fix transpose / permutations fusion pass#10780

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Merged
facebook-github-bot merged 1 commit into from
May 9, 2025
Merged

fix transpose / permutations fusion pass #10780

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13 changes: 11 additions & 2 deletions backends/cadence/aot/fuse_ops.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -885,6 +885,9 @@ class FuseTransposeOrPermuteOpPairsPass(FuseOpPairsAcrossBranchesPass):
"""
Fuse transpose or permute op pairs to a single view op.
(transpose or permutation) -> (quant or dequant) -> (transpose or permutation)
This happens when op2(op1) == identity, modulo unitary dimensions.
'unitary dimensions' example: a tensor of shape [1, 5, 30] is equivalent (in memory) to [5, 1, 30]
so transpose(1, 2) then transpose(0, 2) is a pseudo identity and should be fused.
"""

# A list of ops that can be bypassed when looking for a
Expand All@@ -908,7 +911,7 @@ def can_fuse_for_chain(
if not super().can_fuse_for_chain(producer, consumer, consumer_op_packets):
return False

# checking that permut2(permut1(identify)) == identity
# checking that permut2(permut1(identity)) == identity, modulo unitary dimensions
input_shape = cast(torch.fx.Node, producer.args[0]).meta["val"].shape
ident_dims = list(range(len(input_shape)))
# this mapping helps to handle both transpose and permutations
Expand All@@ -918,14 +921,20 @@ def can_fuse_for_chain(
}
in_dims = f[producer.target](producer, ident_dims)
out_dims = f[consumer.target](consumer, in_dims)
return out_dims == ident_dims
# Filtering out unitary dimensions
non_unit_ident_dims = [dim for dim in ident_dims if input_shape[dim] != 1]
non_unit_out_dims = [dim for dim in out_dims if input_shape[dim] != 1]
return non_unit_out_dims == non_unit_ident_dims

def get_fused_node(
self,
producer: torch.fx.Node,
consumer: torch.fx.Node,
graph_module: torch.fx.GraphModule,
) -> torch.fx.Node:
# This step is important because of how we can fuse transpositions that are not perfectly
# reverse one of another but will be fused if there are unitary dimensions.
# The fused operation must have the same output shape as the consumer.
output_shape = consumer.meta["val"].shape
with graph_module.graph.inserting_after(consumer):
view = graph_module.graph.call_function(
Expand Down
44 changes: 44 additions & 0 deletions backends/cadence/aot/tests/test_fusion_ops_passes.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -584,6 +584,28 @@ def _create_operator(
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
),
# transpose -> quant -> transpose is not the reverse BUT there is a UNITARY dimension
# so it ends up being the same on memory => fuse
(
True,
[0, 1],
True,
[0, 2],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
True,
[5, 40, 1],
),
# transpose -> quant -> transpose is not the reverse, and unitary dimensions
# don't help => don't fuse
(
True,
[0, 1],
True,
[1, 3],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
[5, 40, 1, 4],
),
# permutation -> quant -> opposite permutation => fuse
(
False,
Expand DownExpand Up@@ -622,6 +644,28 @@ def _create_operator(
False,
[4, 4, 4],
),
# permutation -> quant -> a non reverse permutation BUT there is a UNITARY dimension
# so it ends up being the same on memory => fuse
(
False,
[1, 3, 2, 0],
False,
[3, 2, 1, 0],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
True,
[3, 1, 8, 10],
),
# permutation -> quant -> a non reverse permutation, and unitary dimensions
# don't help => don't fuse
(
False,
[1, 3, 2, 0],
False,
[3, 1, 2, 0],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
[3, 1, 8, 10],
),
# transpose -> quant -> transpose as a permutation => fuse
(
True,
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

fix transpose / permutations fusion pass#10780

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Merged
facebook-github-bot merged 1 commit into from
May 9, 2025
Merged

fix transpose / permutations fusion pass #10780

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13 changes: 11 additions & 2 deletions backends/cadence/aot/fuse_ops.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -885,6 +885,9 @@ class FuseTransposeOrPermuteOpPairsPass(FuseOpPairsAcrossBranchesPass):
"""
Fuse transpose or permute op pairs to a single view op.
(transpose or permutation) -> (quant or dequant) -> (transpose or permutation)
This happens when op2(op1) == identity, modulo unitary dimensions.
'unitary dimensions' example: a tensor of shape [1, 5, 30] is equivalent (in memory) to [5, 1, 30]
so transpose(1, 2) then transpose(0, 2) is a pseudo identity and should be fused.
"""

