Remove redundant pt2_mode=True#54

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

Closed
tugsbayasgalan wants to merge 1 commit into from
Closed

Remove redundant pt2_mode=True #54

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
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
4 changes: 2 additions & 2 deletions backends/qnnpack/partition/support_patterns.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -48,9 +48,9 @@ def get_dynamic_quantized_graph(f, example_inputs, dynamic_shape=False):
# Convert module
converted_mod = _convert_to_reference_decomposed_fx(prepared_mod)
if dynamic_shape:
capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=True)
capture_config = CaptureConfig(enable_dynamic_shape=True)
else:
capture_config = CaptureConfig(pt2_mode=True)
capture_config = CaptureConfig()
# EXIR trace
gm = (
exir.capture(converted_mod, example_inputs, capture_config)
Expand Down
26 changes: 10 additions & 16 deletions backends/qnnpack/test/test_qnnpack.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -83,7 +83,7 @@ def test_qnnpack_per_channel_dynamic_mm(self):
)

# Step 2: EXIR capturing
capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
capture_config = CaptureConfig(enable_dynamic_shape=False)
captured_mod = exir.capture(
converted_mod, example_inputs, config=capture_config
).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -115,9 +115,7 @@ def forward(self, x):

composite_model(*example_inputs)
program = (
exir.capture(
composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
)
exir.capture(composite_model, example_inputs, exir.CaptureConfig())
.to_edge(EDGE_COMPILE_CONFIG)
.to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
.program
Expand DownExpand Up@@ -159,7 +157,7 @@ def test_qnnpack_per_channel_dynamic_qlinear(self):
)

# Step 2: EXIR capturing
capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
capture_config = CaptureConfig(enable_dynamic_shape=False)
captured_mod = exir.capture(
converted_mod, example_inputs, config=capture_config
).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -202,9 +200,7 @@ def forward(self, x):

composite_model(*example_inputs)
program = (
exir.capture(
composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
)
exir.capture(composite_model, example_inputs, exir.CaptureConfig())
.to_edge(EDGE_COMPILE_CONFIG)
.to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
.program
Expand DownExpand Up@@ -246,7 +242,7 @@ def test_qnnpack_per_tensor_dynamic_mm(self):
)

# Step 2: EXIR capturing
capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
capture_config = CaptureConfig(enable_dynamic_shape=False)
captured_mod = exir.capture(
converted_mod, example_inputs, config=capture_config
).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -321,7 +317,7 @@ def test_qnnpack_per_tensor_dynamic_qlinear(self):
)

# Step 2: EXIR capturing
capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
capture_config = CaptureConfig(enable_dynamic_shape=False)
captured_mod = exir.capture(
converted_mod, example_inputs, config=capture_config
).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -406,7 +402,7 @@ def test_qnnpack_per_channel_dynamic_mm_with_dynamic_shape(self):
)

# Step 2: EXIR capturing
capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=True)
capture_config = CaptureConfig(enable_dynamic_shape=True)
captured_mod = exir.capture(
converted_mod, example_inputs, config=capture_config
).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -438,9 +434,7 @@ def forward(self, x):

composite_model(*example_inputs)
program = (
exir.capture(
composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
)
exir.capture(composite_model, example_inputs, exir.CaptureConfig())
.to_edge(EDGE_COMPILE_CONFIG)
.to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
.program
Expand DownExpand Up@@ -483,7 +477,7 @@ def test_qnnpack_per_channel_dynamic_qlinear_via_partitioner(self):
)

# Step 2: EXIR capturing
capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
capture_config = CaptureConfig(enable_dynamic_shape=False)
captured_mod = exir.capture(
converted_mod, example_inputs, config=capture_config
).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -538,7 +532,7 @@ def test_qnnpack_per_channel_dynamic_qlinear_via_partitioner(self):
# composite_model(*example_inputs)
# program = (
# exir.capture(
# composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
# composite_model, example_inputs, exir.CaptureConfig()
# )
# .to_edge(EDGE_COMPILE_CONFIG)
# .to_executorch()
Expand Down
2 changes: 1 addition & 1 deletion backends/qnnpack/test/test_qnnpack_partitioner.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -54,7 +54,7 @@ def get_actual_dyanmic_quantized_graph(
converted_mod = _convert_to_reference_decomposed_fx(prepared_mod)

# Step 2: EXIR capturing
capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=dynamic_shape)
capture_config = CaptureConfig(enable_dynamic_shape=dynamic_shape)
dynamic_quantized_exir_graph = (
exir.capture(converted_mod, example_inputs, config=capture_config)
.to_edge(exir.EdgeCompileConfig(_check_ir_validity=False))
Expand Down
8 changes: 2 additions & 6 deletions backends/vulkan/test/test_vulkan_delegate.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -61,9 +61,7 @@ def lower_module_and_test_output(
the given sample inputs. It then runs the lowered module and compares its
outputs with the outputs of the eager module.
"""
edgeir_m = exir.capture(
module, sample_inputs, exir.CaptureConfig(pt2_mode=True)
).to_edge()
edgeir_m = exir.capture(module, sample_inputs, exir.CaptureConfig()).to_edge()
lowered_module = to_backend("VulkanBackend", edgeir_m.exported_program, [])

class WrappedModule(torch.nn.Module):
Expand All@@ -75,9 +73,7 @@ def forward(self, *args):
return self.one_module(*args)

program = (
exir.capture(
WrappedModule(), sample_inputs, exir.CaptureConfig(pt2_mode=True)
)
exir.capture(WrappedModule(), sample_inputs, exir.CaptureConfig())
.to_edge()
.to_executorch()
.program
Expand Down
4 changes: 2 additions & 2 deletions backends/xnnpack/partition/support_patterns.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -41,7 +41,7 @@
exir.capture(
add,
model_inputs,
config=CaptureConfig(pt2_mode=True, enable_dynamic_shape=True),
config=CaptureConfig(enable_dynamic_shape=True),
)
.to_edge().module
.graph
Expand All@@ -68,7 +68,7 @@


def _capture(module, example_inputs, pt_mode=True) -> torch.fx.GraphModule:
capture_config = CaptureConfig(pt2_mode=pt_mode, enable_dynamic_shape=False)
capture_config = CaptureConfig(enable_dynamic_shape=False)
edge_config = exir.EdgeCompileConfig(
_check_ir_validity=False,
passes=[DuplicateDequantNodePass()],
Expand Down
4 changes: 2 additions & 2 deletions backends/xnnpack/test/test_xnnpack.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -236,7 +236,7 @@ def test_xnnpack_backend_conv2d_dw(self):
conv.eval()
self.lower_and_test_with_partitioner(conv, example_inputs)

@torch.inference_mode() # TODO Use pt2_mode=True for capturing.
@torch.inference_mode() # TODO Use for capturing.
def test_xnnpack_backend_mm(self):
in_sizes = [1, 4, 4]
input_sizes = [4, 37, 17]
Expand DownExpand Up@@ -329,7 +329,7 @@ def forward(self, x, y):
)
self.lower_and_test_with_partitioner(module, model_inputs)

@torch.inference_mode() # TODO Use pt2_mode=True for capturing.
@torch.inference_mode() # TODO Use for capturing.
def test_xnnpack_backend_linear(self):
in_size = 2
input_size = 3
Expand Down
6 changes: 2 additions & 4 deletions backends/xnnpack/utils/configs.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -34,8 +34,6 @@ def get_xnnpack_executorch_backend_config(

def get_xnnpack_capture_config(dynamic_shape=False, enable_aot: Optional[bool] = None):
if enable_aot is None:
return CaptureConfig(pt2_mode=True, enable_dynamic_shape=dynamic_shape)
return CaptureConfig(enable_dynamic_shape=dynamic_shape)
else:
return CaptureConfig(
pt2_mode=True, enable_dynamic_shape=dynamic_shape, enable_aot=enable_aot
)
return CaptureConfig(enable_dynamic_shape=dynamic_shape, enable_aot=enable_aot)
2 changes: 1 addition & 1 deletion bundled_program/tests/common.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -229,7 +229,7 @@ def get_common_program() -> Tuple[Program, BundledConfig]:
DEFAULT_INT_INPUT,
)
program = (
exir.capture(eager_model, capture_input, CaptureConfig(pt2_mode=True))
exir.capture(eager_model, capture_input, CaptureConfig())
.to_edge()
.to_executorch()
.program
Expand Down
10 changes: 3 additions & 7 deletions exir/backend/test/demos/rpc/test_rpc.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -103,7 +103,7 @@ def test_delegate_whole_program(self):
simple_net = self.get_a_simple_net()
simple_net_input = simple_net.get_example_inputs()
exported_program = exir.capture(
simple_net, simple_net_input, exir.CaptureConfig(pt2_mode=True)
simple_net, simple_net_input, exir.CaptureConfig()
).to_edge(
exir.EdgeCompileConfig(
_check_ir_validity=False,
Expand All@@ -125,9 +125,7 @@ def forward(self, *args):
composite_model = CompositeModule()

exec_prog = (
exir.capture(
composite_model, simple_net_input, exir.CaptureConfig(pt2_mode=True)
)
exir.capture(composite_model, simple_net_input, exir.CaptureConfig())
.to_edge()
.to_executorch()
)
Expand DownExpand Up@@ -165,9 +163,7 @@ def forward(self, a, x, b):
model = Model()
inputs = (torch.ones(2, 2), torch.ones(2, 2), torch.ones(2, 2))

exported_program = exir.capture(
model, inputs, exir.CaptureConfig(pt2_mode=True)
).to_edge()
exported_program = exir.capture(model, inputs, exir.CaptureConfig()).to_edge()

