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[TorchFX] Export to torch.export.export_for_training #3075

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merged 5 commits into from
Nov 14, 2024
Merged

[TorchFX] Export to torch.export.export_for_training #3075

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78f8588
WIP
daniil-lyakhov Nov 11, 2024
707d4cd
test_shared_constants_unification_not_connected_const
daniil-lyakhov Nov 12, 2024
68bb7b6
Skip capture_pre_autograd tests on Windows
daniil-lyakhov Nov 12, 2024
04290c2
shared_constants_unification_transformation is removed
daniil-lyakhov Nov 13, 2024
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daniil-lyakhov Nov 14, 2024
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5 changes: 5 additions & 0 deletions nncf/experimental/torch/fx/model_transformer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -84,6 +84,11 @@ def _traverse_graph(
continue

visited.add(in_node.name)
# Do not traverse through constant users
# as a constant could be shared and
# some shared ops users could be redundant.
if in_node.op == "get_attr":
continue
input_nodes.extend(in_node.all_input_nodes)
input_nodes.extend(list(in_node.users))

Expand Down
4 changes: 3 additions & 1 deletion nncf/experimental/torch/fx/nncf_graph_builder.py
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Original file line number Diff line number Diff line change
Expand Up @@ -187,7 +187,9 @@ def get_edge_params(
if source_node.op in ("get_attr",):
tensor_shape = tuple(get_tensor_constant_from_node(source_node, model).shape)
elif "val" in source_node.meta:
if source_nncf_node.metatype is om.PTBatchNormMetatype:
if source_nncf_node.metatype is om.PTBatchNormMetatype and isinstance(
source_node.meta["val"], (tuple, list)
):
tensor = source_node.meta["val"][0]
elif source_nncf_node.metatype in [om.PTSplitMetatype, om.PTMaxMetatype, om.PTMinMetatype]:
tensor = source_node.meta["val"][output_idx]
Expand Down
14 changes: 9 additions & 5 deletions nncf/experimental/torch/fx/transformations.py
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Original file line number Diff line number Diff line change
Expand Up @@ -196,14 +196,17 @@ def shared_constants_unification_transformation(model: torch.fx.GraphModule):

:param model: Target Torch FX GraphModule
"""
prev_targets = {}
target_vs_constant = {}

for source_node in model.graph.nodes:
dist_node = list(source_node.users)
if source_node.target in prev_targets and source_node.op in ("get_attr",):
dist_node[0].replace_input_with(source_node, prev_targets[source_node.target])
if source_node.op != "get_attr" or not source_node.users:
continue

if source_node.target in target_vs_constant:
for user in list(source_node.users):
user.replace_input_with(source_node, target_vs_constant[source_node.target])
else:
prev_targets[source_node.target] = source_node
target_vs_constant[source_node.target] = source_node

model.graph.eliminate_dead_code()
model.recompile()
Expand Down Expand Up @@ -541,6 +544,7 @@ def _is_supported_batch_norm_for_training(node: torch.fx.Node):
Return True if the given node refers to an aten batch norm op QAT supports.
"""
supported_ops = [
torch.ops.aten.batch_norm.default,
torch.ops.aten._native_batch_norm_legit.default,
torch.ops.aten.cudnn_batch_norm.default,
torch.ops.aten.miopen_batch_norm.default,
Expand Down
12 changes: 12 additions & 0 deletions tests/torch/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -54,6 +54,14 @@ def pytest_addoption(parser: Parser):
"reference .dot files will be regenerated "
"using the current state of the repository.",
)
parser.addoption(
"--regen-json",
action="store_true",
default=False,
help="If specified, the "
"reference .json files will be regenerated "
"using the current state of the repository.",
)
parser.addoption(
"--torch-home", type=str, default=None, help="Path to cached test models, downloaded by torchvision"
)
Expand Down Expand Up @@ -120,6 +128,10 @@ def pytest_configure(config: Config):
if regen_dot:
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What if I would like to update json files only?

