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pydot<=3.0.4
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@AlexanderDokuchaev
AlexanderDokuchaev committed Feb 19, 2025
1 parent 191b53d commit 96975b3
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Showing 38 changed files with 28,722 additions and 28,722 deletions.
2 changes: 1 addition & 1 deletion pyproject.toml
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Expand Up @@ -44,7 +44,7 @@ dependencies = [
"pandas>=1.1.5,<2.3",
"psutil",
"py-cpuinfo>=9.0.0",
"pydot>=1.4.1, <3.0.0",
"pydot>=1.4.1, <=3.0.4",
"pymoo>=0.6.0.1",
"rich>=13.5.2",
"safetensors>=0.4.1",
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6 changes: 3 additions & 3 deletions tests/common/data/reference_graphs/dot_rw_reference.dot
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@@ -1,9 +1,9 @@
strict digraph {
strict digraph {
"Node^^A" [label=":baz"];
"Node^^B" [label="qux:"];
"Node^^C" [label="Node::C"];
D;
E [label=no_label];
E [label="no_label"];
F [label="has^label"];
"Node^^A" -> "Node^^B" [label="foo:bar"];
"Node^^A" -> "Node^^B" [label="foo:bar"];
}
16 changes: 8 additions & 8 deletions tests/torch2/data/function_hook/graph_visualization/to_pydot_style_disable.dot
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@@ -1,4 +1,4 @@
digraph {
digraph {
rankdir=TB;
0 [label=x];
1 [label="conv.weight"];
Expand All @@ -8,11 +8,11 @@ rankdir=TB;
5 [label="conv/post_hook__conv-conv2d-0__0[0]/add/0"];
6 [label="/relu/0"];
7 [label=output];
0 -> 3 [label="0 → 0"];
1 -> 3 [label="0 → 1"];
2 -> 3 [label="0 → 2"];
3 -> 5 [label="0 → 0"];
4 -> 5 [label="0 → 1"];
5 -> 6 [label="0 → 0"];
6 -> 7 [label="0 → 0"];
0 -> 3 [label="0 → 0"];
1 -> 3 [label="0 → 1"];
2 -> 3 [label="0 → 2"];
3 -> 5 [label="0 → 0"];
4 -> 5 [label="0 → 1"];
5 -> 6 [label="0 → 0"];
6 -> 7 [label="0 → 0"];
}
32 changes: 16 additions & 16 deletions tests/torch2/data/function_hook/graph_visualization/to_pydot_style_full.dot
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@@ -1,18 +1,18 @@
digraph {
digraph {
rankdir=TB;
0 [fillcolor="#adadad", fontcolor="#000000", label="{type: input|name: x|dtype: torch.float32|shape: (1, 1, 3, 3)}", shape=record, style="filled,rounded"];
1 [fillcolor="#ffffff", fontcolor="#000000", label="{type: const|name: conv.weight|dtype: torch.float32|shape: (1, 1, 1, 1)}", shape=record, style="filled,rounded"];
2 [fillcolor="#ffffff", fontcolor="#000000", label="{type: const|name: conv.bias|dtype: torch.float32|shape: (1,)}", shape=record, style="filled,rounded"];
3 [fillcolor="#ffd6a5", fontcolor="#000000", label="{type: function_call|op_name: conv/conv2d/0|fn_name: conv2d|args: [\nTensorMeta(dtype=torch.float32, shape=(1, 1, 3, 3)),\nTensorMeta(dtype=torch.float32, shape=(1, 1, 1, 1)),\nTensorMeta(dtype=torch.float32, shape=(1,)),\n(1, 1),\n(0, 0),\n(1, 1),\n1,\n]|kwargs: \{\}}", shape=record, style="filled,rounded"];
