20338848,bufsize=31290536,time_base=1000/60000,threads=8

21:49:32.330: (+) Video --vid=1 (*) 'HD 1080p AVC' (h264 1920x820 25.000fps)

21:49:32.330: Audio --aid=1 --alang=ger (*) 'Dolby Digital 5.1 ' (ac3 6ch 48000Hz)

21:49:32.330: File tags:

21:49:32.330: Title: CONAIR · UNRATED · EXTENDED (1997)

21:49:32.455: vstrt: TensorRT version mismatch, built with 2135 but loaded with 2136; continue but fingers crossed...

21:49:32.517: C:/Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.4_ensemble.onnx.1920x832_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_139fe355.engine not writable

21:49:32.517: change engine path to C:\Users\HTPC_U~1\AppData\Local\Temp\Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.4_ensemble.onnx.1920x832_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_139fe355.engine

21:49:32.614: &&&& RUNNING TensorRT.trtexec [TensorRT v8501] # C:/Program Files (x86)/SVP 4/rife\vsmlrt-cuda\trtexec --onnx=C:/Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.4_ensemble.onnx --timingCacheFile=C:\Users\HTPC_U~1\AppData\Local\Temp\Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.4_ensemble.onnx.1920x832_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_139fe355.engine.cache --device=0 --saveEngine=C:\Users\HTPC_U~1\AppData\Local\Temp\Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.4_ensemble.onnx.1920x832_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_139fe355.engine --shapes=input:1x7x832x1920 --fp16 --tacticSources=-CUBLAS,-CUBLAS_LT --useCudaGraph --noDataTransfers --inputIOFormats=fp16:chw --outputIOFormats=fp16:chw

21:49:32.614: [03/12/2023-21:49:32] [I] === Model Options ===

21:49:32.614: [03/12/2023-21:49:32] [I] Format: ONNX

21:49:32.614: [03/12/2023-21:49:32] [I] Model: C:/Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.4_ensemble.onnx

21:49:32.614: [03/12/2023-21:49:32] [I] Output:

21:49:32.614: [03/12/2023-21:49:32] [I] === Build Options ===

21:49:32.614: [03/12/2023-21:49:32] [I] Max batch: explicit batch

21:49:32.614: [03/12/2023-21:49:32] [I] Memory Pools: workspace: default, dlaSRAM: default, dlaLocalDRAM: default, dlaGlobalDRAM: default

21:49:32.614: [03/12/2023-21:49:32] [I] minTiming: 1

21:49:32.614: [03/12/2023-21:49:32] [I] avgTiming: 8

21:49:32.614: [03/12/2023-21:49:32] [I] Precision: FP32+FP16

21:49:32.614: [03/12/2023-21:49:32] [I] LayerPrecisions:

21:49:32.614: [03/12/2023-21:49:32] [I] Calibration:

21:49:32.614: [03/12/2023-21:49:32] [I] Refit: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] Sparsity: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] Safe mode: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] DirectIO mode: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] Restricted mode: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] Build only: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] Save engine: C:\Users\HTPC_U~1\AppData\Local\Temp\Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.4_ensemble.onnx.1920x832_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_139fe355.engine

21:49:32.614: [03/12/2023-21:49:32] [I] Load engine:

21:49:32.614: [03/12/2023-21:49:32] [I] Profiling verbosity: 0

21:49:32.614: [03/12/2023-21:49:32] [I] Tactic sources: cublas [OFF], cublasLt [OFF],

21:49:32.614: [03/12/2023-21:49:32] [I] timingCacheMode: global

21:49:32.614: [03/12/2023-21:49:32] [I] timingCacheFile: C:\Users\HTPC_U~1\AppData\Local\Temp\Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.4_ensemble.onnx.1920x832_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_139fe355.engine.cache

21:49:32.614: [03/12/2023-21:49:32] [I] Heuristic: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] Preview Features: Use default preview flags.

21:49:32.614: [03/12/2023-21:49:32] [I] Input(s): fp16:chw

21:49:32.614: [03/12/2023-21:49:32] [I] Output(s): fp16:chw

21:49:32.614: [03/12/2023-21:49:32] [I] Input build shape: input=1x7x832x1920+1x7x832x1920+1x7x832x1920

21:49:32.614: [03/12/2023-21:49:32] [I] Input calibration shapes: model

21:49:32.614: [03/12/2023-21:49:32] [I] === System Options ===

21:49:32.614: [03/12/2023-21:49:32] [I] Device: 0

21:49:32.614: [03/12/2023-21:49:32] [I] DLACore:

21:49:32.614: [03/12/2023-21:49:32] [I] Plugins:

21:49:32.614: [03/12/2023-21:49:32] [I] === Inference Options ===

21:49:32.614: [03/12/2023-21:49:32] [I] Batch: Explicit

21:49:32.614: [03/12/2023-21:49:32] [I] Input inference shape: input=1x7x832x1920

21:49:32.614: [03/12/2023-21:49:32] [I] Iterations: 10

21:49:32.614: [03/12/2023-21:49:32] [I] Duration: 3s (+ 200ms warm up)

21:49:32.614: [03/12/2023-21:49:32] [I] Sleep time: 0ms

21:49:32.614: [03/12/2023-21:49:32] [I] Idle time: 0ms

21:49:32.614: [03/12/2023-21:49:32] [I] Streams: 1

21:49:32.614: [03/12/2023-21:49:32] [I] ExposeDMA: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] Data transfers: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] Spin-wait: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] Multithreading: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] CUDA Graph: Enabled

21:49:32.614: [03/12/2023-21:49:32] [I] Separate profiling: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] Time Deserialize: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] Time Refit: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] NVTX verbosity: 0

21:49:32.614: [03/12/2023-21:49:32] [I] Persistent Cache Ratio: 0

21:49:32.614: [03/12/2023-21:49:32] [I] Inputs:

21:49:32.614: [03/12/2023-21:49:32] [I] === Reporting Options ===

21:49:32.614: [03/12/2023-21:49:32] [I] Verbose: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] Averages: 10 inferences

21:49:32.614: [03/12/2023-21:49:32] [I] Percentiles: 90,95,99

21:49:32.614: [03/12/2023-21:49:32] [I] Dump refittable layers:Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] Dump output: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] Profile: Disabled

21:49:32.614: [03/12/2023-21:49:32] [I] Export timing to JSON file:

21:49:32.614: [03/12/2023-21:49:32] [I] Export output to JSON file:

21:49:32.614: [03/12/2023-21:49:32] [I] Export profile to JSON file:

21:49:32.614: [03/12/2023-21:49:32] [I]

21:49:32.629: [03/12/2023-21:49:32] [I] === Device Information ===

21:49:32.629: [03/12/2023-21:49:32] [I] Selected Device: NVIDIA GeForce RTX 3060 Ti

21:49:32.629: [03/12/2023-21:49:32] [I] Compute Capability: 8.6

21:49:32.629: [03/12/2023-21:49:32] [I] SMs: 38

21:49:32.629: [03/12/2023-21:49:32] [I] Compute Clock Rate: 1.665 GHz

21:49:32.629: [03/12/2023-21:49:32] [I] Device Global Memory: 8191 MiB

21:49:32.629: [03/12/2023-21:49:32] [I] Shared Memory per SM: 100 KiB

21:49:32.629: [03/12/2023-21:49:32] [I] Memory Bus Width: 256 bits (ECC disabled)