# A list of ops that can be bypassed when looking for a
Expand All@@ -908,7 +911,7 @@ def can_fuse_for_chain(
if not super().can_fuse_for_chain(producer, consumer, consumer_op_packets):
return False

# checking that permut2(permut1(identify)) == identity
# checking that permut2(permut1(identity)) == identity, modulo unitary dimensions
input_shape = cast(torch.fx.Node, producer.args[0]).meta["val"].shape
ident_dims = list(range(len(input_shape)))
# this mapping helps to handle both transpose and permutations
Expand All@@ -918,14 +921,20 @@ def can_fuse_for_chain(
}
in_dims = f[producer.target](producer, ident_dims)
out_dims = f[consumer.target](consumer, in_dims)
return out_dims == ident_dims
# Filtering out unitary dimensions
non_unit_ident_dims = [dim for dim in ident_dims if input_shape[dim] != 1]
non_unit_out_dims = [dim for dim in out_dims if input_shape[dim] != 1]
return non_unit_out_dims == non_unit_ident_dims

def get_fused_node(
self,
producer: torch.fx.Node,
consumer: torch.fx.Node,
graph_module: torch.fx.GraphModule,
) -> torch.fx.Node:
# This step is important because of how we can fuse transpositions that are not perfectly
# reverse one of another but will be fused if there are unitary dimensions.
# The fused operation must have the same output shape as the consumer.
output_shape = consumer.meta["val"].shape
with graph_module.graph.inserting_after(consumer):
view = graph_module.graph.call_function(
Expand Down
44 changes: 44 additions & 0 deletions backends/cadence/aot/tests/test_fusion_ops_passes.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -584,6 +584,28 @@ def _create_operator(
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
),
# transpose -> quant -> transpose is not the reverse BUT there is a UNITARY dimension
# so it ends up being the same on memory => fuse
(
True,
[0, 1],
True,
[0, 2],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
True,
[5, 40, 1],
),
# transpose -> quant -> transpose is not the reverse, and unitary dimensions
# don't help => don't fuse
(
True,
[0, 1],
True,
[1, 3],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
[5, 40, 1, 4],
),
# permutation -> quant -> opposite permutation => fuse
(
False,
Expand DownExpand Up@@ -622,6 +644,28 @@ def _create_operator(
False,
[4, 4, 4],
),
# permutation -> quant -> a non reverse permutation BUT there is a UNITARY dimension
# so it ends up being the same on memory => fuse
(
False,
[1, 3, 2, 0],
False,
[3, 2, 1, 0],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
True,
[3, 1, 8, 10],
),
# permutation -> quant -> a non reverse permutation, and unitary dimensions
# don't help => don't fuse
(
False,
[1, 3, 2, 0],
False,
[3, 1, 2, 0],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
[3, 1, 8, 10],
),
# transpose -> quant -> transpose as a permutation => fuse
(
True,
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

fix transpose / permutations fusion pass#10780

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.

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Already on GitHub? Sign in to your account

Merged
facebook-github-bot merged 1 commit into from
May 9, 2025
Merged

fix transpose / permutations fusion pass #10780

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13 changes: 11 additions & 2 deletions backends/cadence/aot/fuse_ops.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -885,6 +885,9 @@ class FuseTransposeOrPermuteOpPairsPass(FuseOpPairsAcrossBranchesPass):
"""
Fuse transpose or permute op pairs to a single view op.
(transpose or permutation) -> (quant or dequant) -> (transpose or permutation)
This happens when op2(op1) == identity, modulo unitary dimensions.
'unitary dimensions' example: a tensor of shape [1, 5, 30] is equivalent (in memory) to [5, 1, 30]
so transpose(1, 2) then transpose(0, 2) is a pseudo identity and should be fused.
"""

# A list of ops that can be bypassed when looking for a
Expand All@@ -908,7 +911,7 @@ def can_fuse_for_chain(
if not super().can_fuse_for_chain(producer, consumer, consumer_op_packets):
return False

