Run test-mcu-cortex-m-backend on ARM-related PR diffs#1

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

Draft
Copilot wants to merge 4 commits into
base:main
Choose a base branch
from
Draft

Run test-mcu-cortex-m-backend on ARM-related PR diffs #1

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
59fdd72
Revert "[cortex_m] Fix linear weight layout: transpose in AOT pass, a…
Jan 27, 2026
0fd11b9
Initial plan
Copilot Jan 27, 2026
b0d5e24
Configure test-mcu-cortex-m-backend to run on ARM-related diffs
Copilot Jan 27, 2026
9c5dfcf
Add ARM paths to workflow-level pull_request trigger
Copilot Jan 27, 2026
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
10 changes: 10 additions & 0 deletions .github/workflows/trunk.yml
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -11,6 +11,9 @@ on:
paths:
- .ci/docker/ci_commit_pins/pytorch.txt
- .ci/scripts/**
- backends/arm/**
- examples/arm/**
- backends/cortex_m/**
workflow_dispatch:

concurrency:
Expand DownExpand Up@@ -1051,6 +1054,7 @@ jobs:
runs-on: ubuntu-latest
outputs:
qnn: ${{ steps.filter.outputs.qnn }}
arm: ${{ steps.filter.outputs.arm }}
steps:
- uses: actions/checkout@v4
- uses: dorny/paths-filter@v3
Expand All@@ -1061,6 +1065,10 @@ jobs:
- 'backends/qualcomm/**'
- 'examples/qualcomm/**'
- 'examples/models/llama/**'
arm:
- 'backends/arm/**'
- 'examples/arm/**'
- 'backends/cortex_m/**'

test-static-llama-qnn-eval-linux:
needs: changes # has dependency on changes jobs defined above
Expand DownExpand Up@@ -1135,6 +1143,8 @@ jobs:
}"

test-mcu-cortex-m-backend:
needs: changes
if: needs.changes.outputs.arm == 'true'
name: test-mcu-cortex-m-backend
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
permissions:
Expand Down
6 changes: 3 additions & 3 deletions backends/cortex_m/ops/operators.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -352,7 +352,7 @@ def quantized_linear_meta(
activation_min,
) -> torch.Tensor:

shape = (*input.shape[:-1], weights.shape[1])
shape = (*input.shape[:-1], weights.shape[0])
return torch.empty(shape, dtype=input.dtype, device=input.device)


Expand DownExpand Up@@ -386,7 +386,7 @@ def quantized_linear_impl(
input_reshaped = input_int32.reshape(new_shape)

lhs_sum = torch.sum(input_reshaped, dim=-1, keepdim=True) * filter_offset
output = torch.mm(input_reshaped, weights_int32) + lhs_sum + kernel_sum
output = torch.mm(input_reshaped, weights_int32.T) + lhs_sum + kernel_sum
output_shape = (*input.shape[:-1], output.shape[-1])
output_reshaped = output.reshape(output_shape)
else:
Expand All@@ -396,7 +396,7 @@ def quantized_linear_impl(
new_shape = (prod(input.shape[:-1]), input.shape[-1])
input_reshaped = input_int32.reshape(new_shape)

output = torch.mm(input_reshaped, weights_int32)
output = torch.mm(input_reshaped, weights_int32.T)
if bias is not None:
output = output + bias
output_shape = (*input.shape[:-1], output.shape[-1])
Expand Down
25 changes: 4 additions & 21 deletions backends/cortex_m/passes/convert_to_cortex_m_pass.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -33,19 +33,14 @@ class ConvertToCortexMPass(XNNPACKPass):
by call_operator.
"""

def _compute_kernel_sum(
self, weights_transposed, bias, input_offset, weight_offset
):
def _compute_kernel_sum(self, weights, bias, input_offset, weight_offset):
"""
Computes the precomputed kernel sum term (bias optional)
a * sum_j(wij + b) + ci

for i = (1, ..., n), where j indexes the input activations.

Args:
weights_transposed: Weights already in [in_features, out_features] format
"""
# No transpose needed - weights already transposed by caller
weights_transposed = weights.T
weights_int32 = weights_transposed.to(torch.int32)
offset_weights = weights_int32 + weight_offset
kernel_sum = torch.sum(offset_weights, dim=0, keepdim=True, dtype=torch.int32)
Expand DownExpand Up@@ -115,12 +110,8 @@ def _get_linear_replacement(self, node):
if len(node.args) > 2
else None
)
# Transpose weights once from PyTorch format [out_features, in_features]
# to CMSIS-NN format [in_features, out_features]
weights_transposed = weights_tensor.T.contiguous()
# Pass already-transposed weights to kernel_sum computation
kernel_sum_tensor = self._compute_kernel_sum(
weights_transposed, bias_tensor, -input_zp, -weight_zp
weights_tensor, bias_tensor, -input_zp, -weight_zp
)
with node.graph.inserting_after(weights):
kernel_sum = create_constant_placeholder(
Expand All@@ -131,17 +122,9 @@ def _get_linear_replacement(self, node):
kernel_sum_tensor,
)

weights_transposed_node = create_constant_placeholder(
self.exported_program,
node.graph,
node.name + "_weights_transposed",
InputKind.PARAMETER,
weights_transposed,
)

args = (
node.args[0],
weights_transposed_node,
weights,
None,
kernel_sum,
-input_zp,
Expand Down
, '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

