Maxvit_t model lowering segfaults on QNN #14050

Description

@GregoryComer

🐛 Describe the bug

The maxvit_t model in torchvision segfaults on QNN when lowering. It doesn't seem to be a 100% repro, but it's pretty close on my local machine.

Output excerpt (note that the segfault happens several pages of logs in):

...
[INFO] [Qnn ExecuTorch]: Initialize Qnn backend parameters for Qnn executorch backend type 2
[INFO] [Qnn ExecuTorch]: Caching: Caching is in RESTORE MODE.
[INFO] [Qnn ExecuTorch]: QnnContextCustomProtocol expected magic number: 0x5678abcd but get: 0x2000000
[INFO] [Qnn ExecuTorch]: Running level=3 optimization.
Segmentation fault

This can be reproduced with the following test case command or standalone script.

python -m executorch.backends.test.suite.runner models --flow qnn --filter "test_maxvit_t_qnn_float32$"

Standalone repro:

fromtypingimportTupleimportexecutorchimporttorchimporttorchvisionfromexecutorch.backends.qualcomm.utils.utilsimport (
generate_qnn_executorch_compiler_spec,
generate_htp_compiler_spec,
QcomChipset,
to_edge_transform_and_lower_to_qnn,
)
inputs= (torch.randn(1, 3, 224, 224),)
model=torchvision.models.maxvit_t().eval()
ep=torch.export.export(model, inputs)
backend_options=generate_htp_compiler_spec(
use_fp16=True,
)
compile_spec=generate_qnn_executorch_compiler_spec(
soc_model=QcomChipset.SM8650,
backend_options=backend_options,
)
model=to_edge_transform_and_lower_to_qnn(
model,
inputs,
compile_spec
).to_executorch()
print("Running model...")
fromexecutorch.extension.pybindings.portable_libimport_load_for_executorch_from_bufferloaded_model=_load_for_executorch_from_buffer(model.buffer)
loaded_model([*inputs])

Note that running the backend test case requires executorch's python bindings to be built with the QNN backend. An example build command is below, Note that it will still need the library paths to be set up properly as described in the ET QNN docs.

CMAKE_ARGS="-DEXECUTORCH_BUILD_QNN=ON -DQNN_SDK_ROOT=$QNN_SDK_ROOT" ./install_executorch.sh --editable

Versions

Commit fbda3a9, x86-64 simulator, WSL

cc @cccclai@winskuo-quic@shewu-quic@cbilgin

Activity

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    backend testerThis bug was found by the backend test suite.module: qnnIssues related to Qualcomm's QNN delegate and code under backends/qualcomm/partner: qualcommFor backend delegation, kernels, demo, etc. from the 3rd-party partner, Qualcomm

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      , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all \u003cpre\u003e\u003ccode\u003e blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks"); } } catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); } })(); (function(){ try { var __m = "github.com"; var __re = new RegExp('^' + "github\\.com" + '
      Skip to content

      Maxvit_t model lowering segfaults on QNN #14050

      Description

      @GregoryComer

      🐛 Describe the bug

      The maxvit_t model in torchvision segfaults on QNN when lowering. It doesn't seem to be a 100% repro, but it's pretty close on my local machine.

      Output excerpt (note that the segfault happens several pages of logs in):

      ...
      [INFO] [Qnn ExecuTorch]: Initialize Qnn backend parameters for Qnn executorch backend type 2
      [INFO] [Qnn ExecuTorch]: Caching: Caching is in RESTORE MODE.
      [INFO] [Qnn ExecuTorch]: QnnContextCustomProtocol expected magic number: 0x5678abcd but get: 0x2000000
      [INFO] [Qnn ExecuTorch]: Running level=3 optimization.
      Segmentation fault
      

      This can be reproduced with the following test case command or standalone script.

      python -m executorch.backends.test.suite.runner models --flow qnn --filter "test_maxvit_t_qnn_float32$"
      

