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fix(diffusers): correctly parse height and width request without parametrization (#4082)
* fix(diffusers): allow to specify width and height without enable-parameters Let's simplify usage by not gating width and height by parameters Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore: use sane defaults Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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@ -409,8 +409,6 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
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# create a dictionary of values for the parameters
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# create a dictionary of values for the parameters
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options = {
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options = {
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"negative_prompt": request.negative_prompt,
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"negative_prompt": request.negative_prompt,
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"width": request.width,
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"height": request.height,
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"num_inference_steps": steps,
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"num_inference_steps": steps,
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}
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}
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@ -428,13 +426,13 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
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keys = options.keys()
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keys = options.keys()
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if request.EnableParameters != "":
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if request.EnableParameters != "":
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keys = request.EnableParameters.split(",")
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keys = [key.strip() for key in request.EnableParameters.split(",")]
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if request.EnableParameters == "none":
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if request.EnableParameters == "none":
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keys = []
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keys = []
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# create a dictionary of parameters by using the keys from EnableParameters and the values from defaults
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# create a dictionary of parameters by using the keys from EnableParameters and the values from defaults
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kwargs = {key: options[key] for key in keys}
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kwargs = {key: options.get(key) for key in keys if key in options}
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# Set seed
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# Set seed
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if request.seed > 0:
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if request.seed > 0:
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@ -445,6 +443,12 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
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if self.PipelineType == "FluxPipeline":
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if self.PipelineType == "FluxPipeline":
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kwargs["max_sequence_length"] = 256
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kwargs["max_sequence_length"] = 256
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if request.width:
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kwargs["width"] = request.width
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if request.height:
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kwargs["height"] = request.height
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if self.PipelineType == "FluxTransformer2DModel":
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if self.PipelineType == "FluxTransformer2DModel":
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kwargs["output_type"] = "pil"
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kwargs["output_type"] = "pil"
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kwargs["generator"] = torch.Generator("cpu").manual_seed(0)
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kwargs["generator"] = torch.Generator("cpu").manual_seed(0)
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@ -464,6 +468,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
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export_to_video(video_frames, request.dst)
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export_to_video(video_frames, request.dst)
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return backend_pb2.Result(message="Media generated successfully", success=True)
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return backend_pb2.Result(message="Media generated successfully", success=True)
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print(f"Generating image with {kwargs=}", file=sys.stderr)
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image = {}
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image = {}
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if COMPEL:
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if COMPEL:
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conditioning, pooled = self.compel.build_conditioning_tensor(prompt)
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conditioning, pooled = self.compel.build_conditioning_tensor(prompt)
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@ -136,6 +136,11 @@ func ImageEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appCon
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config.Backend = model.StableDiffusionBackend
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config.Backend = model.StableDiffusionBackend
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}
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}
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if !strings.Contains(input.Size, "x") {
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input.Size = "512x512"
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log.Warn().Msgf("Invalid size, using default 512x512")
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}
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sizeParts := strings.Split(input.Size, "x")
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sizeParts := strings.Split(input.Size, "x")
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if len(sizeParts) != 2 {
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if len(sizeParts) != 2 {
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return fmt.Errorf("invalid value for 'size'")
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return fmt.Errorf("invalid value for 'size'")
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