4 [fillcolor="#ffffff", fontcolor="#000000", label="{type: const|name: __nncf_hooks.post_hooks.conv/conv2d/0__0.0.w|dtype: torch.float32|shape: (1,)}", shape=record, style="filled,rounded"];
5 [fillcolor="#caffbf", fontcolor="#000000", label="{type: function_call|op_name: conv/post_hook__conv-conv2d-0__0[0]/add/0|fn_name: add|args: [\nTensorMeta(dtype=torch.float32, shape=(1, 1, 3, 3)),\nTensorMeta(dtype=torch.float32, shape=(1,)),\n]|kwargs: \{\}}", shape=record, style="filled,rounded"];
6 [fillcolor="#a0c4ff", fontcolor="#000000", label="{type: function_call|op_name: /relu/0|fn_name: relu|args: [\nTensorMeta(dtype=torch.float32, shape=(1, 1, 3, 3)),\n]|kwargs: \{\}}", shape=record, style="filled,rounded"];
7 [fillcolor="#adadad", fontcolor="#000000", label="{type: output|name: output|dtype: torch.float32|shape: (1, 1, 3, 3)}", shape=record, style="filled,rounded"];
0 -> 3 [label="(1, 1, 3, 3)\n0 → 0"];
1 -> 3 [label="(1, 1, 1, 1)\n0 → 1"];
2 -> 3 [label="(1,)\n0 → 2"];
3 -> 5 [label="(1, 1, 3, 3)\n0 → 0"];
4 -> 5 [label="(1,)\n0 → 1"];
5 -> 6 [label="(1, 1, 3, 3)\n0 → 0"];
6 -> 7 [label="(1, 1, 3, 3)\n0 → 0"];
0 [label="{type: input|name: x|dtype: torch.float32|shape: (1, 1, 3, 3)}", fillcolor="#adadad", fontcolor="#000000", shape=record, style="filled,rounded"];
1 [label="{type: const|name: conv.weight|dtype: torch.float32|shape: (1, 1, 1, 1)}", fillcolor="#ffffff", fontcolor="#000000", shape=record, style="filled,rounded"];
2 [label="{type: const|name: conv.bias|dtype: torch.float32|shape: (1,)}", fillcolor="#ffffff", fontcolor="#000000", shape=record, style="filled,rounded"];
3 [label="{type: function_call|op_name: conv/conv2d/0|fn_name: conv2d|args: [\nTensorMeta(dtype=torch.float32, shape=(1, 1, 3, 3)),\nTensorMeta(dtype=torch.float32, shape=(1, 1, 1, 1)),\nTensorMeta(dtype=torch.float32, shape=(1,)),\n(1, 1),\n(0, 0),\n(1, 1),\n1,\n]|kwargs: \{\}}", fillcolor="#ffd6a5", fontcolor="#000000", shape=record, style="filled,rounded"];
4 [label="{type: const|name: __nncf_hooks.post_hooks.conv/conv2d/0__0.0.w|dtype: torch.float32|shape: (1,)}", fillcolor="#ffffff", fontcolor="#000000", shape=record, style="filled,rounded"];
5 [label="{type: function_call|op_name: conv/post_hook__conv-conv2d-0__0[0]/add/0|fn_name: add|args: [\nTensorMeta(dtype=torch.float32, shape=(1, 1, 3, 3)),\nTensorMeta(dtype=torch.float32, shape=(1,)),\n]|kwargs: \{\}}", fillcolor="#caffbf", fontcolor="#000000", shape=record, style="filled,rounded"];
6 [label="{type: function_call|op_name: /relu/0|fn_name: relu|args: [\nTensorMeta(dtype=torch.float32, shape=(1, 1, 3, 3)),\n]|kwargs: \{\}}", fillcolor="#a0c4ff", fontcolor="#000000", shape=record, style="filled,rounded"];
7 [label="{type: output|name: output|dtype: torch.float32|shape: (1, 1, 3, 3)}", fillcolor="#adadad", fontcolor="#000000", shape=record, style="filled,rounded"];
0 -> 3 [label="(1, 1, 3, 3)\n0 → 0"];
1 -> 3 [label="(1, 1, 1, 1)\n0 → 1"];
2 -> 3 [label="(1,)\n0 → 2"];
3 -> 5 [label="(1, 1, 3, 3)\n0 → 0"];
4 -> 5 [label="(1,)\n0 → 1"];
5 -> 6 [label="(1, 1, 3, 3)\n0 → 0"];
