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update fx notebook (#1297)
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‎notebooks/getting_started_with_fx_path_lower_to_trt.ipynb

+137-46
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@@ -10,14 +10,14 @@
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"bento/extensions/theme/main.css": true
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},
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"kernelspec": {
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"display_name": "accelerators",
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"display_name": "dper3_pytorch (cinder)",
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"language": "python",
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"name": "bento_kernel_accelerators",
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"name": "bento_kernel_dper3_pytorch_cinder",
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"metadata": {
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"kernel_name": "bento_kernel_accelerators",
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"nightly_builds": true,
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"kernel_name": "bento_kernel_dper3_pytorch_cinder",
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"nightly_builds": false,
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"fbpkg_supported": true,
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"cinder_runtime": false,
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"cinder_runtime": true,
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"is_prebuilt": true
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}
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},
@@ -32,10 +32,10 @@
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3"
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},
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"last_server_session_id": "c6f6ab3c-9274-41e7-8592-b1b583442e00",
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"last_kernel_id": "fcbf3a69-76a4-4730-9b41-bcd0b24729ca",
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"last_base_url": "https://devgpu005.ftw6.facebook.com:8093/",
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"last_msg_id": "e28f842c-f32dde25c1b80ef7d423dfee_407",
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"last_server_session_id": "24a1a10c-29aa-4e2b-a11f-2b5108fc1e58",
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"last_kernel_id": "5f014373-151c-4ee8-8939-4daab994d202",
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"last_base_url": "https://devgpu005.ftw6.facebook.com:8091/",
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"last_msg_id": "687e81e8-4414f32c89cd026dd1ea3fd9_139",
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"outputWidgetContext": {}
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},
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"nbformat": 4,
@@ -58,14 +58,14 @@
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{
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"cell_type": "code",
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"metadata": {
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"originalKey": "7909785f-b9b4-41dd-82af-c144b879df39",
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"originalKey": "7db2accc-9fa4-4a1e-8142-d887f2947bcd",
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"showInput": true,
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"customInput": null,
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"collapsed": false,
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"requestMsgId": "7db2accc-9fa4-4a1e-8142-d887f2947bcd",
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"requestMsgId": "b5d8efce-0963-4074-bc9d-e8e1a78fd424",
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"customOutput": null,
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"executionStartTime": 1656395936225,
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"executionStopTime": 1656395937851
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"executionStartTime": 1661189891682,
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"executionStopTime": 1661189891856
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},
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"source": [
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"import typing as t\n",
@@ -74,10 +74,10 @@
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"\n",
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"import torch\n",
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"import torchvision\n",
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"from torch_tensorrt.fx.lower import lower_to_trt\n",
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"from torch_tensorrt.fx.lower import compile\n",
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"from torch_tensorrt.fx.utils import LowerPrecision"
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],
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"execution_count": 4,
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"execution_count": 9,
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"outputs": []
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},
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{
@@ -98,16 +98,16 @@
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{
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"cell_type": "code",
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"metadata": {
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"originalKey": "a4455135-8633-4d2d-bdd3-6435a4a9f4dd",
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"originalKey": "2835fffa-cc50-479a-9080-c4f7002c0726",
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"showInput": true,
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"customInput": null,
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"code_folding": [],
