Skip to content

adds a cupy backend section in the transform demo #871

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
wyli merged 2 commits into from
Aug 19, 2022
Merged

adds a cupy backend section in the transform demo #871

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
005278c
add cupy demo
wyli Aug 18, 2022
bc072d5
remove print config
wyli Aug 18, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
145 changes: 118 additions & 27 deletions acceleration/transform_speed.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": null,
"metadata": {
"tags": []
},
Expand Down Expand Up @@ -99,11 +99,19 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 3,
"metadata": {
"tags": []
},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"/tmp/tmpvaqesd_z\n"
]
}
],
"source": [
"directory = os.environ.get(\"MONAI_DATA_DIRECTORY\")\n",
"if directory:\n",
Expand All @@ -124,7 +132,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -140,7 +148,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -167,7 +175,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"torch.Size([3, 1, 256, 256, 256]) torch.Size([3, 1, 256, 256, 256])\n"
"(3, 1, 256, 256, 256) (3, 1, 256, 256, 256)\n"
]
}
],
Expand All @@ -194,8 +202,8 @@
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 23.3 ms, sys: 133 ms, total: 156 ms\n",
"Wall time: 8.6 s\n"
"CPU times: user 26.1 ms, sys: 172 ms, total: 198 ms\n",
"Wall time: 11 s\n"
]
}
],
Expand Down Expand Up @@ -225,7 +233,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"torch.Size([3, 1, 64, 64, 64]) torch.Size([3, 1, 64, 64, 64])\n"
"(3, 1, 64, 64, 64) (3, 1, 64, 64, 64)\n"
]
}
],
Expand Down Expand Up @@ -272,8 +280,8 @@
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 20.4 ms, sys: 1.07 s, total: 1.09 s\n",
"Wall time: 22.6 s\n"
"CPU times: user 37.6 ms, sys: 498 ms, total: 536 ms\n",
"Wall time: 24.6 s\n"
]
}
],
Expand Down Expand Up @@ -310,7 +318,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"torch.Size([3, 1, 64, 64, 64]) torch.Size([3, 1, 64, 64, 64])\n"
"(3, 1, 64, 64, 64) (3, 1, 64, 64, 64)\n"
]
}
],
Expand All @@ -325,7 +333,6 @@
" translate_range=(96, 96, 96),\n",
" spatial_size=(64, 64, 64),\n",
" mode=\"bilinear\",\n",
" as_tensor_output=True,\n",
" device=torch.device(\"cuda:0\"),\n",
")\n",
"rand_affine_seg = RandAffine(\n",
Expand All @@ -334,7 +341,6 @@
" translate_range=(96, 96, 96),\n",
" spatial_size=(64, 64, 64),\n",
" mode=\"nearest\",\n",
" as_tensor_output=True,\n",
" device=torch.device(\"cuda:0\"),\n",
")\n",
"\n",
Expand Down Expand Up @@ -365,8 +371,8 @@
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 3.25 s, sys: 1.06 s, total: 4.31 s\n",
"Wall time: 4.31 s\n"
"CPU times: user 19.4 s, sys: 2.67 s, total: 22 s\n",
"Wall time: 4.83 s\n"
]
}
],
Expand All @@ -385,29 +391,29 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Tesla V100-SXM3-32GB\n",
"Tesla V100-SXM2-16GB-N\n",
"|===========================================================================|\n",
"| PyTorch CUDA memory summary, device ID 0 |\n",
"|---------------------------------------------------------------------------|\n",
"| CUDA OOMs: 0 | cudaMalloc retries: 0 |\n",
"|===========================================================================|\n",
"| Metric | Cur Usage | Peak Usage | Tot Alloc | Tot Freed |\n",
"|---------------------------------------------------------------------------|\n",
"| Allocated memory | 12288 KB | 88064 KB | 1188 MB | 1176 MB |\n",
"| Allocated memory | 16387 KB | 24580 KB | 118883 KB | 102496 KB |\n",
"|---------------------------------------------------------------------------|\n",
"| Active memory | 12288 KB | 88064 KB | 1188 MB | 1176 MB |\n",