21:49:32.629: [03/12/2023-21:49:32] [I] Memory Clock Rate: 7.001 GHz

21:49:32.629: [03/12/2023-21:49:32] [I]

21:49:32.629: [03/12/2023-21:49:32] [I] TensorRT version: 8.5.1

21:49:32.973: [03/12/2023-21:49:32] [I] [TRT] [MemUsageChange] Init CUDA: CPU +446, GPU +0, now: CPU 10935, GPU 1183 (MiB)

21:49:35.323: [03/12/2023-21:49:35] [I] [TRT] [MemUsageChange] Init builder kernel library: CPU +483, GPU +118, now: CPU 11787, GPU 1301 (MiB)

21:49:35.338: [03/12/2023-21:49:35] [W] [TRT] CUDA lazy loading is not enabled. Enabli

21:49:35.354: ng it can significantly reduce device memory usage. See `CUDA_MODULE_LOADING` in https://docs.n

21:49:35.354: vidia.com/cuda/cuda-c-programming-guide/index.html#env-vars

21:49:35.354: [03/12/2023-21:49:35] [I] Start parsing network model

21:49:35.369: [03/12/2023-21:49:35] [I] [TRT] ----------------------------------------------------------------

21:49:35.369: [03/12/2023-21:49:35] [I] [TRT] Input filename: C:/Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.4_ensemble.onnx

21:49:35.369: [03/12/2023-21:49:35] [I] [TRT] ONNX IR version: 0.0.8

21:49:35.369: [03/12/2023-21:49:35] [I] [TRT] Opset version: 16

21:49:35.369: [03/12/2023-21:49:35] [I] [TRT] Producer name: pytorch

21:49:35.369: [03/12/2023-21:49:35] [I] [TRT] Producer version: 2.0.0

21:49:35.369: [03/12/2023-21:49:35] [I] [TRT] Domain:

21:49:35.369: [03/12/2023-21:49:35] [I] [TRT] Model version: 0

21:49:35.369: [03/12/2023-21:49:35] [I] [TRT] Doc string:

21:49:35.369: [03/12/2023-21:49:35] [I] [TRT] ----------------------------------------------------------------

21:49:35.385: [03/12/2023-21:49:35] [W] [TRT] onnx2trt_utils.cpp:377: Your ONNX model has been generated with INT64 weights, while TensorRT does not natively support INT64. Attempting to cast down to INT32.

21:49:35.385: [03/12/2023-21:49:35] [W] [TRT] onnx2trt_utils.cpp:403: One or more weights outside the range of INT32 was clamped

21:49:35.385: [03/12/2023-21:49:35] [W] [TRT] onnx2trt_utils.cpp:403: One or more weights outside the range of INT32 was clamped

21:49:35.401: [03/12/2023-21:49:35] [W] [TRT] onnx2trt_utils.cpp:403: One or more weights outside the range of INT32 was clamped

21:49:35.401: [03/12/2023-

21:49:35.401: 21:49:35] [W] [TRT] onnx2trt_utils.cpp:403: One or more weights outside the range of INT32 was clamped

21:49:35.916: [03/12/2023-21:49:35] [W] [TRT] onnx2trt_utils.cpp:403: One or more weights outside the range of INT32 was clamped

21:49:35.932: [03/12/2023-21:49:35] [I] Finish parsing network model

21:49:35.932: [03/12/2023-21:49:35] [W] Could not read timing cache from: C:\Users\HTPC_U~1\AppData\Local\Temp\Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.4_ensemble.onnx.1920x832_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_139fe355.engine.cache. A new timing cache will be generated and written.

21:49:37.087: [03/12/2023-21:49:37] [I] [TRT] [MemUsageChange] Init cuDNN: CPU +1091, GPU +406, now: CPU 12525, GPU 1707 (MiB)

21:49:37.087: [03/12/2023-21:49:37] [I] [TRT] Global timing cache in use. Profiling results in this builder pass will be stored.

21:52:48.071: [03/12/2023-21:52:48] [I] [TRT] Total Activation Memory: 9759461888

21:52:48.071: [03/12/2023-21:52:48] [I] [TRT] Detected 4 inputs and 1 output network tensors.

21:52:48.258: [03/12/2023-21:52:48] [I] [TRT] Total Host Persistent Memory: 202848

21:52:48.258: [03/12/2023-21:52:48] [I] [TRT] Total Device Persistent Memory: 16285696

21:52:48.258: [03/12/2023-21:52:48] [I] [TRT] Total Scratch Memory: 19169280

21:52:48.258: [03/12/2023-21:52:48] [I] [TRT] [MemUsageStats] Peak memory usage of TRT CPU/GPU memory allocators: CPU 19 MiB, GPU 4715 MiB

21:52:48.258: [03/12/2023-21:52:48] [I] [TRT] [BlockAssignment] Started assigning block shifts. This will take 154 steps to complete.

21:52:48.274: [03/12/2023-21:52:48] [I] [TRT] [BlockAssignment] Algorithm ShiftNTopDown took 12.6033ms to assign 13 blocks to 154 nodes requiring 233227264 bytes.

21:52:48.274: [03/12/2023-21:52:48] [I] [TRT] Total Activation Memory: 233227264

21:52:48.383: [03/12/2023-21:52:48] [W] [TRT] TensorRT encountered issues when converting weights between types and that could affect accuracy.

21:52:48.383: [03/12/2023-21:52:48] [W] [TRT] If this is not the desired behavior, please modify the weights or retrain with regularization to adjust the magnitude of the weights.

21:52:48.383: [03/12/2023-21:52:48] [W] [TRT] Check verbose logs for the list of affected weights.

21:52:48.383: [03/12/2023-21:

21:52:48.383: 52:48] [W] [TRT] - 94 weights are affected by this issue: Detected subnormal FP16 values.

21:52:48.383: [03/12/2023-21:52:48] [W] [TRT] - 10 weights are affected by this issue: Detected values less than smallest positive FP16 subnormal value and converted them to the FP16 minimum subnormalized value.

21:52:48.383: [03/12/2023-21:52:48] [I] [TRT] [MemUsageChange] TensorRT-managed allocation in building engine: CPU +19, GPU +25, now: CPU 19, GPU 25 (MiB)

21:52:48.399: [03/12/2023-21:52:48] [I] [TRT] [MemUsageChange] Init CUDA: CPU +0, GPU +0, now: CPU 13471, GPU 1933 (MiB)

21:52:48.399: [03/12/2023-21:52:48] [W] [TRT] CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See `CUDA_MODULE_LOADING` in https://docs.nvidia.com/cuda/c…guide/index.html#env-vars

21:52:48.399: [03/12/2023-21:52:48] [I] Saved 190208 bytes of timing cache to C:\Users\HTPC_U~1\AppData\Local\Temp\Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.4_ensemble.onnx.1920x832_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_139fe355.engine.cache

21:52:48.399: [03/12/2023-21:52:48] [I] Engine built in 195.767 sec.

21:52:48.555: [03/12/2023-21:52:48] [I] [TRT] Loaded engine size: 10 MiB

21:52:48.571: [03/12/2023-21:52:48] [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +25, now: CPU 0, GPU 25 (MiB)

21:52:48.571: [03/12/2023-21:52:48] [I] Engine deserialized in 0.0090543 sec.