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@anzr299 anzr299 Nov 14, 2024 •
edited
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The regen_dot was added there by mistake, I have updated the suggestion. https://github.com/openvinotoolkit/nncf/pull/3075/files/68bb7b6f09bba89935ae44a7aff6e8f3bee237ea#r1841827740

os.environ["NNCF_TEST_REGEN_DOT"] = "1"

regen_json = config.getoption("--regen-json", False)
if regen_json:
os.environ["NNCF_TEST_REGEN_JSON"] = "1"

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Suggested change
if regen_dot:
os.environ["NNCF_TEST_REGEN_DOT"] = "1"
regen_json = config.getoption("--regen-json", False)
if regen_json:
os.environ["NNCF_TEST_REGEN_JSON"] = "1"
for option, var in [("--regen-dot", "NNCF_TEST_REGEN_DOT"), ("--regen-json", "NNCF_TEST_REGEN_JSON")]:
regen = config.getoption(option, False)
if regen:
os.environ[env_var] = "1"

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Done, please check


@pytest.fixture(scope="module")
def dataset_dir(request: FixtureRequest):
Expand Down
4 changes: 2 additions & 2 deletions ...data/reference_graphs/fx/extracted/ConvolutionWithAllConstantInputsModelconv2d_conv2d.dot
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@@ -1,10 +1,10 @@
strict digraph {
"0 _param_constant0" [id=0, type=get_attr];
"0 _conv_w" [id=0, type=get_attr];
"1 add" [id=1, type=add];
"2 conv2d_input" [id=2, type=input];
"3 conv2d" [id=3, type=conv2d];
"4 output" [id=4, type=output];
"0 _param_constant0" -> "1 add" [label="(1, 1, 1, 1)", style=solid];
"0 _conv_w" -> "1 add" [label="(1, 1, 1, 1)", style=solid];
"1 add" -> "3 conv2d" [label="(1, 1, 1, 1)", style=solid];
"2 conv2d_input" -> "3 conv2d" [label=None, style=solid];
"3 conv2d" -> "4 output" [label="(1, 1, 1, 1)", style=solid];
Expand Down
4 changes: 2 additions & 2 deletions ...rch/data/reference_graphs/fx/extracted/ConvolutionWithNotTensorBiasModelconv2d_conv2d.dot
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@@ -1,10 +1,10 @@
strict digraph {
"0 _param_constant0" [id=0, type=get_attr];
"0 _conv_w" [id=0, type=get_attr];
"1 add" [id=1, type=add];
"2 conv2d_input" [id=2, type=input];
"3 conv2d" [id=3, type=conv2d];
"4 output" [id=4, type=output];
"0 _param_constant0" -> "1 add" [label="(1, 1, 1, 1)", style=solid];
"0 _conv_w" -> "1 add" [label="(1, 1, 1, 1)", style=solid];
"1 add" -> "3 conv2d" [label="(1, 1, 1, 1)", style=solid];
"2 conv2d_input" -> "3 conv2d" [label=None, style=solid];
"3 conv2d" -> "4 output" [label="(1, 1, 3, 3)", style=solid];
Expand Down
20 changes: 10 additions & 10 deletions ...s/torch/data/reference_graphs/fx/extracted/MultiBranchesConnectedModelconv2d_1_add__1.dot
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@@ -1,15 +1,15 @@
strict digraph {
"0 _param_constant2" [id=0, type=get_attr];
"1 _param_constant3" [id=1, type=get_attr];
"2 conv2d_1_input" [id=2, type=input];
"3 conv2d_1" [id=3, type=conv2d];
"4 _tensor_constant0_1" [id=4, type=get_attr];
"0 conv_b_weight" [id=0, type=get_attr];
"1 conv_b_bias" [id=1, type=get_attr];
"2 bias" [id=2, type=get_attr];
"3 conv2d_1_input" [id=3, type=input];
"4 conv2d_1" [id=4, type=conv2d];
"5 add__1" [id=5, type=add_];
"6 output" [id=6, type=output];
"0 _param_constant2" -> "3 conv2d_1" [label="(3, 3, 1, 1)", style=solid];