# First lower to demo backend
demo_backend_lowered = exported_program
Expand Down
6 changes: 2 additions & 4 deletions exir/backend/test/demos/test_delegate_aten_mode.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -37,7 +37,7 @@ def forward(self, a, x, b):
add_mul_module = AddMulModule()
model_inputs = (torch.ones(2, 2), 2 * torch.ones(2, 2), 3 * torch.ones(2, 2))
edge_graph_module = exir.capture(
add_mul_module, model_inputs, exir.CaptureConfig(pt2_mode=True)
add_mul_module, model_inputs, exir.CaptureConfig()
).to_edge()
max_value = model_inputs[0].shape[0]
compile_specs = [CompileSpec("max_value", bytes([max_value]))]
Expand All@@ -60,9 +60,7 @@ def forward(self, a, x, b):
composite_model(*model_inputs)

exec_prog = (
exir.capture(
composite_model, model_inputs, exir.CaptureConfig(pt2_mode=True)
)
exir.capture(composite_model, model_inputs, exir.CaptureConfig())
.to_edge()
.to_executorch()
)
Expand Down
2 changes: 1 addition & 1 deletion exir/backend/test/demos/test_xnnpack_qnnpack.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -81,7 +81,7 @@ def forward(self, x, y):
)

# Step 2: EXIR capturing
capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
capture_config = CaptureConfig(enable_dynamic_shape=False)
captured_mod = exir.capture(
converted_mod, example_inputs, config=capture_config
).to_edge(
Expand Down
12 changes: 6 additions & 6 deletions exir/backend/test/hta_partitioner_demo.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -62,7 +62,7 @@ def forward(self, x_raw, h, c):
exir.capture(
LSTMConvPattern(),
(input_x, input_h, input_c),
exir.CaptureConfig(pt2_mode=True, enable_aot=True),
exir.CaptureConfig(enable_aot=True),
)
.to_edge(
# torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -74,7 +74,7 @@ def forward(self, x_raw, h, c):
exir.capture(
LSTMConvPattern(),
(input_x, input_h, input_c),
exir.CaptureConfig(pt2_mode=True),
exir.CaptureConfig(),
)
.to_edge(
# torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -90,7 +90,7 @@ def sub(x, y):
exir.capture(
sub,
(input_x, input_h),
exir.CaptureConfig(pt2_mode=True, enable_aot=True, _unlift=False),
exir.CaptureConfig(enable_aot=True, _unlift=False),
)
.to_edge(exir.EdgeCompileConfig(_use_edge_ops=True))
.exported_program.graph_module
Expand All@@ -99,7 +99,7 @@ def sub(x, y):
exir.capture(
sub,
(input_x, input_h),
exir.CaptureConfig(pt2_mode=True),
exir.CaptureConfig(),
)
.to_edge()
.exported_program.graph_module
Expand DownExpand Up@@ -236,7 +236,7 @@ def forward(self, x_raw, h, c):
exir.capture(
LSTMConvPattern(),
(input_x, input_h, input_c),
exir.CaptureConfig(pt2_mode=True, enable_aot=True),
exir.CaptureConfig(enable_aot=True),
)
.to_edge(
# torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -248,7 +248,7 @@ def forward(self, x_raw, h, c):
exir.capture(
LSTMConvPattern(),
(input_x, input_h, input_c),
exir.CaptureConfig(pt2_mode=True),
exir.CaptureConfig(),
)
.to_edge(
# torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand Down
Loading
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 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
Remove redundant pt2_mode=True#54

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

 Closed

tugsbayasgalan
wants to merge
1
commit into

from

 Closed


Remove redundant pt2_mode=True
#54
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


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


4 changes: 2 additions & 2 deletions
backends/qnnpack/partition/support_patterns.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -48,9 +48,9 @@ def get_dynamic_quantized_graph(f, example_inputs, dynamic_shape=False):
 # Convert module
 converted_mod = _convert_to_reference_decomposed_fx(prepared_mod)
 if dynamic_shape:
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=True)
 capture_config = CaptureConfig(enable_dynamic_shape=True)
 else:
 capture_config = CaptureConfig(pt2_mode=True)
 capture_config = CaptureConfig()
 # EXIR trace
 gm = (
 exir.capture(converted_mod, example_inputs, capture_config)
Expand Down

26 changes: 10 additions & 16 deletions
backends/qnnpack/test/test_qnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -83,7 +83,7 @@ def test_qnnpack_per_channel_dynamic_mm(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -115,9 +115,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -159,7 +157,7 @@ def test_qnnpack_per_channel_dynamic_qlinear(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -202,9 +200,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -246,7 +242,7 @@ def test_qnnpack_per_tensor_dynamic_mm(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -321,7 +317,7 @@ def test_qnnpack_per_tensor_dynamic_qlinear(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -406,7 +402,7 @@ def test_qnnpack_per_channel_dynamic_mm_with_dynamic_shape(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=True)
 capture_config = CaptureConfig(enable_dynamic_shape=True)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -438,9 +434,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -483,7 +477,7 @@ def test_qnnpack_per_channel_dynamic_qlinear_via_partitioner(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -538,7 +532,7 @@ def test_qnnpack_per_channel_dynamic_qlinear_via_partitioner(self):
 # composite_model(*example_inputs)
 # program = (
 # exir.capture(
 # composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 # composite_model, example_inputs, exir.CaptureConfig()
 # )
 # .to_edge(EDGE_COMPILE_CONFIG)
 # .to_executorch()
Expand Down

2 changes: 1 addition & 1 deletion
backends/qnnpack/test/test_qnnpack_partitioner.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -54,7 +54,7 @@ def get_actual_dyanmic_quantized_graph(
 converted_mod = _convert_to_reference_decomposed_fx(prepared_mod)

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=dynamic_shape)
 capture_config = CaptureConfig(enable_dynamic_shape=dynamic_shape)
 dynamic_quantized_exir_graph = (
 exir.capture(converted_mod, example_inputs, config=capture_config)
 .to_edge(exir.EdgeCompileConfig(_check_ir_validity=False))
Expand Down

8 changes: 2 additions & 6 deletions
backends/vulkan/test/test_vulkan_delegate.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -61,9 +61,7 @@ def lower_module_and_test_output(
 the given sample inputs. It then runs the lowered module and compares its
 outputs with the outputs of the eager module.
 """
 edgeir_m = exir.capture(
 module, sample_inputs, exir.CaptureConfig(pt2_mode=True)
 ).to_edge()
 edgeir_m = exir.capture(module, sample_inputs, exir.CaptureConfig()).to_edge()
 lowered_module = to_backend("VulkanBackend", edgeir_m.exported_program, [])

 class WrappedModule(torch.nn.Module):
Expand All@@ -75,9 +73,7 @@ def forward(self, *args):
 return self.one_module(*args)

 program = (
 exir.capture(
 WrappedModule(), sample_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(WrappedModule(), sample_inputs, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 .program
Expand Down

4 changes: 2 additions & 2 deletions
backends/xnnpack/partition/support_patterns.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -41,7 +41,7 @@
 exir.capture(
 add,
 model_inputs,
 config=CaptureConfig(pt2_mode=True, enable_dynamic_shape=True),
 config=CaptureConfig(enable_dynamic_shape=True),
 )
 .to_edge().module
 .graph
Expand All@@ -68,7 +68,7 @@


def _capture(module, example_inputs, pt_mode=True) -> torch.fx.GraphModule:
 capture_config = CaptureConfig(pt2_mode=pt_mode, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 edge_config = exir.EdgeCompileConfig(
 _check_ir_validity=False,
 passes=[DuplicateDequantNodePass()],
Expand Down

4 changes: 2 additions & 2 deletions
backends/xnnpack/test/test_xnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -236,7 +236,7 @@ def test_xnnpack_backend_conv2d_dw(self):
 conv.eval()
 self.lower_and_test_with_partitioner(conv, example_inputs)

 @torch.inference_mode() # TODO Use pt2_mode=True for capturing.
 @torch.inference_mode() # TODO Use for capturing.
 def test_xnnpack_backend_mm(self):
 in_sizes = [1, 4, 4]
 input_sizes = [4, 37, 17]
Expand DownExpand Up@@ -329,7 +329,7 @@ def forward(self, x, y):
 )
 self.lower_and_test_with_partitioner(module, model_inputs)

 @torch.inference_mode() # TODO Use pt2_mode=True for capturing.
 @torch.inference_mode() # TODO Use for capturing.
 def test_xnnpack_backend_linear(self):
 in_size = 2
 input_size = 3
Expand Down

6 changes: 2 additions & 4 deletions
backends/xnnpack/utils/configs.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,8 +34,6 @@ def get_xnnpack_executorch_backend_config(

def get_xnnpack_capture_config(dynamic_shape=False, enable_aot: Optional[bool] = None):
 if enable_aot is None:
 return CaptureConfig(pt2_mode=True, enable_dynamic_shape=dynamic_shape)
 return CaptureConfig(enable_dynamic_shape=dynamic_shape)
 else:
 return CaptureConfig(
 pt2_mode=True, enable_dynamic_shape=dynamic_shape, enable_aot=enable_aot
 )
 return CaptureConfig(enable_dynamic_shape=dynamic_shape, enable_aot=enable_aot)

2 changes: 1 addition & 1 deletion
bundled_program/tests/common.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -229,7 +229,7 @@ def get_common_program() -> Tuple[Program, BundledConfig]:
 DEFAULT_INT_INPUT,
 )
 program = (
 exir.capture(eager_model, capture_input, CaptureConfig(pt2_mode=True))
 exir.capture(eager_model, capture_input, CaptureConfig())
 .to_edge()
 .to_executorch()
 .program
Expand Down

10 changes: 3 additions & 7 deletions
exir/backend/test/demos/rpc/test_rpc.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -103,7 +103,7 @@ def test_delegate_whole_program(self):
 simple_net = self.get_a_simple_net()
 simple_net_input = simple_net.get_example_inputs()
 exported_program = exir.capture(
 simple_net, simple_net_input, exir.CaptureConfig(pt2_mode=True)
 simple_net, simple_net_input, exir.CaptureConfig()
 ).to_edge(
 exir.EdgeCompileConfig(
 _check_ir_validity=False,
Expand All@@ -125,9 +125,7 @@ def forward(self, *args):
 composite_model = CompositeModule()

 exec_prog = (
 exir.capture(
 composite_model, simple_net_input, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, simple_net_input, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 )
Expand DownExpand Up@@ -165,9 +163,7 @@ def forward(self, a, x, b):
 model = Model()
 inputs = (torch.ones(2, 2), torch.ones(2, 2), torch.ones(2, 2))

 exported_program = exir.capture(
 model, inputs, exir.CaptureConfig(pt2_mode=True)
 ).to_edge()
 exported_program = exir.capture(model, inputs, exir.CaptureConfig()).to_edge()

