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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,25 @@ | ||
| .PHONY: parler-tts | ||
| parler-tts: protogen | ||
| $(MAKE) -C ../common-env/transformers | ||
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| .PHONY: run | ||
| run: protogen | ||
| @echo "Running transformers..." | ||
| bash run.sh | ||
| @echo "transformers run." | ||
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| .PHONY: test | ||
| test: protogen | ||
| @echo "Testing transformers..." | ||
| bash test.sh | ||
| @echo "transformers tested." | ||
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| .PHONY: protogen | ||
| protogen: backend_pb2_grpc.py backend_pb2.py | ||
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| .PHONY: protogen-clean | ||
| protogen-clean: | ||
| $(RM) backend_pb2_grpc.py backend_pb2.py | ||
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| backend_pb2_grpc.py backend_pb2.py: | ||
| python3 -m grpc_tools.protoc -I../.. --python_out=. --grpc_python_out=. backend.proto |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,125 @@ | ||
| #!/usr/bin/env python3 | ||
| """ | ||
| Extra gRPC server for MusicgenForConditionalGeneration models. | ||
| """ | ||
| from concurrent import futures | ||
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||
| import argparse | ||
| import signal | ||
| import sys | ||
| import os | ||
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||
| import time | ||
| import backend_pb2 | ||
| import backend_pb2_grpc | ||
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| import grpc | ||
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| from scipy.io.wavfile import write as write_wav | ||
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| from parler_tts import ParlerTTSForConditionalGeneration | ||
| from transformers import AutoTokenizer | ||
| import soundfile as sf | ||
| import torch | ||
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| _ONE_DAY_IN_SECONDS = 60 * 60 * 24 | ||
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| # If MAX_WORKERS are specified in the environment use it, otherwise default to 1 | ||
| MAX_WORKERS = int(os.environ.get('PYTHON_GRPC_MAX_WORKERS', '1')) | ||
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| # Implement the BackendServicer class with the service methods | ||
| class BackendServicer(backend_pb2_grpc.BackendServicer): | ||
| """ | ||
| A gRPC servicer for the backend service. | ||
| This class implements the gRPC methods for the backend service, including Health, LoadModel, and Embedding. | ||
| """ | ||
| def Health(self, request, context): | ||
| """ | ||
| A gRPC method that returns the health status of the backend service. | ||
| Args: | ||
| request: A HealthRequest object that contains the request parameters. | ||
| context: A grpc.ServicerContext object that provides information about the RPC. | ||
| Returns: | ||
| A Reply object that contains the health status of the backend service. | ||
| """ | ||
| return backend_pb2.Reply(message=bytes("OK", 'utf-8')) | ||
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| def LoadModel(self, request, context): | ||
| """ | ||
| A gRPC method that loads a model into memory. | ||
| Args: | ||
| request: A LoadModelRequest object that contains the request parameters. | ||
| context: A grpc.ServicerContext object that provides information about the RPC. | ||
| Returns: | ||
| A Result object that contains the result of the LoadModel operation. | ||
| """ | ||
| model_name = request.Model | ||
| device = "cuda:0" if torch.cuda.is_available() else "cpu" | ||
| try: | ||
| self.model = ParlerTTSForConditionalGeneration.from_pretrained(model_name).to(device) | ||
| self.tokenizer = AutoTokenizer.from_pretrained(model_name) | ||
| except Exception as err: | ||
| return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}") | ||
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| return backend_pb2.Result(message="Model loaded successfully", success=True) | ||
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| def TTS(self, request, context): | ||
| model_name = request.model | ||
| voice = request.voice | ||
| if voice == "": | ||
| voice = "A female speaker with a slightly low-pitched voice delivers her words quite expressively, in a very confined sounding environment with clear audio quality. She speaks very fast." | ||
| if model_name == "": | ||
| return backend_pb2.Result(success=False, message="request.model is required") | ||
| try: | ||
| device = "cuda:0" if torch.cuda.is_available() else "cpu" | ||
| input_ids = self.tokenizer(voice, return_tensors="pt").input_ids.to(device) | ||
| prompt_input_ids = self.tokenizer(request.text, return_tensors="pt").input_ids.to(device) | ||
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| generation = self.model.generate(input_ids=input_ids, prompt_input_ids=prompt_input_ids) | ||
| audio_arr = generation.cpu().numpy().squeeze() | ||
| print("[parler-tts] TTS generated!", file=sys.stderr) | ||
| sf.write(request.dst, audio_arr, self.model.config.sampling_rate) | ||
| print("[parler-tts] TTS saved to", request.dst, file=sys.stderr) | ||
| print("[parler-tts] TTS for", file=sys.stderr) | ||
| print(request, file=sys.stderr) | ||
| except Exception as err: | ||
| return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}") | ||
| return backend_pb2.Result(success=True) | ||
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| def serve(address): | ||
| server = grpc.server(futures.ThreadPoolExecutor(max_workers=MAX_WORKERS)) | ||
| backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server) | ||