# checking that permut2(permut1(identify)) == identity
# checking that permut2(permut1(identity)) == identity, modulo unitary dimensions
input_shape = cast(torch.fx.Node, producer.args[0]).meta["val"].shape
ident_dims = list(range(len(input_shape)))
# this mapping helps to handle both transpose and permutations
Expand All@@ -918,14 +921,20 @@ def can_fuse_for_chain(
}
in_dims = f[producer.target](producer, ident_dims)
out_dims = f[consumer.target](consumer, in_dims)
return out_dims == ident_dims
# Filtering out unitary dimensions
non_unit_ident_dims = [dim for dim in ident_dims if input_shape[dim] != 1]
non_unit_out_dims = [dim for dim in out_dims if input_shape[dim] != 1]
return non_unit_out_dims == non_unit_ident_dims

def get_fused_node(
self,
producer: torch.fx.Node,
consumer: torch.fx.Node,
graph_module: torch.fx.GraphModule,
) -> torch.fx.Node:
# This step is important because of how we can fuse transpositions that are not perfectly
# reverse one of another but will be fused if there are unitary dimensions.
# The fused operation must have the same output shape as the consumer.
output_shape = consumer.meta["val"].shape
with graph_module.graph.inserting_after(consumer):
view = graph_module.graph.call_function(
Expand Down
44 changes: 44 additions & 0 deletions backends/cadence/aot/tests/test_fusion_ops_passes.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -584,6 +584,28 @@ def _create_operator(
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
),
# transpose -> quant -> transpose is not the reverse BUT there is a UNITARY dimension
# so it ends up being the same on memory => fuse
(
True,
[0, 1],
True,
[0, 2],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
True,
[5, 40, 1],
),
# transpose -> quant -> transpose is not the reverse, and unitary dimensions
# don't help => don't fuse
(
True,
[0, 1],
True,
[1, 3],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
[5, 40, 1, 4],
),
# permutation -> quant -> opposite permutation => fuse
(
False,
Expand DownExpand Up@@ -622,6 +644,28 @@ def _create_operator(
False,
[4, 4, 4],
),
# permutation -> quant -> a non reverse permutation BUT there is a UNITARY dimension
# so it ends up being the same on memory => fuse
(
False,
[1, 3, 2, 0],
False,
[3, 2, 1, 0],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
True,
[3, 1, 8, 10],
),
# permutation -> quant -> a non reverse permutation, and unitary dimensions
# don't help => don't fuse
(
False,
[1, 3, 2, 0],
False,
[3, 1, 2, 0],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
[3, 1, 8, 10],
),
# transpose -> quant -> transpose as a permutation => fuse
(
True,
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

fix transpose / permutations fusion pass#10780

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

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Already on GitHub? Sign in to your account

Merged
facebook-github-bot merged 1 commit into from
May 9, 2025
Merged

fix transpose / permutations fusion pass #10780

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13 changes: 11 additions & 2 deletions backends/cadence/aot/fuse_ops.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -885,6 +885,9 @@ class FuseTransposeOrPermuteOpPairsPass(FuseOpPairsAcrossBranchesPass):
"""
Fuse transpose or permute op pairs to a single view op.
(transpose or permutation) -> (quant or dequant) -> (transpose or permutation)
This happens when op2(op1) == identity, modulo unitary dimensions.
'unitary dimensions' example: a tensor of shape [1, 5, 30] is equivalent (in memory) to [5, 1, 30]
so transpose(1, 2) then transpose(0, 2) is a pseudo identity and should be fused.
"""

# A list of ops that can be bypassed when looking for a
Expand All@@ -908,7 +911,7 @@ def can_fuse_for_chain(
if not super().can_fuse_for_chain(producer, consumer, consumer_op_packets):
return False

