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Feat: new backend: transformers-musicgen (#1387)
Transformers-MusicGen --------- Signed-off-by: Dave <dave@gray101.com>
This commit is contained in:
Dave
GitHub
parent
6011911746
commit
8b6e601405
1
.gitignore
vendored
1
.gitignore
vendored
@ -3,6 +3,7 @@
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__pycache__/
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*.a
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get-sources
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prepare-sources
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/backend/cpp/llama/grpc-server
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/backend/cpp/llama/llama.cpp
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@ -12,7 +12,9 @@ ARG TARGETARCH
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ARG TARGETVARIANT
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ENV BUILD_TYPE=${BUILD_TYPE}
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ENV EXTERNAL_GRPC_BACKENDS="huggingface-embeddings:/build/backend/python/sentencetransformers/run.sh,petals:/build/backend/python/petals/run.sh,transformers:/build/backend/python/transformers/run.sh,sentencetransformers:/build/backend/python/sentencetransformers/run.sh,autogptq:/build/backend/python/autogptq/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,exllama:/build/backend/python/exllama/run.sh,vall-e-x:/build/backend/python/vall-e-x/run.sh,vllm:/build/backend/python/vllm/run.sh,exllama2:/build/backend/python/exllama2/run.sh"
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ENV EXTERNAL_GRPC_BACKENDS="huggingface-embeddings:/build/backend/python/sentencetransformers/run.sh,petals:/build/backend/python/petals/run.sh,transformers:/build/backend/python/transformers/run.sh,sentencetransformers:/build/backend/python/sentencetransformers/run.sh,autogptq:/build/backend/python/autogptq/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,exllama:/build/backend/python/exllama/run.sh,vall-e-x:/build/backend/python/vall-e-x/run.sh,vllm:/build/backend/python/vllm/run.sh,exllama2:/build/backend/python/exllama2/run.sh,transformers-musicgen:/build/backend/python/transformers-musicgen/run.sh"
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ENV GALLERIES='[{"name":"model-gallery", "url":"github:go-skynet/model-gallery/index.yaml"}, {"url": "github:go-skynet/model-gallery/huggingface.yaml","name":"huggingface"}]'
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ARG GO_TAGS="stablediffusion tts"
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@ -187,6 +189,9 @@ RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
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RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
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PATH=$PATH:/opt/conda/bin make -C backend/python/petals \
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; fi
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RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
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PATH=$PATH:/opt/conda/bin make -C backend/python/transformers-musicgen \
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; fi
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# Define the health check command
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HEALTHCHECK --interval=1m --timeout=10m --retries=10 \
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2
Makefile
2
Makefile
@ -389,6 +389,7 @@ protogen-go:
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protogen-python:
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python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/sentencetransformers/ --grpc_python_out=backend/python/sentencetransformers/ backend/backend.proto
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python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/transformers/ --grpc_python_out=backend/python/transformers/ backend/backend.proto
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python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/transformers-musicgen/ --grpc_python_out=backend/python/transformers-musicgen/ backend/backend.proto
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python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/autogptq/ --grpc_python_out=backend/python/autogptq/ backend/backend.proto
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python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/exllama/ --grpc_python_out=backend/python/exllama/ backend/backend.proto
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python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/bark/ --grpc_python_out=backend/python/bark/ backend/backend.proto
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@ -407,6 +408,7 @@ prepare-extra-conda-environments:
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$(MAKE) -C backend/python/vllm
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$(MAKE) -C backend/python/sentencetransformers
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$(MAKE) -C backend/python/transformers
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$(MAKE) -C backend/python/transformers-musicgen
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$(MAKE) -C backend/python/vall-e-x
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$(MAKE) -C backend/python/exllama
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$(MAKE) -C backend/python/petals
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@ -59,9 +59,13 @@ func ModelTTS(backend, text, modelFile string, loader *model.ModelLoader, o *opt
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// If the model file is not empty, we pass it joined with the model path
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modelPath := ""
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if modelFile != "" {
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modelPath = filepath.Join(o.Loader.ModelPath, modelFile)
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if err := utils.VerifyPath(modelPath, o.Loader.ModelPath); err != nil {
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return "", nil, err
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if bb != model.TransformersMusicGen {
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modelPath = filepath.Join(o.Loader.ModelPath, modelFile)
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if err := utils.VerifyPath(modelPath, o.Loader.ModelPath); err != nil {
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return "", nil, err
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}
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} else {
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modelPath = modelFile
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}
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}
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@ -19,7 +19,6 @@ _globals = globals()
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_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
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_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'backend_pb2', _globals)
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if _descriptor._USE_C_DESCRIPTORS == False:
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DESCRIPTOR._options = None
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DESCRIPTOR._serialized_options = b'\n\031io.skynet.localai.backendB\016LocalAIBackendP\001Z+github.com/go-skynet/LocalAI/pkg/grpc/proto'
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_MEMORYUSAGEDATA_BREAKDOWNENTRY._options = None