6 -> 7 [label="(1, 1, 3, 3)\n0 → 0"];
}
32 changes: 16 additions & 16 deletions tests/torch2/data/function_hook/graph_visualization/to_pydot_style_short.dot
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@@ -1,18 +1,18 @@
digraph {
digraph {
rankdir=TB;
0 [fillcolor="#adadad", fontcolor="#000000", label=x, shape=record, style="filled,rounded"];
1 [fillcolor="#ffffff", fontcolor="#000000", label="conv.weight", shape=record, style="filled,rounded"];
2 [fillcolor="#ffffff", fontcolor="#000000", label="conv.bias", shape=record, style="filled,rounded"];
3 [fillcolor="#ffd6a5", fontcolor="#000000", label="conv/conv2d/0", shape=record, style="filled,rounded"];
4 [fillcolor="#ffffff", fontcolor="#000000", label="__nncf_hooks.post_hooks.conv/conv2d/0__0.0.w", shape=record, style="filled,rounded"];
5 [fillcolor="#caffbf", fontcolor="#000000", label="conv/post_hook__conv-conv2d-0__0[0]/add/0", shape=record, style="filled,rounded"];
6 [fillcolor="#a0c4ff", fontcolor="#000000", label="/relu/0", shape=record, style="filled,rounded"];
7 [fillcolor="#adadad", fontcolor="#000000", label=output, shape=record, style="filled,rounded"];
0 -> 3 [label="(1, 1, 3, 3)\n0 → 0"];
1 -> 3 [label="(1, 1, 1, 1)\n0 → 1"];
2 -> 3 [label="(1,)\n0 → 2"];
3 -> 5 [label="(1, 1, 3, 3)\n0 → 0"];
4 -> 5 [label="(1,)\n0 → 1"];
5 -> 6 [label="(1, 1, 3, 3)\n0 → 0"];
6 -> 7 [label="(1, 1, 3, 3)\n0 → 0"];
0 [label=x, fillcolor="#adadad", fontcolor="#000000", shape=record, style="filled,rounded"];
1 [label="conv.weight", fillcolor="#ffffff", fontcolor="#000000", shape=record, style="filled,rounded"];
2 [label="conv.bias", fillcolor="#ffffff", fontcolor="#000000", shape=record, style="filled,rounded"];
3 [label="conv/conv2d/0", fillcolor="#ffd6a5", fontcolor="#000000", shape=record, style="filled,rounded"];
4 [label="__nncf_hooks.post_hooks.conv/conv2d/0__0.0.w", fillcolor="#ffffff", fontcolor="#000000", shape=record, style="filled,rounded"];
5 [label="conv/post_hook__conv-conv2d-0__0[0]/add/0", fillcolor="#caffbf", fontcolor="#000000", shape=record, style="filled,rounded"];
6 [label="/relu/0", fillcolor="#a0c4ff", fontcolor="#000000", shape=record, style="filled,rounded"];
7 [label=output, fillcolor="#adadad", fontcolor="#000000", shape=record, style="filled,rounded"];
0 -> 3 [label="(1, 1, 3, 3)\n0 → 0"];
1 -> 3 [label="(1, 1, 1, 1)\n0 → 1"];
2 -> 3 [label="(1,)\n0 → 2"];
3 -> 5 [label="(1, 1, 3, 3)\n0 → 0"];
4 -> 5 [label="(1,)\n0 → 1"];
5 -> 6 [label="(1, 1, 3, 3)\n0 → 0"];
6 -> 7 [label="(1, 1, 3, 3)\n0 → 0"];
}
28 changes: 14 additions & 14 deletions tests/torch2/data/function_hook/handle_inner_functions/inner_functions_BatchNormModel.dot
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@@ -1,16 +1,16 @@
digraph {
digraph {
rankdir=TB;
0 [fillcolor="#adadad", fontcolor="#000000", label="{type: input|name: x|dtype: torch.float32|shape: (1, 1, 1)}", shape=record, style="filled,rounded"];
1 [fillcolor="#ffffff", fontcolor="#000000", label="{type: const|name: bn.weight|dtype: torch.float32|shape: (1,)}", shape=record, style="filled,rounded"];