 # First lower to demo backend
 demo_backend_lowered = exported_program
Expand Down

6 changes: 2 additions & 4 deletions
exir/backend/test/demos/test_delegate_aten_mode.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -37,7 +37,7 @@ def forward(self, a, x, b):
 add_mul_module = AddMulModule()
 model_inputs = (torch.ones(2, 2), 2 * torch.ones(2, 2), 3 * torch.ones(2, 2))
 edge_graph_module = exir.capture(
 add_mul_module, model_inputs, exir.CaptureConfig(pt2_mode=True)
 add_mul_module, model_inputs, exir.CaptureConfig()
 ).to_edge()
 max_value = model_inputs[0].shape[0]
 compile_specs = [CompileSpec("max_value", bytes([max_value]))]
Expand All@@ -60,9 +60,7 @@ def forward(self, a, x, b):
 composite_model(*model_inputs)

 exec_prog = (
 exir.capture(
 composite_model, model_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, model_inputs, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 )
Expand Down

2 changes: 1 addition & 1 deletion
exir/backend/test/demos/test_xnnpack_qnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -81,7 +81,7 @@ def forward(self, x, y):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(
Expand Down

12 changes: 6 additions & 6 deletions
exir/backend/test/hta_partitioner_demo.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -62,7 +62,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True),
 exir.CaptureConfig(enable_aot=True),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -74,7 +74,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -90,7 +90,7 @@ def sub(x, y):
 exir.capture(
 sub,
 (input_x, input_h),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True, _unlift=False),
 exir.CaptureConfig(enable_aot=True, _unlift=False),
 )
 .to_edge(exir.EdgeCompileConfig(_use_edge_ops=True))
 .exported_program.graph_module
Expand All@@ -99,7 +99,7 @@ def sub(x, y):
 exir.capture(
 sub,
 (input_x, input_h),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge()
 .exported_program.graph_module
Expand DownExpand Up@@ -236,7 +236,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True),
 exir.CaptureConfig(enable_aot=True),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -248,7 +248,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand Down
Loading

, '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
Remove redundant pt2_mode=True#54

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

 Closed

tugsbayasgalan
wants to merge
1
commit into

from

 Closed


Remove redundant pt2_mode=True
#54
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


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


4 changes: 2 additions & 2 deletions
backends/qnnpack/partition/support_patterns.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -48,9 +48,9 @@ def get_dynamic_quantized_graph(f, example_inputs, dynamic_shape=False):
 # Convert module
 converted_mod = _convert_to_reference_decomposed_fx(prepared_mod)
 if dynamic_shape:
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=True)
 capture_config = CaptureConfig(enable_dynamic_shape=True)
 else:
 capture_config = CaptureConfig(pt2_mode=True)
 capture_config = CaptureConfig()
 # EXIR trace
 gm = (
 exir.capture(converted_mod, example_inputs, capture_config)
Expand Down

26 changes: 10 additions & 16 deletions
backends/qnnpack/test/test_qnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -83,7 +83,7 @@ def test_qnnpack_per_channel_dynamic_mm(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -115,9 +115,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -159,7 +157,7 @@ def test_qnnpack_per_channel_dynamic_qlinear(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -202,9 +200,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -246,7 +242,7 @@ def test_qnnpack_per_tensor_dynamic_mm(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -321,7 +317,7 @@ def test_qnnpack_per_tensor_dynamic_qlinear(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -406,7 +402,7 @@ def test_qnnpack_per_channel_dynamic_mm_with_dynamic_shape(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=True)
 capture_config = CaptureConfig(enable_dynamic_shape=True)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -438,9 +434,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -483,7 +477,7 @@ def test_qnnpack_per_channel_dynamic_qlinear_via_partitioner(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -538,7 +532,7 @@ def test_qnnpack_per_channel_dynamic_qlinear_via_partitioner(self):
 # composite_model(*example_inputs)
 # program = (
 # exir.capture(
 # composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 # composite_model, example_inputs, exir.CaptureConfig()
 # )
 # .to_edge(EDGE_COMPILE_CONFIG)
 # .to_executorch()
Expand Down

2 changes: 1 addition & 1 deletion
backends/qnnpack/test/test_qnnpack_partitioner.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -54,7 +54,7 @@ def get_actual_dyanmic_quantized_graph(
 converted_mod = _convert_to_reference_decomposed_fx(prepared_mod)

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=dynamic_shape)
 capture_config = CaptureConfig(enable_dynamic_shape=dynamic_shape)
 dynamic_quantized_exir_graph = (
 exir.capture(converted_mod, example_inputs, config=capture_config)
 .to_edge(exir.EdgeCompileConfig(_check_ir_validity=False))
Expand Down

8 changes: 2 additions & 6 deletions
backends/vulkan/test/test_vulkan_delegate.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -61,9 +61,7 @@ def lower_module_and_test_output(
 the given sample inputs. It then runs the lowered module and compares its
 outputs with the outputs of the eager module.
 """
 edgeir_m = exir.capture(
 module, sample_inputs, exir.CaptureConfig(pt2_mode=True)
 ).to_edge()
 edgeir_m = exir.capture(module, sample_inputs, exir.CaptureConfig()).to_edge()
 lowered_module = to_backend("VulkanBackend", edgeir_m.exported_program, [])

 class WrappedModule(torch.nn.Module):
Expand All@@ -75,9 +73,7 @@ def forward(self, *args):
 return self.one_module(*args)

 program = (
 exir.capture(
 WrappedModule(), sample_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(WrappedModule(), sample_inputs, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 .program
Expand Down

4 changes: 2 additions & 2 deletions
backends/xnnpack/partition/support_patterns.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -41,7 +41,7 @@
 exir.capture(
 add,
 model_inputs,
 config=CaptureConfig(pt2_mode=True, enable_dynamic_shape=True),
 config=CaptureConfig(enable_dynamic_shape=True),
 )
 .to_edge().module
 .graph
Expand All@@ -68,7 +68,7 @@


def _capture(module, example_inputs, pt_mode=True) -> torch.fx.GraphModule:
 capture_config = CaptureConfig(pt2_mode=pt_mode, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 edge_config = exir.EdgeCompileConfig(
 _check_ir_validity=False,
 passes=[DuplicateDequantNodePass()],
Expand Down

4 changes: 2 additions & 2 deletions
backends/xnnpack/test/test_xnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -236,7 +236,7 @@ def test_xnnpack_backend_conv2d_dw(self):
 conv.eval()
 self.lower_and_test_with_partitioner(conv, example_inputs)

 @torch.inference_mode() # TODO Use pt2_mode=True for capturing.
 @torch.inference_mode() # TODO Use for capturing.
 def test_xnnpack_backend_mm(self):
 in_sizes = [1, 4, 4]
 input_sizes = [4, 37, 17]
Expand DownExpand Up@@ -329,7 +329,7 @@ def forward(self, x, y):
 )
 self.lower_and_test_with_partitioner(module, model_inputs)

 @torch.inference_mode() # TODO Use pt2_mode=True for capturing.
 @torch.inference_mode() # TODO Use for capturing.
 def test_xnnpack_backend_linear(self):
 in_size = 2
 input_size = 3
Expand Down

6 changes: 2 additions & 4 deletions
backends/xnnpack/utils/configs.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,8 +34,6 @@ def get_xnnpack_executorch_backend_config(

def get_xnnpack_capture_config(dynamic_shape=False, enable_aot: Optional[bool] = None):
 if enable_aot is None:
 return CaptureConfig(pt2_mode=True, enable_dynamic_shape=dynamic_shape)
 return CaptureConfig(enable_dynamic_shape=dynamic_shape)
 else:
 return CaptureConfig(
 pt2_mode=True, enable_dynamic_shape=dynamic_shape, enable_aot=enable_aot
 )
 return CaptureConfig(enable_dynamic_shape=dynamic_shape, enable_aot=enable_aot)

2 changes: 1 addition & 1 deletion
bundled_program/tests/common.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -229,7 +229,7 @@ def get_common_program() -> Tuple[Program, BundledConfig]:
 DEFAULT_INT_INPUT,
 )
 program = (
 exir.capture(eager_model, capture_input, CaptureConfig(pt2_mode=True))
 exir.capture(eager_model, capture_input, CaptureConfig())
 .to_edge()
 .to_executorch()
 .program
Expand Down

10 changes: 3 additions & 7 deletions
exir/backend/test/demos/rpc/test_rpc.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -103,7 +103,7 @@ def test_delegate_whole_program(self):
 simple_net = self.get_a_simple_net()
 simple_net_input = simple_net.get_example_inputs()
 exported_program = exir.capture(
 simple_net, simple_net_input, exir.CaptureConfig(pt2_mode=True)
 simple_net, simple_net_input, exir.CaptureConfig()
 ).to_edge(
 exir.EdgeCompileConfig(
 _check_ir_validity=False,
Expand All@@ -125,9 +125,7 @@ def forward(self, *args):
 composite_model = CompositeModule()

 exec_prog = (
 exir.capture(
 composite_model, simple_net_input, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, simple_net_input, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 )
Expand DownExpand Up@@ -165,9 +163,7 @@ def forward(self, a, x, b):
 model = Model()
 inputs = (torch.ones(2, 2), torch.ones(2, 2), torch.ones(2, 2))

 exported_program = exir.capture(
 model, inputs, exir.CaptureConfig(pt2_mode=True)
 ).to_edge()
 exported_program = exir.capture(model, inputs, exir.CaptureConfig()).to_edge()