"1 _param_constant3" -> "3 conv2d_1" [label="(3,)", style=solid];
"2 conv2d_1_input" -> "3 conv2d_1" [label=None, style=solid];
"3 conv2d_1" -> "5 add__1" [label="(1, 3, 3, 3)", style=solid];
"4 _tensor_constant0_1" -> "5 add__1" [label="(1,)", style=solid];
"0 conv_b_weight" -> "4 conv2d_1" [label="(3, 3, 1, 1)", style=solid];
"1 conv_b_bias" -> "4 conv2d_1" [label="(3,)", style=solid];
"2 bias" -> "5 add__1" [label="(1,)", style=solid];
"3 conv2d_1_input" -> "4 conv2d_1" [label=None, style=solid];
"4 conv2d_1" -> "5 add__1" [label="(1, 3, 3, 3)", style=solid];
"5 add__1" -> "6 output" [label="(1, 3, 3, 3)", style=solid];
}
70 changes: 34 additions & 36 deletions tests/torch/data/reference_graphs/fx/extracted/MultiBranchesConnectedModelconv2d_add__1.dot
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@@ -1,38 +1,36 @@
strict digraph {
"0 _param_constant0" [id=0, type=get_attr];
"1 _param_constant1" [id=1, type=get_attr];
"2 conv2d_input" [id=2, type=input];
"3 conv2d" [id=3, type=conv2d];
"4 _param_constant2" [id=4, type=get_attr];
"5 _param_constant3" [id=5, type=get_attr];
"6 conv2d_1" [id=6, type=conv2d];
"7 _tensor_constant0" [id=7, type=get_attr];
"8 add_" [id=8, type=add_];
"9 _tensor_constant0_1" [id=9, type=get_attr];
"10 add__1" [id=10, type=add_];
"11 add" [id=11, type=add];
"12 _param_constant4" [id=12, type=get_attr];
"13 _param_constant5" [id=13, type=get_attr];
"14 conv2d_2" [id=14, type=conv2d];
"15 _tensor_constant0_2" [id=15, type=get_attr];
"16 add_1" [id=16, type=add];
"17 output" [id=17, type=output];
"0 _param_constant0" -> "3 conv2d" [label="(3, 3, 1, 1)", style=solid];
"1 _param_constant1" -> "3 conv2d" [label="(3,)", style=solid];
"2 conv2d_input" -> "3 conv2d" [label=None, style=solid];
"3 conv2d" -> "6 conv2d_1" [label="(1, 3, 3, 3)", style=solid];
"3 conv2d" -> "8 add_" [label="(1, 3, 3, 3)", style=solid];
"4 _param_constant2" -> "6 conv2d_1" [label="(3, 3, 1, 1)", style=solid];
"5 _param_constant3" -> "6 conv2d_1" [label="(3,)", style=solid];
"6 conv2d_1" -> "10 add__1" [label="(1, 3, 3, 3)", style=solid];
"7 _tensor_constant0" -> "8 add_" [label="(1,)", style=solid];
"8 add_" -> "11 add" [label="(1, 3, 3, 3)", style=solid];
"9 _tensor_constant0_1" -> "10 add__1" [label="(1,)", style=solid];
"10 add__1" -> "11 add" [label="(1, 3, 3, 3)", style=solid];
"10 add__1" -> "17 output" [label="(1, 3, 3, 3)", style=solid];
"11 add" -> "14 conv2d_2" [label="(1, 3, 3, 3)", style=solid];
"12 _param_constant4" -> "14 conv2d_2" [label="(3, 3, 1, 1)", style=solid];
"13 _param_constant5" -> "14 conv2d_2" [label="(3,)", style=solid];
"14 conv2d_2" -> "16 add_1" [label="(1, 3, 3, 3)", style=solid];
"15 _tensor_constant0_2" -> "16 add_1" [label="(1,)", style=solid];
"0 conv_a_weight" [id=0, type=get_attr];
"1 conv_a_bias" [id=1, type=get_attr];
"2 conv_b_weight" [id=2, type=get_attr];
"3 conv_b_bias" [id=3, type=get_attr];
"4 conv_c_weight" [id=4, type=get_attr];
"5 conv_c_bias" [id=5, type=get_attr];
"6 bias" [id=6, type=get_attr];
"7 conv2d_input" [id=7, type=input];
"8 conv2d" [id=8, type=conv2d];
"9 conv2d_1" [id=9, type=conv2d];
"10 add_" [id=10, type=add_];
"11 add__1" [id=11, type=add_];
"12 add" [id=12, type=add];
"13 conv2d_2" [id=13, type=conv2d];
"14 add_1" [id=14, type=add];
"15 output" [id=15, type=output];
"0 conv_a_weight" -> "8 conv2d" [label="(3, 3, 1, 1)", style=solid];