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@ -19,7 +19,6 @@ _globals = globals()
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_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
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_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'backend_pb2', _globals)
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if _descriptor._USE_C_DESCRIPTORS == False:
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DESCRIPTOR._options = None
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DESCRIPTOR._serialized_options = b'\n\031io.skynet.localai.backendB\016LocalAIBackendP\001Z+github.com/go-skynet/LocalAI/pkg/grpc/proto'
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_MEMORYUSAGEDATA_BREAKDOWNENTRY._options = None
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@ -19,7 +19,6 @@ _globals = globals()
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_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
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_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'backend_pb2', _globals)
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if _descriptor._USE_C_DESCRIPTORS == False:
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DESCRIPTOR._options = None
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DESCRIPTOR._serialized_options = b'\n\031io.skynet.localai.backendB\016LocalAIBackendP\001Z+github.com/go-skynet/LocalAI/pkg/grpc/proto'
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_MEMORYUSAGEDATA_BREAKDOWNENTRY._options = None
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@ -19,7 +19,6 @@ _globals = globals()
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_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
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_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'backend_pb2', _globals)
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if _descriptor._USE_C_DESCRIPTORS == False:
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DESCRIPTOR._options = None
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DESCRIPTOR._serialized_options = b'\n\031io.skynet.localai.backendB\016LocalAIBackendP\001Z+github.com/go-skynet/LocalAI/pkg/grpc/proto'
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_MEMORYUSAGEDATA_BREAKDOWNENTRY._options = None
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@ -19,7 +19,6 @@ _globals = globals()
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_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
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_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'backend_pb2', _globals)
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if _descriptor._USE_C_DESCRIPTORS == False:
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DESCRIPTOR._options = None
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DESCRIPTOR._serialized_options = b'\n\031io.skynet.localai.backendB\016LocalAIBackendP\001Z+github.com/go-skynet/LocalAI/pkg/grpc/proto'
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_MEMORYUSAGEDATA_BREAKDOWNENTRY._options = None
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@ -19,7 +19,6 @@ _globals = globals()
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_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
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_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'backend_pb2', _globals)
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if _descriptor._USE_C_DESCRIPTORS == False:
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DESCRIPTOR._options = None
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DESCRIPTOR._serialized_options = b'\n\031io.skynet.localai.backendB\016LocalAIBackendP\001Z+github.com/go-skynet/LocalAI/pkg/grpc/proto'
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_MEMORYUSAGEDATA_BREAKDOWNENTRY._options = None
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25
backend/python/transformers-musicgen/Makefile
Normal file
25
backend/python/transformers-musicgen/Makefile
Normal file
@ -0,0 +1,25 @@
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TRANSFORMERS_MUSICGEN_CONDA_PATH = "transformers-musicgen.yml"
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ifeq ($(BUILD_TYPE), cublas)
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TRANSFORMERS_MUSICGEN_CONDA_PATH = "transformers-musicgen-nvidia.yml"
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endif
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.PHONY: transformers-musicgen
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transformers-musicgen:
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@echo "Creating virtual environment..."
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@conda env create --name transformers-musicgen --file $(TRANSFORMERS_MUSICGEN_CONDA_PATH)
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@echo "Virtual environment created."
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.PHONY: run
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run:
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@echo "Running transformers..."
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bash run.sh
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@echo "transformers run."
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# It is not working well by using command line. It only6 works with IDE like VSCode.
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.PHONY: test
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test:
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@echo "Testing transformers..."
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bash test.sh
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@echo "transformers tested."
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5
backend/python/transformers-musicgen/README.md
Normal file
5
backend/python/transformers-musicgen/README.md
Normal file
@ -0,0 +1,5 @@
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# Creating a separate environment for the transformers project
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```
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make transformers-musicgen
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```
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60
backend/python/transformers-musicgen/backend_pb2.py
Normal file
60
backend/python/transformers-musicgen/backend_pb2.py
Normal file
File diff suppressed because one or more lines are too long
363
backend/python/transformers-musicgen/backend_pb2_grpc.py
Normal file
363
backend/python/transformers-musicgen/backend_pb2_grpc.py
Normal file
@ -0,0 +1,363 @@
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# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
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"""Client and server classes corresponding to protobuf-defined services."""
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import grpc
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import backend_pb2 as backend__pb2
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class BackendStub(object):
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"""Missing associated documentation comment in .proto file."""
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def __init__(self, channel):
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"""Constructor.
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Args:
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channel: A grpc.Channel.
