From ea7760261aac0f09e0a011ea93bc5880627ba6ce Mon Sep 17 00:00:00 2001 From: Xinqi Li Date: Thu, 31 Jul 2025 08:23:16 +0000 Subject: [PATCH 01/10] support checking model redundancy --- graph_net/test/vision_model_test.py | 4 +- graph_net/torch/__init__.py | 3 +- .../torch/check_redundant_incrementally.py | 64 +++++++++++++++++ graph_net/torch/extractor.py | 17 ++++- .../torch/remove_redundant_incrementally.py | 69 +++++++++++++++++++ graph_net/torch/samples_util.py | 5 ++ graph_net/torch/single_device_runner.py | 67 +++++++++++++----- graph_net/torch/validate.py | 14 +++- samples/torchvision/alexnet/graph_hash.txt | 1 + .../torchvision/convnext_base/graph_hash.txt | 1 + .../torchvision/convnext_large/graph_hash.txt | 1 + .../torchvision/convnext_small/graph_hash.txt | 1 + .../torchvision/convnext_tiny/graph_hash.txt | 1 + .../torchvision/densenet121/graph_hash.txt | 1 + .../torchvision/densenet161/graph_hash.txt | 1 + .../torchvision/densenet169/graph_hash.txt | 1 + .../torchvision/densenet201/graph_hash.txt | 1 + .../efficientnet_b0/graph_hash.txt | 1 + .../efficientnet_b1/graph_hash.txt | 1 + samples/torchvision/googlenet/graph_hash.txt | 1 + .../torchvision/inception_v3/graph_hash.txt | 1 + samples/torchvision/mnasnet0_5/graph_hash.txt | 1 + .../torchvision/mnasnet0_75/graph_hash.txt | 1 + samples/torchvision/mnasnet1_0/graph_hash.txt | 1 + samples/torchvision/mnasnet1_3/graph_hash.txt | 1 + .../torchvision/mobilenet_v2/graph_hash.txt | 1 + .../mobilenet_v3_large/graph_hash.txt | 1 + .../mobilenet_v3_small/graph_hash.txt | 1 + samples/torchvision/r3d_18/graph_hash.txt | 1 + .../torchvision/regnet_x_16gf/graph_hash.txt | 1 + .../torchvision/regnet_x_1_6gf/graph_hash.txt | 1 + .../torchvision/regnet_x_32gf/graph_hash.txt | 1 + .../torchvision/regnet_x_3_2gf/graph_hash.txt | 1 + .../torchvision/regnet_x_400mf/graph_hash.txt | 1 + .../torchvision/regnet_x_800mf/graph_hash.txt | 1 + .../torchvision/regnet_x_8gf/graph_hash.txt | 1 + .../torchvision/regnet_y_128gf/graph_hash.txt | 1 + samples/torchvision/resnet101/graph_hash.txt | 1 + samples/torchvision/resnet152/graph_hash.txt | 1 + samples/torchvision/resnet18/graph_hash.txt | 1 + samples/torchvision/resnet34/graph_hash.txt | 1 + samples/torchvision/resnet50/graph_hash.txt | 1 + .../resnext101_32x8d/graph_hash.txt | 1 + .../resnext101_64x4d/graph_hash.txt | 1 + .../resnext50_32x4d/graph_hash.txt | 1 + .../torchvision/squeezenet1_0/graph_hash.txt | 1 + .../torchvision/squeezenet1_1/graph_hash.txt | 1 + samples/torchvision/vgg11/graph_hash.txt | 1 + samples/torchvision/vgg11_bn/graph_hash.txt | 1 + samples/torchvision/vgg13/graph_hash.txt | 1 + samples/torchvision/vgg13_bn/graph_hash.txt | 1 + samples/torchvision/vgg16/graph_hash.txt | 1 + samples/torchvision/vgg16_bn/graph_hash.txt | 1 + samples/torchvision/vgg19/graph_hash.txt | 1 + samples/torchvision/vgg19_bn/graph_hash.txt | 1 + .../distilbert-base-uncased/graph_hash.txt | 1 + 56 files changed, 268 insertions(+), 23 deletions(-) create mode 100644 graph_net/torch/check_redundant_incrementally.py create mode 100644 graph_net/torch/remove_redundant_incrementally.py create mode 100644 graph_net/torch/samples_util.py create mode 100644 samples/torchvision/alexnet/graph_hash.txt create mode 100644 samples/torchvision/convnext_base/graph_hash.txt create mode 100644 samples/torchvision/convnext_large/graph_hash.txt create mode 100644 samples/torchvision/convnext_small/graph_hash.txt create mode 100644 samples/torchvision/convnext_tiny/graph_hash.txt create mode 100644 samples/torchvision/densenet121/graph_hash.txt