21:52:48.586: [03/12/2023-21:52:48] [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +238, now: CPU 0, GPU 263 (MiB)

21:52:48.586: [03/12/2023-21:52:48] [W] [TRT] CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See `CUDA_MODULE_LOADING` in https://docs.nvidia.com/cuda/c…guide/index.html#env-vars

21:52:48.586: [03/12/2023-21:52:48] [I] Setting persistentCacheLimit to 0 bytes.

21:52:48.586: [03/12/2023-21:52:48] [I] Using random values for input input

21:52:48.727: [03/12/2023-21:52:48] [I] Created input binding for input with dimensions 1x7x832x1920

21:52:48.727: [03/12/2023-21:52:48] [I] Using random values for output output

21:52:48.727: [03/12/2023-21:52:48] [I] Created output binding for output with dimensions 1x3x832x1920

21:52:48.727: [03/12/2023-21:52:48] [I] Starting inference

21:52:51.983: [03/12/2023-21:52:51] [I] Warmup completed 12 queries over 200 ms

21:52:51.983: [03/12/2023-21:52:51] [I] Timing trace has 214 queries over 3.03613 s

21:52:51.983: [03/12/2023-21:52:51] [I]

21:52:51.983: [03/12/2023-21:52:51] [I] === Trace details ===

21:52:51.983: [03/12/2023-21:52:51] [I] Trace averages of 10 runs:

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.2143 ms - Host latency: 14.2143 ms (enqueue 0.0871597 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.0171 ms - Host latency: 14.0171 ms (enqueue 0.0539063 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.1252 ms - Host latency: 14.1252 ms (enqueue 0.069458 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.1378 ms - Host latency: 14.1378 ms (enqueue 0.0795288 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.152 ms - Host latency: 14.152 ms (enqueue 0.0790649 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.1415 ms - Host latency: 14.1415 ms (enqueue 0.0941895 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.2885 ms - Host latency: 14.2885 ms (enqueue 0.0805664 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.2182 ms - Host latency: 14.2182 ms (enqueue 0.0821167 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.0829 ms - Host latency: 14.0829 ms (enqueue 0.0558594 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.023 ms - Host latency: 14.023 ms (enqueue 0.0457031 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.2037 ms - Host latency: 14.2037 ms (enqueue 0.0845825 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.1831 ms - Host latency: 14.1831 ms (enqueue 0.0817749 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.2008 ms - Host latency: 14.2008 ms (enqueue 0.0818237 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.1933 ms - Host latency: 14.1933 ms (enqueue 0.0807739 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.2031 ms - Host latency: 14.2031 ms (enqueue 0.0953369 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.1423 ms - Host latency: 14.1423 ms (enqueue 0.0489014 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.2208 ms - Host latency: 14.2208 ms (enqueue 0.0665527 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.1942 ms - Host latency: 14.1942 ms (enqueue 0.0705078 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.214 ms - Host latency: 14.214 ms (enqueue 0.0716553 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.2147 ms - Host latency: 14.2147 ms (enqueue 0.0909668 ms)

21:52:51.983: [03/12/2023-21:52:51] [I] Average on 10 runs - GPU latency: 14.2426 ms - Host latency: 14.2426 ms (enqueue 0.0773682 ms)

21:52:51.983: [03/12/2023-21:52:51] [I]

21:52:51.983: [03/12/2023-21:52:51] [I] === Performance summary ===

21:52:51.983: [03/12/2023-21:52:51] [I] Throughput: 70.4844 qps

21:52:51.983: [03/12/2023-21:52:51] [I] Latency: min = 13.8905 ms, max = 15.1262 ms, mean = 14.1728 ms, median = 14.1734 ms, percentile(90%) = 14.2683 ms, percentile(95%) = 14.302 ms, percentile(99%) = 14.4467 ms

21:52:51.983: [03/12/2023-21:52:51] [I] Enqueue Time: min = 0.0153809 ms, max = 0.233643 ms, mean = 0.0750602 ms, median = 0.0795898 ms, percentile(90%) = 0.0843506 ms, percentile(95%) = 0.0913086 ms, percentile(99%) = 0.193237 ms

21:52:51.983: [03/12/2023-21:52:51] [I] H2D Latency: min = 0 ms, max = 0 ms, mean = 0 ms, median = 0 ms, percentile(90%) = 0 ms, percentile(95%) = 0 ms, percentile(99%) = 0 ms

21:52:51.983: [03/12/2023-21:52:51] [I] GPU Compute Time: min = 13.8905 ms, max = 15.1262 ms, mean = 14.1728 ms, median = 14.1734 ms, percentile(90%) = 14.2683 ms, percentile(95%) = 14.302 ms, percentile(99%) = 14.4467 ms

21:52:51.983: [03/12/2023-21:52:51] [I] D2H Latency: min = 0 ms, max = 0 ms, mean = 0 ms, median = 0 ms, percentile(90%) = 0 ms, percentile(95%) = 0 ms, percentile(99%) = 0 ms

21:52:51.983: [03/12/2023-21:52:51] [I] Total Host Walltime: 3.03613 s

21:52:51.983: [03/12/2023-21:52:51] [I] Total GPU Compute Time: 3.03299 s

21:52:51.983: [03/12/2023-21:52:51] [I] Explanations of the performance metrics are printed in the verbose logs.

21:52:51.983: [03/12/2023-21:52:51] [I]

21:52:51.983: &&&& PASSED TensorRT.trtexec [TensorRT v8501] # C:/Program Files (x86)/SVP 4/rife\vsmlrt-cuda\trtexec --onnx=C:/Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.4_ensemble.onnx --timingCacheFile=C:\Users\HTPC_U~1\AppData\Local\Temp\Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.4_ensemble.onnx.1920x832_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_139fe355.engine.cache --device=0 --saveEngine=C:\Users\HTPC_U~1\AppData\Local\Temp\Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.4_ensemble.onnx.1920x832_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_139fe355.engine --shapes=input:1x7x832x1920 --fp16 --tacticSources=-CUBLAS,-CUBLAS_LT --useCudaGraph --noDataTransfers --inputIOFormats=fp16:chw --outputIOFormats=fp16:chw

21:52:53.034: CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See `CUDA_MODULE_LOADING` in https://docs.nvidia.com/cuda/c…guide/index.html#env-vars

21:52:53.095: CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See `CUDA_MODULE_LOADING` in https://docs.nvidia.com/cuda/c…guide/index.html#env-vars

21:52:53.141: CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See `CUDA_MODULE_LOADING` in https://docs.nvidia.com/cuda/c…guide/index.html#env-vars

21:52:53.188: CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See `CUDA_MODULE_LOADING` in https://docs.nvidia.com/cuda/c…guide/index.html#env-vars

21:52:53.297: VO: [lavc] 1920x820 yuv420p

21:52:53.297: [vo/lavc] Opening encoder: NVIDIA NVENC hevc encoder [hevc_nvenc]

21:52:53.448: [encode] Opening output file: M:/Filme/Con Air - Extended Edition (1997)/Con Air - Extended Edition (1997) 1080p AC3.SVP.temporary.mkv