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"""
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self.Health = channel.unary_unary(
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'/backend.Backend/Health',
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request_serializer=backend__pb2.HealthMessage.SerializeToString,
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response_deserializer=backend__pb2.Reply.FromString,
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)
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self.Predict = channel.unary_unary(
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'/backend.Backend/Predict',
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request_serializer=backend__pb2.PredictOptions.SerializeToString,
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response_deserializer=backend__pb2.Reply.FromString,
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)
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self.LoadModel = channel.unary_unary(
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'/backend.Backend/LoadModel',
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request_serializer=backend__pb2.ModelOptions.SerializeToString,
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response_deserializer=backend__pb2.Result.FromString,
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)
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self.PredictStream = channel.unary_stream(
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'/backend.Backend/PredictStream',
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request_serializer=backend__pb2.PredictOptions.SerializeToString,
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response_deserializer=backend__pb2.Reply.FromString,
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)
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self.Embedding = channel.unary_unary(
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'/backend.Backend/Embedding',
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request_serializer=backend__pb2.PredictOptions.SerializeToString,
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response_deserializer=backend__pb2.EmbeddingResult.FromString,
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)
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self.GenerateImage = channel.unary_unary(
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'/backend.Backend/GenerateImage',
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request_serializer=backend__pb2.GenerateImageRequest.SerializeToString,
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response_deserializer=backend__pb2.Result.FromString,
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)
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self.AudioTranscription = channel.unary_unary(
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'/backend.Backend/AudioTranscription',
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request_serializer=backend__pb2.TranscriptRequest.SerializeToString,
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response_deserializer=backend__pb2.TranscriptResult.FromString,
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)
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self.TTS = channel.unary_unary(
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'/backend.Backend/TTS',
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request_serializer=backend__pb2.TTSRequest.SerializeToString,
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response_deserializer=backend__pb2.Result.FromString,
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)
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self.TokenizeString = channel.unary_unary(
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'/backend.Backend/TokenizeString',
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request_serializer=backend__pb2.PredictOptions.SerializeToString,
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response_deserializer=backend__pb2.TokenizationResponse.FromString,
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)
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self.Status = channel.unary_unary(
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'/backend.Backend/Status',
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request_serializer=backend__pb2.HealthMessage.SerializeToString,
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response_deserializer=backend__pb2.StatusResponse.FromString,
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)
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class BackendServicer(object):
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"""Missing associated documentation comment in .proto file."""
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def Health(self, request, context):
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"""Missing associated documentation comment in .proto file."""
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context.set_code(grpc.StatusCode.UNIMPLEMENTED)
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context.set_details('Method not implemented!')
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raise NotImplementedError('Method not implemented!')
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def Predict(self, request, context):
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"""Missing associated documentation comment in .proto file."""
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context.set_code(grpc.StatusCode.UNIMPLEMENTED)
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context.set_details('Method not implemented!')
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raise NotImplementedError('Method not implemented!')
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def LoadModel(self, request, context):
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"""Missing associated documentation comment in .proto file."""
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context.set_code(grpc.StatusCode.UNIMPLEMENTED)
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context.set_details('Method not implemented!')
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raise NotImplementedError('Method not implemented!')
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def PredictStream(self, request, context):
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"""Missing associated documentation comment in .proto file."""
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context.set_code(grpc.StatusCode.UNIMPLEMENTED)
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context.set_details('Method not implemented!')
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raise NotImplementedError('Method not implemented!')
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def Embedding(self, request, context):
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"""Missing associated documentation comment in .proto file."""
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context.set_code(grpc.StatusCode.UNIMPLEMENTED)
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context.set_details('Method not implemented!')
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raise NotImplementedError('Method not implemented!')
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def GenerateImage(self, request, context):
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"""Missing associated documentation comment in .proto file."""
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context.set_code(grpc.StatusCode.UNIMPLEMENTED)
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context.set_details('Method not implemented!')
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raise NotImplementedError('Method not implemented!')
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def AudioTranscription(self, request, context):
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"""Missing associated documentation comment in .proto file."""
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context.set_code(grpc.StatusCode.UNIMPLEMENTED)
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context.set_details('Method not implemented!')
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raise NotImplementedError('Method not implemented!')
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|
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def TTS(self, request, context):
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"""Missing associated documentation comment in .proto file."""
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context.set_code(grpc.StatusCode.UNIMPLEMENTED)
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context.set_details('Method not implemented!')
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raise NotImplementedError('Method not implemented!')
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|
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def TokenizeString(self, request, context):
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"""Missing associated documentation comment in .proto file."""
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context.set_code(grpc.StatusCode.UNIMPLEMENTED)
|
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context.set_details('Method not implemented!')
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raise NotImplementedError('Method not implemented!')
|
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|
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def Status(self, request, context):
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"""Missing associated documentation comment in .proto file."""
|
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context.set_code(grpc.StatusCode.UNIMPLEMENTED)
|
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context.set_details('Method not implemented!')
