Create shape.py

shape.py

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+from shap_e.diffusion.sample import sample_latents
+from shap_e.diffusion.gaussian_diffusion import diffusion_from_config as diffusion_from_config_shape
+from shap_e.models.download import load_model, load_config
+from shap_e.util.notebooks import create_pan_cameras, decode_latent_images, gif_widget
+from shap_e.util.notebooks import decode_latent_mesh
+device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+xm = load_model('transmitter', device=device)
+model = load_model('text300M', device=device)
+# model.load_state_dict(torch.load('./load/shapE_finetuned_with_330kdata.pth', map_location=device)['model_state_dict'])
+diffusion = diffusion_from_config_shape(load_config('diffusion'))