 # First lower to demo backend
 demo_backend_lowered = exported_program
Expand Down

6 changes: 2 additions & 4 deletions
exir/backend/test/demos/test_delegate_aten_mode.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -37,7 +37,7 @@ def forward(self, a, x, b):
 add_mul_module = AddMulModule()
 model_inputs = (torch.ones(2, 2), 2 * torch.ones(2, 2), 3 * torch.ones(2, 2))
 edge_graph_module = exir.capture(
 add_mul_module, model_inputs, exir.CaptureConfig(pt2_mode=True)
 add_mul_module, model_inputs, exir.CaptureConfig()
 ).to_edge()
 max_value = model_inputs[0].shape[0]
 compile_specs = [CompileSpec("max_value", bytes([max_value]))]
Expand All@@ -60,9 +60,7 @@ def forward(self, a, x, b):
 composite_model(*model_inputs)

 exec_prog = (
 exir.capture(
 composite_model, model_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, model_inputs, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 )
Expand Down

2 changes: 1 addition & 1 deletion
exir/backend/test/demos/test_xnnpack_qnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -81,7 +81,7 @@ def forward(self, x, y):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(
Expand Down

12 changes: 6 additions & 6 deletions
exir/backend/test/hta_partitioner_demo.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -62,7 +62,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True),
 exir.CaptureConfig(enable_aot=True),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -74,7 +74,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -90,7 +90,7 @@ def sub(x, y):
 exir.capture(
 sub,
 (input_x, input_h),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True, _unlift=False),
 exir.CaptureConfig(enable_aot=True, _unlift=False),
 )
 .to_edge(exir.EdgeCompileConfig(_use_edge_ops=True))
 .exported_program.graph_module
Expand All@@ -99,7 +99,7 @@ def sub(x, y):
 exir.capture(
 sub,
 (input_x, input_h),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge()
 .exported_program.graph_module
Expand DownExpand Up@@ -236,7 +236,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True),
 exir.CaptureConfig(enable_aot=True),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -248,7 +248,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand Down
Loading

, '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 > 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
Remove redundant pt2_mode=True#54

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

 Closed

tugsbayasgalan
wants to merge
1
commit into

from

 Closed


Remove redundant pt2_mode=True
#54
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


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


4 changes: 2 additions & 2 deletions
backends/qnnpack/partition/support_patterns.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -48,9 +48,9 @@ def get_dynamic_quantized_graph(f, example_inputs, dynamic_shape=False):
 # Convert module
 converted_mod = _convert_to_reference_decomposed_fx(prepared_mod)
 if dynamic_shape:
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=True)
 capture_config = CaptureConfig(enable_dynamic_shape=True)
 else:
 capture_config = CaptureConfig(pt2_mode=True)
 capture_config = CaptureConfig()
 # EXIR trace
 gm = (
 exir.capture(converted_mod, example_inputs, capture_config)
Expand Down

26 changes: 10 additions & 16 deletions
backends/qnnpack/test/test_qnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -83,7 +83,7 @@ def test_qnnpack_per_channel_dynamic_mm(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -115,9 +115,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -159,7 +157,7 @@ def test_qnnpack_per_channel_dynamic_qlinear(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -202,9 +200,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -246,7 +242,7 @@ def test_qnnpack_per_tensor_dynamic_mm(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -321,7 +317,7 @@ def test_qnnpack_per_tensor_dynamic_qlinear(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -406,7 +402,7 @@ def test_qnnpack_per_channel_dynamic_mm_with_dynamic_shape(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=True)
 capture_config = CaptureConfig(enable_dynamic_shape=True)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -438,9 +434,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -483,7 +477,7 @@ def test_qnnpack_per_channel_dynamic_qlinear_via_partitioner(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -538,7 +532,7 @@ def test_qnnpack_per_channel_dynamic_qlinear_via_partitioner(self):
 # composite_model(*example_inputs)
 # program = (
 # exir.capture(
 # composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 # composite_model, example_inputs, exir.CaptureConfig()
 # )
 # .to_edge(EDGE_COMPILE_CONFIG)
 # .to_executorch()
Expand Down

2 changes: 1 addition & 1 deletion
backends/qnnpack/test/test_qnnpack_partitioner.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -54,7 +54,7 @@ def get_actual_dyanmic_quantized_graph(
 converted_mod = _convert_to_reference_decomposed_fx(prepared_mod)

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=dynamic_shape)
 capture_config = CaptureConfig(enable_dynamic_shape=dynamic_shape)
 dynamic_quantized_exir_graph = (
 exir.capture(converted_mod, example_inputs, config=capture_config)
 .to_edge(exir.EdgeCompileConfig(_check_ir_validity=False))
Expand Down

8 changes: 2 additions & 6 deletions
backends/vulkan/test/test_vulkan_delegate.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -61,9 +61,7 @@ def lower_module_and_test_output(
 the given sample inputs. It then runs the lowered module and compares its
 outputs with the outputs of the eager module.
 """
 edgeir_m = exir.capture(
 module, sample_inputs, exir.CaptureConfig(pt2_mode=True)
 ).to_edge()
 edgeir_m = exir.capture(module, sample_inputs, exir.CaptureConfig()).to_edge()
 lowered_module = to_backend("VulkanBackend", edgeir_m.exported_program, [])

 class WrappedModule(torch.nn.Module):
Expand All@@ -75,9 +73,7 @@ def forward(self, *args):
 return self.one_module(*args)

 program = (
 exir.capture(
 WrappedModule(), sample_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(WrappedModule(), sample_inputs, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 .program
Expand Down

4 changes: 2 additions & 2 deletions
backends/xnnpack/partition/support_patterns.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -41,7 +41,7 @@
 exir.capture(
 add,
 model_inputs,
 config=CaptureConfig(pt2_mode=True, enable_dynamic_shape=True),
 config=CaptureConfig(enable_dynamic_shape=True),
 )
 .to_edge().module
 .graph
Expand All@@ -68,7 +68,7 @@


def _capture(module, example_inputs, pt_mode=True) -> torch.fx.GraphModule:
 capture_config = CaptureConfig(pt2_mode=pt_mode, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 edge_config = exir.EdgeCompileConfig(
 _check_ir_validity=False,
 passes=[DuplicateDequantNodePass()],
Expand Down

4 changes: 2 additions & 2 deletions
backends/xnnpack/test/test_xnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -236,7 +236,7 @@ def test_xnnpack_backend_conv2d_dw(self):
 conv.eval()
 self.lower_and_test_with_partitioner(conv, example_inputs)

 @torch.inference_mode() # TODO Use pt2_mode=True for capturing.
 @torch.inference_mode() # TODO Use for capturing.
 def test_xnnpack_backend_mm(self):
 in_sizes = [1, 4, 4]
 input_sizes = [4, 37, 17]
Expand DownExpand Up@@ -329,7 +329,7 @@ def forward(self, x, y):
 )
 self.lower_and_test_with_partitioner(module, model_inputs)

 @torch.inference_mode() # TODO Use pt2_mode=True for capturing.
 @torch.inference_mode() # TODO Use for capturing.
 def test_xnnpack_backend_linear(self):
 in_size = 2
 input_size = 3
Expand Down

6 changes: 2 additions & 4 deletions
backends/xnnpack/utils/configs.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,8 +34,6 @@ def get_xnnpack_executorch_backend_config(

def get_xnnpack_capture_config(dynamic_shape=False, enable_aot: Optional[bool] = None):
 if enable_aot is None:
 return CaptureConfig(pt2_mode=True, enable_dynamic_shape=dynamic_shape)
 return CaptureConfig(enable_dynamic_shape=dynamic_shape)
 else:
 return CaptureConfig(
 pt2_mode=True, enable_dynamic_shape=dynamic_shape, enable_aot=enable_aot
 )
 return CaptureConfig(enable_dynamic_shape=dynamic_shape, enable_aot=enable_aot)

2 changes: 1 addition & 1 deletion
bundled_program/tests/common.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -229,7 +229,7 @@ def get_common_program() -> Tuple[Program, BundledConfig]:
 DEFAULT_INT_INPUT,
 )
 program = (
 exir.capture(eager_model, capture_input, CaptureConfig(pt2_mode=True))
 exir.capture(eager_model, capture_input, CaptureConfig())
 .to_edge()
 .to_executorch()
 .program
Expand Down

10 changes: 3 additions & 7 deletions
exir/backend/test/demos/rpc/test_rpc.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -103,7 +103,7 @@ def test_delegate_whole_program(self):
 simple_net = self.get_a_simple_net()
 simple_net_input = simple_net.get_example_inputs()
 exported_program = exir.capture(
 simple_net, simple_net_input, exir.CaptureConfig(pt2_mode=True)
 simple_net, simple_net_input, exir.CaptureConfig()
 ).to_edge(
 exir.EdgeCompileConfig(
 _check_ir_validity=False,
Expand All@@ -125,9 +125,7 @@ def forward(self, *args):
 composite_model = CompositeModule()

 exec_prog = (
 exir.capture(
 composite_model, simple_net_input, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, simple_net_input, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 )
Expand DownExpand Up@@ -165,9 +163,7 @@ def forward(self, a, x, b):
 model = Model()
 inputs = (torch.ones(2, 2), torch.ones(2, 2), torch.ones(2, 2))

 exported_program = exir.capture(
 model, inputs, exir.CaptureConfig(pt2_mode=True)
 ).to_edge()
 exported_program = exir.capture(model, inputs, exir.CaptureConfig()).to_edge()

 # First lower to demo backend
 demo_backend_lowered = exported_program
Expand Down

6 changes: 2 additions & 4 deletions
exir/backend/test/demos/test_delegate_aten_mode.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -37,7 +37,7 @@ def forward(self, a, x, b):
 add_mul_module = AddMulModule()
 model_inputs = (torch.ones(2, 2), 2 * torch.ones(2, 2), 3 * torch.ones(2, 2))
 edge_graph_module = exir.capture(
 add_mul_module, model_inputs, exir.CaptureConfig(pt2_mode=True)
 add_mul_module, model_inputs, exir.CaptureConfig()
 ).to_edge()
 max_value = model_inputs[0].shape[0]
 compile_specs = [CompileSpec("max_value", bytes([max_value]))]
Expand All@@ -60,9 +60,7 @@ def forward(self, a, x, b):
 composite_model(*model_inputs)

 exec_prog = (
 exir.capture(
 composite_model, model_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, model_inputs, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 )
Expand Down