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raise NotImplementedError('Method not implemented!')
|
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|
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|
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def add_BackendServicer_to_server(servicer, server):
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rpc_method_handlers = {
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'Health': grpc.unary_unary_rpc_method_handler(
|
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servicer.Health,
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request_deserializer=backend__pb2.HealthMessage.FromString,
|
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response_serializer=backend__pb2.Reply.SerializeToString,
|
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),
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'Predict': grpc.unary_unary_rpc_method_handler(
|
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servicer.Predict,
|
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request_deserializer=backend__pb2.PredictOptions.FromString,
|
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response_serializer=backend__pb2.Reply.SerializeToString,
|
||||
),
|
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'LoadModel': grpc.unary_unary_rpc_method_handler(
|
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servicer.LoadModel,
|
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request_deserializer=backend__pb2.ModelOptions.FromString,
|
||||
response_serializer=backend__pb2.Result.SerializeToString,
|
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),
|
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'PredictStream': grpc.unary_stream_rpc_method_handler(
|
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servicer.PredictStream,
|
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request_deserializer=backend__pb2.PredictOptions.FromString,
|
||||
response_serializer=backend__pb2.Reply.SerializeToString,
|
||||
),
|
||||
'Embedding': grpc.unary_unary_rpc_method_handler(
|
||||
servicer.Embedding,
|
||||
request_deserializer=backend__pb2.PredictOptions.FromString,
|
||||
response_serializer=backend__pb2.EmbeddingResult.SerializeToString,
|
||||
),
|
||||
'GenerateImage': grpc.unary_unary_rpc_method_handler(
|
||||
servicer.GenerateImage,
|
||||
request_deserializer=backend__pb2.GenerateImageRequest.FromString,
|
||||
response_serializer=backend__pb2.Result.SerializeToString,
|
||||
),
|
||||
'AudioTranscription': grpc.unary_unary_rpc_method_handler(
|
||||
servicer.AudioTranscription,
|
||||
request_deserializer=backend__pb2.TranscriptRequest.FromString,
|
||||
response_serializer=backend__pb2.TranscriptResult.SerializeToString,
|
||||
),
|
||||
'TTS': grpc.unary_unary_rpc_method_handler(
|
||||
servicer.TTS,
|
||||
request_deserializer=backend__pb2.TTSRequest.FromString,
|
||||
response_serializer=backend__pb2.Result.SerializeToString,
|
||||
),
|
||||
'TokenizeString': grpc.unary_unary_rpc_method_handler(
|
||||
servicer.TokenizeString,
|
||||
request_deserializer=backend__pb2.PredictOptions.FromString,
|
||||
response_serializer=backend__pb2.TokenizationResponse.SerializeToString,
|
||||
),
|
||||
'Status': grpc.unary_unary_rpc_method_handler(
|
||||
servicer.Status,
|
||||
request_deserializer=backend__pb2.HealthMessage.FromString,
|
||||
response_serializer=backend__pb2.StatusResponse.SerializeToString,
|
||||
),
|
||||
}
|
||||
generic_handler = grpc.method_handlers_generic_handler(
|
||||
'backend.Backend', rpc_method_handlers)
|
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server.add_generic_rpc_handlers((generic_handler,))
|
||||
|
||||
|
||||
# This class is part of an EXPERIMENTAL API.
|
||||
class Backend(object):
|
||||
"""Missing associated documentation comment in .proto file."""
|
||||
|
||||
@staticmethod
|
||||
def Health(request,
|
||||
target,
|
||||
options=(),
|
||||
channel_credentials=None,
|
||||
call_credentials=None,
|
||||
insecure=False,
|
||||
compression=None,
|
||||
wait_for_ready=None,
|
||||
timeout=None,
|
||||
metadata=None):
|
||||
return grpc.experimental.unary_unary(request, target, '/backend.Backend/Health',
|
||||
backend__pb2.HealthMessage.SerializeToString,
|
||||
backend__pb2.Reply.FromString,
|
||||
options, channel_credentials,
|
||||
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
|
||||
|
||||
@staticmethod
|
||||
def Predict(request,
|
||||
target,
|
||||
options=(),
|
||||
channel_credentials=None,