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"hidden_ranges": [],
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"collapsed": false,
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"requestMsgId": "2835fffa-cc50-479a-9080-c4f7002c0726",
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"requestMsgId": "6ea72dbf-dbfe-451e-8613-15f87e34a1a5",
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"customOutput": null,
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"executionStartTime": 1656398717455,
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"executionStopTime": 1656398717662
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"executionStartTime": 1661189260550,
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"executionStopTime": 1661189262039
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},
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"source": [
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"@dataclass\n",
@@ -159,24 +159,39 @@
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" f\"Accuracy: {self.accuracy_res} (rtol={self.conf.accuracy_rtol})\"\n",
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" )"
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],
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"execution_count": 22,
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"outputs": []
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"execution_count": 2,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"I0822 102740.872 _utils_internal.py:179] NCCL_DEBUG env var is set to None\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"I0822 102740.873 _utils_internal.py:188] NCCL_DEBUG is INFO from /etc/nccl.conf\n"
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]
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}
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"originalKey": "3e462cf6-d282-402d-955b-a3ecb400bf0b",
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"showInput": true,
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"showInput": false,
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"customInput": null,
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"code_folding": [],
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"hidden_ranges": []
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},
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"source": [
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"Run FX path lowering and benchmark the given model according to the specified benchmark configuration. Prints the benchmark result for each configuration at the end of the run. `benchmark_torch_function` is the actual function that computes the fixed number of iterations of functions runs.\n",
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"The FX path lowering and TensorRT engine creation is integrated into `low_to_trt()` API which is defined in `fx/lower.py` file.\n",
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"The FX path lowering and TensorRT engine creation is integrated into `compile()` API which is defined in `fx/lower.py` file.\n",
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"It is good to list it out and show the usage of it. It takes in original module, input and lowering setting, run lowering workflow to turn module into a executable TRT engine \n",
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"```\n",
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"def lower_to_trt(\n",
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"def compile(\n",
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" module: nn.Module,\n",
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" input: ,\n",
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" max_batch_size: int = 2048,\n",
@@ -212,22 +227,18 @@
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{
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"cell_type": "code",
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"metadata": {
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"originalKey": "91333212-7f6d-4bde-a248-44d485e83e5e",
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"originalKey": "3002935b-b95a-4a08-a57f-f7a35485af5b",
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"showInput": true,
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"customInput": null,
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"code_folding": [],
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"hidden_ranges": [],
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"collapsed": false,
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"requestMsgId": "3002935b-b95a-4a08-a57f-f7a35485af5b",
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"requestMsgId": "dc73f2d0-427b-4f71-bec1-b118cc5642d0",
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"customOutput": null,
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"executionStartTime": 1656397903207,
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"executionStopTime": 1656397964752
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"executionStartTime": 1661189697773,
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"executionStopTime": 1661189753875
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},
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"source": [
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"test_model = torchvision.models.resnet18(pretrained=True)\n",
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"input = [torch.rand(128, 3, 224, 224)] \n",
229-
"benchmark(test_model, input, 50, 128)\n",
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"\n",
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"def benchmark_torch_function(iters: int, f, *args) -> float:\n",
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" \"\"\"Estimates the average time duration for a single inference call in second\n",
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"\n",
@@ -266,7 +277,7 @@
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" time = benchmark_torch_function(conf.batch_iter, lambda: module(*input))\n",