"1 conv_a_bias" -> "8 conv2d" [label="(3,)", style=solid];
"2 conv_b_weight" -> "9 conv2d_1" [label="(3, 3, 1, 1)", style=solid];
"3 conv_b_bias" -> "9 conv2d_1" [label="(3,)", style=solid];
"4 conv_c_weight" -> "13 conv2d_2" [label="(3, 3, 1, 1)", style=solid];
"5 conv_c_bias" -> "13 conv2d_2" [label="(3,)", style=solid];
"6 bias" -> "10 add_" [label="(1,)", style=solid];
"6 bias" -> "11 add__1" [label="(1,)", style=solid];
"6 bias" -> "14 add_1" [label="(1,)", style=solid];
"7 conv2d_input" -> "8 conv2d" [label=None, style=solid];
"8 conv2d" -> "9 conv2d_1" [label="(1, 3, 3, 3)", style=solid];
"8 conv2d" -> "10 add_" [label="(1, 3, 3, 3)", style=solid];
"9 conv2d_1" -> "11 add__1" [label="(1, 3, 3, 3)", style=solid];
"10 add_" -> "12 add" [label="(1, 3, 3, 3)", style=solid];
"11 add__1" -> "12 add" [label="(1, 3, 3, 3)", style=solid];
"11 add__1" -> "15 output" [label="(1, 3, 3, 3)", style=solid];
"12 add" -> "13 conv2d_2" [label="(1, 3, 3, 3)", style=solid];
"13 conv2d_2" -> "14 add_1" [label="(1, 3, 3, 3)", style=solid];
}
51 changes: 25 additions & 26 deletions ...s/torch/data/reference_graphs/fx/extracted/MultiBranchesConnectedModelconv2d_add__add.dot
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@@ -1,29 +1,28 @@
strict digraph {
"0 _param_constant0" [id=0, type=get_attr];
"1 _param_constant1" [id=1, type=get_attr];
"2 conv2d_input" [id=2, type=input];
"3 conv2d" [id=3, type=conv2d];
"4 _param_constant2" [id=4, type=get_attr];
"5 _param_constant3" [id=5, type=get_attr];
"6 conv2d_1" [id=6, type=conv2d];
"7 _tensor_constant0" [id=7, type=get_attr];
"0 conv_a_weight" [id=0, type=get_attr];
"1 conv_a_bias" [id=1, type=get_attr];
"2 conv_b_weight" [id=2, type=get_attr];
"3 conv_b_bias" [id=3, type=get_attr];
"4 bias" [id=4, type=get_attr];
"5 conv2d_input" [id=5, type=input];
"6 conv2d" [id=6, type=conv2d];
"7 conv2d_1" [id=7, type=conv2d];
"8 add_" [id=8, type=add_];
"9 _tensor_constant0_1" [id=9, type=get_attr];
"10 add__1" [id=10, type=add_];
"11 add" [id=11, type=add];
"12 output" [id=12, type=output];
"0 _param_constant0" -> "3 conv2d" [label="(3, 3, 1, 1)", style=solid];
"1 _param_constant1" -> "3 conv2d" [label="(3,)", style=solid];
"2 conv2d_input" -> "3 conv2d" [label=None, style=solid];
"3 conv2d" -> "6 conv2d_1" [label="(1, 3, 3, 3)", style=solid];
"3 conv2d" -> "8 add_" [label="(1, 3, 3, 3)", style=solid];
"4 _param_constant2" -> "6 conv2d_1" [label="(3, 3, 1, 1)", style=solid];
"5 _param_constant3" -> "6 conv2d_1" [label="(3,)", style=solid];
"6 conv2d_1" -> "10 add__1" [label="(1, 3, 3, 3)", style=solid];
"7 _tensor_constant0" -> "8 add_" [label="(1,)", style=solid];
"8 add_" -> "11 add" [label="(1, 3, 3, 3)", style=solid];
"8 add_" -> "12 output" [label="(1, 3, 3, 3)", style=solid];
"9 _tensor_constant0_1" -> "10 add__1" [label="(1,)", style=solid];
"10 add__1" -> "11 add" [label="(1, 3, 3, 3)", style=solid];
"11 add" -> "12 output" [label="(1, 3, 3, 3)", style=solid];
"9 add__1" [id=9, type=add_];
"10 add" [id=10, type=add];
"11 output" [id=11, type=output];
"0 conv_a_weight" -> "6 conv2d" [label="(3, 3, 1, 1)", style=solid];
"1 conv_a_bias" -> "6 conv2d" [label="(3,)", style=solid];
"2 conv_b_weight" -> "7 conv2d_1" [label="(3, 3, 1, 1)", style=solid];
"3 conv_b_bias" -> "7 conv2d_1" [label="(3,)", style=solid];
