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set_use_memory_efficient_attention_xformers method # gets the message def fn_recursive_set_mem_eff(module: torch.nn.Module): - if hasattr(module, "set_use_memory_efficient_attention_xformers"): - module.set_use_memory_efficient_attention_xformers(valid, attention_op) + #if hasattr(module, "set_use_memory_efficient_attention_xformers"): + # module.set_use_memory_efficient_attention_xformers(valid, attention_op) for child in module.children(): fn_recursive_set_mem_eff(child) diff --git a/3D_Stage/lrm/systems/__pycache__/__init__.cpython-310.pyc b/3D_Stage/lrm/systems/__pycache__/__init__.cpython-310.pyc index cf1919ac3ec290a368a055e64a355edde16ef688..49401dc1367d0627993e20fa143ada8235e26dae 100644 Binary files a/3D_Stage/lrm/systems/__pycache__/__init__.cpython-310.pyc and b/3D_Stage/lrm/systems/__pycache__/__init__.cpython-310.pyc differ diff --git a/3D_Stage/lrm/systems/__pycache__/base.cpython-310.pyc b/3D_Stage/lrm/systems/__pycache__/base.cpython-310.pyc index 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448f37ea4432b9d351dee39f77e82665a4a78cbb..9c17775d071e798cc20ab5f5c74c2adaf6adc9bd 100644 --- a/3D_Stage/lrm/utils/rasterize.py +++ b/3D_Stage/lrm/utils/rasterize.py @@ -7,7 +7,8 @@ from .typing import * class NVDiffRasterizerContext: def __init__(self, context_type: str, device: torch.device) -> None: self.device = device - self.ctx = self.initialize_context(context_type, device) + self.ctx = None + #self.ctx = self.initialize_context(context_type, device) def initialize_context( self, context_type: str, device: torch.device diff --git a/app.py b/app.py index d333c95fe05d9e377a6153863260689357cc55ee..5319f784dbf00157ca32350f715efb83aba57a82 100644 --- a/app.py +++ b/app.py @@ -1,3 +1,5 @@ +import spaces + import gradio as gr from PIL import Image import glob @@ -218,8 +220,9 @@ class Inference2D_API: ) self.validation_pipeline.enable_vae_slicing() self.validation_pipeline.set_progress_bar_config(disable=True) - self.generator = torch.Generator(device=device) + self.generator = torch.Generator() + @spaces.GPU @torch.no_grad() def inference(self, input_image, val_width, val_height, use_shifted_noise=False, crop=False, seed=100, timestep=20): @@ -314,6 +317,7 @@ class Inference3D_API: self.system = lrm.find(self.cfg.system_cls)(self.cfg.system).to(self.device) self.system.eval() + @spaces.GPU def process_images(self, img_input0, img_input1, img_input2, img_input3, back_proj, smooth_iter): meta = json.load(open("./3D_Stage/material/meta.json")) c2w_cond = [np.array(loc["transform_matrix"]) for loc in meta["locations"]] @@ -370,7 +374,7 @@ class Inference3D_API: material.pbrMetallicRoughness.roughnessFactor = 1.0 gltf.save(f'{save_dir}/output.glb') - return save_dir, f"{save_dir}/output.obj", f"{save_dir}/output.glb" + return f"{save_dir}/output.obj", f"{save_dir}/output.glb" @torch.no_grad() def main( @@ -420,11 +424,11 @@ def main( img_input2 = gr.Image(type="pil", label="Right Image", image_mode="RGBA", width=256, height=384) img_input3 = gr.Image(type="pil", label="Left Image", image_mode="RGBA", width=256, height=384) with gr.Column(variant="panel"): - smooth_iter = gr.Slider(minimum=0, maximum=10, step=1, value=5, label="Laplacian Smoothing Iterations") + smooth_iter = gr.Slider(minimum=0, maximum=5, step=1, value=3, label="Laplacian Smoothing Iterations") with gr.Row(): back_proj = gr.Checkbox(label="Back Projection") button2 = gr.Button(value="Generate 3D Mesh") - output_dir = gr.Textbox(label="Output Directory") + # output_dir = gr.Textbox(label="Output Directory") with gr.Row(): with gr.Tab("GLB"): output_model_glb = gr.Model3D( label="Output Model (GLB Format)", height=512) @@ -440,7 +444,7 @@ def main( button2.click( infer3dapi.process_images, inputs=[img_input0, img_input1, img_input2, img_input3, back_proj, smooth_iter], - outputs=[output_dir, output_model_obj, output_model_glb] + outputs=[output_model_obj, output_model_glb] ) demo.launch()