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" elif not conf.jit:\n",
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" # Run lowering eager mode benchmark\n",
269-
" lowered_module = lower_to_trt(\n",
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" lowered_module = compile(\n",
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" module,\n",
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" input,\n",
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" max_batch_size=conf.batch_size,\n",
@@ -279,6 +290,7 @@
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" result = Result(module=module, input=input, conf=conf, time_sec=time)\n",
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" return result\n",
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"\n",
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"\n",
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"@torch.inference_mode()\n",
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"def benchmark(\n",
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" model,\n",
@@ -315,16 +327,25 @@
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" ),\n",
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" ]\n",
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"\n",
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" results = [\n",
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" run_configuration_benchmark(deepcopy(model), inputs, conf_)\n",
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" for conf_ in configurations\n",
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" ]\n",
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" results = [run_configuration_benchmark(deepcopy(model), inputs, conf_) for conf_ in configurations]\n",
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"\n",
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" for res in results:\n",
324-
" print(res.format())"
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" print(res.format())\n",
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"\n",
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"\n",
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"test_model = torchvision.models.resnet18(pretrained=True)\n",
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"input = [torch.rand(128, 3, 224, 224)]\n",
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"benchmark(test_model, input, 50, 128)"
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],
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"execution_count": 21,
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"execution_count": 8,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"I0822 103458.189 manifold.py:1435] URL manifold://torchvision/tree/models/resnet18-f37072fd.pth was already cached in /home/wwei6/.torch/iopath_cache/manifold_cache/tree/models/resnet18-f37072fd.pth\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stdout",
@@ -339,25 +360,60 @@
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"== End benchmark iterations\n=== Running benchmark for: Configuration(batch_iter=50, batch_size=128, name='TRT FP32 Eager', trt=True, jit=False, fp16=False, accuracy_rtol=0.001) green\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"I0822 103501.297 pass_utils.py:166] == Log pass <function fuse_permute_matmul at 0x7f787a0e08b0> before/after graph to /tmp/tmpe_7p37fq\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"I0822 103501.390 pass_utils.py:166] == Log pass <function fuse_permute_linear at 0x7f787a0e0670> before/after graph to /tmp/tmpg_a347f0\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"I0822 103501.509 lower_pass_manager_builder.py:151] Now lowering submodule _run_on_acc_0\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"I0822 103501.511 lower.py:89] split_name='_run_on_acc_0' self.lower_setting.input_specs=[InputTensorSpec(shape=torch.Size([128, 3, 224, 224]), dtype=torch.float32, device=device(type='cuda', index=0), shape_ranges=[], has_batch_dim=True)]\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"== Log pass <function fuse_permute_matmul at 0x7fbdfcc9f1f0> before/after graph to /tmp/tmpaayayg72\n== Log pass <function fuse_permute_linear at 0x7fbe36555f70> before/after graph to /tmp/tmpdw_pq71j\n\nSupported node types in the model:\nacc_ops.conv2d: ((), {'input': torch.float32, 'weight': torch.float32})\nacc_ops.batch_norm: ((), {'input': torch.float32, 'running_mean': torch.float32, 'running_var': torch.float32, 'weight': torch.float32, 'bias': torch.float32})\nacc_ops.relu: ((), {'input': torch.float32})\nacc_ops.max_pool2d: ((), {'input': torch.float32})\nacc_ops.add: ((), {'input': torch.float32, 'other': torch.float32})\nacc_ops.adaptive_avg_pool2d: ((), {'input': torch.float32})\nacc_ops.flatten: ((), {'input': torch.float32})\nacc_ops.linear: ((), {'input': torch.float32, 'weight': torch.float32, 'bias': torch.float32})\n\nUnsupported node types in the model:\n\nGot 1 acc subgraphs and 0 non-acc subgraphs\n"
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"\nSupported node types in the model:\nacc_ops.conv2d: ((), {'input': torch.float32, 'weight': torch.float32})\nacc_ops.batch_norm: ((), {'input': torch.float32, 'running_mean': torch.float32, 'running_var': torch.float32, 'weight': torch.float32, 'bias': torch.float32})\nacc_ops.relu: ((), {'input': torch.float32})\nacc_ops.max_pool2d: ((), {'input': torch.float32})\nacc_ops.add: ((), {'input': torch.float32, 'other': torch.float32})\nacc_ops.adaptive_avg_pool2d: ((), {'input': torch.float32})\nacc_ops.flatten: ((), {'input': torch.float32})\nacc_ops.linear: ((), {'input': torch.float32, 'weight': torch.float32, 'bias': torch.float32})\n\nUnsupported node types in the model:\n\nGot 1 acc subgraphs and 0 non-acc subgraphs\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"I0627 233146.650 fx2trt.py:190] Run Module elapsed time: 0:00:00.244369\n"