|
||||
call_credentials=None,
|
||||
insecure=False,
|
||||
compression=None,
|
||||
wait_for_ready=None,
|
||||
timeout=None,
|
||||
metadata=None):
|
||||
return grpc.experimental.unary_unary(request, target, '/backend.Backend/Predict',
|
||||
backend__pb2.PredictOptions.SerializeToString,
|
||||
backend__pb2.Reply.FromString,
|
||||
options, channel_credentials,
|
||||
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
|
||||
|
||||
@staticmethod
|
||||
def LoadModel(request,
|
||||
target,
|
||||
options=(),
|
||||
channel_credentials=None,
|
||||
call_credentials=None,
|
||||
insecure=False,
|
||||
compression=None,
|
||||
wait_for_ready=None,
|
||||
timeout=None,
|
||||
metadata=None):
|
||||
return grpc.experimental.unary_unary(request, target, '/backend.Backend/LoadModel',
|
||||
backend__pb2.ModelOptions.SerializeToString,
|
||||
backend__pb2.Result.FromString,
|
||||
options, channel_credentials,
|
||||
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
|
||||
|
||||
@staticmethod
|
||||
def PredictStream(request,
|
||||
target,
|
||||
options=(),
|
||||
channel_credentials=None,
|
||||
call_credentials=None,
|
||||
insecure=False,
|
||||
compression=None,
|
||||
wait_for_ready=None,
|
||||
timeout=None,
|
||||
metadata=None):
|
||||
return grpc.experimental.unary_stream(request, target, '/backend.Backend/PredictStream',
|
||||
backend__pb2.PredictOptions.SerializeToString,
|
||||
backend__pb2.Reply.FromString,
|
||||
options, channel_credentials,
|
||||
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
|
||||
|
||||
@staticmethod
|
||||
def Embedding(request,
|
||||
target,
|
||||
options=(),
|
||||
channel_credentials=None,
|
||||
call_credentials=None,
|
||||
insecure=False,
|
||||
compression=None,
|
||||
wait_for_ready=None,
|
||||
timeout=None,
|
||||
metadata=None):
|
||||
return grpc.experimental.unary_unary(request, target, '/backend.Backend/Embedding',
|
||||
backend__pb2.PredictOptions.SerializeToString,
|
||||
backend__pb2.EmbeddingResult.FromString,
|
||||
options, channel_credentials,
|
||||
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
|
||||
|
||||
@staticmethod
|
||||
def GenerateImage(request,
|
||||
target,
|
||||
options=(),
|
||||
channel_credentials=None,
|
||||
call_credentials=None,
|
||||
insecure=False,
|
||||
compression=None,
|
||||
wait_for_ready=None,
|
||||
timeout=None,
|
||||
metadata=None):
|
||||
return grpc.experimental.unary_unary(request, target, '/backend.Backend/GenerateImage',
|
||||
backend__pb2.GenerateImageRequest.SerializeToString,
|
||||
backend__pb2.Result.FromString,
|
||||
options, channel_credentials,
|
||||
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
|
||||
|
||||
@staticmethod
|
||||
def AudioTranscription(request,
|
||||
target,
|
||||
options=(),
|
||||
channel_credentials=None,
|
||||
call_credentials=None,
|
||||
insecure=False,
|
||||
compression=None,
|
||||
wait_for_ready=None,
|
||||
timeout=None,
|
||||
metadata=None):
|
||||
return grpc.experimental.unary_unary(request, target, '/backend.Backend/AudioTranscription',
|
||||
backend__pb2.TranscriptRequest.SerializeToString,
|
||||
backend__pb2.TranscriptResult.FromString,
|
||||
options, channel_credentials,
|
||||
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
|
||||
|
||||
@staticmethod
|
||||
def TTS(request,
|
||||
target,
|
||||
options=(),
|
||||
channel_credentials=None,
|
||||
call_credentials=None,
|
||||
insecure=False,
|
||||
compression=None,
|
||||
wait_for_ready=None,
|
||||
timeout=None,
|
||||
metadata=None):
|
||||
return grpc.experimental.unary_unary(request, target, '/backend.Backend/TTS',
|
||||
backend__pb2.TTSRequest.SerializeToString,
|
||||
backend__pb2.Result.FromString,
|
||||
options, channel_credentials,
|
||||
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
|
||||
|
||||
@staticmethod
|
||||
def TokenizeString(request,
|
||||
target,
|
||||
options=(),
|
||||
channel_credentials=None,
|
||||
call_credentials=None,
|
||||
insecure=False,
|
||||
compression=None,
|
||||
wait_for_ready=None,
|
||||
timeout=None,
|
||||
metadata=None):
|
||||
return grpc.experimental.unary_unary(request, target, '/backend.Backend/TokenizeString',
|
||||
backend__pb2.PredictOptions.SerializeToString,
|
||||
backend__pb2.TokenizationResponse.FromString,
|
||||
options, channel_credentials,
|
||||
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
|
||||
|
||||
@staticmethod
|
||||
def Status(request,
|
||||
target,
|
||||
options=(),
|
||||
channel_credentials=None,
|
||||
call_credentials=None,
|
||||
