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APPLE: Enabling Shap-E to run on Apple Silicon GPUs via Metal Performance Shaders (MPS) Acceleration #159

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APPLE: Enabling Shap-E to run on Apple Silicon GPUs via Metal Performance Shaders (MPS) Acceleration #159

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12 changes: 11 additions & 1 deletion shap_e/diffusion/gaussian_diffusion.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1057,6 +1057,7 @@ def __call__(self, x, ts, **kwargs):

def _extract_into_tensor(arr, timesteps, broadcast_shape):
"""
UPDATED to include PyTorch MPS compatibility for Apple Silicon.
Extract values from a 1-D numpy array for a batch of indices.

:param arr: the 1-D numpy array.
Expand All @@ -1065,7 +1066,16 @@ def _extract_into_tensor(arr, timesteps, broadcast_shape):
dimension equal to the length of timesteps.
:return: a tensor of shape [batch_size, 1, ...] where the shape has K dims.
"""
res = th.from_numpy(arr).to(device=timesteps.device)[timesteps].float()
res = None
is_mps = hasattr(timesteps, "device") and timesteps.device.type == "mps"

if is_mps:
# Create the tensor on the CPU and perform indexing there
cpu_tensor = th.from_numpy(arr.copy().astype(np.float32))[timesteps.cpu()].clone().contiguous().float()
# Then transfer the result to the target device (e.g., MPS)
res = cpu_tensor.to(device=timesteps.device)
else:
res = th.from_numpy(arr).to(device=timesteps.device)[timesteps].float()
while len(res.shape) < len(broadcast_shape):
res = res[..., None]
return res + th.zeros(broadcast_shape, device=timesteps.device)
Expand Down
19 changes: 14 additions & 5 deletions shap_e/examples/encode_model.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,8 @@
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"execution_count": null,
"id": "65b721ee",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -15,16 +16,22 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": null,
"id": "3088e7fd",
"metadata": {},
"outputs": [],
"source": [
"device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')"
"device = torch.device(\n",
" 'mps' if torch.backends.mps.is_available()\n",
" else 'cuda' if torch.cuda.is_available()\n",
" else 'cpu'\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "48ecf7fd",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -33,7 +40,8 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": null,
"id": "cc779df5",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -54,6 +62,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "d0a488c0",
"metadata": {},
"outputs": [],
"source": [
Expand Down Expand Up @@ -85,7 +94,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.9"
"version": "3.13.2"
}
},
"nbformat": 4,
Expand Down
16 changes: 14 additions & 2 deletions shap_e/examples/sample_image_to_3d.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,11 @@
"metadata": {},
"outputs": [],
"source": [
"device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')"
"device = torch.device(\n",
" 'mps' if torch.backends.mps.is_available()\n",
" else 'cuda' if torch.cuda.is_available()\n",
" else 'cpu'\n",
")"
]
},
{
Expand Down Expand Up @@ -83,6 +87,14 @@
" images = decode_latent_images(xm, latent, cameras, rendering_mode=render_mode)\n",
" display(gif_widget(images))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7e8ee2b6-3534-4c89-bd88-eb8f24ca1496",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
Expand All @@ -101,7 +113,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.9"
"version": "3.13.2"
}
},
"nbformat": 4,
Expand Down
16 changes: 14 additions & 2 deletions shap_e/examples/sample_text_to_3d.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,11 @@
"metadata": {},
"outputs": [],
"source": [
"device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')"
"device = torch.device(\n",
" 'mps' if torch.backends.mps.is_available()\n",
" else 'cuda' if torch.cuda.is_available()\n",
" else 'cpu'\n",
")"
]
},
{
Expand Down Expand Up @@ -98,6 +102,14 @@
" with open(f'example_mesh_{i}.obj', 'w') as f:\n",
" t.write_obj(f)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1752a20a-e83d-4450-88c9-640b7e25bb7c",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
Expand All @@ -116,7 +128,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
"version": "3.13.2"
}
},
"nbformat": 4,
Expand Down