Run test-mcu-cortex-m-backend on ARM-related PR diffs#1

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

Draft
Copilot wants to merge 4 commits into
base:main
Choose a base branch
from
Draft

Run test-mcu-cortex-m-backend on ARM-related PR diffs #1

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
59fdd72
Revert "[cortex_m] Fix linear weight layout: transpose in AOT pass, a…
Jan 27, 2026
0fd11b9
Initial plan
Copilot Jan 27, 2026
b0d5e24
Configure test-mcu-cortex-m-backend to run on ARM-related diffs
Copilot Jan 27, 2026
9c5dfcf
Add ARM paths to workflow-level pull_request trigger
Copilot Jan 27, 2026
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
10 changes: 10 additions & 0 deletions .github/workflows/trunk.yml
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -11,6 +11,9 @@ on:
paths:
- .ci/docker/ci_commit_pins/pytorch.txt
- .ci/scripts/**
- backends/arm/**
- examples/arm/**
- backends/cortex_m/**
workflow_dispatch:

concurrency:
Expand DownExpand Up@@ -1051,6 +1054,7 @@ jobs:
runs-on: ubuntu-latest
outputs:
qnn: ${{ steps.filter.outputs.qnn }}
arm: ${{ steps.filter.outputs.arm }}
steps:
- uses: actions/checkout@v4
- uses: dorny/paths-filter@v3
Expand All@@ -1061,6 +1065,10 @@ jobs:
- 'backends/qualcomm/**'
- 'examples/qualcomm/**'
- 'examples/models/llama/**'
arm:
- 'backends/arm/**'
- 'examples/arm/**'
- 'backends/cortex_m/**'

test-static-llama-qnn-eval-linux:
needs: changes # has dependency on changes jobs defined above
Expand DownExpand Up@@ -1135,6 +1143,8 @@ jobs:
}"

test-mcu-cortex-m-backend:
needs: changes
if: needs.changes.outputs.arm == 'true'
name: test-mcu-cortex-m-backend
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
permissions:
Expand Down
6 changes: 3 additions & 3 deletions backends/cortex_m/ops/operators.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -352,7 +352,7 @@ def quantized_linear_meta(
activation_min,
) -> torch.Tensor:

shape = (*input.shape[:-1], weights.shape[1])
shape = (*input.shape[:-1], weights.shape[0])
return torch.empty(shape, dtype=input.dtype, device=input.device)


Expand DownExpand Up@@ -386,7 +386,7 @@ def quantized_linear_impl(
input_reshaped = input_int32.reshape(new_shape)

lhs_sum = torch.sum(input_reshaped, dim=-1, keepdim=True) * filter_offset
output = torch.mm(input_reshaped, weights_int32) + lhs_sum + kernel_sum
output = torch.mm(input_reshaped, weights_int32.T) + lhs_sum + kernel_sum
output_shape = (*input.shape[:-1], output.shape[-1])
output_reshaped = output.reshape(output_shape)
else:
Expand All@@ -396,7 +396,7 @@ def quantized_linear_impl(
new_shape = (prod(input.shape[:-1]), input.shape[-1])
input_reshaped = input_int32.reshape(new_shape)

output = torch.mm(input_reshaped, weights_int32)
output = torch.mm(input_reshaped, weights_int32.T)
if bias is not None:
output = output + bias
output_shape = (*input.shape[:-1], output.shape[-1])
Expand Down
25 changes: 4 additions & 21 deletions backends/cortex_m/passes/convert_to_cortex_m_pass.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -33,19 +33,14 @@ class ConvertToCortexMPass(XNNPACKPass):
by call_operator.
"""

def _compute_kernel_sum(
self, weights_transposed, bias, input_offset, weight_offset
):
def _compute_kernel_sum(self, weights, bias, input_offset, weight_offset):
"""
Computes the precomputed kernel sum term (bias optional)
a * sum_j(wij + b) + ci

for i = (1, ..., n), where j indexes the input activations.

Args:
weights_transposed: Weights already in [in_features, out_features] format
"""
# No transpose needed - weights already transposed by caller
weights_transposed = weights.T
weights_int32 = weights_transposed.to(torch.int32)
offset_weights = weights_int32 + weight_offset
kernel_sum = torch.sum(offset_weights, dim=0, keepdim=True, dtype=torch.int32)
Expand DownExpand Up@@ -115,12 +110,8 @@ def _get_linear_replacement(self, node):
if len(node.args) > 2
else None
)
# Transpose weights once from PyTorch format [out_features, in_features]
# to CMSIS-NN format [in_features, out_features]
weights_transposed = weights_tensor.T.contiguous()
# Pass already-transposed weights to kernel_sum computation
kernel_sum_tensor = self._compute_kernel_sum(
weights_transposed, bias_tensor, -input_zp, -weight_zp
weights_tensor, bias_tensor, -input_zp, -weight_zp
)
with node.graph.inserting_after(weights):
kernel_sum = create_constant_placeholder(
Expand All@@ -131,17 +122,9 @@ def _get_linear_replacement(self, node):
kernel_sum_tensor,
)

weights_transposed_node = create_constant_placeholder(
self.exported_program,
node.graph,
node.name + "_weights_transposed",
InputKind.PARAMETER,
weights_transposed,
)

args = (
node.args[0],
weights_transposed_node,
weights,
None,
kernel_sum,
-input_zp,
Expand Down
, '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