21:52:53.566: [encode] Opening muxer: Matroska [matroska]

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23:39:00.957: V: 01:47:09 / 01:56:39 (92%) {7.7min 60.6fps 13020.8MB} Cache: 568s/135MB

23:40:00.976: V: 01:48:11 / 01:56:39 (93%) {6.5min 60.6fps 12983.2MB} Cache: 506s/112MB

23:41:01.008: V: 01:49:13 / 01:56:39 (94%) {5.2min 60.6fps 12958.4MB} Cache: 444s/90MB

23:42:01.055: V: 01:50:17 / 01:56:39 (95%) {4.3min 60.6fps 12953.3MB} Cache: 379s/73MB

23:43:01.063: V: 01:51:19 / 01:56:39 (95%) {3.9min 60.7fps 13003.1MB} Cache: 318s/66MB

23:44:01.154: V: 01:52:19 / 01:56:39 (96%) {3.2min 60.6fps 13060.9MB} Cache: 258s/54MB

23:45:01.196: V: 01:53:22 / 01:56:39 (97%) {2.5min 60.7fps 13116.2MB} Cache: 195s/43MB

23:46:01.208: V: 01:54:26 / 01:56:39 (98%) {1.6min 60.7fps 13151.3MB} Cache: 131s/28MB

23:47:01.234: V: 01:55:31 / 01:56:39 (99%) {0.8min 60.7fps 13167.5MB} Cache: 66s/12MB

23:48:01.288: [encode] video: encoded 13817356403 bytes

23:48:01.288: [encode] audio: encoded 0 bytes

23:48:01.288: [encode] muxing overhead 3334476 bytes

23:48:01.316: Exiting... (End of file)

23:48:01.509: ===== Starting mkvmerge ======

23:48:01.509: Command line: C:\Program Files (x86)\SVP 4\extensions\code\mkvmerge.exe -o M:/Filme/Con Air - Extended Edition (1997)/Con Air - Extended Edition (1997) 1080p AC3.SVP.mkv M:/Filme/Con Air - Extended Edition (1997)/Con Air - Extended Edition (1997) 1080p AC3.SVP.temporary.mkv -D M:/Filme/Con Air - Extended Edition (1997)/Con Air - Extended Edition (1997) 1080p AC3.mkv

23:48:01.582: mkvmerge v73.0.0 ('25 or 6 to 4') 64-bit

23:48:02.118: 'M:/Filme/Con Air - Extended Edition (1997)/Con Air - Extended Edition (1997) 1080p AC3.SVP.temporary.mkv': Using the demultiplexer for the format 'Matroska'.

23:48:02.274: 'M:/Filme/Con Air - Extended Edition (1997)/Con Air - Extended Edition (1997) 1080p AC3.mkv': Using the demultiplexer for the format 'Matroska'.

23:48:02.274: 'M:/Filme/Con Air - Extended Edition (1997)/Con Air - Extended Edition (1997) 1080p AC3.SVP.temporary.mkv' track 0: Using the output module for the format 'HEVC/H.265'.

23:48:02.274: 'M:/Filme/Con Air - Extended Edition (1997)/Con Air - Extended Edition (1997) 1080p AC3.mkv' track 1: Using the output module for the format 'AC-3'.

23:48:02.384: The file 'M:/Filme/Con Air - Extended Edition (1997)/Con Air - Extended Edition (1997) 1080p AC3.SVP.mkv' has been opened for writing.

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00:12:15.965: The cue entries (the index) are being written...

00:12:24.171: Multiplexing took 24 minutes 22 seconds.

Alles anzeigen

Habe es eben mal nachinstalliert und mit einem älteren Titel am laufen:

Lasse es mal so bis morgen früh stehen, mal schauen was dabei rauskommt:

Wenn ich einen FullHD Film (Avengers) abspiele, kann ich auf RIFE AI umschalten sofern ich bei Avisynth bleibe und "an Bildschirm" einstelle.

Es startet dann allerdings keine CMD. Gehe ich auf x2 oder x2.5 stottert es.

Stelle ich auf VPS um, so öffnet sich zwar die CMD, aber die bleibt leer (5 Min gewartet) während im Hintergrund nur der Ton läuft.

Sonic Ist das ein Unterschied wegen dem + ? 3.7.2 hab ich ja installiert.

Radschi : Ja ich schau UHD, allerdings nur wenige Filme sind nativ vorhanden, der meiste Content ist 1080p.

Energieeinstellungen sind/waren auf Max.

Meine Fresse bin ich ein Trottel

Ich habe die vsmirt.py per Rechtsklick aus der File Übersicht in GitHub gespeichert und auch brav

die Bool Werte editiert.

Eben fiel mir das auf, dass ganz oben DOCTYPE steht.

Also anständig denn Code per Copy&Paste in die Datei kopiert und die Bool Werte erneut angepasst,

jetzt macht der Textblock auch mehr Sinn für ein Python Skript.

Im MPV funktioniert es jetzt bedingt, er zeigt beim Wechsel auf RIFE AI die SVP Meldung an, allerdings mit Farbfehler (s/w).

Außerdem kommt die CMD mit den richtigen Models hoch.

Zitat

&&&& RUNNING TensorRT.trtexec [TensorRT v8501] # C:/Program Files (x86)/SVP 4/rife\vsmlrt-cuda\trtexec --onnx=C:/Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.6_ensemble.onnx --timingCacheFile=C:\Users\HTPC_U~1\AppData\Local\Temp\Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.6_ensemble.onnx.3840x2144_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_f0d2d789.engine.cache --device=0 --saveEngine=C:\Users\HTPC_U~1\AppData\Local\Temp\Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.6_ensemble.onnx.3840x2144_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_f0d2d789.engine --shapes=input:1x7x2144x3840 --fp16 --tacticSources=-CUBLAS,-CUBLAS_LT --useCudaGraph --noDataTransfers --inputIOFormats=fp16:chw --outputIOFormats=fp16:chw

[03/12/2023-15:50:25] [I] === Model Options ===

[03/12/2023-15:50:25] [I] Format: ONNX

[03/12/2023-15:50:25] [I] Model: C:/Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.6_ensemble.onnx

[03/12/2023-15:50:25] [I] Output:

[03/12/2023-15:50:25] [I] === Build Options ===

[03/12/2023-15:50:25] [I] Max batch: explicit batch

[03/12/2023-15:50:25] [I] Memory Pools: workspace: default, dlaSRAM: default, dlaLocalDRAM: default, dlaGlobalDRAM: default

[03/12/2023-15:50:25] [I] minTiming: 1

[03/12/2023-15:50:25] [I] avgTiming: 8

[03/12/2023-15:50:25] [I] Precision: FP32+FP16

[03/12/2023-15:50:25] [I] LayerPrecisions:

[03/12/2023-15:50:25] [I] Calibration:

[03/12/2023-15:50:25] [I] Refit: Disabled

[03/12/2023-15:50:25] [I] Sparsity: Disabled

[03/12/2023-15:50:25] [I] Safe mode: Disabled

[03/12/2023-15:50:25] [I] DirectIO mode: Disabled

[03/12/2023-15:50:25] [I] Restricted mode: Disabled

[03/12/2023-15:50:25] [I] Build only: Disabled

[03/12/2023-15:50:25] [I] Save engine: C:\Users\HTPC_U~1\AppData\Local\Temp\Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.6_ensemble.onnx.3840x2144_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_f0d2d789.engine

[03/12/2023-15:50:25] [I] Load engine:

[03/12/2023-15:50:25] [I] Profiling verbosity: 0

[03/12/2023-15:50:25] [I] Tactic sources: cublas [OFF], cublasLt [OFF],

[03/12/2023-15:50:25] [I] timingCacheMode: global

[03/12/2023-15:50:25] [I] timingCacheFile: C:\Users\HTPC_U~1\AppData\Local\Temp\Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.6_ensemble.onnx.3840x2144_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_f0d2d789.engine.cache

[03/12/2023-15:50:25] [I] Heuristic: Disabled

[03/12/2023-15:50:25] [I] Preview Features: Use default preview flags.