"| Active memory | 16387 KB | 24580 KB | 118883 KB | 102496 KB |\n",
"|---------------------------------------------------------------------------|\n",
"| GPU reserved memory | 159744 KB | 159744 KB | 159744 KB | 0 B |\n",
"| GPU reserved memory | 43008 KB | 43008 KB | 43008 KB | 0 B |\n",
"|---------------------------------------------------------------------------|\n",
"| Non-releasable memory | 8192 KB | 77823 KB | 833 MB | 825 MB |\n",
"| Non-releasable memory | 6141 KB | 22527 KB | 274525 KB | 268384 KB |\n",
"|---------------------------------------------------------------------------|\n",
"| Allocations | 4 | 12 | 208 | 204 |\n",
"| Allocations | 8 | 15 | 226 | 218 |\n",
"|---------------------------------------------------------------------------|\n",
"| Active allocs | 4 | 12 | 208 | 204 |\n",
"| Active allocs | 8 | 15 | 226 | 218 |\n",
"|---------------------------------------------------------------------------|\n",
"| GPU reserved segments | 7 | 7 | 7 | 0 |\n",
"| GPU reserved segments | 3 | 3 | 3 | 0 |\n",
"|---------------------------------------------------------------------------|\n",
"| Non-releasable allocs | 1 | 4 | 133 | 132 |\n",
"| Non-releasable allocs | 5 | 7 | 165 | 160 |\n",
"|===========================================================================|\n",
"\n"
]
Expand All @@ -418,6 +424,91 @@
"print(torch.cuda.memory_summary(0, abbreviated=True))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 4. Test image-patch loading with preprocessing on GPU using the Cupy backend:\n",
"\n",
"In the cupy package is installed correctly along with MONAI, \n",
"setting the `mode` to an integer in `[0-5]` and `device` to a cuda device will enable the cupy backend resampling.\n",
"\n",
"- random rotate (256, 256, 256)-voxel in the plane axes=(1, 2)\n",
"- extract random (64, 64, 64) patches\n",
"- implemented in MONAI using the cupy backend for high-order spline interpolation"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(3, 1, 64, 64, 64) (3, 1, 64, 64, 64)\n"
]
}
],
"source": [
"images = sorted(glob.glob(os.path.join(root_dir, \"im*.nii.gz\")))\n",
"segs = sorted(glob.glob(os.path.join(root_dir, \"seg*.nii.gz\")))\n",
"\n",
"# same parameter with different interpolation mode for image and segmentation\n",
"rand_affine_img = RandAffine(\n",
" prob=1.0,\n",
" rotate_range=np.pi / 4,\n",
" translate_range=(96, 96, 96),\n",
" spatial_size=(64, 64, 64),\n",
" mode=3,\n",
" padding_mode=\"reflect\",\n",
" device=torch.device(\"cuda:0\"),\n",
")\n",
"rand_affine_seg = RandAffine(\n",
" prob=1.0,\n",
" rotate_range=np.pi / 4,\n",
" translate_range=(96, 96, 96),\n",
" spatial_size=(64, 64, 64),\n",
" mode=0,\n",
Comment thread
wyli marked this conversation as resolved.
" padding_mode=\"reflect\",\n",
" device=torch.device(\"cuda:0\"),\n",
")\n",
"\n",
"imtrans = Compose(\n",
" [LoadImage(image_only=True), ScaleIntensity(),\n",
" EnsureChannelFirst(), rand_affine_img]\n",
")\n",
"\n",
"segtrans = Compose([LoadImage(image_only=True),\n",
" EnsureChannelFirst(), rand_affine_seg])\n",
"\n",
"ds = ArrayDataset(images, imtrans, segs, segtrans)\n",
"loader = torch.utils.data.DataLoader(ds, batch_size=3, num_workers=0)\n",
"\n",
"im, seg = first(loader)\n",
"\n",
"print(im.shape, seg.shape)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 15.4 s, sys: 3.15 s, total: 18.5 s\n",
"Wall time: 7.7 s\n"
]
}
],
"source": [
"%time data = next(iter(loader))"
]
},
{
"cell_type": "markdown",
"metadata": {},
Expand All @@ -429,7 +520,7 @@
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -454,7 +545,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.13"
"version": "3.8.12"
}
},
"nbformat": 4,
Expand Down