2 changes: 1 addition & 1 deletion
exir/backend/test/demos/test_xnnpack_qnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -81,7 +81,7 @@ def forward(self, x, y):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(
Expand Down

12 changes: 6 additions & 6 deletions
exir/backend/test/hta_partitioner_demo.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -62,7 +62,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True),
 exir.CaptureConfig(enable_aot=True),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -74,7 +74,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -90,7 +90,7 @@ def sub(x, y):
 exir.capture(
 sub,
 (input_x, input_h),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True, _unlift=False),
 exir.CaptureConfig(enable_aot=True, _unlift=False),
 )
 .to_edge(exir.EdgeCompileConfig(_use_edge_ops=True))
 .exported_program.graph_module
Expand All@@ -99,7 +99,7 @@ def sub(x, y):
 exir.capture(
 sub,
 (input_x, input_h),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge()
 .exported_program.graph_module
Expand DownExpand Up@@ -236,7 +236,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True),
 exir.CaptureConfig(enable_aot=True),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -248,7 +248,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand Down
Loading

, '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
Remove redundant pt2_mode=True#54

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

 Closed

tugsbayasgalan
wants to merge
1
commit into

from

 Closed


Remove redundant pt2_mode=True
#54
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


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


4 changes: 2 additions & 2 deletions
backends/qnnpack/partition/support_patterns.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -48,9 +48,9 @@ def get_dynamic_quantized_graph(f, example_inputs, dynamic_shape=False):
 # Convert module
 converted_mod = _convert_to_reference_decomposed_fx(prepared_mod)
 if dynamic_shape:
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=True)
 capture_config = CaptureConfig(enable_dynamic_shape=True)
 else:
 capture_config = CaptureConfig(pt2_mode=True)
 capture_config = CaptureConfig()
 # EXIR trace
 gm = (
 exir.capture(converted_mod, example_inputs, capture_config)
Expand Down

26 changes: 10 additions & 16 deletions
backends/qnnpack/test/test_qnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -83,7 +83,7 @@ def test_qnnpack_per_channel_dynamic_mm(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -115,9 +115,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -159,7 +157,7 @@ def test_qnnpack_per_channel_dynamic_qlinear(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -202,9 +200,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -246,7 +242,7 @@ def test_qnnpack_per_tensor_dynamic_mm(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -321,7 +317,7 @@ def test_qnnpack_per_tensor_dynamic_qlinear(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -406,7 +402,7 @@ def test_qnnpack_per_channel_dynamic_mm_with_dynamic_shape(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=True)
 capture_config = CaptureConfig(enable_dynamic_shape=True)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -438,9 +434,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -483,7 +477,7 @@ def test_qnnpack_per_channel_dynamic_qlinear_via_partitioner(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -538,7 +532,7 @@ def test_qnnpack_per_channel_dynamic_qlinear_via_partitioner(self):
 # composite_model(*example_inputs)
 # program = (
 # exir.capture(
 # composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 # composite_model, example_inputs, exir.CaptureConfig()
 # )
 # .to_edge(EDGE_COMPILE_CONFIG)
 # .to_executorch()
Expand Down

2 changes: 1 addition & 1 deletion
backends/qnnpack/test/test_qnnpack_partitioner.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -54,7 +54,7 @@ def get_actual_dyanmic_quantized_graph(
 converted_mod = _convert_to_reference_decomposed_fx(prepared_mod)

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=dynamic_shape)
 capture_config = CaptureConfig(enable_dynamic_shape=dynamic_shape)
 dynamic_quantized_exir_graph = (
 exir.capture(converted_mod, example_inputs, config=capture_config)
 .to_edge(exir.EdgeCompileConfig(_check_ir_validity=False))
Expand Down

8 changes: 2 additions & 6 deletions
backends/vulkan/test/test_vulkan_delegate.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -61,9 +61,7 @@ def lower_module_and_test_output(
 the given sample inputs. It then runs the lowered module and compares its
 outputs with the outputs of the eager module.
 """
 edgeir_m = exir.capture(
 module, sample_inputs, exir.CaptureConfig(pt2_mode=True)
 ).to_edge()
 edgeir_m = exir.capture(module, sample_inputs, exir.CaptureConfig()).to_edge()
 lowered_module = to_backend("VulkanBackend", edgeir_m.exported_program, [])

 class WrappedModule(torch.nn.Module):
Expand All@@ -75,9 +73,7 @@ def forward(self, *args):
 return self.one_module(*args)

 program = (
 exir.capture(
 WrappedModule(), sample_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(WrappedModule(), sample_inputs, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 .program
Expand Down

4 changes: 2 additions & 2 deletions
backends/xnnpack/partition/support_patterns.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -41,7 +41,7 @@
 exir.capture(
 add,
 model_inputs,
 config=CaptureConfig(pt2_mode=True, enable_dynamic_shape=True),
 config=CaptureConfig(enable_dynamic_shape=True),
 )
 .to_edge().module
 .graph
Expand All@@ -68,7 +68,7 @@


def _capture(module, example_inputs, pt_mode=True) -> torch.fx.GraphModule:
 capture_config = CaptureConfig(pt2_mode=pt_mode, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 edge_config = exir.EdgeCompileConfig(
 _check_ir_validity=False,
 passes=[DuplicateDequantNodePass()],
Expand Down

4 changes: 2 additions & 2 deletions
backends/xnnpack/test/test_xnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -236,7 +236,7 @@ def test_xnnpack_backend_conv2d_dw(self):
 conv.eval()
 self.lower_and_test_with_partitioner(conv, example_inputs)

 @torch.inference_mode() # TODO Use pt2_mode=True for capturing.
 @torch.inference_mode() # TODO Use for capturing.
 def test_xnnpack_backend_mm(self):
 in_sizes = [1, 4, 4]
 input_sizes = [4, 37, 17]
Expand DownExpand Up@@ -329,7 +329,7 @@ def forward(self, x, y):
 )
 self.lower_and_test_with_partitioner(module, model_inputs)

 @torch.inference_mode() # TODO Use pt2_mode=True for capturing.
 @torch.inference_mode() # TODO Use for capturing.
 def test_xnnpack_backend_linear(self):
 in_size = 2
 input_size = 3
Expand Down

6 changes: 2 additions & 4 deletions
backends/xnnpack/utils/configs.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,8 +34,6 @@ def get_xnnpack_executorch_backend_config(

def get_xnnpack_capture_config(dynamic_shape=False, enable_aot: Optional[bool] = None):
 if enable_aot is None:
 return CaptureConfig(pt2_mode=True, enable_dynamic_shape=dynamic_shape)
 return CaptureConfig(enable_dynamic_shape=dynamic_shape)
 else:
 return CaptureConfig(
 pt2_mode=True, enable_dynamic_shape=dynamic_shape, enable_aot=enable_aot
 )
 return CaptureConfig(enable_dynamic_shape=dynamic_shape, enable_aot=enable_aot)

2 changes: 1 addition & 1 deletion
bundled_program/tests/common.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -229,7 +229,7 @@ def get_common_program() -> Tuple[Program, BundledConfig]:
 DEFAULT_INT_INPUT,
 )
 program = (
 exir.capture(eager_model, capture_input, CaptureConfig(pt2_mode=True))
 exir.capture(eager_model, capture_input, CaptureConfig())
 .to_edge()
 .to_executorch()
 .program
Expand Down

10 changes: 3 additions & 7 deletions
exir/backend/test/demos/rpc/test_rpc.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -103,7 +103,7 @@ def test_delegate_whole_program(self):
 simple_net = self.get_a_simple_net()
 simple_net_input = simple_net.get_example_inputs()
 exported_program = exir.capture(
 simple_net, simple_net_input, exir.CaptureConfig(pt2_mode=True)
 simple_net, simple_net_input, exir.CaptureConfig()
 ).to_edge(
 exir.EdgeCompileConfig(
 _check_ir_validity=False,
Expand All@@ -125,9 +125,7 @@ def forward(self, *args):
 composite_model = CompositeModule()

 exec_prog = (
 exir.capture(
 composite_model, simple_net_input, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, simple_net_input, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 )
Expand DownExpand Up@@ -165,9 +163,7 @@ def forward(self, a, x, b):
 model = Model()
 inputs = (torch.ones(2, 2), torch.ones(2, 2), torch.ones(2, 2))

 exported_program = exir.capture(
 model, inputs, exir.CaptureConfig(pt2_mode=True)
 ).to_edge()
 exported_program = exir.capture(model, inputs, exir.CaptureConfig()).to_edge()

 # First lower to demo backend
 demo_backend_lowered = exported_program
Expand Down

6 changes: 2 additions & 4 deletions
exir/backend/test/demos/test_delegate_aten_mode.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -37,7 +37,7 @@ def forward(self, a, x, b):
 add_mul_module = AddMulModule()
 model_inputs = (torch.ones(2, 2), 2 * torch.ones(2, 2), 3 * torch.ones(2, 2))
 edge_graph_module = exir.capture(
 add_mul_module, model_inputs, exir.CaptureConfig(pt2_mode=True)
 add_mul_module, model_inputs, exir.CaptureConfig()
 ).to_edge()
 max_value = model_inputs[0].shape[0]
 compile_specs = [CompileSpec("max_value", bytes([max_value]))]
Expand All@@ -60,9 +60,7 @@ def forward(self, a, x, b):
 composite_model(*model_inputs)

 exec_prog = (
 exir.capture(
 composite_model, model_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, model_inputs, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 )
Expand Down

2 changes: 1 addition & 1 deletion
exir/backend/test/demos/test_xnnpack_qnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -81,7 +81,7 @@ def forward(self, x, y):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(
Expand Down

12 changes: 6 additions & 6 deletions
exir/backend/test/hta_partitioner_demo.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -62,7 +62,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True),
 exir.CaptureConfig(enable_aot=True),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -74,7 +74,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -90,7 +90,7 @@ def sub(x, y):
 exir.capture(
 sub,
 (input_x, input_h),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True, _unlift=False),
 exir.CaptureConfig(enable_aot=True, _unlift=False),
 )
 .to_edge(exir.EdgeCompileConfig(_use_edge_ops=True))
 .exported_program.graph_module
Expand All@@ -99,7 +99,7 @@ def sub(x, y):
 exir.capture(
 sub,
 (input_x, input_h),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge()
 .exported_program.graph_module
Expand DownExpand Up@@ -236,7 +236,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True),
 exir.CaptureConfig(enable_aot=True),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -248,7 +248,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand Down
Loading