Run test-mcu-cortex-m-backend on ARM-related PR diffs#1

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

Draft
Copilot wants to merge 4 commits into
base:main
Choose a base branch
from
Draft

Run test-mcu-cortex-m-backend on ARM-related PR diffs #1

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
59fdd72
Revert "[cortex_m] Fix linear weight layout: transpose in AOT pass, a…
Jan 27, 2026
0fd11b9
Initial plan
Copilot Jan 27, 2026
b0d5e24
Configure test-mcu-cortex-m-backend to run on ARM-related diffs
Copilot Jan 27, 2026
9c5dfcf
Add ARM paths to workflow-level pull_request trigger
Copilot Jan 27, 2026
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
10 changes: 10 additions & 0 deletions .github/workflows/trunk.yml
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -11,6 +11,9 @@ on:
paths:
- .ci/docker/ci_commit_pins/pytorch.txt
- .ci/scripts/**
- backends/arm/**
- examples/arm/**
- backends/cortex_m/**
workflow_dispatch:

concurrency:
Expand DownExpand Up@@ -1051,6 +1054,7 @@ jobs:
runs-on: ubuntu-latest
outputs:
qnn: ${{ steps.filter.outputs.qnn }}
arm: ${{ steps.filter.outputs.arm }}
steps:
- uses: actions/checkout@v4
- uses: dorny/paths-filter@v3
Expand All@@ -1061,6 +1065,10 @@ jobs:
- 'backends/qualcomm/**'
- 'examples/qualcomm/**'
- 'examples/models/llama/**'
arm:
- 'backends/arm/**'
- 'examples/arm/**'
- 'backends/cortex_m/**'

test-static-llama-qnn-eval-linux:
needs: changes # has dependency on changes jobs defined above
Expand DownExpand Up@@ -1135,6 +1143,8 @@ jobs:
}"

test-mcu-cortex-m-backend:
needs: changes
if: needs.changes.outputs.arm == 'true'
name: test-mcu-cortex-m-backend
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
permissions:
Expand Down
6 changes: 3 additions & 3 deletions backends/cortex_m/ops/operators.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -352,7 +352,7 @@ def quantized_linear_meta(
activation_min,
) -> torch.Tensor:

shape = (*input.shape[:-1], weights.shape[1])
shape = (*input.shape[:-1], weights.shape[0])
return torch.empty(shape, dtype=input.dtype, device=input.device)


Expand DownExpand Up@@ -386,7 +386,7 @@ def quantized_linear_impl(
input_reshaped = input_int32.reshape(new_shape)

lhs_sum = torch.sum(input_reshaped, dim=-1, keepdim=True) * filter_offset
output = torch.mm(input_reshaped, weights_int32) + lhs_sum + kernel_sum
output = torch.mm(input_reshaped, weights_int32.T) + lhs_sum + kernel_sum
output_shape = (*input.shape[:-1], output.shape[-1])
output_reshaped = output.reshape(output_shape)
else:
Expand All@@ -396,7 +396,7 @@ def quantized_linear_impl(
new_shape = (prod(input.shape[:-1]), input.shape[-1])
input_reshaped = input_int32.reshape(new_shape)

output = torch.mm(input_reshaped, weights_int32)
output = torch.mm(input_reshaped, weights_int32.T)
if bias is not None:
output = output + bias
output_shape = (*input.shape[:-1], output.shape[-1])
Expand Down
25 changes: 4 additions & 21 deletions backends/cortex_m/passes/convert_to_cortex_m_pass.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -33,19 +33,14 @@ class ConvertToCortexMPass(XNNPACKPass):
by call_operator.
"""

def _compute_kernel_sum(
self, weights_transposed, bias, input_offset, weight_offset
):
def _compute_kernel_sum(self, weights, bias, input_offset, weight_offset):
"""
Computes the precomputed kernel sum term (bias optional)
a * sum_j(wij + b) + ci

for i = (1, ..., n), where j indexes the input activations.

Args:
weights_transposed: Weights already in [in_features, out_features] format
"""
# No transpose needed - weights already transposed by caller
weights_transposed = weights.T
weights_int32 = weights_transposed.to(torch.int32)
offset_weights = weights_int32 + weight_offset
kernel_sum = torch.sum(offset_weights, dim=0, keepdim=True, dtype=torch.int32)
Expand DownExpand Up@@ -115,12 +110,8 @@ def _get_linear_replacement(self, node):
if len(node.args) > 2
else None
)
# Transpose weights once from PyTorch format [out_features, in_features]
# to CMSIS-NN format [in_features, out_features]
weights_transposed = weights_tensor.T.contiguous()
# Pass already-transposed weights to kernel_sum computation
kernel_sum_tensor = self._compute_kernel_sum(
weights_transposed, bias_tensor, -input_zp, -weight_zp
weights_tensor, bias_tensor, -input_zp, -weight_zp
)
with node.graph.inserting_after(weights):
kernel_sum = create_constant_placeholder(
Expand All@@ -131,17 +122,9 @@ def _get_linear_replacement(self, node):
kernel_sum_tensor,
)

weights_transposed_node = create_constant_placeholder(
self.exported_program,
node.graph,
node.name + "_weights_transposed",
InputKind.PARAMETER,
weights_transposed,
)

args = (
node.args[0],
weights_transposed_node,
weights,
None,
kernel_sum,
-input_zp,
Expand Down
, '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