[03/12/2023-15:50:25] [I] Input(s): fp16:chw

[03/12/2023-15:50:25] [I] Output(s): fp16:chw

[03/12/2023-15:50:25] [I] Input build shape: input=1x7x2144x3840+1x7x2144x3840+1x7x2144x3840

[03/12/2023-15:50:25] [I] Input calibration shapes: model

[03/12/2023-15:50:25] [I] === System Options ===

[03/12/2023-15:50:25] [I] Device: 0

[03/12/2023-15:50:25] [I] DLACore:

[03/12/2023-15:50:25] [I] Plugins:

[03/12/2023-15:50:25] [I] === Inference Options ===

[03/12/2023-15:50:25] [I] Batch: Explicit

[03/12/2023-15:50:25] [I] Input inference shape: input=1x7x2144x3840

[03/12/2023-15:50:25] [I] Iterations: 10

[03/12/2023-15:50:25] [I] Duration: 3s (+ 200ms warm up)

[03/12/2023-15:50:25] [I] Sleep time: 0ms

[03/12/2023-15:50:25] [I] Idle time: 0ms

[03/12/2023-15:50:25] [I] Streams: 1

[03/12/2023-15:50:25] [I] ExposeDMA: Disabled

[03/12/2023-15:50:25] [I] Data transfers: Disabled

[03/12/2023-15:50:25] [I] Spin-wait: Disabled

[03/12/2023-15:50:25] [I] Multithreading: Disabled

[03/12/2023-15:50:25] [I] CUDA Graph: Enabled

[03/12/2023-15:50:25] [I] Separate profiling: Disabled

[03/12/2023-15:50:25] [I] Time Deserialize: Disabled

[03/12/2023-15:50:25] [I] Time Refit: Disabled

[03/12/2023-15:50:25] [I] NVTX verbosity: 0

[03/12/2023-15:50:25] [I] Persistent Cache Ratio: 0

[03/12/2023-15:50:25] [I] Inputs:

[03/12/2023-15:50:25] [I] === Reporting Options ===

[03/12/2023-15:50:25] [I] Verbose: Disabled

[03/12/2023-15:50:25] [I] Averages: 10 inferences

[03/12/2023-15:50:25] [I] Percentiles: 90,95,99

[03/12/2023-15:50:25] [I] Dump refittable layers:Disabled

[03/12/2023-15:50:25] [I] Dump output: Disabled

[03/12/2023-15:50:25] [I] Profile: Disabled

[03/12/2023-15:50:25] [I] Export timing to JSON file:

[03/12/2023-15:50:25] [I] Export output to JSON file:

[03/12/2023-15:50:25] [I] Export profile to JSON file:

[03/12/2023-15:50:25] [I]

[03/12/2023-15:50:25] [I] === Device Information ===

[03/12/2023-15:50:25] [I] Selected Device: NVIDIA GeForce RTX 3060 Ti

[03/12/2023-15:50:25] [I] Compute Capability: 8.6

[03/12/2023-15:50:25] [I] SMs: 38

[03/12/2023-15:50:25] [I] Compute Clock Rate: 1.665 GHz

[03/12/2023-15:50:25] [I] Device Global Memory: 8191 MiB

[03/12/2023-15:50:25] [I] Shared Memory per SM: 100 KiB

[03/12/2023-15:50:25] [I] Memory Bus Width: 256 bits (ECC disabled)

[03/12/2023-15:50:25] [I] Memory Clock Rate: 7.001 GHz

[03/12/2023-15:50:25] [I]

[03/12/2023-15:50:25] [I] TensorRT version: 8.5.1

[03/12/2023-15:50:26] [I] [TRT] [MemUsageChange] Init CUDA: CPU +449, GPU +0, now: CPU 10062, GPU 1183 (MiB)

[03/12/2023-15:50:28] [I] [TRT] [MemUsageChange] Init builder kernel library: CPU +423, GPU +118, now: CPU 10968, GPU 1301 (MiB)

[03/12/2023-15:50:28] [W] [TRT] CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See `CUDA_MODULE_LOADING` in https://docs.nvidia.com/cuda/c…guide/index.html#env-vars

[03/12/2023-15:50:28] [I] Start parsing network model

[03/12/2023-15:50:28] [I] [TRT] ----------------------------------------------------------------

[03/12/2023-15:50:28] [I] [TRT] Input filename: C:/Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.6_ensemble.onnx

[03/12/2023-15:50:28] [I] [TRT] ONNX IR version: 0.0.8

[03/12/2023-15:50:28] [I] [TRT] Opset version: 16

[03/12/2023-15:50:28] [I] [TRT] Producer name: pytorch

[03/12/2023-15:50:28] [I] [TRT] Producer version: 2.0.0

[03/12/2023-15:50:28] [I] [TRT] Domain:

[03/12/2023-15:50:28] [I] [TRT] Model version: 0

[03/12/2023-15:50:28] [I] [TRT] Doc string:

[03/12/2023-15:50:28] [I] [TRT] ----------------------------------------------------------------

[03/12/2023-15:50:28] [W] [TRT] onnx2trt_utils.cpp:377: Your ONNX model has been generated with INT64 weights, while TensorRT does not natively support INT64. Attempting to cast down to INT32.

[03/12/2023-15:50:28] [W] [TRT] onnx2trt_utils.cpp:403: One or more weights outside the range of INT32 was clamped

[03/12/2023-15:50:28] [W] [TRT] onnx2trt_utils.cpp:403: One or more weights outside the range of INT32 was clamped

[03/12/2023-15:50:28] [W] [TRT] onnx2trt_utils.cpp:403: One or more weights outside the range of INT32 was clamped

[03/12/2023-15:50:28] [W] [TRT] onnx2trt_utils.cpp:403: One or more weights outside the range of INT32 was clamped

[03/12/2023-15:50:29] [W] [TRT] onnx2trt_utils.cpp:403: One or more weights outside the range of INT32 was clamped

[03/12/2023-15:50:29] [I] Finish parsing network model

[03/12/2023-15:50:29] [W] Could not read timing cache from: C:\Users\HTPC_U~1\AppData\Local\Temp\Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.6_ensemble.onnx.3840x2144_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_f0d2d789.engine.cache. A new timing cache will be generated and written.

[03/12/2023-15:50:31] [I] [TRT] [MemUsageChange] Init cuDNN: CPU +1090, GPU +406, now: CPU 11762, GPU 1707 (MiB)

[03/12/2023-15:50:31] [I] [TRT] Global timing cache in use. Profiling results in this builder pass will be stored.