      Standalone repro:

      fromtypingimportTupleimportexecutorchimporttorchimporttorchvisionfromexecutorch.backends.qualcomm.utils.utilsimport (
      generate_qnn_executorch_compiler_spec,
      generate_htp_compiler_spec,
      QcomChipset,
      to_edge_transform_and_lower_to_qnn,
      )
      inputs= (torch.randn(1, 3, 224, 224),)
      model=torchvision.models.maxvit_t().eval()
      ep=torch.export.export(model, inputs)
      backend_options=generate_htp_compiler_spec(
      use_fp16=True,
      )
      compile_spec=generate_qnn_executorch_compiler_spec(
      soc_model=QcomChipset.SM8650,
      backend_options=backend_options,
      )
      model=to_edge_transform_and_lower_to_qnn(
      model,
      inputs,
      compile_spec
      ).to_executorch()
      print("Running model...")
      fromexecutorch.extension.pybindings.portable_libimport_load_for_executorch_from_bufferloaded_model=_load_for_executorch_from_buffer(model.buffer)
      loaded_model([*inputs])

      Note that running the backend test case requires executorch's python bindings to be built with the QNN backend. An example build command is below, Note that it will still need the library paths to be set up properly as described in the ET QNN docs.

      CMAKE_ARGS="-DEXECUTORCH_BUILD_QNN=ON -DQNN_SDK_ROOT=$QNN_SDK_ROOT" ./install_executorch.sh --editable
      

      Versions

      Commit fbda3a9, x86-64 simulator, WSL

      cc @cccclai@winskuo-quic@shewu-quic@cbilgin

      Activity

      Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

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        Labels

        backend testerThis bug was found by the backend test suite.module: qnnIssues related to Qualcomm's QNN delegate and code under backends/qualcomm/partner: qualcommFor backend delegation, kernels, demo, etc. from the 3rd-party partner, Qualcomm

        Type

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          No milestone

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          None yet

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          No branches or pull requests

          Issue actions

          , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
          Skip to content

          Maxvit_t model lowering segfaults on QNN #14050

          Description

          @GregoryComer

          🐛 Describe the bug

          The maxvit_t model in torchvision segfaults on QNN when lowering. It doesn't seem to be a 100% repro, but it's pretty close on my local machine.

          Output excerpt (note that the segfault happens several pages of logs in):

          ...
          [INFO] [Qnn ExecuTorch]: Initialize Qnn backend parameters for Qnn executorch backend type 2
          [INFO] [Qnn ExecuTorch]: Caching: Caching is in RESTORE MODE.
          [INFO] [Qnn ExecuTorch]: QnnContextCustomProtocol expected magic number: 0x5678abcd but get: 0x2000000
          [INFO] [Qnn ExecuTorch]: Running level=3 optimization.
          Segmentation fault
          

          This can be reproduced with the following test case command or standalone script.

          python -m executorch.backends.test.suite.runner models --flow qnn --filter "test_maxvit_t_qnn_float32$"
          

          Standalone repro:

          fromtypingimportTupleimportexecutorchimporttorchimporttorchvisionfromexecutorch.backends.qualcomm.utils.utilsimport (
          generate_qnn_executorch_compiler_spec,
          generate_htp_compiler_spec,
          QcomChipset,
          to_edge_transform_and_lower_to_qnn,
          )
          inputs= (torch.randn(1, 3, 224, 224),)
          model=torchvision.models.maxvit_t().eval()
          ep=torch.export.export(model, inputs)
          backend_options=generate_htp_compiler_spec(
          use_fp16=True,
          )
          compile_spec=generate_qnn_executorch_compiler_spec(
          soc_model=QcomChipset.SM8650,
          backend_options=backend_options,
          )
          model=to_edge_transform_and_lower_to_qnn(
          model,
          inputs,
          compile_spec
          ).to_executorch()
          print("Running model...")
          fromexecutorch.extension.pybindings.portable_libimport_load_for_executorch_from_bufferloaded_model=_load_for_executorch_from_buffer(model.buffer)
          loaded_model([*inputs])

          Note that running the backend test case requires executorch's python bindings to be built with the QNN backend. An example build command is below, Note that it will still need the library paths to be set up properly as described in the ET QNN docs.