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"I0822 103503.964 fx2trt.py:204] Run Module elapsed time: 0:00:00.435984\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"I0627 233206.570 fx2trt.py:241] Build TRT engine elapsed time: 0:00:19.918630\n"
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"I0822 103520.647 fx2trt.py:258] Build TRT engine elapsed time: 0:00:16.681226\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"I0822 103520.658 lower_pass_manager_builder.py:168] Lowering submodule _run_on_acc_0 elapsed time 0:00:19.147071\n"
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]
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},
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{
@@ -374,25 +430,60 @@
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"== End benchmark iterations\n=== Running benchmark for: Configuration(batch_iter=50, batch_size=128, name='TRT FP16 Eager', trt=True, jit=False, fp16=True, accuracy_rtol=0.01) green\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"I0822 103523.067 pass_utils.py:166] == Log pass <function fuse_permute_matmul at 0x7f787a0e08b0> before/after graph to /tmp/tmpgphlicna\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"I0822 103523.106 pass_utils.py:166] == Log pass <function fuse_permute_linear at 0x7f787a0e0670> before/after graph to /tmp/tmpy9cumddi\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"I0822 103523.173 lower_pass_manager_builder.py:151] Now lowering submodule _run_on_acc_0\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"I0822 103523.174 lower.py:89] split_name='_run_on_acc_0' self.lower_setting.input_specs=[InputTensorSpec(shape=torch.Size([128, 3, 224, 224]), dtype=torch.float16, device=device(type='cuda', index=0), shape_ranges=[], has_batch_dim=True)]\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"== Log pass <function fuse_permute_matmul at 0x7fbdfcc9f1f0> before/after graph to /tmp/tmpnoeblgd5\n== Log pass <function fuse_permute_linear at 0x7fbe36555f70> before/after graph to /tmp/tmpyb1egsof\n\nSupported node types in the model:\nacc_ops.conv2d: ((), {'input': torch.float16, 'weight': torch.float16})\nacc_ops.batch_norm: ((), {'input': torch.float16, 'running_mean': torch.float16, 'running_var': torch.float16, 'weight': torch.float16, 'bias': torch.float16})\nacc_ops.relu: ((), {'input': torch.float16})\nacc_ops.max_pool2d: ((), {'input': torch.float16})\nacc_ops.add: ((), {'input': torch.float16, 'other': torch.float16})\nacc_ops.adaptive_avg_pool2d: ((), {'input': torch.float16})\nacc_ops.flatten: ((), {'input': torch.float16})\nacc_ops.linear: ((), {'input': torch.float16, 'weight': torch.float16, 'bias': torch.float16})\n\nUnsupported node types in the model:\n\nGot 1 acc subgraphs and 0 non-acc subgraphs\n"
465+
"\nSupported node types in the model:\nacc_ops.conv2d: ((), {'input': torch.float16, 'weight': torch.float16})\nacc_ops.batch_norm: ((), {'input': torch.float16, 'running_mean': torch.float16, 'running_var': torch.float16, 'weight': torch.float16, 'bias': torch.float16})\nacc_ops.relu: ((), {'input': torch.float16})\nacc_ops.max_pool2d: ((), {'input': torch.float16})\nacc_ops.add: ((), {'input': torch.float16, 'other': torch.float16})\nacc_ops.adaptive_avg_pool2d: ((), {'input': torch.float16})\nacc_ops.flatten: ((), {'input': torch.float16})\nacc_ops.linear: ((), {'input': torch.float16, 'weight': torch.float16, 'bias': torch.float16})\n\nUnsupported node types in the model:\n\nGot 1 acc subgraphs and 0 non-acc subgraphs\n"
466+
]
467+
},
468+
{
469+
"output_type": "stream",
470+
"name": "stderr",
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"text": [
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"I0822 103523.466 fx2trt.py:204] Run Module elapsed time: 0:00:00.288043\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"I0627 233208.996 fx2trt.py:190] Run Module elapsed time: 0:00:00.217076\n"
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"I0822 103553.687 fx2trt.py:258] Build TRT engine elapsed time: 0:00:30.220316\n"
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]
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},
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"I0627 233244.147 fx2trt.py:241] Build TRT engine elapsed time: 0:00:35.150950\n"
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"I0822 103553.698 lower_pass_manager_builder.py:168] Lowering submodule _run_on_acc_0 elapsed time 0:00:30.523791\n"
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]
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},
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{
@@ -406,7 +497,7 @@
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"== End benchmark iterations\n== Benchmark Result for: Configuration(batch_iter=50, batch_size=128, name='CUDA Eager', trt=False, jit=False, fp16=False, accuracy_rtol=-1)\nBS: 128, Time per iter: 15.00ms, QPS: 8530.72, Accuracy: None (rtol=-1)\n== Benchmark Result for: Configuration(batch_iter=50, batch_size=128, name='TRT FP32 Eager', trt=True, jit=False, fp16=False, accuracy_rtol=0.001)\nBS: 128, Time per iter: 7.95ms, QPS: 16098.45, Accuracy: None (rtol=0.001)\n== Benchmark Result for: Configuration(batch_iter=50, batch_size=128, name='TRT FP16 Eager', trt=True, jit=False, fp16=True, accuracy_rtol=0.01)\nBS: 128, Time per iter: 4.36ms, QPS: 29365.31, Accuracy: None (rtol=0.01)\n"
500+
"== End benchmark iterations\n== Benchmark Result for: Configuration(batch_iter=50, batch_size=128, name='CUDA Eager', trt=False, jit=False, fp16=False, accuracy_rtol=-1)\nBS: 128, Time per iter: 14.66ms, QPS: 8732.53, Accuracy: None (rtol=-1)\n== Benchmark Result for: Configuration(batch_iter=50, batch_size=128, name='TRT FP32 Eager', trt=True, jit=False, fp16=False, accuracy_rtol=0.001)\nBS: 128, Time per iter: 7.27ms, QPS: 17595.70, Accuracy: None (rtol=0.001)\n== Benchmark Result for: Configuration(batch_iter=50, batch_size=128, name='TRT FP16 Eager', trt=True, jit=False, fp16=True, accuracy_rtol=0.01)\nBS: 128, Time per iter: 4.49ms, QPS: 28480.34, Accuracy: None (rtol=0.01)\n"
410501
]
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}
412503
]

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