insecure=False,
|
||||
compression=None,
|
||||
wait_for_ready=None,
|
||||
timeout=None,
|
||||
metadata=None):
|
||||
return grpc.experimental.unary_unary(request, target, '/backend.Backend/Status',
|
||||
backend__pb2.HealthMessage.SerializeToString,
|
||||
backend__pb2.StatusResponse.FromString,
|
||||
options, channel_credentials,
|
||||
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
|
||||
16
backend/python/transformers-musicgen/run.sh
Normal file
16
backend/python/transformers-musicgen/run.sh
Normal file
@ -0,0 +1,16 @@
|
||||
#!/bin/bash
|
||||
|
||||
##
|
||||
## A bash script wrapper that runs the transformers-musicgen server with conda
|
||||
|
||||
echo "Launching gRPC server for transformers-musicgen"
|
||||
|
||||
|
||||
# Activate conda environment
|
||||
source $CONDA_PREFIX/etc/profile.d/conda.sh
|
||||
conda activate transformers-musicgen
|
||||
|
||||
# get the directory where the bash script is located
|
||||
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
|
||||
|
||||
python $DIR/transformers_server.py $@
|
||||
11
backend/python/transformers-musicgen/test.sh
Normal file
11
backend/python/transformers-musicgen/test.sh
Normal file
@ -0,0 +1,11 @@
|
||||
#!/bin/bash
|
||||
##
|
||||
## A bash script wrapper that runs the transformers server with conda
|
||||
|
||||
# Activate conda environment
|
||||
source conda activate transformers-musicgen
|
||||
|
||||
# get the directory where the bash script is located
|
||||
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
|
||||
|
||||
python -m unittest $DIR/test_transformers_server.py
|
||||
81
backend/python/transformers-musicgen/test_transformers.py
Normal file
81
backend/python/transformers-musicgen/test_transformers.py
Normal file
@ -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
|
||||
|
||||
import grpc
|
||||
|
||||
|
||||
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", "transformers_server.py", "--addr", "localhost:50051"])
|
||||
|
||||
def tearDown(self) -> None:
|
||||
"""
|
||||
This method tears down the gRPC service by terminating the server
|
||||
"""
|
||||
self.service.terminate()
|
||||
self.service.wait()
|
||||
|
||||
def test_server_startup(self):
|
||||
"""
|
||||
This method tests if the server starts up successfully
|
||||
"""
|
||||
time.sleep(2)
|
||||
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()
|
||||
|
||||
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="facebook/musicgen-small"))
|
||||
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()
|
||||
|
||||
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="facebook/musicgen-small"))
|
||||
self.assertTrue(response.success)
|
||||
tts_request = backend_pb2.TTSRequest(Model="facebook/musicgen-small", Input="80s TV news production music hit for tonight's biggest story")
|
||||
tts_response = stub.TTS(tts_request)
|
||||
self.assertIsNotNone(tts_response)
|
||||
except Exception as err:
|
||||
print(err)
|
||||
self.fail("TTS service failed")
|
||||
finally:
|
||||
self.tearDown()
|
||||
@ -0,0 +1,71 @@
|
||||
name: transformers-musicgen
|
||||
channels:
|
||||
- defaults
|
||||
dependencies:
|
||||
- bzip2=1.0.8
|
||||
- ca-certificates=2023.08.22
|
||||
- libffi=3.4.4
|
||||
- libuuid=1.41.5
|
||||
- ncurses=6.4
|
||||
- openssl=3.0.11
|
||||
- pip=23.2.1
|
||||
- python=3.11.5
|
||||
- readline=8.2
|
||||
- setuptools=68.0.0
|
||||
- sqlite=3.41.2
|
||||
- tk=8.6.12
|
||||
- tzdata=2023c
|
||||
- wheel=0.41.2
|
||||
- xz=5.4.2
|
||||
- zlib=1.2.13
|
||||
- pip:
|
||||
- certifi==2023.7.22
|
||||
- charset-normalizer==3.3.0
|
||||
- click==8.1.7
|
||||
- filelock==3.12.4
|
||||
- fsspec==2023.9.2
|
||||
- grpcio==1.59.0
|
||||
- huggingface-hub==0.17.3
|
||||
- idna==3.4
|
||||
- install==1.3.5
|
||||
- jinja2==3.1.2
|
||||
- joblib==1.3.2
|
||||
- markupsafe==2.1.3
|
||||
- mpmath==1.3.0
|
||||
- networkx==3.1
|
||||
- nltk==3.8.1
|
||||
- numpy==1.26.0
|
||||
- nvidia-cublas-cu12==12.1.3.1
|
||||
- nvidia-cuda-cupti-cu12==12.1.105
|
||||
- nvidia-cuda-nvrtc-cu12==12.1.105
|
||||
- nvidia-cuda-runtime-cu12==12.1.105
|
||||
- nvidia-cudnn-cu12==8.9.2.26
|
||||
- nvidia-cufft-cu12==11.0.2.54
|
||||
- nvidia-curand-cu12==10.3.2.106
|
||||
- nvidia-cusolver-cu12==11.4.5.107
|
||||
- nvidia-cusparse-cu12==12.1.0.106
|
||||
- nvidia-nccl-cu12==2.18.1
|
||||
- nvidia-nvjitlink-cu12==12.2.140
|
||||
- nvidia-nvtx-cu12==12.1.105
|
||||
- packaging==23.2
|
||||
- pillow==10.0.1
|
||||
- protobuf==4.24.4
|
||||
- pyyaml==6.0.1
|
||||
- regex==2023.10.3
|
||||
- requests==2.31.0
|
||||