Run test-mcu-cortex-m-backend on ARM-related PR diffs#1

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

Draft
Copilot wants to merge 4 commits into
base:main
Choose a base branch
from
Draft

Run test-mcu-cortex-m-backend on ARM-related PR diffs #1

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
59fdd72
Revert "[cortex_m] Fix linear weight layout: transpose in AOT pass, a…
Jan 27, 2026
0fd11b9
Initial plan
Copilot Jan 27, 2026
b0d5e24
Configure test-mcu-cortex-m-backend to run on ARM-related diffs
Copilot Jan 27, 2026
9c5dfcf
Add ARM paths to workflow-level pull_request trigger
Copilot Jan 27, 2026
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
10 changes: 10 additions & 0 deletions .github/workflows/trunk.yml
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -11,6 +11,9 @@ on:
paths:
- .ci/docker/ci_commit_pins/pytorch.txt
- .ci/scripts/**
- backends/arm/**
- examples/arm/**
- backends/cortex_m/**
workflow_dispatch:

concurrency:
Expand DownExpand Up@@ -1051,6 +1054,7 @@ jobs:
runs-on: ubuntu-latest
outputs:
qnn: ${{ steps.filter.outputs.qnn }}
arm: ${{ steps.filter.outputs.arm }}
steps:
- uses: actions/checkout@v4
- uses: dorny/paths-filter@v3
Expand All@@ -1061,6 +1065,10 @@ jobs:
- 'backends/qualcomm/**'
- 'examples/qualcomm/**'
- 'examples/models/llama/**'
arm:
- 'backends/arm/**'
- 'examples/arm/**'
- 'backends/cortex_m/**'

test-static-llama-qnn-eval-linux:
needs: changes # has dependency on changes jobs defined above
Expand DownExpand Up@@ -1135,6 +1143,8 @@ jobs:
}"

test-mcu-cortex-m-backend:
needs: changes
if: needs.changes.outputs.arm == 'true'
name: test-mcu-cortex-m-backend
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
permissions:
Expand Down
6 changes: 3 additions & 3 deletions backends/cortex_m/ops/operators.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -352,7 +352,7 @@ def quantized_linear_meta(
activation_min,
) -> torch.Tensor:

shape = (*input.shape[:-1], weights.shape[1])
shape = (*input.shape[:-1], weights.shape[0])
return torch.empty(shape, dtype=input.dtype, device=input.device)


Expand DownExpand Up@@ -386,7 +386,7 @@ def quantized_linear_impl(
input_reshaped = input_int32.reshape(new_shape)

lhs_sum = torch.sum(input_reshaped, dim=-1, keepdim=True) * filter_offset
output = torch.mm(input_reshaped, weights_int32) + lhs_sum + kernel_sum
output = torch.mm(input_reshaped, weights_int32.T) + lhs_sum + kernel_sum
output_shape = (*input.shape[:-1], output.shape[-1])
output_reshaped = output.reshape(output_shape)
else:
Expand All@@ -396,7 +396,7 @@ def quantized_linear_impl(
new_shape = (prod(input.shape[:-1]), input.shape[-1])
input_reshaped = input_int32.reshape(new_shape)

output = torch.mm(input_reshaped, weights_int32)
output = torch.mm(input_reshaped, weights_int32.T)
if bias is not None:
output = output + bias
output_shape = (*input.shape[:-1], output.shape[-1])
Expand Down
25 changes: 4 additions & 21 deletions backends/cortex_m/passes/convert_to_cortex_m_pass.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -33,19 +33,14 @@ class ConvertToCortexMPass(XNNPACKPass):
by call_operator.
"""

def _compute_kernel_sum(
self, weights_transposed, bias, input_offset, weight_offset
):
def _compute_kernel_sum(self, weights, bias, input_offset, weight_offset):
"""
Computes the precomputed kernel sum term (bias optional)
a * sum_j(wij + b) + ci

for i = (1, ..., n), where j indexes the input activations.

Args:
weights_transposed: Weights already in [in_features, out_features] format
"""
# No transpose needed - weights already transposed by caller
weights_transposed = weights.T
weights_int32 = weights_transposed.to(torch.int32)
offset_weights = weights_int32 + weight_offset
kernel_sum = torch.sum(offset_weights, dim=0, keepdim=True, dtype=torch.int32)
Expand DownExpand Up@@ -115,12 +110,8 @@ def _get_linear_replacement(self, node):
if len(node.args) > 2
else None
)
# Transpose weights once from PyTorch format [out_features, in_features]
# to CMSIS-NN format [in_features, out_features]
weights_transposed = weights_tensor.T.contiguous()
# Pass already-transposed weights to kernel_sum computation
kernel_sum_tensor = self._compute_kernel_sum(
weights_transposed, bias_tensor, -input_zp, -weight_zp
weights_tensor, bias_tensor, -input_zp, -weight_zp
)
with node.graph.inserting_after(weights):
kernel_sum = create_constant_placeholder(
Expand All@@ -131,17 +122,9 @@ def _get_linear_replacement(self, node):
kernel_sum_tensor,
)

weights_transposed_node = create_constant_placeholder(
self.exported_program,
node.graph,
node.name + "_weights_transposed",
InputKind.PARAMETER,
weights_transposed,
)

args = (
node.args[0],
weights_transposed_node,
weights,
None,
kernel_sum,
-input_zp,
Expand Down
, '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