"4 bias" -> "8 add_" [label="(1,)", style=solid];
"4 bias" -> "9 add__1" [label="(1,)", style=solid];
"5 conv2d_input" -> "6 conv2d" [label=None, style=solid];
"6 conv2d" -> "7 conv2d_1" [label="(1, 3, 3, 3)", style=solid];
"6 conv2d" -> "8 add_" [label="(1, 3, 3, 3)", style=solid];
"7 conv2d_1" -> "9 add__1" [label="(1, 3, 3, 3)", style=solid];
"8 add_" -> "10 add" [label="(1, 3, 3, 3)", style=solid];
"8 add_" -> "11 output" [label="(1, 3, 3, 3)", style=solid];
"9 add__1" -> "10 add" [label="(1, 3, 3, 3)", style=solid];
"10 add" -> "11 output" [label="(1, 3, 3, 3)", style=solid];
}
47 changes: 23 additions & 24 deletions .../reference_graphs/fx/extracted/MultiBranchesConnectedModelconv2d_conv2d_1_add__add__1.dot
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@@ -1,27 +1,26 @@
strict digraph {
"0 _param_constant0" [id=0, type=get_attr];
"1 _param_constant1" [id=1, type=get_attr];
"2 conv2d_input" [id=2, type=input];
"3 conv2d" [id=3, type=conv2d];
"4 _param_constant2" [id=4, type=get_attr];
"5 _param_constant3" [id=5, type=get_attr];
"6 conv2d_1_input" [id=6, type=input];
"7 conv2d_1" [id=7, type=conv2d];
"8 _tensor_constant0" [id=8, type=get_attr];
"0 conv_a_weight" [id=0, type=get_attr];
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"4 bias" [id=4, type=get_attr];
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"6 conv2d" [id=6, type=conv2d];
"7 conv2d_1_input" [id=7, type=input];
"8 conv2d_1" [id=8, type=conv2d];
"9 add_" [id=9, type=add_];
"10 _tensor_constant0_1" [id=10, type=get_attr];
"11 add__1" [id=11, type=add_];
"12 output" [id=12, type=output];
"0 _param_constant0" -> "3 conv2d" [label="(3, 3, 1, 1)", style=solid];
"1 _param_constant1" -> "3 conv2d" [label="(3,)", style=solid];
"2 conv2d_input" -> "3 conv2d" [label=None, style=solid];
"3 conv2d" -> "9 add_" [label="(1, 3, 3, 3)", style=solid];
"4 _param_constant2" -> "7 conv2d_1" [label="(3, 3, 1, 1)", style=solid];
"5 _param_constant3" -> "7 conv2d_1" [label="(3,)", style=solid];
"6 conv2d_1_input" -> "7 conv2d_1" [label=None, style=solid];
"7 conv2d_1" -> "11 add__1" [label="(1, 3, 3, 3)", style=solid];
"8 _tensor_constant0" -> "9 add_" [label="(1,)", style=solid];
"9 add_" -> "12 output" [label="(1, 3, 3, 3)", style=solid];
"10 _tensor_constant0_1" -> "11 add__1" [label="(1,)", style=solid];
"11 add__1" -> "12 output" [label="(1, 3, 3, 3)", style=solid];
"10 add__1" [id=10, type=add_];
"11 output" [id=11, type=output];
"0 conv_a_weight" -> "6 conv2d" [label="(3, 3, 1, 1)", style=solid];
"1 conv_a_bias" -> "6 conv2d" [label="(3,)", style=solid];
"2 conv_b_weight" -> "8 conv2d_1" [label="(3, 3, 1, 1)", style=solid];
"3 conv_b_bias" -> "8 conv2d_1" [label="(3,)", style=solid];
"4 bias" -> "9 add_" [label="(1,)", style=solid];
"4 bias" -> "10 add__1" [label="(1,)", style=solid];
"5 conv2d_input" -> "6 conv2d" [label=None, style=solid];
"6 conv2d" -> "9 add_" [label="(1, 3, 3, 3)", style=solid];
"7 conv2d_1_input" -> "8 conv2d_1" [label=None, style=solid];
"8 conv2d_1" -> "10 add__1" [label="(1, 3, 3, 3)", style=solid];
"9 add_" -> "11 output" [label="(1, 3, 3, 3)", style=solid];
"10 add__1" -> "11 output" [label="(1, 3, 3, 3)", style=solid];
}
63 changes: 31 additions & 32 deletions ...s/torch/data/reference_graphs/fx/extracted/MultiBranchesConnectedModelconv2d_conv2d_2.dot