# checking that permut2(permut1(identify)) == identity
# checking that permut2(permut1(identity)) == identity, modulo unitary dimensions
input_shape = cast(torch.fx.Node, producer.args[0]).meta["val"].shape
ident_dims = list(range(len(input_shape)))
# this mapping helps to handle both transpose and permutations
Expand All@@ -918,14 +921,20 @@ def can_fuse_for_chain(
}
in_dims = f[producer.target](producer, ident_dims)
out_dims = f[consumer.target](consumer, in_dims)
return out_dims == ident_dims
# Filtering out unitary dimensions
non_unit_ident_dims = [dim for dim in ident_dims if input_shape[dim] != 1]
non_unit_out_dims = [dim for dim in out_dims if input_shape[dim] != 1]
return non_unit_out_dims == non_unit_ident_dims

def get_fused_node(
self,
producer: torch.fx.Node,
consumer: torch.fx.Node,
graph_module: torch.fx.GraphModule,
) -> torch.fx.Node:
# This step is important because of how we can fuse transpositions that are not perfectly
# reverse one of another but will be fused if there are unitary dimensions.
# The fused operation must have the same output shape as the consumer.
output_shape = consumer.meta["val"].shape
with graph_module.graph.inserting_after(consumer):
view = graph_module.graph.call_function(
Expand Down
44 changes: 44 additions & 0 deletions backends/cadence/aot/tests/test_fusion_ops_passes.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -584,6 +584,28 @@ def _create_operator(
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
),
# transpose -> quant -> transpose is not the reverse BUT there is a UNITARY dimension
# so it ends up being the same on memory => fuse
(
True,
[0, 1],
True,
[0, 2],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
True,
[5, 40, 1],
),
# transpose -> quant -> transpose is not the reverse, and unitary dimensions
# don't help => don't fuse
(
True,
[0, 1],
True,
[1, 3],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
[5, 40, 1, 4],
),
# permutation -> quant -> opposite permutation => fuse
(
False,
Expand DownExpand Up@@ -622,6 +644,28 @@ def _create_operator(
False,
[4, 4, 4],
),
# permutation -> quant -> a non reverse permutation BUT there is a UNITARY dimension
# so it ends up being the same on memory => fuse
(
False,
[1, 3, 2, 0],
False,
[3, 2, 1, 0],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
True,
[3, 1, 8, 10],
),
# permutation -> quant -> a non reverse permutation, and unitary dimensions
# don't help => don't fuse
(
False,
[1, 3, 2, 0],
False,
[3, 1, 2, 0],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
[3, 1, 8, 10],
),
# transpose -> quant -> transpose as a permutation => fuse
(
True,
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

fix transpose / permutations fusion pass#10780

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Merged
facebook-github-bot merged 1 commit into from
May 9, 2025
Merged

fix transpose / permutations fusion pass #10780

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13 changes: 11 additions & 2 deletions backends/cadence/aot/fuse_ops.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -885,6 +885,9 @@ class FuseTransposeOrPermuteOpPairsPass(FuseOpPairsAcrossBranchesPass):
"""
Fuse transpose or permute op pairs to a single view op.
(transpose or permutation) -> (quant or dequant) -> (transpose or permutation)
This happens when op2(op1) == identity, modulo unitary dimensions.
'unitary dimensions' example: a tensor of shape [1, 5, 30] is equivalent (in memory) to [5, 1, 30]
so transpose(1, 2) then transpose(0, 2) is a pseudo identity and should be fused.
"""

# A list of ops that can be bypassed when looking for a
Expand All@@ -908,7 +911,7 @@ def can_fuse_for_chain(
if not super().can_fuse_for_chain(producer, consumer, consumer_op_packets):
return False

# checking that permut2(permut1(identify)) == identity
# checking that permut2(permut1(identity)) == identity, modulo unitary dimensions
input_shape = cast(torch.fx.Node, producer.args[0]).meta["val"].shape
ident_dims = list(range(len(input_shape)))
# this mapping helps to handle both transpose and permutations
Expand All@@ -918,14 +921,20 @@ def can_fuse_for_chain(
}
in_dims = f[producer.target](producer, ident_dims)
out_dims = f[consumer.target](consumer, in_dims)
return out_dims == ident_dims
# Filtering out unitary dimensions
non_unit_ident_dims = [dim for dim in ident_dims if input_shape[dim] != 1]
non_unit_out_dims = [dim for dim in out_dims if input_shape[dim] != 1]
return non_unit_out_dims == non_unit_ident_dims

