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Variable length intermediate conv padding check #2231

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Variable length intermediate conv padding check #2231

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27 changes: 21 additions & 6 deletions TrainingExtensions/torch/src/python/aimet_torch/arch_checker/arch_checker_rules.py
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Original file line number Diff line number Diff line change
Expand Up @@ -110,14 +110,29 @@ def _examine_intermediate_padding_in_op_subset(op_subset):
If both 1st and 2nd conv have paddings, add conv2 to inter_pad_node_list.
"""
if len(op_subset) == 4:
conv1, _, _, conv2 = op_subset
conv1, _, _, next_node = op_subset
else:
conv1, _, conv2 = op_subset
conv1, _, next_node = op_subset

conv1_padding = sum(conv1.get_module().padding)
conv2_padding = sum(conv2.get_module().padding)
if conv1_padding and conv2_padding:
inter_pad_op_list.append(conv2)
previous_padding = sum(conv1.get_module().padding)

# Examine all following nodes, while ignore activations and break if meets none conv node.
while next_node:
if next_node.type in _support_conv_op_type:
current_padding = sum(next_node.get_module().padding)

if previous_padding and current_padding:
inter_pad_op_list.append(next_node)

previous_padding = previous_padding or current_padding

next_outputs = next_node.output_ops

# Break if next_outputs has more than 1 output or not a activation/conv.
if len(next_outputs) != 1 or (next_outputs[0].type not in _support_activation_op_type and next_outputs[0].type not in _support_conv_op_type):
break
else:
next_node = next_outputs[0]

_support_activation_op_type = ("Relu", "Tanh", "HardSwish")
_support_conv_op_type = ("Conv", "Conv2D")
Expand Down
22 changes: 18 additions & 4 deletions TrainingExtensions/torch/test/python/test_arch_checker.py
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Original file line number Diff line number Diff line change
Expand Up @@ -74,6 +74,7 @@ def __init__(self):
self.bn2 = torch.nn.BatchNorm2d(32)
self.conv4 = torch.nn.Conv2d(32, 32, kernel_size=2, stride=2, padding=2, bias=False)

# conv5 has intermediate paddings when consider (conv3, conv4, conv5)
# conv6 has no intermediate paddings
self.conv5 = torch.nn.Conv2d(32, 32, kernel_size=2, padding=2, bias=False)
self.relu3 = torch.nn.ReLU()
Expand Down Expand Up @@ -129,17 +130,19 @@ def __init__(self):
self.relu1 = torch.nn.ReLU()
self.conv2 = torch.nn.Conv2d(32, 32, kernel_size=2, stride=2, padding=2, bias=False)

# conv4 has no intermediate paddings since conv3 has no paddings
# conv4 has intermediate paddings consider (conv1, conv2, conv3, conv4)
self.conv3 = torch.nn.Conv2d(32, 32, kernel_size=2, stride=2, padding=0, bias=False)
self.relu2 = torch.nn.ReLU()
self.conv4 = torch.nn.Conv2d(32, 32, kernel_size=2, stride=2, padding=2, bias=False)


# PReLU is not a supported activation, stop examining the nodes after for (conv1, relu1, conv2) pattern.
self.prelu = torch.nn.PReLU()
# conv6 has no intermediate paddings
self.conv5 = torch.nn.Conv2d(32, 32, kernel_size=2, padding=2, bias=False)
self.relu3 = torch.nn.ReLU()
self.conv6 = torch.nn.Conv2d(32, 32, kernel_size=2, padding=0, bias=False)

# conv7 has no intermediate paddings
# conv7, conv8 has no intermediate paddings
self.conv7 = torch.nn.Conv2d(32, 32, kernel_size=2, padding=0, bias=False)
self.relu4 = torch.nn.ReLU()
self.conv8 = torch.nn.Conv2d(32, 32, kernel_size=2, padding=0, bias=False)
Expand All @@ -153,6 +156,7 @@ def forward(self, x):
x = self.relu2(x)
x = self.conv4(x)

x = self.prelu(x)
x = self.conv5(x)
x = self.relu3(x)
x = self.conv6(x)
Expand Down Expand Up @@ -198,14 +202,17 @@ def forward(self, x):
x = self.conv1(x)
x = self.relu(x)
x = self.conv2(x)
x = self.prelu(x) # Break point for variable length

x = self.conv3(x)
x = self.tanh(x)
x = self.conv4(x)
x = self.prelu(x) # Break point for variable length

x = self.conv5(x)
x = self.hardswich(x)
x = self.conv6(x)
x = self.prelu(x) # Break point for variable length

x = self.conv7(x)
x = self.prelu(x)
Expand Down Expand Up @@ -324,6 +331,7 @@ def test_intermediate_padding(self):
ArchChecker.check_model_arch(model, self.dummy_input)
arch_checker_report = ArchChecker._arch_checker_report
assert "_check_intermediate_padding" in arch_checker_report.raw_report["Model_inter_pad_with_BN.conv2"].failed_checks
assert "_check_intermediate_padding" in arch_checker_report.raw_report["Model_inter_pad_with_BN.conv5"].failed_checks
assert "Model_inter_pad_with_BN.conv4" not in arch_checker_report.raw_report
assert "Model_inter_pad_with_BN.conv6" not in arch_checker_report.raw_report
assert "Model_inter_pad_with_BN.conv8" not in arch_checker_report.raw_report
Expand All @@ -334,18 +342,24 @@ def test_intermediate_padding(self):
ArchChecker.check_model_arch(model, self.dummy_input)
arch_checker_report = ArchChecker._arch_checker_report
assert "_check_intermediate_padding" in arch_checker_report.raw_report["Model_inter_pad_without_BN.conv2"].failed_checks
assert "Model_inter_pad_without_BN.conv4" not in arch_checker_report.raw_report
assert "_check_intermediate_padding" in arch_checker_report.raw_report["Model_inter_pad_without_BN.conv4"].failed_checks
assert "Model_inter_pad_without_BN.conv6" not in arch_checker_report.raw_report
assert "Model_inter_pad_without_BN.conv8" not in arch_checker_report.raw_report
arch_checker_report.reset_raw_report()

model = Model_inter_pad_act_type()
ArchChecker.check_model_arch(model, self.dummy_input)
arch_checker_report = ArchChecker._arch_checker_report

assert "_check_intermediate_padding" not in arch_checker_report.raw_report["Model_inter_pad_act_type.conv1"].failed_checks
assert "_check_intermediate_padding" in arch_checker_report.raw_report["Model_inter_pad_act_type.conv2"].failed_checks
assert "Model_inter_pad_act_type.conv3" not in arch_checker_report.raw_report
assert "_check_intermediate_padding" in arch_checker_report.raw_report["Model_inter_pad_act_type.conv4"].failed_checks
assert "Model_inter_pad_act_type.conv5" not in arch_checker_report.raw_report
assert "_check_intermediate_padding" in arch_checker_report.raw_report["Model_inter_pad_act_type.conv6"].failed_checks
assert "Model_inter_pad_act_type.conv7" not in arch_checker_report.raw_report
assert "Model_inter_pad_act_type.conv8" not in arch_checker_report.raw_report

arch_checker_report.reset_raw_report()

filepath = ArchChecker._arch_checker_report._get_write_path(".html")
Expand Down