- safetensors==0.4.0
|
||||
- scikit-learn==1.3.1
|
||||
- scipy==1.11.3
|
||||
- sentence-transformers==2.2.2
|
||||
- sentencepiece==0.1.99
|
||||
- sympy==1.12
|
||||
- threadpoolctl==3.2.0
|
||||
- tokenizers==0.14.1
|
||||
- torch==2.1.0
|
||||
- torchvision==0.16.0
|
||||
- tqdm==4.66.1
|
||||
- transformers==4.34.0
|
||||
- triton==2.1.0
|
||||
- typing-extensions==4.8.0
|
||||
- urllib3==2.0.6
|
||||
prefix: /opt/conda/envs/transformers-musicgen
|
||||
@ -0,0 +1,58 @@
|
||||
name: transformers-musicgen
|
||||
channels:
|
||||
- defaults
|
||||
dependencies:
|
||||
- bzip2=1.0.8
|
||||
- ca-certificates=2023.08.22
|
||||
- libffi=3.4.4
|
||||
- libuuid=1.41.5
|
||||
- ncurses=6.4
|
||||
- openssl=3.0.11
|
||||
- pip=23.2.1
|
||||
- python=3.11.5
|
||||
- readline=8.2
|
||||
- setuptools=68.0.0
|
||||
- sqlite=3.41.2
|
||||
- tk=8.6.12
|
||||
- tzdata=2023c
|
||||
- wheel=0.41.2
|
||||
- xz=5.4.2
|
||||
- zlib=1.2.13
|
||||
- pip:
|
||||
- certifi==2023.7.22
|
||||
- charset-normalizer==3.3.0
|
||||
- click==8.1.7
|
||||
- filelock==3.12.4
|
||||
- fsspec==2023.9.2
|
||||
- grpcio==1.59.0
|
||||
- huggingface-hub==0.17.3
|
||||
- idna==3.4
|
||||
- install==1.3.5
|
||||
- jinja2==3.1.2
|
||||
- joblib==1.3.2
|
||||
- markupsafe==2.1.3
|
||||
- mpmath==1.3.0
|
||||
- networkx==3.1
|
||||
- nltk==3.8.1
|
||||
- numpy==1.26.0
|
||||
- packaging==23.2
|
||||
- pillow==10.0.1
|
||||
- protobuf==4.24.4
|
||||
- pyyaml==6.0.1
|
||||
- regex==2023.10.3
|
||||
- requests==2.31.0
|
||||
- safetensors==0.4.0
|
||||
- scikit-learn==1.3.1
|
||||
- scipy==1.11.3
|
||||
- sentence-transformers==2.2.2
|
||||
- sentencepiece==0.1.99
|
||||
- sympy==1.12
|
||||
- threadpoolctl==3.2.0
|
||||
- tokenizers==0.14.1
|
||||
- torch==2.1.0
|
||||
- torchvision==0.16.0
|
||||
- tqdm==4.66.1
|
||||
- transformers==4.34.0
|
||||
- typing-extensions==4.8.0
|
||||
- urllib3==2.0.6
|
||||
prefix: /opt/conda/envs/transformers-musicgen
|
||||
122
backend/python/transformers-musicgen/transformers_server.py
Normal file
122
backend/python/transformers-musicgen/transformers_server.py
Normal file
@ -0,0 +1,122 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Extra gRPC server for MusicgenForConditionalGeneration models.
|
||||
"""
|
||||
from concurrent import futures
|
||||
|
||||
import argparse
|
||||
import signal
|
||||
import sys
|
||||
import os
|
||||
|
||||
import time
|
||||
import backend_pb2
|
||||
import backend_pb2_grpc
|
||||
|
||||
import grpc
|
||||
|
||||
from scipy.io.wavfile import write as write_wav
|
||||
from transformers import AutoProcessor, MusicgenForConditionalGeneration
|
||||
|
||||
_ONE_DAY_IN_SECONDS = 60 * 60 * 24
|
||||
|
||||
# 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'))
|
||||
|
||||
# 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'))
|
||||
|
||||
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
|
||||
try:
|
||||
self.processor = AutoProcessor.from_pretrained(model_name)
|
||||
self.model = MusicgenForConditionalGeneration.from_pretrained(model_name)
|
||||
except Exception as err:
|
||||
return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
|
||||
|
||||
return backend_pb2.Result(message="Model loaded successfully", success=True)
|
||||
|
||||
def TTS(self, request, context):
|
||||
model_name = request.model
|
||||
if model_name == "":
|
||||
return backend_pb2.Result(success=False, message="request.model is required")
|
||||
try:
|
||||
self.processor = AutoProcessor.from_pretrained(model_name)
|
||||
self.model = MusicgenForConditionalGeneration.from_pretrained(model_name)
|
||||
inputs = self.processor(
|
||||
text=[request.text],
|
||||
padding=True,
|
||||
return_tensors="pt",
|
||||
)
|
||||
tokens = 256
|
||||
# TODO get tokens from request?
|
||||
audio_values = self.model.generate(**inputs, max_new_tokens=tokens)
|
||||
print("[transformers-musicgen] TTS generated!", file=sys.stderr)
|
||||
sampling_rate = self.model.config.audio_encoder.sampling_rate
|
||||
write_wav(request.dst, rate=sampling_rate, data=audio_values[0, 0].numpy())
|
||||
print("[transformers-musicgen] TTS saved to", request.dst, file=sys.stderr)
|
||||
print("[transformers-musicgen] 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)
|
||||
|
||||
|
||||
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("[transformers-musicgen] Server started. Listening on: " + address, file=sys.stderr)
|
||||
|
||||
# Define the signal handler function
|
||||
def signal_handler(sig, frame):
|
||||
print("[transformers-musicgen] Received termination signal. Shutting down...")