          CMAKE_ARGS="-DEXECUTORCH_BUILD_QNN=ON -DQNN_SDK_ROOT=$QNN_SDK_ROOT" ./install_executorch.sh --editable
          

          Versions

          Commit fbda3a9, x86-64 simulator, WSL

          cc @cccclai@winskuo-quic@shewu-quic@cbilgin

          Activity

          Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

          Metadata

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            Labels

            backend testerThis bug was found by the backend test suite.module: qnnIssues related to Qualcomm's QNN delegate and code under backends/qualcomm/partner: qualcommFor backend delegation, kernels, demo, etc. from the 3rd-party partner, Qualcomm

            Type

            No type

            Projects

            No projects

              Milestone

              No milestone

              Relationships

              None yet

              Development

              No branches or pull requests

              Issue actions

              , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length \u003e 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
              Skip to content

              Maxvit_t model lowering segfaults on QNN #14050

              Description

              @GregoryComer

              🐛 Describe the bug

              The maxvit_t model in torchvision segfaults on QNN when lowering. It doesn't seem to be a 100% repro, but it's pretty close on my local machine.

              Output excerpt (note that the segfault happens several pages of logs in):

              ...
              [INFO] [Qnn ExecuTorch]: Initialize Qnn backend parameters for Qnn executorch backend type 2
              [INFO] [Qnn ExecuTorch]: Caching: Caching is in RESTORE MODE.
              [INFO] [Qnn ExecuTorch]: QnnContextCustomProtocol expected magic number: 0x5678abcd but get: 0x2000000
              [INFO] [Qnn ExecuTorch]: Running level=3 optimization.
              Segmentation fault
              

              This can be reproduced with the following test case command or standalone script.

              python -m executorch.backends.test.suite.runner models --flow qnn --filter "test_maxvit_t_qnn_float32$"
              

              Standalone repro:

              fromtypingimportTupleimportexecutorchimporttorchimporttorchvisionfromexecutorch.backends.qualcomm.utils.utilsimport (
              generate_qnn_executorch_compiler_spec,
              generate_htp_compiler_spec,
              QcomChipset,
              to_edge_transform_and_lower_to_qnn,
              )
              inputs= (torch.randn(1, 3, 224, 224),)
              model=torchvision.models.maxvit_t().eval()
              ep=torch.export.export(model, inputs)
              backend_options=generate_htp_compiler_spec(
              use_fp16=True,
              )
              compile_spec=generate_qnn_executorch_compiler_spec(
              soc_model=QcomChipset.SM8650,
              backend_options=backend_options,
              )
              model=to_edge_transform_and_lower_to_qnn(
              model,
              inputs,
              compile_spec
              ).to_executorch()
              print("Running model...")
              fromexecutorch.extension.pybindings.portable_libimport_load_for_executorch_from_bufferloaded_model=_load_for_executorch_from_buffer(model.buffer)
              loaded_model([*inputs])

              Note that running the backend test case requires executorch's python bindings to be built with the QNN backend. An example build command is below, Note that it will still need the library paths to be set up properly as described in the ET QNN docs.

              CMAKE_ARGS="-DEXECUTORCH_BUILD_QNN=ON -DQNN_SDK_ROOT=$QNN_SDK_ROOT" ./install_executorch.sh --editable
              

              Versions

              Commit fbda3a9, x86-64 simulator, WSL

              cc @cccclai@winskuo-quic@shewu-quic@cbilgin

              Activity

              Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

              Metadata

              Metadata

              Assignees

              No one assigned

                Labels

                backend testerThis bug was found by the backend test suite.module: qnnIssues related to Qualcomm's QNN delegate and code under backends/qualcomm/partner: qualcommFor backend delegation, kernels, demo, etc. from the 3rd-party partner, Qualcomm

                Type

                No type

                Projects

                No projects

                  Milestone

                  No milestone

                  Relationships

                  None yet

                  Development

                  No branches or pull requests

                  Issue actions

                  , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
                  Skip to content

                  Maxvit_t model lowering segfaults on QNN #14050

                  Description

                  @GregoryComer

                  🐛 Describe the bug

                  The maxvit_t model in torchvision segfaults on QNN when lowering. It doesn't seem to be a 100% repro, but it's pretty close on my local machine.