Run test-mcu-cortex-m-backend on ARM-related PR diffs#1

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

Draft
Copilot wants to merge 4 commits into
base:main
Choose a base branch
from
Draft

Run test-mcu-cortex-m-backend on ARM-related PR diffs #1

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
59fdd72
Revert "[cortex_m] Fix linear weight layout: transpose in AOT pass, a…
Jan 27, 2026
0fd11b9
Initial plan
Copilot Jan 27, 2026
b0d5e24
Configure test-mcu-cortex-m-backend to run on ARM-related diffs
Copilot Jan 27, 2026
9c5dfcf
Add ARM paths to workflow-level pull_request trigger
Copilot Jan 27, 2026
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
10 changes: 10 additions & 0 deletions .github/workflows/trunk.yml
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -11,6 +11,9 @@ on:
paths:
- .ci/docker/ci_commit_pins/pytorch.txt
- .ci/scripts/**
- backends/arm/**
- examples/arm/**
- backends/cortex_m/**
workflow_dispatch:

concurrency:
Expand DownExpand Up@@ -1051,6 +1054,7 @@ jobs:
runs-on: ubuntu-latest
outputs:
qnn: ${{ steps.filter.outputs.qnn }}
arm: ${{ steps.filter.outputs.arm }}
steps:
- uses: actions/checkout@v4
- uses: dorny/paths-filter@v3
Expand All@@ -1061,6 +1065,10 @@ jobs:
- 'backends/qualcomm/**'
- 'examples/qualcomm/**'
- 'examples/models/llama/**'
arm:
- 'backends/arm/**'
- 'examples/arm/**'
- 'backends/cortex_m/**'

test-static-llama-qnn-eval-linux:
needs: changes # has dependency on changes jobs defined above
Expand DownExpand Up@@ -1135,6 +1143,8 @@ jobs:
}"

test-mcu-cortex-m-backend:
needs: changes
if: needs.changes.outputs.arm == 'true'
name: test-mcu-cortex-m-backend
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
permissions:
Expand Down
6 changes: 3 additions & 3 deletions backends/cortex_m/ops/operators.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -352,7 +352,7 @@ def quantized_linear_meta(
activation_min,
) -> torch.Tensor:

shape = (*input.shape[:-1], weights.shape[1])
shape = (*input.shape[:-1], weights.shape[0])
return torch.empty(shape, dtype=input.dtype, device=input.device)


Expand DownExpand Up@@ -386,7 +386,7 @@ def quantized_linear_impl(
input_reshaped = input_int32.reshape(new_shape)

lhs_sum = torch.sum(input_reshaped, dim=-1, keepdim=True) * filter_offset
output = torch.mm(input_reshaped, weights_int32) + lhs_sum + kernel_sum
output = torch.mm(input_reshaped, weights_int32.T) + lhs_sum + kernel_sum
output_shape = (*input.shape[:-1], output.shape[-1])
output_reshaped = output.reshape(output_shape)
else:
Expand All@@ -396,7 +396,7 @@ def quantized_linear_impl(
new_shape = (prod(input.shape[:-1]), input.shape[-1])
input_reshaped = input_int32.reshape(new_shape)

output = torch.mm(input_reshaped, weights_int32)
output = torch.mm(input_reshaped, weights_int32.T)
if bias is not None:
output = output + bias
output_shape = (*input.shape[:-1], output.shape[-1])
Expand Down
25 changes: 4 additions & 21 deletions backends/cortex_m/passes/convert_to_cortex_m_pass.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -33,19 +33,14 @@ class ConvertToCortexMPass(XNNPACKPass):
by call_operator.
"""

def _compute_kernel_sum(
self, weights_transposed, bias, input_offset, weight_offset
):
def _compute_kernel_sum(self, weights, bias, input_offset, weight_offset):
"""
Computes the precomputed kernel sum term (bias optional)
a * sum_j(wij + b) + ci

for i = (1, ..., n), where j indexes the input activations.

Args:
weights_transposed: Weights already in [in_features, out_features] format
"""
# No transpose needed - weights already transposed by caller
weights_transposed = weights.T
weights_int32 = weights_transposed.to(torch.int32)
offset_weights = weights_int32 + weight_offset
kernel_sum = torch.sum(offset_weights, dim=0, keepdim=True, dtype=torch.int32)
Expand DownExpand Up@@ -115,12 +110,8 @@ def _get_linear_replacement(self, node):
if len(node.args) > 2
else None
)
# Transpose weights once from PyTorch format [out_features, in_features]
# to CMSIS-NN format [in_features, out_features]
weights_transposed = weights_tensor.T.contiguous()
# Pass already-transposed weights to kernel_sum computation
kernel_sum_tensor = self._compute_kernel_sum(
weights_transposed, bias_tensor, -input_zp, -weight_zp
weights_tensor, bias_tensor, -input_zp, -weight_zp
)
with node.graph.inserting_after(weights):
kernel_sum = create_constant_placeholder(
Expand All@@ -131,17 +122,9 @@ def _get_linear_replacement(self, node):
kernel_sum_tensor,
)

weights_transposed_node = create_constant_placeholder(
self.exported_program,
node.graph,
node.name + "_weights_transposed",
InputKind.PARAMETER,
weights_transposed,
)

args = (
node.args[0],
weights_transposed_node,
weights,
None,
kernel_sum,
-input_zp,
Expand Down
, '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