|
||||
server.stop(0)
|
||||
sys.exit(0)
|
||||
|
||||
# Set the signal handlers for SIGINT and SIGTERM
|
||||
signal.signal(signal.SIGINT, signal_handler)
|
||||
signal.signal(signal.SIGTERM, signal_handler)
|
||||
|
||||
try:
|
||||
while True:
|
||||
time.sleep(_ONE_DAY_IN_SECONDS)
|
||||
except KeyboardInterrupt:
|
||||
server.stop(0)
|
||||
|
||||
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"[transformers-musicgen] startup: {args}", file=sys.stderr)
|
||||
serve(args.addr)
|
||||
@ -19,7 +19,6 @@ _globals = globals()
|
||||
_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
|
||||
_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'backend_pb2', _globals)
|
||||
if _descriptor._USE_C_DESCRIPTORS == False:
|
||||
|
||||
DESCRIPTOR._options = None
|
||||
DESCRIPTOR._serialized_options = b'\n\031io.skynet.localai.backendB\016LocalAIBackendP\001Z+github.com/go-skynet/LocalAI/pkg/grpc/proto'
|
||||
_MEMORYUSAGEDATA_BREAKDOWNENTRY._options = None
|
||||
|
||||
@ -19,7 +19,6 @@ _globals = globals()
|
||||
_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
|
||||
_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'backend_pb2', _globals)
|
||||
if _descriptor._USE_C_DESCRIPTORS == False:
|
||||
|
||||
DESCRIPTOR._options = None
|
||||
DESCRIPTOR._serialized_options = b'\n\031io.skynet.localai.backendB\016LocalAIBackendP\001Z+github.com/go-skynet/LocalAI/pkg/grpc/proto'
|
||||
_MEMORYUSAGEDATA_BREAKDOWNENTRY._options = None
|
||||
|
||||
@ -19,7 +19,6 @@ _globals = globals()
|
||||
_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
|
||||
_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'backend_pb2', _globals)
|
||||
if _descriptor._USE_C_DESCRIPTORS == False:
|
||||
|
||||
DESCRIPTOR._options = None
|
||||
DESCRIPTOR._serialized_options = b'\n\031io.skynet.localai.backendB\016LocalAIBackendP\001Z+github.com/go-skynet/LocalAI/pkg/grpc/proto'
|
||||
_MEMORYUSAGEDATA_BREAKDOWNENTRY._options = None
|
||||
|
||||
@ -52,6 +52,20 @@ Note:
|
||||
- The model name is case sensitive.
|
||||
- LocalAI must be compiled with the `GO_TAGS=tts` flag.
|
||||
|
||||
LocalAI also has experimental support for `transformers-musicgen` for the generation of short musical compositions. Currently, this is implemented via the same requests used for text to speech:
|
||||
|
||||
```
|
||||
curl --request POST \
|
||||
--url http://localhost:8080/tts \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data '{
|
||||
"backend": "transformers-musicgen",
|
||||
"model": "facebook/musicgen-medium",
|
||||
"input": "Cello Rave"
|
||||
}' | aplay```
|
||||
|
||||
Future versions of LocalAI will expose additional control over audio generation beyond the text prompt.
|
||||
|
||||
#### Configuration
|
||||
|
||||
Audio models can be configured via `YAML` files. This allows to configure specific setting for each backend. For instance, backends might be specifying a voice or supports voice cloning which must be specified in the configuration file.
|
||||
|
||||
23
examples/bruno/LocalAI Test Requests/tts/musicgen.bru
Normal file
23
examples/bruno/LocalAI Test Requests/tts/musicgen.bru
Normal file
@ -0,0 +1,23 @@
|
||||
meta {
|
||||
name: musicgen
|
||||
type: http
|
||||
seq: 2
|
||||
}
|
||||
|
||||
post {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/tts
|
||||
body: json
|
||||
auth: none
|
||||
}
|
||||
|
||||
headers {
|
||||
Content-Type: application/json
|
||||
}
|
||||
|
||||
body:json {
|
||||
{
|
||||
"backend": "transformers-musicgen",
|
||||
"model": "facebook/musicgen-small",
|
||||
"input": "80s Synths playing Jazz"
|
||||
}
|
||||
}
|
||||
@ -37,6 +37,9 @@ const (
|
||||
StableDiffusionBackend = "stablediffusion"
|
||||
PiperBackend = "piper"
|
||||
LCHuggingFaceBackend = "langchain-huggingface"
|
||||
|
||||
// External Backends that need special handling within LocalAI:
|
||||
TransformersMusicGen = "transformers-musicgen"
|
||||
)
|
||||
|
||||
var AutoLoadBackends []string = []string{
|
||||
|
||||
Loading…
Reference in New Issue
Block a user