                  Output excerpt (note that the segfault happens several pages of logs in):

                  ...
                  [INFO] [Qnn ExecuTorch]: Initialize Qnn backend parameters for Qnn executorch backend type 2
                  [INFO] [Qnn ExecuTorch]: Caching: Caching is in RESTORE MODE.
                  [INFO] [Qnn ExecuTorch]: QnnContextCustomProtocol expected magic number: 0x5678abcd but get: 0x2000000
                  [INFO] [Qnn ExecuTorch]: Running level=3 optimization.
                  Segmentation fault
                  

                  This can be reproduced with the following test case command or standalone script.

                  python -m executorch.backends.test.suite.runner models --flow qnn --filter "test_maxvit_t_qnn_float32$"
                  

                  Standalone repro:

                  fromtypingimportTupleimportexecutorchimporttorchimporttorchvisionfromexecutorch.backends.qualcomm.utils.utilsimport (
                  generate_qnn_executorch_compiler_spec,
                  generate_htp_compiler_spec,
                  QcomChipset,
                  to_edge_transform_and_lower_to_qnn,
                  )
                  inputs= (torch.randn(1, 3, 224, 224),)
                  model=torchvision.models.maxvit_t().eval()
                  ep=torch.export.export(model, inputs)
                  backend_options=generate_htp_compiler_spec(
                  use_fp16=True,
                  )
                  compile_spec=generate_qnn_executorch_compiler_spec(
                  soc_model=QcomChipset.SM8650,
                  backend_options=backend_options,
                  )
                  model=to_edge_transform_and_lower_to_qnn(
                  model,
                  inputs,
                  compile_spec
                  ).to_executorch()
                  print("Running model...")
                  fromexecutorch.extension.pybindings.portable_libimport_load_for_executorch_from_bufferloaded_model=_load_for_executorch_from_buffer(model.buffer)
                  loaded_model([*inputs])

                  Note that running the backend test case requires executorch's python bindings to be built with the QNN backend. An example build command is below, Note that it will still need the library paths to be set up properly as described in the ET QNN docs.

                  CMAKE_ARGS="-DEXECUTORCH_BUILD_QNN=ON -DQNN_SDK_ROOT=$QNN_SDK_ROOT" ./install_executorch.sh --editable
                  

                  Versions

                  Commit fbda3a9, x86-64 simulator, WSL

                  cc @cccclai@winskuo-quic@shewu-quic@cbilgin

                  Activity

                  Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

                  Metadata

                  Metadata

                  Assignees

                  No one assigned

                    Labels

                    backend testerThis bug was found by the backend test suite.module: qnnIssues related to Qualcomm's QNN delegate and code under backends/qualcomm/partner: qualcommFor backend delegation, kernels, demo, etc. from the 3rd-party partner, Qualcomm

                    Type

                    No type

                    Projects

                    No projects

                      Milestone

                      No milestone

                      Relationships

                      None yet

                      Development

                      No branches or pull requests

                      Issue actions

                      , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
                      Skip to content

                      Maxvit_t model lowering segfaults on QNN #14050

                      Description

                      @GregoryComer

                      🐛 Describe the bug

                      The maxvit_t model in torchvision segfaults on QNN when lowering. It doesn't seem to be a 100% repro, but it's pretty close on my local machine.

                      Output excerpt (note that the segfault happens several pages of logs in):

                      ...
                      [INFO] [Qnn ExecuTorch]: Initialize Qnn backend parameters for Qnn executorch backend type 2
                      [INFO] [Qnn ExecuTorch]: Caching: Caching is in RESTORE MODE.
                      [INFO] [Qnn ExecuTorch]: QnnContextCustomProtocol expected magic number: 0x5678abcd but get: 0x2000000
                      [INFO] [Qnn ExecuTorch]: Running level=3 optimization.
                      Segmentation fault
                      

                      This can be reproduced with the following test case command or standalone script.

                      python -m executorch.backends.test.suite.runner models --flow qnn --filter "test_maxvit_t_qnn_float32$"
                      