[03/12/2023-15:58:33] [I] [TRT] Total Activation Memory: 15198938624

[03/12/2023-15:59:49] [I] [TRT] Detected 4 inputs and 1 output network tensors.

[03/12/2023-15:59:49] [I] [TRT] Total Host Persistent Memory: 169056

[03/12/2023-15:59:49] [I] [TRT] Total Device Persistent Memory: 97262592

[03/12/2023-15:59:49] [I] [TRT] Total Scratch Memory: 98795520

[03/12/2023-15:59:49] [I] [TRT] [MemUsageStats] Peak memory usage of TRT CPU/GPU memory allocators: CPU 56 MiB, GPU 4736 MiB

[03/12/2023-15:59:49] [I] [TRT] [BlockAssignment] Started assigning block shifts. This will take 168 steps to complete.

[03/12/2023-15:59:49] [I] [TRT] [BlockAssignment] Algorithm ShiftNTopDown took 15.1665ms to assign 13 blocks to 168 nodes requiring 1202013184 bytes.

[03/12/2023-15:59:49] [I] [TRT] Total Activation Memory: 1202013184

[03/12/2023-15:59:50] [W] [TRT] TensorRT encountered issues when converting weights between types and that could affect accuracy.

[03/12/2023-15:59:50] [W] [TRT] If this is not the desired behavior, please modify the weights or retrain with regularization to adjust the magnitude of the weights.

[03/12/2023-15:59:50] [W] [TRT] Check verbose logs for the list of affected weights.

[03/12/2023-15:59:50] [W] [TRT] - 88 weights are affected by this issue: Detected subnormal FP16 values.

[03/12/2023-15:59:50] [W] [TRT] - 16 weights are affected by this issue: Detected values less than smallest positive FP16 subnormal value and converted them to the FP16 minimum subnormalized value.

[03/12/2023-15:59:50] [I] [TRT] [MemUsageChange] TensorRT-managed allocation in building engine: CPU +20, GPU +103, now: CPU 20, GPU 103 (MiB)

[03/12/2023-15:59:50] [I] [TRT] [MemUsageChange] Init CUDA: CPU +0, GPU +0, now: CPU 13380, GPU 1933 (MiB)

[03/12/2023-15:59:50] [W] [TRT] CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See `CUDA_MODULE_LOADING` in https://docs.nvidia.com/cuda/c…guide/index.html#env-vars

[03/12/2023-15:59:50] [I] Saved 274240 bytes of timing cache to C:\Users\HTPC_U~1\AppData\Local\Temp\Program Files (x86)/SVP 4/rife\models\rife_v2\rife_v4.6_ensemble.onnx.3840x2144_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_f0d2d789.engine.cache

[03/12/2023-15:59:50] [I] Engine built in 564.417 sec.

[03/12/2023-15:59:50] [I] [TRT] Loaded engine size: 10 MiB

[03/12/2023-15:59:50] [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +102, now: CPU 0, GPU 102 (MiB)

[03/12/2023-15:59:50] [I] Engine deserialized in 0.0180156 sec.

[03/12/2023-15:59:50] [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +1239, now: CPU 0, GPU 1341 (MiB)

[03/12/2023-15:59:50] [W] [TRT] CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See `CUDA_MODULE_LOADING` in https://docs.nvidia.com/cuda/c…guide/index.html#env-vars

[03/12/2023-15:59:50] [I] Setting persistentCacheLimit to 0 bytes.

[03/12/2023-15:59:50] [I] Using random values for input input

[03/12/2023-15:59:51] [I] Created input binding for input with dimensions 1x7x2144x3840

[03/12/2023-15:59:51] [I] Using random values for output output

[03/12/2023-15:59:51] [I] Created output binding for output with dimensions 1x3x2144x3840

[03/12/2023-15:59:51] [I] Starting inference

Alles anzeigen

Nachdem das beendet ist (2x knapp 10min bei The Hateful 8 UHD) läuft der Film an, aber der Cache ist mit 32secs winzig und nach 40secs bleibt

das Bild stehen, weil der Cache leer ist (lt. SVP ist die GPU zwischen 60 und 70%).

Wohlgemerkt bei RIFE AI 4.6 und den folgenden Settings:

Switche ich auf AI Model 4.4, so dauert die CMD fast 25 Minuten. Starte ich die Wiedergabe des gleichen Films erneut, beginnt die CMD wieder zu laufen,

ich dachte die Ergebnisse würden gespeichert werden, und man muss es nicht jedes Mal machen ?

Wie auch immer, hier das gleiche Ergebnis, ein winziger Cache läuft leer, dann hängt es für 1-2 Sekunden und läuft stotternd weiter bei 67% GPU Last.

Ich glaube mittlerweile, dass mein i3 -12100 hier die Limitierung ist und nicht die 3060ti.

Schalte ich auf automatisch kann ich den Film mit fix 60fps ohne Probleme laufen lassen im mpv.

Ebenso in MPC-HC.

Rife-AI funktioniert hingegen nicht beim MPC-HC (weder mit Vaporsynth noch mit Avisynth) der Player crashed nach max. 5 Sekunden ohne Fehlermeldung.

Scheint als ob ich das Projekt RIFE zurückstellen muss, bis ich mir irgendwann mal nen neuen HTPC baue. Das ist aber nicht in Sicht.

Meiner ist ja erst wenige Monate als und für MadVR absolut ausreichend.

Danke für eure Hilfe. Wie immer tolle Hilfe hier im Forum

Stell ich im SVP während der Wiedergabe mit MPV auf Profil Automatic, erfolgt die bekannte Einblendung. Einstellung: an Bildschirm

Schalte ich dann zurück auf RIFE AI bzw "MY Rife AI" hängt das Bild eine Sekunde und läuft dann weiter, aber es erfolgt keine Anzeige.

Einstellung ist fix 60FPS

Bei MPV kommt keinerlei Meldung nach dem Wechsel auf RIFE AI.

In MPV bekomme ich allerdings auch keine SVP Anzeige was die Bildrate angeht.

Da ich MPV noch nie wirklich genutzt habe, weiß ich nicht ob das normal ist. Einstellen kann ich da nix (Rechtsklick bzw. ALT bringt keinerlei Menüs).

Habe jetzt noch Rife mit Ensemble nachgezogen, aber die Fehlermeldung bleibt (nur andere Zeilen)

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<title>vs-mlrt/vsmlrt.py at master · AmusementClub/vs-mlrt</title>

Das ist eine gute Frage, ich glaube nein, aber finde den Fehler nicht.

Habe SVP neu installiert mit folgenden Optionen:

Dann habe ich meinen madVR 165 Ordner Inhalt nach "C:\Program Files (x86)\SVP 4\madVR " kopiert und anschließend,

der Anleitung folgend Avisynth 3.7.2 manuell.

Das RIFE AI Profil ist da und TensorRT ausgewählt

Im MPC-HC habe ich VPS eingestellt als prefered:

Was ich nicht im Menü finde sind die Variablen für VPS, bei mir will er nur VLC und MPV setzen:

Starte ich nun einen Film im MPC-HC, standsarmäßig automatic (wo kann man das denn ändern ?).