| server.add_insecure_port(address) | ||
| server.start() | ||
| print("[parler-tts] Server started. Listening on: " + address, file=sys.stderr) | ||
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| # Define the signal handler function | ||
| def signal_handler(sig, frame): | ||
| print("[parler-tts] Received termination signal. Shutting down...") | ||
| server.stop(0) | ||
| sys.exit(0) | ||
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| # Set the signal handlers for SIGINT and SIGTERM | ||
| signal.signal(signal.SIGINT, signal_handler) | ||
| signal.signal(signal.SIGTERM, signal_handler) | ||
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| try: | ||
| while True: | ||
| time.sleep(_ONE_DAY_IN_SECONDS) | ||
| except KeyboardInterrupt: | ||
| server.stop(0) | ||
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| if __name__ == "__main__": | ||
| parser = argparse.ArgumentParser(description="Run the gRPC server.") | ||
| parser.add_argument( | ||
| "--addr", default="localhost:50051", help="The address to bind the server to." | ||
| ) | ||
| args = parser.parse_args() | ||
| print(f"[parler-tts] startup: {args}", file=sys.stderr) | ||
| serve(args.addr) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,16 @@ | ||
| #!/bin/bash | ||
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| ## | ||
| ## A bash script wrapper that runs the parler-tts server with conda | ||
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| echo "Launching gRPC server for parler-tts" | ||
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| export PATH=$PATH:/opt/conda/bin | ||
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| # Activate conda environment | ||
| source activate transformers | ||
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| # get the directory where the bash script is located | ||
| DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )" | ||
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| python $DIR/parler_tts_server.py $@ |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,11 @@ | ||
| #!/bin/bash | ||
| ## | ||
| ## A bash script wrapper that runs the transformers server with conda | ||
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| # Activate conda environment | ||
| source activate transformers | ||
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| # get the directory where the bash script is located | ||
| DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )" | ||
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| python -m unittest $DIR/test_parler.py |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,81 @@ | ||
| """ | ||
| A test script to test the gRPC service | ||
| """ | ||
| import unittest | ||
| import subprocess | ||
| import time | ||
| import backend_pb2 | ||
| import backend_pb2_grpc | ||
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| import grpc | ||
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| class TestBackendServicer(unittest.TestCase): | ||
| """ | ||
| TestBackendServicer is the class that tests the gRPC service | ||
| """ | ||
| def setUp(self): | ||
| """ | ||
| This method sets up the gRPC service by starting the server | ||
| """ | ||
| self.service = subprocess.Popen(["python3", "parler_tts_server.py", "--addr", "localhost:50051"]) | ||
| time.sleep(10) | ||
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| def tearDown(self) -> None: | ||
| """ | ||
| This method tears down the gRPC service by terminating the server | ||
| """ | ||
| self.service.terminate() | ||
| self.service.wait() | ||
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| def test_server_startup(self): | ||
| """ | ||
| This method tests if the server starts up successfully | ||
| """ | ||
| try: | ||
| self.setUp() | ||
| with grpc.insecure_channel("localhost:50051") as channel: | ||
| stub = backend_pb2_grpc.BackendStub(channel) | ||
| response = stub.Health(backend_pb2.HealthMessage()) | ||
| self.assertEqual(response.message, b'OK') | ||
| except Exception as err: | ||
| print(err) | ||
| self.fail("Server failed to start") | ||
| finally: | ||
| self.tearDown() | ||
|
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| def test_load_model(self): | ||
| """ | ||
| This method tests if the model is loaded successfully | ||
| """ | ||
| try: | ||
| self.setUp() | ||
| with grpc.insecure_channel("localhost:50051") as channel: | ||
| stub = backend_pb2_grpc.BackendStub(channel) | ||
| response = stub.LoadModel(backend_pb2.ModelOptions(Model="parler-tts/parler_tts_mini_v0.1")) | ||
| self.assertTrue(response.success) | ||
| self.assertEqual(response.message, "Model loaded successfully") | ||
| except Exception as err: | ||
| print(err) | ||
| self.fail("LoadModel service failed") | ||
| finally: | ||
| self.tearDown() | ||
|
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| def test_tts(self): | ||
| """ | ||
| This method tests if the embeddings are generated successfully | ||
| """ | ||
| try: | ||
| self.setUp() | ||
| with grpc.insecure_channel("localhost:50051") as channel: | ||
| stub = backend_pb2_grpc.BackendStub(channel) | ||
| response = stub.LoadModel(backend_pb2.ModelOptions(Model="parler-tts/parler_tts_mini_v0.1")) | ||
| self.assertTrue(response.success) | ||
| tts_request = backend_pb2.TTSRequest(text="Hey, how are you doing today?") | ||
| tts_response = stub.TTS(tts_request) | ||
| self.assertIsNotNone(tts_response) | ||
| except Exception as err: | ||
| print(err) | ||
| self.fail("TTS service failed") | ||
| finally: | ||
| self.tearDown() |
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