                      Standalone repro:

                      fromtypingimportTupleimportexecutorchimporttorchimporttorchvisionfromexecutorch.backends.qualcomm.utils.utilsimport (
                      generate_qnn_executorch_compiler_spec,
                      generate_htp_compiler_spec,
                      QcomChipset,
                      to_edge_transform_and_lower_to_qnn,
                      )
                      inputs= (torch.randn(1, 3, 224, 224),)
                      model=torchvision.models.maxvit_t().eval()
                      ep=torch.export.export(model, inputs)
                      backend_options=generate_htp_compiler_spec(
                      use_fp16=True,
                      )
                      compile_spec=generate_qnn_executorch_compiler_spec(
                      soc_model=QcomChipset.SM8650,
                      backend_options=backend_options,
                      )
                      model=to_edge_transform_and_lower_to_qnn(
                      model,
                      inputs,
                      compile_spec
                      ).to_executorch()
                      print("Running model...")
                      fromexecutorch.extension.pybindings.portable_libimport_load_for_executorch_from_bufferloaded_model=_load_for_executorch_from_buffer(model.buffer)
                      loaded_model([*inputs])

                      Note that running the backend test case requires executorch's python bindings to be built with the QNN backend. An example build command is below, Note that it will still need the library paths to be set up properly as described in the ET QNN docs.

                      CMAKE_ARGS="-DEXECUTORCH_BUILD_QNN=ON -DQNN_SDK_ROOT=$QNN_SDK_ROOT" ./install_executorch.sh --editable
                      

                      Versions

                      Commit fbda3a9, x86-64 simulator, WSL

                      cc @cccclai@winskuo-quic@shewu-quic@cbilgin

                      Activity

                      Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

                      Metadata

                      Metadata

                      Assignees

                      No one assigned

                        Labels

                        backend testerThis bug was found by the backend test suite.module: qnnIssues related to Qualcomm's QNN delegate and code under backends/qualcomm/partner: qualcommFor backend delegation, kernels, demo, etc. from the 3rd-party partner, Qualcomm

                        Type

                        No type

                        Projects

                        No projects

                          Milestone

                          No milestone

                          Relationships

                          None yet

                          Development

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                          , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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                          Maxvit_t model lowering segfaults on QNN #14050

                          Description

                          @GregoryComer

                          🐛 Describe the bug

                          The maxvit_t model in torchvision segfaults on QNN when lowering. It doesn't seem to be a 100% repro, but it's pretty close on my local machine.

                          Output excerpt (note that the segfault happens several pages of logs in):

                          ...
                          [INFO] [Qnn ExecuTorch]: Initialize Qnn backend parameters for Qnn executorch backend type 2
                          [INFO] [Qnn ExecuTorch]: Caching: Caching is in RESTORE MODE.
                          [INFO] [Qnn ExecuTorch]: QnnContextCustomProtocol expected magic number: 0x5678abcd but get: 0x2000000
                          [INFO] [Qnn ExecuTorch]: Running level=3 optimization.
                          Segmentation fault
                          

                          This can be reproduced with the following test case command or standalone script.

                          python -m executorch.backends.test.suite.runner models --flow qnn --filter "test_maxvit_t_qnn_float32$"
                          

                          Standalone repro:

                          fromtypingimportTupleimportexecutorchimporttorchimporttorchvisionfromexecutorch.backends.qualcomm.utils.utilsimport (
                          generate_qnn_executorch_compiler_spec,
                          generate_htp_compiler_spec,
                          QcomChipset,
                          to_edge_transform_and_lower_to_qnn,
                          )
                          inputs= (torch.randn(1, 3, 224, 224),)
                          model=torchvision.models.maxvit_t().eval()
                          ep=torch.export.export(model, inputs)
                          backend_options=generate_htp_compiler_spec(
                          use_fp16=True,
                          )
                          compile_spec=generate_qnn_executorch_compiler_spec(
                          soc_model=QcomChipset.SM8650,
                          backend_options=backend_options,
                          )
                          model=to_edge_transform_and_lower_to_qnn(
                          model,
                          inputs,
                          compile_spec
                          ).to_executorch()
                          print("Running model...")
                          fromexecutorch.extension.pybindings.portable_libimport_load_for_executorch_from_bufferloaded_model=_load_for_executorch_from_buffer(model.buffer)
                          loaded_model([*inputs])

                          Note that running the backend test case requires executorch's python bindings to be built with the QNN backend. An example build command is below, Note that it will still need the library paths to be set up properly as described in the ET QNN docs.