def get_fused_node(
self,
producer: torch.fx.Node,
consumer: torch.fx.Node,
graph_module: torch.fx.GraphModule,
) -> torch.fx.Node:
# This step is important because of how we can fuse transpositions that are not perfectly
# reverse one of another but will be fused if there are unitary dimensions.
# The fused operation must have the same output shape as the consumer.
output_shape = consumer.meta["val"].shape
with graph_module.graph.inserting_after(consumer):
view = graph_module.graph.call_function(
Expand Down
44 changes: 44 additions & 0 deletions backends/cadence/aot/tests/test_fusion_ops_passes.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -584,6 +584,28 @@ def _create_operator(
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
),
# transpose -> quant -> transpose is not the reverse BUT there is a UNITARY dimension
# so it ends up being the same on memory => fuse
(
True,
[0, 1],
True,
[0, 2],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
True,
[5, 40, 1],
),
# transpose -> quant -> transpose is not the reverse, and unitary dimensions
# don't help => don't fuse
(
True,
[0, 1],
True,
[1, 3],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
[5, 40, 1, 4],
),
# permutation -> quant -> opposite permutation => fuse
(
False,
Expand DownExpand Up@@ -622,6 +644,28 @@ def _create_operator(
False,
[4, 4, 4],
),
# permutation -> quant -> a non reverse permutation BUT there is a UNITARY dimension
# so it ends up being the same on memory => fuse
(
False,
[1, 3, 2, 0],
False,
[3, 2, 1, 0],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
True,
[3, 1, 8, 10],
),
# permutation -> quant -> a non reverse permutation, and unitary dimensions
# don't help => don't fuse
(
False,
[1, 3, 2, 0],
False,
[3, 1, 2, 0],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
[3, 1, 8, 10],
),
# transpose -> quant -> transpose as a permutation => fuse
(
True,
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

fix transpose / permutations fusion pass#10780

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Merged
facebook-github-bot merged 1 commit into from
May 9, 2025
Merged

fix transpose / permutations fusion pass #10780

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13 changes: 11 additions & 2 deletions backends/cadence/aot/fuse_ops.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -885,6 +885,9 @@ class FuseTransposeOrPermuteOpPairsPass(FuseOpPairsAcrossBranchesPass):
"""
Fuse transpose or permute op pairs to a single view op.
(transpose or permutation) -> (quant or dequant) -> (transpose or permutation)
This happens when op2(op1) == identity, modulo unitary dimensions.
'unitary dimensions' example: a tensor of shape [1, 5, 30] is equivalent (in memory) to [5, 1, 30]
so transpose(1, 2) then transpose(0, 2) is a pseudo identity and should be fused.
"""

# A list of ops that can be bypassed when looking for a
Expand All@@ -908,7 +911,7 @@ def can_fuse_for_chain(
if not super().can_fuse_for_chain(producer, consumer, consumer_op_packets):
return False

# checking that permut2(permut1(identify)) == identity
# checking that permut2(permut1(identity)) == identity, modulo unitary dimensions
input_shape = cast(torch.fx.Node, producer.args[0]).meta["val"].shape
ident_dims = list(range(len(input_shape)))
# this mapping helps to handle both transpose and permutations
Expand All@@ -918,14 +921,20 @@ def can_fuse_for_chain(
}
in_dims = f[producer.target](producer, ident_dims)
out_dims = f[consumer.target](consumer, in_dims)
return out_dims == ident_dims
# Filtering out unitary dimensions
non_unit_ident_dims = [dim for dim in ident_dims if input_shape[dim] != 1]
non_unit_out_dims = [dim for dim in out_dims if input_shape[dim] != 1]
return non_unit_out_dims == non_unit_ident_dims