, '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
Remove redundant pt2_mode=True#54

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

 Closed

tugsbayasgalan
wants to merge
1
commit into

from

 Closed


Remove redundant pt2_mode=True
#54
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


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


4 changes: 2 additions & 2 deletions
backends/qnnpack/partition/support_patterns.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -48,9 +48,9 @@ def get_dynamic_quantized_graph(f, example_inputs, dynamic_shape=False):
 # Convert module
 converted_mod = _convert_to_reference_decomposed_fx(prepared_mod)
 if dynamic_shape:
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=True)
 capture_config = CaptureConfig(enable_dynamic_shape=True)
 else:
 capture_config = CaptureConfig(pt2_mode=True)
 capture_config = CaptureConfig()
 # EXIR trace
 gm = (
 exir.capture(converted_mod, example_inputs, capture_config)
Expand Down

26 changes: 10 additions & 16 deletions
backends/qnnpack/test/test_qnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -83,7 +83,7 @@ def test_qnnpack_per_channel_dynamic_mm(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -115,9 +115,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -159,7 +157,7 @@ def test_qnnpack_per_channel_dynamic_qlinear(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -202,9 +200,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -246,7 +242,7 @@ def test_qnnpack_per_tensor_dynamic_mm(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -321,7 +317,7 @@ def test_qnnpack_per_tensor_dynamic_qlinear(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -406,7 +402,7 @@ def test_qnnpack_per_channel_dynamic_mm_with_dynamic_shape(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=True)
 capture_config = CaptureConfig(enable_dynamic_shape=True)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -438,9 +434,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -483,7 +477,7 @@ def test_qnnpack_per_channel_dynamic_qlinear_via_partitioner(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -538,7 +532,7 @@ def test_qnnpack_per_channel_dynamic_qlinear_via_partitioner(self):
 # composite_model(*example_inputs)
 # program = (
 # exir.capture(
 # composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 # composite_model, example_inputs, exir.CaptureConfig()
 # )
 # .to_edge(EDGE_COMPILE_CONFIG)
 # .to_executorch()
Expand Down

2 changes: 1 addition & 1 deletion
backends/qnnpack/test/test_qnnpack_partitioner.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -54,7 +54,7 @@ def get_actual_dyanmic_quantized_graph(
 converted_mod = _convert_to_reference_decomposed_fx(prepared_mod)

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=dynamic_shape)
 capture_config = CaptureConfig(enable_dynamic_shape=dynamic_shape)
 dynamic_quantized_exir_graph = (
 exir.capture(converted_mod, example_inputs, config=capture_config)
 .to_edge(exir.EdgeCompileConfig(_check_ir_validity=False))
Expand Down

8 changes: 2 additions & 6 deletions
backends/vulkan/test/test_vulkan_delegate.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -61,9 +61,7 @@ def lower_module_and_test_output(
 the given sample inputs. It then runs the lowered module and compares its
 outputs with the outputs of the eager module.
 """
 edgeir_m = exir.capture(
 module, sample_inputs, exir.CaptureConfig(pt2_mode=True)
 ).to_edge()
 edgeir_m = exir.capture(module, sample_inputs, exir.CaptureConfig()).to_edge()
 lowered_module = to_backend("VulkanBackend", edgeir_m.exported_program, [])

 class WrappedModule(torch.nn.Module):
Expand All@@ -75,9 +73,7 @@ def forward(self, *args):
 return self.one_module(*args)

 program = (
 exir.capture(
 WrappedModule(), sample_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(WrappedModule(), sample_inputs, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 .program
Expand Down

4 changes: 2 additions & 2 deletions
backends/xnnpack/partition/support_patterns.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -41,7 +41,7 @@
 exir.capture(
 add,
 model_inputs,
 config=CaptureConfig(pt2_mode=True, enable_dynamic_shape=True),
 config=CaptureConfig(enable_dynamic_shape=True),
 )
 .to_edge().module
 .graph
Expand All@@ -68,7 +68,7 @@


def _capture(module, example_inputs, pt_mode=True) -> torch.fx.GraphModule:
 capture_config = CaptureConfig(pt2_mode=pt_mode, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 edge_config = exir.EdgeCompileConfig(
 _check_ir_validity=False,
 passes=[DuplicateDequantNodePass()],
Expand Down

4 changes: 2 additions & 2 deletions
backends/xnnpack/test/test_xnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -236,7 +236,7 @@ def test_xnnpack_backend_conv2d_dw(self):
 conv.eval()
 self.lower_and_test_with_partitioner(conv, example_inputs)

 @torch.inference_mode() # TODO Use pt2_mode=True for capturing.
 @torch.inference_mode() # TODO Use for capturing.
 def test_xnnpack_backend_mm(self):
 in_sizes = [1, 4, 4]
 input_sizes = [4, 37, 17]
Expand DownExpand Up@@ -329,7 +329,7 @@ def forward(self, x, y):
 )
 self.lower_and_test_with_partitioner(module, model_inputs)

 @torch.inference_mode() # TODO Use pt2_mode=True for capturing.
 @torch.inference_mode() # TODO Use for capturing.
 def test_xnnpack_backend_linear(self):
 in_size = 2
 input_size = 3
Expand Down

6 changes: 2 additions & 4 deletions
backends/xnnpack/utils/configs.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,8 +34,6 @@ def get_xnnpack_executorch_backend_config(

def get_xnnpack_capture_config(dynamic_shape=False, enable_aot: Optional[bool] = None):
 if enable_aot is None:
 return CaptureConfig(pt2_mode=True, enable_dynamic_shape=dynamic_shape)
 return CaptureConfig(enable_dynamic_shape=dynamic_shape)
 else:
 return CaptureConfig(
 pt2_mode=True, enable_dynamic_shape=dynamic_shape, enable_aot=enable_aot
 )
 return CaptureConfig(enable_dynamic_shape=dynamic_shape, enable_aot=enable_aot)

2 changes: 1 addition & 1 deletion
bundled_program/tests/common.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -229,7 +229,7 @@ def get_common_program() -> Tuple[Program, BundledConfig]:
 DEFAULT_INT_INPUT,
 )
 program = (
 exir.capture(eager_model, capture_input, CaptureConfig(pt2_mode=True))
 exir.capture(eager_model, capture_input, CaptureConfig())
 .to_edge()
 .to_executorch()
 .program
Expand Down

10 changes: 3 additions & 7 deletions
exir/backend/test/demos/rpc/test_rpc.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -103,7 +103,7 @@ def test_delegate_whole_program(self):
 simple_net = self.get_a_simple_net()
 simple_net_input = simple_net.get_example_inputs()
 exported_program = exir.capture(
 simple_net, simple_net_input, exir.CaptureConfig(pt2_mode=True)
 simple_net, simple_net_input, exir.CaptureConfig()
 ).to_edge(
 exir.EdgeCompileConfig(
 _check_ir_validity=False,
Expand All@@ -125,9 +125,7 @@ def forward(self, *args):
 composite_model = CompositeModule()

 exec_prog = (
 exir.capture(
 composite_model, simple_net_input, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, simple_net_input, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 )
Expand DownExpand Up@@ -165,9 +163,7 @@ def forward(self, a, x, b):
 model = Model()
 inputs = (torch.ones(2, 2), torch.ones(2, 2), torch.ones(2, 2))

 exported_program = exir.capture(
 model, inputs, exir.CaptureConfig(pt2_mode=True)
 ).to_edge()
 exported_program = exir.capture(model, inputs, exir.CaptureConfig()).to_edge()

 # First lower to demo backend
 demo_backend_lowered = exported_program
Expand Down

6 changes: 2 additions & 4 deletions
exir/backend/test/demos/test_delegate_aten_mode.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -37,7 +37,7 @@ def forward(self, a, x, b):
 add_mul_module = AddMulModule()
 model_inputs = (torch.ones(2, 2), 2 * torch.ones(2, 2), 3 * torch.ones(2, 2))
 edge_graph_module = exir.capture(
 add_mul_module, model_inputs, exir.CaptureConfig(pt2_mode=True)
 add_mul_module, model_inputs, exir.CaptureConfig()
 ).to_edge()
 max_value = model_inputs[0].shape[0]
 compile_specs = [CompileSpec("max_value", bytes([max_value]))]
Expand All@@ -60,9 +60,7 @@ def forward(self, a, x, b):
 composite_model(*model_inputs)

 exec_prog = (
 exir.capture(
 composite_model, model_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, model_inputs, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 )
Expand Down

2 changes: 1 addition & 1 deletion
exir/backend/test/demos/test_xnnpack_qnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -81,7 +81,7 @@ def forward(self, x, y):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(
Expand Down

12 changes: 6 additions & 6 deletions
exir/backend/test/hta_partitioner_demo.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -62,7 +62,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True),
 exir.CaptureConfig(enable_aot=True),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -74,7 +74,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -90,7 +90,7 @@ def sub(x, y):
 exir.capture(
 sub,
 (input_x, input_h),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True, _unlift=False),
 exir.CaptureConfig(enable_aot=True, _unlift=False),
 )
 .to_edge(exir.EdgeCompileConfig(_use_edge_ops=True))
 .exported_program.graph_module
Expand All@@ -99,7 +99,7 @@ def sub(x, y):
 exir.capture(
 sub,
 (input_x, input_h),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge()
 .exported_program.graph_module
Expand DownExpand Up@@ -236,7 +236,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True),
 exir.CaptureConfig(enable_aot=True),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -248,7 +248,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand Down
Loading

, '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
Remove redundant pt2_mode=True#54

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

 Closed

tugsbayasgalan
wants to merge
1
commit into

from

 Closed


Remove redundant pt2_mode=True
#54
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