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@@ -1,34 +1,33 @@
strict digraph {
"0 _param_constant0" [id=0, type=get_attr];
"1 _param_constant1" [id=1, type=get_attr];
"2 conv2d_input" [id=2, type=input];
"3 conv2d" [id=3, type=conv2d];
"4 _param_constant2" [id=4, type=get_attr];
"5 _param_constant3" [id=5, type=get_attr];
"6 conv2d_1" [id=6, type=conv2d];
"7 _tensor_constant0" [id=7, type=get_attr];
"8 add_" [id=8, type=add_];
"9 _tensor_constant0_1" [id=9, type=get_attr];
"10 add__1" [id=10, type=add_];
"11 add" [id=11, type=add];
"12 _param_constant4" [id=12, type=get_attr];
"13 _param_constant5" [id=13, type=get_attr];
"14 conv2d_2" [id=14, type=conv2d];
"15 output" [id=15, type=output];
"0 _param_constant0" -> "3 conv2d" [label="(3, 3, 1, 1)", style=solid];
"1 _param_constant1" -> "3 conv2d" [label="(3,)", style=solid];
"2 conv2d_input" -> "3 conv2d" [label=None, style=solid];
"3 conv2d" -> "6 conv2d_1" [label="(1, 3, 3, 3)", style=solid];
"3 conv2d" -> "8 add_" [label="(1, 3, 3, 3)", style=solid];
"4 _param_constant2" -> "6 conv2d_1" [label="(3, 3, 1, 1)", style=solid];
"5 _param_constant3" -> "6 conv2d_1" [label="(3,)", style=solid];
"6 conv2d_1" -> "10 add__1" [label="(1, 3, 3, 3)", style=solid];
"7 _tensor_constant0" -> "8 add_" [label="(1,)", style=solid];
"8 add_" -> "11 add" [label="(1, 3, 3, 3)", style=solid];
"9 _tensor_constant0_1" -> "10 add__1" [label="(1,)", style=solid];
"10 add__1" -> "11 add" [label="(1, 3, 3, 3)", style=solid];
"11 add" -> "14 conv2d_2" [label="(1, 3, 3, 3)", style=solid];
"12 _param_constant4" -> "14 conv2d_2" [label="(3, 3, 1, 1)", style=solid];
"13 _param_constant5" -> "14 conv2d_2" [label="(3,)", style=solid];
"14 conv2d_2" -> "15 output" [label="(1, 3, 3, 3)", style=solid];
"0 conv_a_weight" [id=0, type=get_attr];
"1 conv_a_bias" [id=1, type=get_attr];
"2 conv_b_weight" [id=2, type=get_attr];
"3 conv_b_bias" [id=3, type=get_attr];
"4 conv_c_weight" [id=4, type=get_attr];
"5 conv_c_bias" [id=5, type=get_attr];
"6 bias" [id=6, type=get_attr];
"7 conv2d_input" [id=7, type=input];
"8 conv2d" [id=8, type=conv2d];
"9 conv2d_1" [id=9, type=conv2d];
"10 add_" [id=10, type=add_];
"11 add__1" [id=11, type=add_];
"12 add" [id=12, type=add];
"13 conv2d_2" [id=13, type=conv2d];
"14 output" [id=14, type=output];
"0 conv_a_weight" -> "8 conv2d" [label="(3, 3, 1, 1)", style=solid];
"1 conv_a_bias" -> "8 conv2d" [label="(3,)", style=solid];
"2 conv_b_weight" -> "9 conv2d_1" [label="(3, 3, 1, 1)", style=solid];
"3 conv_b_bias" -> "9 conv2d_1" [label="(3,)", style=solid];
"4 conv_c_weight" -> "13 conv2d_2" [label="(3, 3, 1, 1)", style=solid];
"5 conv_c_bias" -> "13 conv2d_2" [label="(3,)", style=solid];
"6 bias" -> "10 add_" [label="(1,)", style=solid];
"6 bias" -> "11 add__1" [label="(1,)", style=solid];
"7 conv2d_input" -> "8 conv2d" [label=None, style=solid];
"8 conv2d" -> "9 conv2d_1" [label="(1, 3, 3, 3)", style=solid];
"8 conv2d" -> "10 add_" [label="(1, 3, 3, 3)", style=solid];
"9 conv2d_1" -> "11 add__1" [label="(1, 3, 3, 3)", style=solid];
"10 add_" -> "12 add" [label="(1, 3, 3, 3)", style=solid];
"11 add__1" -> "12 add" [label="(1, 3, 3, 3)", style=solid];
"12 add" -> "13 conv2d_2" [label="(1, 3, 3, 3)", style=solid];
"13 conv2d_2" -> "14 output" [label="(1, 3, 3, 3)", style=solid];
}
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