def get_fused_node(
self,
producer: torch.fx.Node,
consumer: torch.fx.Node,
graph_module: torch.fx.GraphModule,
) -> torch.fx.Node:
# This step is important because of how we can fuse transpositions that are not perfectly
# reverse one of another but will be fused if there are unitary dimensions.
# The fused operation must have the same output shape as the consumer.
output_shape = consumer.meta["val"].shape
with graph_module.graph.inserting_after(consumer):
view = graph_module.graph.call_function(
Expand Down
44 changes: 44 additions & 0 deletions backends/cadence/aot/tests/test_fusion_ops_passes.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -584,6 +584,28 @@ def _create_operator(
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
),
# transpose -> quant -> transpose is not the reverse BUT there is a UNITARY dimension
# so it ends up being the same on memory => fuse
(
True,
[0, 1],
True,
[0, 2],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
True,
[5, 40, 1],
),
# transpose -> quant -> transpose is not the reverse, and unitary dimensions
# don't help => don't fuse
(
True,
[0, 1],
True,
[1, 3],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
[5, 40, 1, 4],
),
# permutation -> quant -> opposite permutation => fuse
(
False,
Expand DownExpand Up@@ -622,6 +644,28 @@ def _create_operator(
False,
[4, 4, 4],
),
# permutation -> quant -> a non reverse permutation BUT there is a UNITARY dimension
# so it ends up being the same on memory => fuse
(
False,
[1, 3, 2, 0],
False,
[3, 2, 1, 0],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
True,
[3, 1, 8, 10],
),
# permutation -> quant -> a non reverse permutation, and unitary dimensions
# don't help => don't fuse
(
False,
[1, 3, 2, 0],
False,
[3, 1, 2, 0],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
[3, 1, 8, 10],
),
# transpose -> quant -> transpose as a permutation => fuse
(
True,
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

fix transpose / permutations fusion pass#10780

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

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

Already on GitHub? Sign in to your account

Merged
facebook-github-bot merged 1 commit into from
May 9, 2025
Merged

fix transpose / permutations fusion pass #10780

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13 changes: 11 additions & 2 deletions backends/cadence/aot/fuse_ops.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -885,6 +885,9 @@ class FuseTransposeOrPermuteOpPairsPass(FuseOpPairsAcrossBranchesPass):
"""
Fuse transpose or permute op pairs to a single view op.
(transpose or permutation) -> (quant or dequant) -> (transpose or permutation)
This happens when op2(op1) == identity, modulo unitary dimensions.
'unitary dimensions' example: a tensor of shape [1, 5, 30] is equivalent (in memory) to [5, 1, 30]
so transpose(1, 2) then transpose(0, 2) is a pseudo identity and should be fused.
"""

# A list of ops that can be bypassed when looking for a
Expand All@@ -908,7 +911,7 @@ def can_fuse_for_chain(
if not super().can_fuse_for_chain(producer, consumer, consumer_op_packets):
return False

# checking that permut2(permut1(identify)) == identity
# checking that permut2(permut1(identity)) == identity, modulo unitary dimensions
input_shape = cast(torch.fx.Node, producer.args[0]).meta["val"].shape
ident_dims = list(range(len(input_shape)))
# this mapping helps to handle both transpose and permutations
Expand All@@ -918,14 +921,20 @@ def can_fuse_for_chain(
}
in_dims = f[producer.target](producer, ident_dims)
out_dims = f[consumer.target](consumer, in_dims)
return out_dims == ident_dims
# Filtering out unitary dimensions
non_unit_ident_dims = [dim for dim in ident_dims if input_shape[dim] != 1]
non_unit_out_dims = [dim for dim in out_dims if input_shape[dim] != 1]
return non_unit_out_dims == non_unit_ident_dims

def get_fused_node(
self,
producer: torch.fx.Node,
consumer: torch.fx.Node,
graph_module: torch.fx.GraphModule,
) -> torch.fx.Node:
# This step is important because of how we can fuse transpositions that are not perfectly
# reverse one of another but will be fused if there are unitary dimensions.
# The fused operation must have the same output shape as the consumer.
output_shape = consumer.meta["val"].shape
with graph_module.graph.inserting_after(consumer):
view = graph_module.graph.call_function(
Expand Down
44 changes: 44 additions & 0 deletions backends/cadence/aot/tests/test_fusion_ops_passes.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -584,6 +584,28 @@ def _create_operator(
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
),
# transpose -> quant -> transpose is not the reverse BUT there is a UNITARY dimension
# so it ends up being the same on memory => fuse
(
True,
[0, 1],
True,
[0, 2],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
True,
[5, 40, 1],
),
# transpose -> quant -> transpose is not the reverse, and unitary dimensions
# don't help => don't fuse
(
True,
[0, 1],
True,
[1, 3],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
[5, 40, 1, 4],
),
# permutation -> quant -> opposite permutation => fuse
(
False,
Expand DownExpand Up@@ -622,6 +644,28 @@ def _create_operator(
False,
[4, 4, 4],
),
# permutation -> quant -> a non reverse permutation BUT there is a UNITARY dimension
# so it ends up being the same on memory => fuse
(
False,
[1, 3, 2, 0],
False,
[3, 2, 1, 0],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
True,
[3, 1, 8, 10],
),
# permutation -> quant -> a non reverse permutation, and unitary dimensions
# don't help => don't fuse
(
False,
[1, 3, 2, 0],
False,
[3, 1, 2, 0],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
[3, 1, 8, 10],
),
# transpose -> quant -> transpose as a permutation => fuse
(
True,
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

fix transpose / permutations fusion pass#10780

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.

