{ "cells": [ { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# pip install tritonclient[http] ipykernel ipywidgets numpy scipy\n", "!mkdir -p ../wavs\n", "import numpy as np\n", "SAMPLING_RATE = 22050\n", "from tritonclient.utils import *\n", "from IPython.display import Audio\n", "from scipy.io.wavfile import write\n", "import tritonclient.http as httpclient\n", "triton_client = httpclient.InferenceServerClient(url=\"localhost:8011\")" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "source_data = np.array([['this']], dtype='object')\n", "inputs = [httpclient.InferInput(\"INPUT_TEXT\", source_data.shape, np_to_triton_dtype(source_data.dtype)), httpclient.InferInput(\"INPUT_SPEAKER_ID\", source_data.shape, np_to_triton_dtype(source_data.dtype)), httpclient.InferInput(\"INPUT_LANGUAGE_ID\", source_data.shape, np_to_triton_dtype(source_data.dtype))]\n", "inputs[0].set_data_from_numpy(np.array([['this is a spartfa!']], dtype='object'))\n", "inputs[1].set_data_from_numpy(np.array([['m']], dtype='object'))\n", "inputs[2].set_data_from_numpy(np.array([['hi']], dtype='object'))\n", "outputs = [httpclient.InferRequestedOutput(\"OUTPUT_GENERATED_AUDIO\")]\n", "result = triton_client.infer(model_name='tts', inputs=inputs, outputs=outputs)\n", "result = np.frombuffer(result.as_numpy('OUTPUT_GENERATED_AUDIO')[0][0], dtype='int16')\n", "write('../wavs/test.wav', SAMPLING_RATE, result)\n", "display(Audio(f\"../wavs/test.wav\"))" ] } ], "metadata": { "kernelspec": { "display_name": "dhruva-iitm-tts", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.6" } }, "nbformat": 4, "nbformat_minor": 2 }