2 [fillcolor="#ffffff", fontcolor="#000000", label="{type: const|name: bn.bias|dtype: torch.float32|shape: (1,)}", shape=record, style="filled,rounded"];
3 [fillcolor="#ffffff", fontcolor="#000000", label="{type: const|name: bn.running_mean|dtype: torch.float32|shape: (1,)}", shape=record, style="filled,rounded"];
4 [fillcolor="#ffffff", fontcolor="#000000", label="{type: const|name: bn.running_var|dtype: torch.float32|shape: (1,)}", shape=record, style="filled,rounded"];
5 [fillcolor="#ffadad", fontcolor="#000000", label="{type: function_call|op_name: bn/batch_norm/0|fn_name: batch_norm|args: [\nTensorMeta(dtype=torch.float32, shape=(1, 1, 1)),\nTensorMeta(dtype=torch.float32, shape=(1,)),\nTensorMeta(dtype=torch.float32, shape=(1,)),\nTensorMeta(dtype=torch.float32, shape=(1,)),\nTensorMeta(dtype=torch.float32, shape=(1,)),\nFalse,\n0.1,\n1e-05,\nTrue,\n]|kwargs: \{\}}", shape=record, style="filled,rounded"];
6 [fillcolor="#adadad", fontcolor="#000000", label="{type: output|name: output|dtype: torch.float32|shape: (1, 1, 1)}", shape=record, style="filled,rounded"];
0 -> 5 [label="(1, 1, 1)\n0 → 0"];
1 -> 5 [label="(1,)\n0 → 1"];
2 -> 5 [label="(1,)\n0 → 2"];
3 -> 5 [label="(1,)\n0 → 3"];
4 -> 5 [label="(1,)\n0 → 4"];
5 -> 6 [label="(1, 1, 1)\n0 → 0"];
0 [label="{type: input|name: x|dtype: torch.float32|shape: (1, 1, 1)}", fillcolor="#adadad", fontcolor="#000000", shape=record, style="filled,rounded"];
1 [label="{type: const|name: bn.weight|dtype: torch.float32|shape: (1,)}", fillcolor="#ffffff", fontcolor="#000000", shape=record, style="filled,rounded"];
2 [label="{type: const|name: bn.bias|dtype: torch.float32|shape: (1,)}", fillcolor="#ffffff", fontcolor="#000000", shape=record, style="filled,rounded"];
3 [label="{type: const|name: bn.running_mean|dtype: torch.float32|shape: (1,)}", fillcolor="#ffffff", fontcolor="#000000", shape=record, style="filled,rounded"];
4 [label="{type: const|name: bn.running_var|dtype: torch.float32|shape: (1,)}", fillcolor="#ffffff", fontcolor="#000000", shape=record, style="filled,rounded"];
5 [label="{type: function_call|op_name: bn/batch_norm/0|fn_name: batch_norm|args: [\nTensorMeta(dtype=torch.float32, shape=(1, 1, 1)),\nTensorMeta(dtype=torch.float32, shape=(1,)),\nTensorMeta(dtype=torch.float32, shape=(1,)),\nTensorMeta(dtype=torch.float32, shape=(1,)),\nTensorMeta(dtype=torch.float32, shape=(1,)),\nFalse,\n0.1,\n1e-05,\nTrue,\n]|kwargs: \{\}}", fillcolor="#ffadad", fontcolor="#000000", shape=record, style="filled,rounded"];
6 [label="{type: output|name: output|dtype: torch.float32|shape: (1, 1, 1)}", fillcolor="#adadad", fontcolor="#000000", shape=record, style="filled,rounded"];
0 -> 5 [label="(1, 1, 1)\n0 → 0"];
1 -> 5 [label="(1,)\n0 → 1"];
2 -> 5 [label="(1,)\n0 → 2"];
3 -> 5 [label="(1,)\n0 → 3"];
4 -> 5 [label="(1,)\n0 → 4"];
5 -> 6 [label="(1, 1, 1)\n0 → 0"];
}
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