47 lines
1.3 KiB
Bash
Executable file
47 lines
1.3 KiB
Bash
Executable file
#!/usr/bin/env bash
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: ${WAVEGLOW:="pretrained_models/waveglow/nvidia_waveglow256pyt_fp16.pt"}
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: ${FASTPITCH:="pretrained_models/fastpitch/nvidia_fastpitch_210824.pt"}
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: ${BATCH_SIZE:=32}
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: ${PHRASES:="phrases/devset10.tsv"}
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: ${OUTPUT_DIR:="./output/audio_$(basename ${PHRASES} .tsv)"}
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: ${LOG_FILE:="$OUTPUT_DIR/nvlog_infer.json"}
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: ${AMP:=false}
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: ${TORCHSCRIPT:=false}
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: ${PHONE:=true}
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: ${ENERGY:=true}
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: ${DENOISING:=0.01}
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: ${WARMUP:=0}
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: ${REPEATS:=1}
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: ${CPU:=false}
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: ${SPEAKER:=0}
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: ${NUM_SPEAKERS:=1}
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echo -e "\nAMP=$AMP, batch_size=$BATCH_SIZE\n"
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ARGS=""
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ARGS+=" -i $PHRASES"
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ARGS+=" -o $OUTPUT_DIR"
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ARGS+=" --log-file $LOG_FILE"
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ARGS+=" --fastpitch $FASTPITCH"
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ARGS+=" --waveglow $WAVEGLOW"
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ARGS+=" --wn-channels 256"
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ARGS+=" --batch-size $BATCH_SIZE"
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ARGS+=" --text-cleaners english_cleaners_v2"
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ARGS+=" --denoising-strength $DENOISING"
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ARGS+=" --repeats $REPEATS"
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ARGS+=" --warmup-steps $WARMUP"
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ARGS+=" --speaker $SPEAKER"
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ARGS+=" --n-speakers $NUM_SPEAKERS"
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[ "$CPU" = false ] && ARGS+=" --cuda"
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[ "$CPU" = false ] && ARGS+=" --cudnn-benchmark"
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[ "$AMP" = true ] && ARGS+=" --amp"
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[ "$PHONE" = "true" ] && ARGS+=" --p-arpabet 1.0"
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[ "$ENERGY" = "true" ] && ARGS+=" --energy-conditioning"
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[ "$TORCHSCRIPT" = "true" ] && ARGS+=" --torchscript"
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mkdir -p "$OUTPUT_DIR"
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python inference.py $ARGS "$@"
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