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


4 changes: 2 additions & 2 deletions
backends/qnnpack/partition/support_patterns.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -48,9 +48,9 @@ def get_dynamic_quantized_graph(f, example_inputs, dynamic_shape=False):
 # Convert module
 converted_mod = _convert_to_reference_decomposed_fx(prepared_mod)
 if dynamic_shape:
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=True)
 capture_config = CaptureConfig(enable_dynamic_shape=True)
 else:
 capture_config = CaptureConfig(pt2_mode=True)
 capture_config = CaptureConfig()
 # EXIR trace
 gm = (
 exir.capture(converted_mod, example_inputs, capture_config)
Expand Down

26 changes: 10 additions & 16 deletions
backends/qnnpack/test/test_qnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -83,7 +83,7 @@ def test_qnnpack_per_channel_dynamic_mm(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -115,9 +115,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -159,7 +157,7 @@ def test_qnnpack_per_channel_dynamic_qlinear(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -202,9 +200,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -246,7 +242,7 @@ def test_qnnpack_per_tensor_dynamic_mm(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -321,7 +317,7 @@ def test_qnnpack_per_tensor_dynamic_qlinear(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -406,7 +402,7 @@ def test_qnnpack_per_channel_dynamic_mm_with_dynamic_shape(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=True)
 capture_config = CaptureConfig(enable_dynamic_shape=True)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -438,9 +434,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -483,7 +477,7 @@ def test_qnnpack_per_channel_dynamic_qlinear_via_partitioner(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -538,7 +532,7 @@ def test_qnnpack_per_channel_dynamic_qlinear_via_partitioner(self):
 # composite_model(*example_inputs)
 # program = (
 # exir.capture(
 # composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 # composite_model, example_inputs, exir.CaptureConfig()
 # )
 # .to_edge(EDGE_COMPILE_CONFIG)
 # .to_executorch()
Expand Down

2 changes: 1 addition & 1 deletion
backends/qnnpack/test/test_qnnpack_partitioner.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -54,7 +54,7 @@ def get_actual_dyanmic_quantized_graph(
 converted_mod = _convert_to_reference_decomposed_fx(prepared_mod)

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=dynamic_shape)
 capture_config = CaptureConfig(enable_dynamic_shape=dynamic_shape)
 dynamic_quantized_exir_graph = (
 exir.capture(converted_mod, example_inputs, config=capture_config)
 .to_edge(exir.EdgeCompileConfig(_check_ir_validity=False))
Expand Down

8 changes: 2 additions & 6 deletions
backends/vulkan/test/test_vulkan_delegate.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -61,9 +61,7 @@ def lower_module_and_test_output(
 the given sample inputs. It then runs the lowered module and compares its
 outputs with the outputs of the eager module.
 """
 edgeir_m = exir.capture(
 module, sample_inputs, exir.CaptureConfig(pt2_mode=True)
 ).to_edge()
 edgeir_m = exir.capture(module, sample_inputs, exir.CaptureConfig()).to_edge()
 lowered_module = to_backend("VulkanBackend", edgeir_m.exported_program, [])

 class WrappedModule(torch.nn.Module):
Expand All@@ -75,9 +73,7 @@ def forward(self, *args):
 return self.one_module(*args)

 program = (
 exir.capture(
 WrappedModule(), sample_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(WrappedModule(), sample_inputs, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 .program
Expand Down

4 changes: 2 additions & 2 deletions
backends/xnnpack/partition/support_patterns.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -41,7 +41,7 @@
 exir.capture(
 add,
 model_inputs,
 config=CaptureConfig(pt2_mode=True, enable_dynamic_shape=True),
 config=CaptureConfig(enable_dynamic_shape=True),
 )
 .to_edge().module
 .graph
Expand All@@ -68,7 +68,7 @@


def _capture(module, example_inputs, pt_mode=True) -> torch.fx.GraphModule:
 capture_config = CaptureConfig(pt2_mode=pt_mode, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 edge_config = exir.EdgeCompileConfig(
 _check_ir_validity=False,
 passes=[DuplicateDequantNodePass()],
Expand Down

4 changes: 2 additions & 2 deletions
backends/xnnpack/test/test_xnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -236,7 +236,7 @@ def test_xnnpack_backend_conv2d_dw(self):
 conv.eval()
 self.lower_and_test_with_partitioner(conv, example_inputs)

 @torch.inference_mode() # TODO Use pt2_mode=True for capturing.
 @torch.inference_mode() # TODO Use for capturing.
 def test_xnnpack_backend_mm(self):
 in_sizes = [1, 4, 4]
 input_sizes = [4, 37, 17]
Expand DownExpand Up@@ -329,7 +329,7 @@ def forward(self, x, y):
 )
 self.lower_and_test_with_partitioner(module, model_inputs)

 @torch.inference_mode() # TODO Use pt2_mode=True for capturing.
 @torch.inference_mode() # TODO Use for capturing.
 def test_xnnpack_backend_linear(self):
 in_size = 2
 input_size = 3
Expand Down

6 changes: 2 additions & 4 deletions
backends/xnnpack/utils/configs.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,8 +34,6 @@ def get_xnnpack_executorch_backend_config(

def get_xnnpack_capture_config(dynamic_shape=False, enable_aot: Optional[bool] = None):
 if enable_aot is None:
 return CaptureConfig(pt2_mode=True, enable_dynamic_shape=dynamic_shape)
 return CaptureConfig(enable_dynamic_shape=dynamic_shape)
 else:
 return CaptureConfig(
 pt2_mode=True, enable_dynamic_shape=dynamic_shape, enable_aot=enable_aot
 )
 return CaptureConfig(enable_dynamic_shape=dynamic_shape, enable_aot=enable_aot)

2 changes: 1 addition & 1 deletion
bundled_program/tests/common.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -229,7 +229,7 @@ def get_common_program() -> Tuple[Program, BundledConfig]:
 DEFAULT_INT_INPUT,
 )
 program = (
 exir.capture(eager_model, capture_input, CaptureConfig(pt2_mode=True))
 exir.capture(eager_model, capture_input, CaptureConfig())
 .to_edge()
 .to_executorch()
 .program
Expand Down

10 changes: 3 additions & 7 deletions
exir/backend/test/demos/rpc/test_rpc.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -103,7 +103,7 @@ def test_delegate_whole_program(self):
 simple_net = self.get_a_simple_net()
 simple_net_input = simple_net.get_example_inputs()
 exported_program = exir.capture(
 simple_net, simple_net_input, exir.CaptureConfig(pt2_mode=True)
 simple_net, simple_net_input, exir.CaptureConfig()
 ).to_edge(
 exir.EdgeCompileConfig(
 _check_ir_validity=False,
Expand All@@ -125,9 +125,7 @@ def forward(self, *args):
 composite_model = CompositeModule()

 exec_prog = (
 exir.capture(
 composite_model, simple_net_input, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, simple_net_input, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 )
Expand DownExpand Up@@ -165,9 +163,7 @@ def forward(self, a, x, b):
 model = Model()
 inputs = (torch.ones(2, 2), torch.ones(2, 2), torch.ones(2, 2))

 exported_program = exir.capture(
 model, inputs, exir.CaptureConfig(pt2_mode=True)
 ).to_edge()
 exported_program = exir.capture(model, inputs, exir.CaptureConfig()).to_edge()

 # First lower to demo backend
 demo_backend_lowered = exported_program
Expand Down

6 changes: 2 additions & 4 deletions
exir/backend/test/demos/test_delegate_aten_mode.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -37,7 +37,7 @@ def forward(self, a, x, b):
 add_mul_module = AddMulModule()
 model_inputs = (torch.ones(2, 2), 2 * torch.ones(2, 2), 3 * torch.ones(2, 2))
 edge_graph_module = exir.capture(
 add_mul_module, model_inputs, exir.CaptureConfig(pt2_mode=True)
 add_mul_module, model_inputs, exir.CaptureConfig()
 ).to_edge()
 max_value = model_inputs[0].shape[0]
 compile_specs = [CompileSpec("max_value", bytes([max_value]))]
Expand All@@ -60,9 +60,7 @@ def forward(self, a, x, b):
 composite_model(*model_inputs)

 exec_prog = (
 exir.capture(
 composite_model, model_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, model_inputs, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 )
Expand Down

2 changes: 1 addition & 1 deletion
exir/backend/test/demos/test_xnnpack_qnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -81,7 +81,7 @@ def forward(self, x, y):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(
Expand Down

12 changes: 6 additions & 6 deletions
exir/backend/test/hta_partitioner_demo.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -62,7 +62,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True),
 exir.CaptureConfig(enable_aot=True),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -74,7 +74,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -90,7 +90,7 @@ def sub(x, y):
 exir.capture(
 sub,
 (input_x, input_h),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True, _unlift=False),
 exir.CaptureConfig(enable_aot=True, _unlift=False),
 )
 .to_edge(exir.EdgeCompileConfig(_use_edge_ops=True))
 .exported_program.graph_module
Expand All@@ -99,7 +99,7 @@ def sub(x, y):
 exir.capture(
 sub,
 (input_x, input_h),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge()
 .exported_program.graph_module
Expand DownExpand Up@@ -236,7 +236,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True),
 exir.CaptureConfig(enable_aot=True),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -248,7 +248,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand Down
Loading

, '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
Remove redundant pt2_mode=True#54

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

 Closed

tugsbayasgalan
wants to merge
1
commit into

from

 Closed


Remove redundant pt2_mode=True
#54
Show file tree
Hide file tree
 Changes from all commits
Commits

Show all changes


1 commit


Select commit


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


4 changes: 2 additions & 2 deletions
backends/qnnpack/partition/support_patterns.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -48,9 +48,9 @@ def get_dynamic_quantized_graph(f, example_inputs, dynamic_shape=False):
 # Convert module
 converted_mod = _convert_to_reference_decomposed_fx(prepared_mod)
 if dynamic_shape:
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=True)
 capture_config = CaptureConfig(enable_dynamic_shape=True)
 else:
 capture_config = CaptureConfig(pt2_mode=True)
 capture_config = CaptureConfig()
 # EXIR trace
 gm = (
 exir.capture(converted_mod, example_inputs, capture_config)
Expand Down