Run test-mcu-cortex-m-backend on ARM-related PR diffs#1

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

Draft
Copilot wants to merge 4 commits into
base:main
Choose a base branch
from
Draft

Run test-mcu-cortex-m-backend on ARM-related PR diffs #1

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
59fdd72
Revert "[cortex_m] Fix linear weight layout: transpose in AOT pass, a…
Jan 27, 2026
0fd11b9
Initial plan
Copilot Jan 27, 2026
b0d5e24
Configure test-mcu-cortex-m-backend to run on ARM-related diffs
Copilot Jan 27, 2026
9c5dfcf
Add ARM paths to workflow-level pull_request trigger
Copilot Jan 27, 2026
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
10 changes: 10 additions & 0 deletions .github/workflows/trunk.yml
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -11,6 +11,9 @@ on:
paths:
- .ci/docker/ci_commit_pins/pytorch.txt
- .ci/scripts/**
- backends/arm/**
- examples/arm/**
- backends/cortex_m/**
workflow_dispatch:

concurrency:
Expand DownExpand Up@@ -1051,6 +1054,7 @@ jobs:
runs-on: ubuntu-latest
outputs:
qnn: ${{ steps.filter.outputs.qnn }}
arm: ${{ steps.filter.outputs.arm }}
steps:
- uses: actions/checkout@v4
- uses: dorny/paths-filter@v3
Expand All@@ -1061,6 +1065,10 @@ jobs:
- 'backends/qualcomm/**'
- 'examples/qualcomm/**'
- 'examples/models/llama/**'
arm:
- 'backends/arm/**'
- 'examples/arm/**'
- 'backends/cortex_m/**'

test-static-llama-qnn-eval-linux:
needs: changes # has dependency on changes jobs defined above
Expand DownExpand Up@@ -1135,6 +1143,8 @@ jobs:
}"

test-mcu-cortex-m-backend:
needs: changes
if: needs.changes.outputs.arm == 'true'
name: test-mcu-cortex-m-backend
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
permissions:
Expand Down
6 changes: 3 additions & 3 deletions backends/cortex_m/ops/operators.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -352,7 +352,7 @@ def quantized_linear_meta(
activation_min,
) -> torch.Tensor:

shape = (*input.shape[:-1], weights.shape[1])
shape = (*input.shape[:-1], weights.shape[0])
return torch.empty(shape, dtype=input.dtype, device=input.device)


Expand DownExpand Up@@ -386,7 +386,7 @@ def quantized_linear_impl(
input_reshaped = input_int32.reshape(new_shape)

lhs_sum = torch.sum(input_reshaped, dim=-1, keepdim=True) * filter_offset
output = torch.mm(input_reshaped, weights_int32) + lhs_sum + kernel_sum
output = torch.mm(input_reshaped, weights_int32.T) + lhs_sum + kernel_sum
output_shape = (*input.shape[:-1], output.shape[-1])
output_reshaped = output.reshape(output_shape)
else:
Expand All@@ -396,7 +396,7 @@ def quantized_linear_impl(
new_shape = (prod(input.shape[:-1]), input.shape[-1])
input_reshaped = input_int32.reshape(new_shape)

output = torch.mm(input_reshaped, weights_int32)
output = torch.mm(input_reshaped, weights_int32.T)
if bias is not None:
output = output + bias
output_shape = (*input.shape[:-1], output.shape[-1])
Expand Down
25 changes: 4 additions & 21 deletions backends/cortex_m/passes/convert_to_cortex_m_pass.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -33,19 +33,14 @@ class ConvertToCortexMPass(XNNPACKPass):
by call_operator.
"""

def _compute_kernel_sum(
self, weights_transposed, bias, input_offset, weight_offset
):
def _compute_kernel_sum(self, weights, bias, input_offset, weight_offset):
"""
Computes the precomputed kernel sum term (bias optional)
a * sum_j(wij + b) + ci

for i = (1, ..., n), where j indexes the input activations.

Args:
weights_transposed: Weights already in [in_features, out_features] format
"""
# No transpose needed - weights already transposed by caller
weights_transposed = weights.T
weights_int32 = weights_transposed.to(torch.int32)
offset_weights = weights_int32 + weight_offset
kernel_sum = torch.sum(offset_weights, dim=0, keepdim=True, dtype=torch.int32)
Expand DownExpand Up@@ -115,12 +110,8 @@ def _get_linear_replacement(self, node):
if len(node.args) > 2
else None
)
# Transpose weights once from PyTorch format [out_features, in_features]
# to CMSIS-NN format [in_features, out_features]
weights_transposed = weights_tensor.T.contiguous()
# Pass already-transposed weights to kernel_sum computation
kernel_sum_tensor = self._compute_kernel_sum(
weights_transposed, bias_tensor, -input_zp, -weight_zp
weights_tensor, bias_tensor, -input_zp, -weight_zp
)
with node.graph.inserting_after(weights):
kernel_sum = create_constant_placeholder(
Expand All@@ -131,17 +122,9 @@ def _get_linear_replacement(self, node):
kernel_sum_tensor,
)

weights_transposed_node = create_constant_placeholder(
self.exported_program,
node.graph,
node.name + "_weights_transposed",
InputKind.PARAMETER,
weights_transposed,
)

args = (
node.args[0],
weights_transposed_node,
weights,
None,
kernel_sum,
-input_zp,
Expand Down
, '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('^' + ".*" + '
Skip to content