Wechsle ich im SVP manuell auf RIFE AI, so bekomme ich eine dauerhafte Fehlermeldung ins Bild und der FIlm läuft ohne eine Art der Vorberechnung:

Habe wie erwähnt nochmal von Vorne angefangen, die V2 Models sind aktuell nicht auf dem HTPC.

Bin für jede Hilfe dankbar

EDIT: Stelle ich RIFE 4.4 ein, so öffnet sich die CMD und ich warte brav 3 Minuten beginnt der Film, aber ebenfalls mit der Fehlermeldung.

&&&& RUNNING TensorRT.trtexec [TensorRT v8501] # C:/Program Files (x86)/SVP 4/rife\vsmlrt-cuda\trtexec --onnx=C:/Program Files (x86)/SVP 4/rife\models\rife\rife_v4.4.onnx --timingCacheFile=C:\Users\HTPC_User\AppData\Roaming\SVP4\cache\Program Files (x86)/SVP 4/rife\models\rife\rife_v4.4.onnx.1920x800_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_a8b3b7a9.engine.cache --device=0 --saveEngine=C:\Users\HTPC_User\AppData\Roaming\SVP4\cache\Program Files (x86)/SVP 4/rife\models\rife\rife_v4.4.onnx.1920x800_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_a8b3b7a9.engine --shapes=input:1x11x800x1920 --fp16 --tacticSources=-CUBLAS,-CUBLAS_LT --useCudaGraph --noDataTransfers --inputIOFormats=fp16:chw --outputIOFormats=fp16:chw
[03/12/2023-13:59:09] [I] === Model Options ===
[03/12/2023-13:59:09] [I] Format: ONNX
[03/12/2023-13:59:09] [I] Model: C:/Program Files (x86)/SVP 4/rife\models\rife\rife_v4.4.onnx
[03/12/2023-13:59:09] [I] Output:
[03/12/2023-13:59:09] [I] === Build Options ===
[03/12/2023-13:59:09] [I] Max batch: explicit batch
[03/12/2023-13:59:09] [I] Memory Pools: workspace: default, dlaSRAM: default, dlaLocalDRAM: default, dlaGlobalDRAM: default
[03/12/2023-13:59:09] [I] minTiming: 1
[03/12/2023-13:59:09] [I] avgTiming: 8
[03/12/2023-13:59:09] [I] Precision: FP32+FP16
[03/12/2023-13:59:09] [I] LayerPrecisions:
[03/12/2023-13:59:09] [I] Calibration:
[03/12/2023-13:59:09] [I] Refit: Disabled
[03/12/2023-13:59:09] [I] Sparsity: Disabled
[03/12/2023-13:59:09] [I] Safe mode: Disabled
[03/12/2023-13:59:09] [I] DirectIO mode: Disabled
[03/12/2023-13:59:09] [I] Restricted mode: Disabled
[03/12/2023-13:59:09] [I] Build only: Disabled
[03/12/2023-13:59:09] [I] Save engine: C:\Users\HTPC_User\AppData\Roaming\SVP4\cache\Program Files (x86)/SVP 4/rife\models\rife\rife_v4.4.onnx.1920x800_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_a8b3b7a9.engine
[03/12/2023-13:59:09] [I] Load engine:
[03/12/2023-13:59:09] [I] Profiling verbosity: 0
[03/12/2023-13:59:09] [I] Tactic sources: cublas [OFF], cublasLt [OFF],
[03/12/2023-13:59:09] [I] timingCacheMode: global
[03/12/2023-13:59:09] [I] timingCacheFile: C:\Users\HTPC_User\AppData\Roaming\SVP4\cache\Program Files (x86)/SVP 4/rife\models\rife\rife_v4.4.onnx.1920x800_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_a8b3b7a9.engine.cache
[03/12/2023-13:59:09] [I] Heuristic: Disabled
[03/12/2023-13:59:09] [I] Preview Features: Use default preview flags.
[03/12/2023-13:59:09] [I] Input(s): fp16:chw
[03/12/2023-13:59:09] [I] Output(s): fp16:chw
[03/12/2023-13:59:09] [I] Input build shape: input=1x11x800x1920+1x11x800x1920+1x11x800x1920
[03/12/2023-13:59:09] [I] Input calibration shapes: model
[03/12/2023-13:59:09] [I] === System Options ===
[03/12/2023-13:59:09] [I] Device: 0
[03/12/2023-13:59:09] [I] DLACore:
[03/12/2023-13:59:09] [I] Plugins:
[03/12/2023-13:59:09] [I] === Inference Options ===
[03/12/2023-13:59:09] [I] Batch: Explicit
[03/12/2023-13:59:09] [I] Input inference shape: input=1x11x800x1920
[03/12/2023-13:59:09] [I] Iterations: 10
[03/12/2023-13:59:09] [I] Duration: 3s (+ 200ms warm up)
[03/12/2023-13:59:09] [I] Sleep time: 0ms
[03/12/2023-13:59:09] [I] Idle time: 0ms
[03/12/2023-13:59:09] [I] Streams: 1
[03/12/2023-13:59:09] [I] ExposeDMA: Disabled
[03/12/2023-13:59:09] [I] Data transfers: Disabled
[03/12/2023-13:59:09] [I] Spin-wait: Disabled
[03/12/2023-13:59:09] [I] Multithreading: Disabled
[03/12/2023-13:59:09] [I] CUDA Graph: Enabled
[03/12/2023-13:59:09] [I] Separate profiling: Disabled
[03/12/2023-13:59:09] [I] Time Deserialize: Disabled
[03/12/2023-13:59:09] [I] Time Refit: Disabled
[03/12/2023-13:59:09] [I] NVTX verbosity: 0
[03/12/2023-13:59:09] [I] Persistent Cache Ratio: 0
[03/12/2023-13:59:09] [I] Inputs:
[03/12/2023-13:59:09] [I] === Reporting Options ===
[03/12/2023-13:59:09] [I] Verbose: Disabled
[03/12/2023-13:59:09] [I] Averages: 10 inferences
[03/12/2023-13:59:09] [I] Percentiles: 90,95,99
[03/12/2023-13:59:09] [I] Dump refittable layers:Disabled
[03/12/2023-13:59:09] [I] Dump output: Disabled
[03/12/2023-13:59:09] [I] Profile: Disabled
[03/12/2023-13:59:09] [I] Export timing to JSON file:
[03/12/2023-13:59:09] [I] Export output to JSON file:
[03/12/2023-13:59:09] [I] Export profile to JSON file:
[03/12/2023-13:59:09] [I]
[03/12/2023-13:59:09] [I] === Device Information ===
[03/12/2023-13:59:09] [I] Selected Device: NVIDIA GeForce RTX 3060 Ti
[03/12/2023-13:59:09] [I] Compute Capability: 8.6
[03/12/2023-13:59:09] [I] SMs: 38
[03/12/2023-13:59:09] [I] Compute Clock Rate: 1.665 GHz
[03/12/2023-13:59:09] [I] Device Global Memory: 8191 MiB
[03/12/2023-13:59:09] [I] Shared Memory per SM: 100 KiB
[03/12/2023-13:59:09] [I] Memory Bus Width: 256 bits (ECC disabled)
[03/12/2023-13:59:09] [I] Memory Clock Rate: 7.001 GHz
[03/12/2023-13:59:09] [I]
[03/12/2023-13:59:09] [I] TensorRT version: 8.5.1
[03/12/2023-13:59:10] [I] [TRT] [MemUsageChange] Init CUDA: CPU +413, GPU +0, now: CPU 11023, GPU 1183 (MiB)
[03/12/2023-13:59:11] [I] [TRT] [MemUsageChange] Init builder kernel library: CPU +480, GPU +118, now: CPU 11926, GPU 1301 (MiB)
[03/12/2023-13:59:11] [W] [TRT] CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See `CUDA_MODULE_LOADING` in https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#env-vars
[03/12/2023-13:59:11] [I] Start parsing network model
[03/12/2023-13:59:11] [I] [TRT] ----------------------------------------------------------------
[03/12/2023-13:59:11] [I] [TRT] Input filename:   C:/Program Files (x86)/SVP 4/rife\models\rife\rife_v4.4.onnx
[03/12/2023-13:59:11] [I] [TRT] ONNX IR version:  0.0.8
[03/12/2023-13:59:11] [I] [TRT] Opset version:    16
[03/12/2023-13:59:11] [I] [TRT] Producer name:    pytorch
[03/12/2023-13:59:11] [I] [TRT] Producer version: 1.12.0
[03/12/2023-13:59:11] [I] [TRT] Domain:
[03/12/2023-13:59:11] [I] [TRT] Model version:    0
[03/12/2023-13:59:11] [I] [TRT] Doc string:
[03/12/2023-13:59:11] [I] [TRT] ----------------------------------------------------------------
[03/12/2023-13:59:11] [W] [TRT] onnx2trt_utils.cpp:377: Your ONNX model has been generated with INT64 weights, while TensorRT does not natively support INT64. Attempting to cast down to INT32.
[03/12/2023-13:59:11] [I] Finish parsing network model
[03/12/2023-13:59:11] [W] Could not read timing cache from: C:\Users\HTPC_User\AppData\Roaming\SVP4\cache\Program Files (x86)/SVP 4/rife\models\rife\rife_v4.4.onnx.1920x800_fp16_trt-8502_cudnn_I-fp16_O-fp16_NVIDIA-GeForce-RTX-3060-Ti_a8b3b7a9.engine.cache. A new timing cache will be generated and written.
[03/12/2023-13:59:12] [I] [TRT] [MemUsageChange] Init cuDNN: CPU +1109, GPU +406, now: CPU 12710, GPU 1707 (MiB)
[03/12/2023-13:59:12] [I] [TRT] Global timing cache in use. Profiling results in this builder pass will be stored.