26 changes: 10 additions & 16 deletions
backends/qnnpack/test/test_qnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -83,7 +83,7 @@ def test_qnnpack_per_channel_dynamic_mm(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -115,9 +115,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -159,7 +157,7 @@ def test_qnnpack_per_channel_dynamic_qlinear(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -202,9 +200,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -246,7 +242,7 @@ def test_qnnpack_per_tensor_dynamic_mm(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -321,7 +317,7 @@ def test_qnnpack_per_tensor_dynamic_qlinear(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -406,7 +402,7 @@ def test_qnnpack_per_channel_dynamic_mm_with_dynamic_shape(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=True)
 capture_config = CaptureConfig(enable_dynamic_shape=True)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -438,9 +434,7 @@ def forward(self, x):

 composite_model(*example_inputs)
 program = (
 exir.capture(
 composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, example_inputs, exir.CaptureConfig())
 .to_edge(EDGE_COMPILE_CONFIG)
 .to_executorch(config=EXECUTORCH_BACKEND_CONFIG)
 .program
Expand DownExpand Up@@ -483,7 +477,7 @@ def test_qnnpack_per_channel_dynamic_qlinear_via_partitioner(self):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(EDGE_COMPILE_CONFIG)
Expand DownExpand Up@@ -538,7 +532,7 @@ def test_qnnpack_per_channel_dynamic_qlinear_via_partitioner(self):
 # composite_model(*example_inputs)
 # program = (
 # exir.capture(
 # composite_model, example_inputs, exir.CaptureConfig(pt2_mode=True)
 # composite_model, example_inputs, exir.CaptureConfig()
 # )
 # .to_edge(EDGE_COMPILE_CONFIG)
 # .to_executorch()
Expand Down

2 changes: 1 addition & 1 deletion
backends/qnnpack/test/test_qnnpack_partitioner.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -54,7 +54,7 @@ def get_actual_dyanmic_quantized_graph(
 converted_mod = _convert_to_reference_decomposed_fx(prepared_mod)

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=dynamic_shape)
 capture_config = CaptureConfig(enable_dynamic_shape=dynamic_shape)
 dynamic_quantized_exir_graph = (
 exir.capture(converted_mod, example_inputs, config=capture_config)
 .to_edge(exir.EdgeCompileConfig(_check_ir_validity=False))
Expand Down

8 changes: 2 additions & 6 deletions
backends/vulkan/test/test_vulkan_delegate.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -61,9 +61,7 @@ def lower_module_and_test_output(
 the given sample inputs. It then runs the lowered module and compares its
 outputs with the outputs of the eager module.
 """
 edgeir_m = exir.capture(
 module, sample_inputs, exir.CaptureConfig(pt2_mode=True)
 ).to_edge()
 edgeir_m = exir.capture(module, sample_inputs, exir.CaptureConfig()).to_edge()
 lowered_module = to_backend("VulkanBackend", edgeir_m.exported_program, [])

 class WrappedModule(torch.nn.Module):
Expand All@@ -75,9 +73,7 @@ def forward(self, *args):
 return self.one_module(*args)

 program = (
 exir.capture(
 WrappedModule(), sample_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(WrappedModule(), sample_inputs, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 .program
Expand Down

4 changes: 2 additions & 2 deletions
backends/xnnpack/partition/support_patterns.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -41,7 +41,7 @@
 exir.capture(
 add,
 model_inputs,
 config=CaptureConfig(pt2_mode=True, enable_dynamic_shape=True),
 config=CaptureConfig(enable_dynamic_shape=True),
 )
 .to_edge().module
 .graph
Expand All@@ -68,7 +68,7 @@


def _capture(module, example_inputs, pt_mode=True) -> torch.fx.GraphModule:
 capture_config = CaptureConfig(pt2_mode=pt_mode, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 edge_config = exir.EdgeCompileConfig(
 _check_ir_validity=False,
 passes=[DuplicateDequantNodePass()],
Expand Down

4 changes: 2 additions & 2 deletions
backends/xnnpack/test/test_xnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -236,7 +236,7 @@ def test_xnnpack_backend_conv2d_dw(self):
 conv.eval()
 self.lower_and_test_with_partitioner(conv, example_inputs)

 @torch.inference_mode() # TODO Use pt2_mode=True for capturing.
 @torch.inference_mode() # TODO Use for capturing.
 def test_xnnpack_backend_mm(self):
 in_sizes = [1, 4, 4]
 input_sizes = [4, 37, 17]
Expand DownExpand Up@@ -329,7 +329,7 @@ def forward(self, x, y):
 )
 self.lower_and_test_with_partitioner(module, model_inputs)

 @torch.inference_mode() # TODO Use pt2_mode=True for capturing.
 @torch.inference_mode() # TODO Use for capturing.
 def test_xnnpack_backend_linear(self):
 in_size = 2
 input_size = 3
Expand Down

6 changes: 2 additions & 4 deletions
backends/xnnpack/utils/configs.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,8 +34,6 @@ def get_xnnpack_executorch_backend_config(

def get_xnnpack_capture_config(dynamic_shape=False, enable_aot: Optional[bool] = None):
 if enable_aot is None:
 return CaptureConfig(pt2_mode=True, enable_dynamic_shape=dynamic_shape)
 return CaptureConfig(enable_dynamic_shape=dynamic_shape)
 else:
 return CaptureConfig(
 pt2_mode=True, enable_dynamic_shape=dynamic_shape, enable_aot=enable_aot
 )
 return CaptureConfig(enable_dynamic_shape=dynamic_shape, enable_aot=enable_aot)

2 changes: 1 addition & 1 deletion
bundled_program/tests/common.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -229,7 +229,7 @@ def get_common_program() -> Tuple[Program, BundledConfig]:
 DEFAULT_INT_INPUT,
 )
 program = (
 exir.capture(eager_model, capture_input, CaptureConfig(pt2_mode=True))
 exir.capture(eager_model, capture_input, CaptureConfig())
 .to_edge()
 .to_executorch()
 .program
Expand Down

10 changes: 3 additions & 7 deletions
exir/backend/test/demos/rpc/test_rpc.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -103,7 +103,7 @@ def test_delegate_whole_program(self):
 simple_net = self.get_a_simple_net()
 simple_net_input = simple_net.get_example_inputs()
 exported_program = exir.capture(
 simple_net, simple_net_input, exir.CaptureConfig(pt2_mode=True)
 simple_net, simple_net_input, exir.CaptureConfig()
 ).to_edge(
 exir.EdgeCompileConfig(
 _check_ir_validity=False,
Expand All@@ -125,9 +125,7 @@ def forward(self, *args):
 composite_model = CompositeModule()

 exec_prog = (
 exir.capture(
 composite_model, simple_net_input, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, simple_net_input, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 )
Expand DownExpand Up@@ -165,9 +163,7 @@ def forward(self, a, x, b):
 model = Model()
 inputs = (torch.ones(2, 2), torch.ones(2, 2), torch.ones(2, 2))

 exported_program = exir.capture(
 model, inputs, exir.CaptureConfig(pt2_mode=True)
 ).to_edge()
 exported_program = exir.capture(model, inputs, exir.CaptureConfig()).to_edge()

 # First lower to demo backend
 demo_backend_lowered = exported_program
Expand Down

6 changes: 2 additions & 4 deletions
exir/backend/test/demos/test_delegate_aten_mode.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -37,7 +37,7 @@ def forward(self, a, x, b):
 add_mul_module = AddMulModule()
 model_inputs = (torch.ones(2, 2), 2 * torch.ones(2, 2), 3 * torch.ones(2, 2))
 edge_graph_module = exir.capture(
 add_mul_module, model_inputs, exir.CaptureConfig(pt2_mode=True)
 add_mul_module, model_inputs, exir.CaptureConfig()
 ).to_edge()
 max_value = model_inputs[0].shape[0]
 compile_specs = [CompileSpec("max_value", bytes([max_value]))]
Expand All@@ -60,9 +60,7 @@ def forward(self, a, x, b):
 composite_model(*model_inputs)

 exec_prog = (
 exir.capture(
 composite_model, model_inputs, exir.CaptureConfig(pt2_mode=True)
 )
 exir.capture(composite_model, model_inputs, exir.CaptureConfig())
 .to_edge()
 .to_executorch()
 )
Expand Down

2 changes: 1 addition & 1 deletion
exir/backend/test/demos/test_xnnpack_qnnpack.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -81,7 +81,7 @@ def forward(self, x, y):
 )

 # Step 2: EXIR capturing
 capture_config = CaptureConfig(pt2_mode=True, enable_dynamic_shape=False)
 capture_config = CaptureConfig(enable_dynamic_shape=False)
 captured_mod = exir.capture(
 converted_mod, example_inputs, config=capture_config
 ).to_edge(
Expand Down

12 changes: 6 additions & 6 deletions
exir/backend/test/hta_partitioner_demo.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -62,7 +62,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True),
 exir.CaptureConfig(enable_aot=True),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -74,7 +74,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -90,7 +90,7 @@ def sub(x, y):
 exir.capture(
 sub,
 (input_x, input_h),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True, _unlift=False),
 exir.CaptureConfig(enable_aot=True, _unlift=False),
 )
 .to_edge(exir.EdgeCompileConfig(_use_edge_ops=True))
 .exported_program.graph_module
Expand All@@ -99,7 +99,7 @@ def sub(x, y):
 exir.capture(
 sub,
 (input_x, input_h),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge()
 .exported_program.graph_module
Expand DownExpand Up@@ -236,7 +236,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True, enable_aot=True),
 exir.CaptureConfig(enable_aot=True),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand All@@ -248,7 +248,7 @@ def forward(self, x_raw, h, c):
 exir.capture(
 LSTMConvPattern(),
 (input_x, input_h, input_c),
 exir.CaptureConfig(pt2_mode=True),
 exir.CaptureConfig(),
 )
 .to_edge(
 # torch._export.verifier.SpecViolationError: Operator torch._ops.aten.mkldnn_rnn_layer.default is not Aten Canonical.
Expand Down
Loading