Run test-mcu-cortex-m-backend on ARM-related PR diffs#1

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

Draft
Copilot wants to merge 4 commits into
base:main
Choose a base branch
from
Draft

Run test-mcu-cortex-m-backend on ARM-related PR diffs #1

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
59fdd72
Revert "[cortex_m] Fix linear weight layout: transpose in AOT pass, a…
Jan 27, 2026
0fd11b9
Initial plan
Copilot Jan 27, 2026
b0d5e24
Configure test-mcu-cortex-m-backend to run on ARM-related diffs
Copilot Jan 27, 2026
9c5dfcf
Add ARM paths to workflow-level pull_request trigger
Copilot Jan 27, 2026
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
10 changes: 10 additions & 0 deletions .github/workflows/trunk.yml
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -11,6 +11,9 @@ on:
paths:
- .ci/docker/ci_commit_pins/pytorch.txt
- .ci/scripts/**
- backends/arm/**
- examples/arm/**
- backends/cortex_m/**
workflow_dispatch:

concurrency:
Expand DownExpand Up@@ -1051,6 +1054,7 @@ jobs:
runs-on: ubuntu-latest
outputs:
qnn: ${{ steps.filter.outputs.qnn }}
arm: ${{ steps.filter.outputs.arm }}
steps:
- uses: actions/checkout@v4
- uses: dorny/paths-filter@v3
Expand All@@ -1061,6 +1065,10 @@ jobs:
- 'backends/qualcomm/**'
- 'examples/qualcomm/**'
- 'examples/models/llama/**'
arm:
- 'backends/arm/**'
- 'examples/arm/**'
- 'backends/cortex_m/**'

test-static-llama-qnn-eval-linux:
needs: changes # has dependency on changes jobs defined above
Expand DownExpand Up@@ -1135,6 +1143,8 @@ jobs:
}"

test-mcu-cortex-m-backend:
needs: changes
if: needs.changes.outputs.arm == 'true'
name: test-mcu-cortex-m-backend
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
permissions:
Expand Down
6 changes: 3 additions & 3 deletions backends/cortex_m/ops/operators.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -352,7 +352,7 @@ def quantized_linear_meta(
activation_min,
) -> torch.Tensor:

shape = (*input.shape[:-1], weights.shape[1])
shape = (*input.shape[:-1], weights.shape[0])
return torch.empty(shape, dtype=input.dtype, device=input.device)


Expand DownExpand Up@@ -386,7 +386,7 @@ def quantized_linear_impl(
input_reshaped = input_int32.reshape(new_shape)

lhs_sum = torch.sum(input_reshaped, dim=-1, keepdim=True) * filter_offset
output = torch.mm(input_reshaped, weights_int32) + lhs_sum + kernel_sum
output = torch.mm(input_reshaped, weights_int32.T) + lhs_sum + kernel_sum
output_shape = (*input.shape[:-1], output.shape[-1])
output_reshaped = output.reshape(output_shape)
else:
Expand All@@ -396,7 +396,7 @@ def quantized_linear_impl(
new_shape = (prod(input.shape[:-1]), input.shape[-1])
input_reshaped = input_int32.reshape(new_shape)

output = torch.mm(input_reshaped, weights_int32)
output = torch.mm(input_reshaped, weights_int32.T)
if bias is not None:
output = output + bias
output_shape = (*input.shape[:-1], output.shape[-1])
Expand Down
25 changes: 4 additions & 21 deletions backends/cortex_m/passes/convert_to_cortex_m_pass.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -33,19 +33,14 @@ class ConvertToCortexMPass(XNNPACKPass):
by call_operator.
"""

def _compute_kernel_sum(
self, weights_transposed, bias, input_offset, weight_offset
):
def _compute_kernel_sum(self, weights, bias, input_offset, weight_offset):
"""
Computes the precomputed kernel sum term (bias optional)
a * sum_j(wij + b) + ci

for i = (1, ..., n), where j indexes the input activations.

Args:
weights_transposed: Weights already in [in_features, out_features] format
"""
# No transpose needed - weights already transposed by caller
weights_transposed = weights.T
weights_int32 = weights_transposed.to(torch.int32)
offset_weights = weights_int32 + weight_offset
kernel_sum = torch.sum(offset_weights, dim=0, keepdim=True, dtype=torch.int32)
Expand DownExpand Up@@ -115,12 +110,8 @@ def _get_linear_replacement(self, node):
if len(node.args) > 2
else None
)
# Transpose weights once from PyTorch format [out_features, in_features]
# to CMSIS-NN format [in_features, out_features]
weights_transposed = weights_tensor.T.contiguous()
# Pass already-transposed weights to kernel_sum computation
kernel_sum_tensor = self._compute_kernel_sum(
weights_transposed, bias_tensor, -input_zp, -weight_zp
weights_tensor, bias_tensor, -input_zp, -weight_zp
)
with node.graph.inserting_after(weights):
kernel_sum = create_constant_placeholder(
Expand All@@ -131,17 +122,9 @@ def _get_linear_replacement(self, node):
kernel_sum_tensor,
)

weights_transposed_node = create_constant_placeholder(
self.exported_program,
node.graph,
node.name + "_weights_transposed",
InputKind.PARAMETER,
weights_transposed,
)

args = (
node.args[0],
weights_transposed_node,
weights,
None,
kernel_sum,
-input_zp,
Expand Down
, '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