Bei 3x dachte ich erstmal an eine Art Stress Test, ich sehe ehrlich gesagt keinen Unterschied zwischen 2,5x und 3x.

Aber irgendwie kommt meine 3060ti dabei nichts ins Schwitzen, so um die 14% Last zeigt mir SVP an, und das wundert mich doch

bei RIFE AI mit allen Settings auf MAX.

Hab ich das richtig gemacht ?

unpack "rife_v2" into SVP 4\rife\models (i.e. there must be SVP 4\rife\models\rife_v2\rife_v4.6.onnx) - CHECK

replace SVP 4\rife\vsmlrt.py - CHECK

SVP neugestartet und Anwendungseinstellungen auf:

Bedeutet doch das Profil RIFE AI (3x) soll bei allen Filmen die unter 2160 sind und mit mpv (Player) abgespielt werden aktiv sein, oder ?

Sehe ich wie Viktor, egal welches Gerät du einschickst, steht immer irgendwas von „Alle Einstellungen können verloren gehen.“

Sorry, das geht auf mich. Da habe ich dich falsch verstanden.

Ich nutze es andersherum.

Anfang in iOS App bzw. WebApp und dann im Theater.

So herum funktioniert es.

Für das was du vorhast, kannst du ja mal Emby probieren.

Die haben einen eigenen Server und eine eigene "Theater App", ich weiß nicht ob die Theater App

mit einem Jellyfin Server funktioniert, aber genaugenommen ist Jellyfin ja ein Emby Fork, sollte theoretisch gehen.

Ich habe den Server zentral (NAS), die Theater App auf dem HTPC (dort kann man ext. Player definieren)

in Verbindung mit MPC+madvr. Und für unterwegs gibt's auch mobile Apps.

In der Konstellation funktioniert bei mir auch das merken der Wiedergabe Position in Verbindung mit MPC+madvr,

was so über KODI nicht funktioniert, wenn man einen anderen Player als den internen nutzt.

Und ja Emby benötigt für einiges eine Lizenz, aber ob du die für deine Anforderungen benötigst, oder ob

die Free Version reicht, musst du recherchieren.

Zitat von Kosta

Nachdem ich jetzt auf madVR gehe...

Gibt es eine Möglichkeit Kodi wieder als Player, aber extern einzusetzen? (mit extern meine ich ein separater Rechner wie NUC o.ä.)

Hier wird eben gefragt dass das Signal unverändert an madVR geschickt wird.

Mein Z9X ist zwar OK zum schauen, macht seine Arbeit sauber, die Bildqualität ist auch gut, aber die Menus sind ein Graus. Richtig langsam.

Die Frage verstehe ich nicht ganz.

Du lässt das processing demnächst madvr machen, soweit ok.

Von was kommst du und wieso möchtest du madvr vom Player getrennt laufen lassen ?

KODI ist ja eigentlich ein Mediencenter/Server, ja da ist auch ein Player integriert, aber der ist nicht das gelbe vom Ei und nicht mit madvr

kompatibel, sprich wenn KODI+madvr, dann musst du auch eine anderen Player einsetzen MPC, MPV o.ä.

Vielleicht lesen hier mehr Nutzer mit, deswegen stelle ich meine Frage hier nochmal:

Zitat

Die Leinwand hört sich auch für mich sehr interessant an, kann mir jemand etwas zu den Tüchern sagen ?

Die meisten nehmen ja die AT Version mit Sound Max4K Tuch, da ich keine Verwendung für ein AT Tuch habe,

würde mir das WG1PRO Tuch reichen.

Hat das zufällig jemand im Einsatz ?

Aktuell nutze ich eine uralte 16:9 Rollo Leinwand mit Gain 1.3 im 100" Format.

Quelle: Link

Ich glaub da das Board ja nur den vorletzten Sockel 1151 unterstützt, wäre imho ein späteres Komplett-Upgrade,

sinnvoller.

Ist das Bild "so schlecht", dass es eine stärkere GPU unbedingt benötigt ?

Evtl. würde ich dann auf dem Gebrauchtmarkt nachsehen, wenn die 40er jetzt gut verfügbar sind,

dürften ältere 30er günstig abzufischen sein.

Ich überlege ja selbst meine 3060ti gegen eine 4090 zu tauschen (man gönnt sich ja sonst nix ),

aber dann gehts wieder los mit neuem NT wegen den HPW Anschlüssen usw.

Im SVP Thread hat auch ein Nutzer gesagt das in Zusammenspiel mit SVP der Speicher schnell die Limitierung

wird, dort wurde dann direkt DDR5 als sinnvoll erachtet.

Wenn man sich dann auf DDR6 RAM vorbereitet (geplant 2024)....