                          CMAKE_ARGS="-DEXECUTORCH_BUILD_QNN=ON -DQNN_SDK_ROOT=$QNN_SDK_ROOT" ./install_executorch.sh --editable
                          

                          Versions

                          Commit fbda3a9, x86-64 simulator, WSL

                          cc @cccclai@winskuo-quic@shewu-quic@cbilgin

                          Activity

                          Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

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                            Labels

                            backend testerThis bug was found by the backend test suite.module: qnnIssues related to Qualcomm's QNN delegate and code under backends/qualcomm/partner: qualcommFor backend delegation, kernels, demo, etc. from the 3rd-party partner, Qualcomm

                            Type

                            No type

                            Projects

                            No projects

                              Milestone

                              No milestone

                              Relationships

                              None yet

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                              No branches or pull requests

                              Issue actions

                              , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode"); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
                              Skip to content

                              Maxvit_t model lowering segfaults on QNN #14050

                              Description

                              @GregoryComer

                              🐛 Describe the bug

                              The maxvit_t model in torchvision segfaults on QNN when lowering. It doesn't seem to be a 100% repro, but it's pretty close on my local machine.

                              Output excerpt (note that the segfault happens several pages of logs in):

                              ...
                              [INFO] [Qnn ExecuTorch]: Initialize Qnn backend parameters for Qnn executorch backend type 2
                              [INFO] [Qnn ExecuTorch]: Caching: Caching is in RESTORE MODE.
                              [INFO] [Qnn ExecuTorch]: QnnContextCustomProtocol expected magic number: 0x5678abcd but get: 0x2000000
                              [INFO] [Qnn ExecuTorch]: Running level=3 optimization.
                              Segmentation fault
                              

                              This can be reproduced with the following test case command or standalone script.

                              python -m executorch.backends.test.suite.runner models --flow qnn --filter "test_maxvit_t_qnn_float32$"
                              

                              Standalone repro:

                              fromtypingimportTupleimportexecutorchimporttorchimporttorchvisionfromexecutorch.backends.qualcomm.utils.utilsimport (
                              generate_qnn_executorch_compiler_spec,
                              generate_htp_compiler_spec,
                              QcomChipset,
                              to_edge_transform_and_lower_to_qnn,
                              )
                              inputs= (torch.randn(1, 3, 224, 224),)
                              model=torchvision.models.maxvit_t().eval()
                              ep=torch.export.export(model, inputs)
                              backend_options=generate_htp_compiler_spec(
                              use_fp16=True,
                              )
                              compile_spec=generate_qnn_executorch_compiler_spec(
                              soc_model=QcomChipset.SM8650,
                              backend_options=backend_options,
                              )
                              model=to_edge_transform_and_lower_to_qnn(
                              model,
                              inputs,
                              compile_spec
                              ).to_executorch()
                              print("Running model...")
                              fromexecutorch.extension.pybindings.portable_libimport_load_for_executorch_from_bufferloaded_model=_load_for_executorch_from_buffer(model.buffer)
                              loaded_model([*inputs])

                              Note that running the backend test case requires executorch's python bindings to be built with the QNN backend. An example build command is below, Note that it will still need the library paths to be set up properly as described in the ET QNN docs.

                              CMAKE_ARGS="-DEXECUTORCH_BUILD_QNN=ON -DQNN_SDK_ROOT=$QNN_SDK_ROOT" ./install_executorch.sh --editable
                              

                              Versions

                              Commit fbda3a9, x86-64 simulator, WSL

                              cc @cccclai@winskuo-quic@shewu-quic@cbilgin

                              Activity

                              Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

                              Metadata

                              Metadata

                              Assignees

                              No one assigned

                                Labels

                                backend testerThis bug was found by the backend test suite.module: qnnIssues related to Qualcomm's QNN delegate and code under backends/qualcomm/partner: qualcommFor backend delegation, kernels, demo, etc. from the 3rd-party partner, Qualcomm

                                Type

                                No type

                                Projects

                                No projects

                                  Milestone

                                  No milestone

                                  Relationships

                                  None yet

                                  Development

                                  No branches or pull requests

                                  Issue actions