Run test-mcu-cortex-m-backend on ARM-related PR diffs#1

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

Draft
Copilot wants to merge 4 commits into
base:main
Choose a base branch
from
Draft

Run test-mcu-cortex-m-backend on ARM-related PR diffs #1

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
59fdd72
Revert "[cortex_m] Fix linear weight layout: transpose in AOT pass, a…
Jan 27, 2026
0fd11b9
Initial plan
Copilot Jan 27, 2026
b0d5e24
Configure test-mcu-cortex-m-backend to run on ARM-related diffs
Copilot Jan 27, 2026
9c5dfcf
Add ARM paths to workflow-level pull_request trigger
Copilot Jan 27, 2026
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
10 changes: 10 additions & 0 deletions .github/workflows/trunk.yml
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -11,6 +11,9 @@ on:
paths:
- .ci/docker/ci_commit_pins/pytorch.txt
- .ci/scripts/**
- backends/arm/**
- examples/arm/**
- backends/cortex_m/**
workflow_dispatch:

concurrency:
Expand DownExpand Up@@ -1051,6 +1054,7 @@ jobs:
runs-on: ubuntu-latest
outputs:
qnn: ${{ steps.filter.outputs.qnn }}
arm: ${{ steps.filter.outputs.arm }}
steps:
- uses: actions/checkout@v4
- uses: dorny/paths-filter@v3
Expand All@@ -1061,6 +1065,10 @@ jobs:
- 'backends/qualcomm/**'
- 'examples/qualcomm/**'
- 'examples/models/llama/**'
arm:
- 'backends/arm/**'
- 'examples/arm/**'
- 'backends/cortex_m/**'

test-static-llama-qnn-eval-linux:
needs: changes # has dependency on changes jobs defined above
Expand DownExpand Up@@ -1135,6 +1143,8 @@ jobs:
}"

test-mcu-cortex-m-backend:
needs: changes
if: needs.changes.outputs.arm == 'true'
name: test-mcu-cortex-m-backend
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
permissions:
Expand Down
6 changes: 3 additions & 3 deletions backends/cortex_m/ops/operators.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -352,7 +352,7 @@ def quantized_linear_meta(
activation_min,
) -> torch.Tensor:

shape = (*input.shape[:-1], weights.shape[1])
shape = (*input.shape[:-1], weights.shape[0])
return torch.empty(shape, dtype=input.dtype, device=input.device)


Expand DownExpand Up@@ -386,7 +386,7 @@ def quantized_linear_impl(
input_reshaped = input_int32.reshape(new_shape)

lhs_sum = torch.sum(input_reshaped, dim=-1, keepdim=True) * filter_offset
output = torch.mm(input_reshaped, weights_int32) + lhs_sum + kernel_sum
output = torch.mm(input_reshaped, weights_int32.T) + lhs_sum + kernel_sum
output_shape = (*input.shape[:-1], output.shape[-1])
output_reshaped = output.reshape(output_shape)
else:
Expand All@@ -396,7 +396,7 @@ def quantized_linear_impl(
new_shape = (prod(input.shape[:-1]), input.shape[-1])
input_reshaped = input_int32.reshape(new_shape)

output = torch.mm(input_reshaped, weights_int32)
output = torch.mm(input_reshaped, weights_int32.T)
if bias is not None:
output = output + bias
output_shape = (*input.shape[:-1], output.shape[-1])
Expand Down
25 changes: 4 additions & 21 deletions backends/cortex_m/passes/convert_to_cortex_m_pass.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -33,19 +33,14 @@ class ConvertToCortexMPass(XNNPACKPass):
by call_operator.
"""

def _compute_kernel_sum(
self, weights_transposed, bias, input_offset, weight_offset
):
def _compute_kernel_sum(self, weights, bias, input_offset, weight_offset):
"""
Computes the precomputed kernel sum term (bias optional)
a * sum_j(wij + b) + ci

for i = (1, ..., n), where j indexes the input activations.

Args:
weights_transposed: Weights already in [in_features, out_features] format
"""
# No transpose needed - weights already transposed by caller
weights_transposed = weights.T
weights_int32 = weights_transposed.to(torch.int32)
offset_weights = weights_int32 + weight_offset
kernel_sum = torch.sum(offset_weights, dim=0, keepdim=True, dtype=torch.int32)
Expand DownExpand Up@@ -115,12 +110,8 @@ def _get_linear_replacement(self, node):
if len(node.args) > 2
else None
)
# Transpose weights once from PyTorch format [out_features, in_features]
# to CMSIS-NN format [in_features, out_features]
weights_transposed = weights_tensor.T.contiguous()
# Pass already-transposed weights to kernel_sum computation
kernel_sum_tensor = self._compute_kernel_sum(
weights_transposed, bias_tensor, -input_zp, -weight_zp
weights_tensor, bias_tensor, -input_zp, -weight_zp
)
with node.graph.inserting_after(weights):
kernel_sum = create_constant_placeholder(
Expand All@@ -131,17 +122,9 @@ def _get_linear_replacement(self, node):
kernel_sum_tensor,
)

weights_transposed_node = create_constant_placeholder(
self.exported_program,
node.graph,
node.name + "_weights_transposed",
InputKind.PARAMETER,
weights_transposed,
)

args = (
node.args[0],
weights_transposed_node,
weights,
None,
kernel_sum,
-input_zp,
Expand Down