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Merged
facebook-github-bot merged 1 commit into from
May 9, 2025
Merged

fix transpose / permutations fusion pass #10780

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13 changes: 11 additions & 2 deletions backends/cadence/aot/fuse_ops.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -885,6 +885,9 @@ class FuseTransposeOrPermuteOpPairsPass(FuseOpPairsAcrossBranchesPass):
"""
Fuse transpose or permute op pairs to a single view op.
(transpose or permutation) -> (quant or dequant) -> (transpose or permutation)
This happens when op2(op1) == identity, modulo unitary dimensions.
'unitary dimensions' example: a tensor of shape [1, 5, 30] is equivalent (in memory) to [5, 1, 30]
so transpose(1, 2) then transpose(0, 2) is a pseudo identity and should be fused.
"""

# A list of ops that can be bypassed when looking for a
Expand All@@ -908,7 +911,7 @@ def can_fuse_for_chain(
if not super().can_fuse_for_chain(producer, consumer, consumer_op_packets):
return False

# checking that permut2(permut1(identify)) == identity
# checking that permut2(permut1(identity)) == identity, modulo unitary dimensions
input_shape = cast(torch.fx.Node, producer.args[0]).meta["val"].shape
ident_dims = list(range(len(input_shape)))
# this mapping helps to handle both transpose and permutations
Expand All@@ -918,14 +921,20 @@ def can_fuse_for_chain(
}
in_dims = f[producer.target](producer, ident_dims)
out_dims = f[consumer.target](consumer, in_dims)
return out_dims == ident_dims
# Filtering out unitary dimensions
non_unit_ident_dims = [dim for dim in ident_dims if input_shape[dim] != 1]
non_unit_out_dims = [dim for dim in out_dims if input_shape[dim] != 1]
return non_unit_out_dims == non_unit_ident_dims

def get_fused_node(
self,
producer: torch.fx.Node,
consumer: torch.fx.Node,
graph_module: torch.fx.GraphModule,
) -> torch.fx.Node:
# This step is important because of how we can fuse transpositions that are not perfectly
# reverse one of another but will be fused if there are unitary dimensions.
# The fused operation must have the same output shape as the consumer.
output_shape = consumer.meta["val"].shape
with graph_module.graph.inserting_after(consumer):
view = graph_module.graph.call_function(
Expand Down
44 changes: 44 additions & 0 deletions backends/cadence/aot/tests/test_fusion_ops_passes.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -584,6 +584,28 @@ def _create_operator(
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
),
# transpose -> quant -> transpose is not the reverse BUT there is a UNITARY dimension
# so it ends up being the same on memory => fuse
(
True,
[0, 1],
True,
[0, 2],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
True,
[5, 40, 1],
),
# transpose -> quant -> transpose is not the reverse, and unitary dimensions
# don't help => don't fuse
(
True,
[0, 1],
True,
[1, 3],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
[5, 40, 1, 4],
),
# permutation -> quant -> opposite permutation => fuse
(
False,
Expand DownExpand Up@@ -622,6 +644,28 @@ def _create_operator(
False,
[4, 4, 4],
),
# permutation -> quant -> a non reverse permutation BUT there is a UNITARY dimension
# so it ends up being the same on memory => fuse
(
False,
[1, 3, 2, 0],
False,
[3, 2, 1, 0],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
True,
[3, 1, 8, 10],
),
# permutation -> quant -> a non reverse permutation, and unitary dimensions
# don't help => don't fuse
(
False,
[1, 3, 2, 0],
False,
[3, 1, 2, 0],
exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
False,
[3, 1, 8, 10],
),
# transpose -> quant -> transpose as a permutation => fuse
(
True,
Expand Down