create mode 100644 samples/torchvision/densenet161/graph_hash.txt create mode 100644 samples/torchvision/densenet169/graph_hash.txt create mode 100644 samples/torchvision/densenet201/graph_hash.txt create mode 100644 samples/torchvision/efficientnet_b0/graph_hash.txt create mode 100644 samples/torchvision/efficientnet_b1/graph_hash.txt create mode 100644 samples/torchvision/googlenet/graph_hash.txt create mode 100644 samples/torchvision/inception_v3/graph_hash.txt create mode 100644 samples/torchvision/mnasnet0_5/graph_hash.txt create mode 100644 samples/torchvision/mnasnet0_75/graph_hash.txt create mode 100644 samples/torchvision/mnasnet1_0/graph_hash.txt create mode 100644 samples/torchvision/mnasnet1_3/graph_hash.txt create mode 100644 samples/torchvision/mobilenet_v2/graph_hash.txt create mode 100644 samples/torchvision/mobilenet_v3_large/graph_hash.txt create mode 100644 samples/torchvision/mobilenet_v3_small/graph_hash.txt create mode 100644 samples/torchvision/r3d_18/graph_hash.txt create mode 100644 samples/torchvision/regnet_x_16gf/graph_hash.txt create mode 100644 samples/torchvision/regnet_x_1_6gf/graph_hash.txt create mode 100644 samples/torchvision/regnet_x_32gf/graph_hash.txt create mode 100644 samples/torchvision/regnet_x_3_2gf/graph_hash.txt create mode 100644 samples/torchvision/regnet_x_400mf/graph_hash.txt create mode 100644 samples/torchvision/regnet_x_800mf/graph_hash.txt create mode 100644 samples/torchvision/regnet_x_8gf/graph_hash.txt create mode 100644 samples/torchvision/regnet_y_128gf/graph_hash.txt create mode 100644 samples/torchvision/resnet101/graph_hash.txt create mode 100644 samples/torchvision/resnet152/graph_hash.txt create mode 100644 samples/torchvision/resnet18/graph_hash.txt create mode 100644 samples/torchvision/resnet34/graph_hash.txt create mode 100644 samples/torchvision/resnet50/graph_hash.txt create mode 100644 samples/torchvision/resnext101_32x8d/graph_hash.txt create mode 100644 samples/torchvision/resnext101_64x4d/graph_hash.txt create mode 100644 samples/torchvision/resnext50_32x4d/graph_hash.txt create mode 100644 samples/torchvision/squeezenet1_0/graph_hash.txt create mode 100644 samples/torchvision/squeezenet1_1/graph_hash.txt create mode 100644 samples/torchvision/vgg11/graph_hash.txt create mode 100644 samples/torchvision/vgg11_bn/graph_hash.txt create mode 100644 samples/torchvision/vgg13/graph_hash.txt create mode 100644 samples/torchvision/vgg13_bn/graph_hash.txt create mode 100644 samples/torchvision/vgg16/graph_hash.txt create mode 100644 samples/torchvision/vgg16_bn/graph_hash.txt create mode 100644 samples/torchvision/vgg19/graph_hash.txt create mode 100644 samples/torchvision/vgg19_bn/graph_hash.txt create mode 100644 samples/transformers-auto-model/distilbert-base-uncased/graph_hash.txt diff --git a/graph_net/test/vision_model_test.py b/graph_net/test/vision_model_test.py index 498a9c207..0002cbec6 100644 --- a/graph_net/test/vision_model_test.py +++ b/graph_net/test/vision_model_test.py @@ -29,9 +29,9 @@ model.to(device) normalized_input = normalized_input.to(device) - model = graph_net.torch.extract(name="resnet18")(model) + model = graph_net.torch.extract(name="resnet18", placeholder_auto_rename=True)(model) print("Running inference...") print("Input shape:", normalized_input.shape) output = model(normalized_input) - print("Inference finished. Output shape:", output.shape) \ No newline at end of file + print("Inference finished. Output shape:", output.shape) diff --git a/graph_net/torch/__init__.py b/graph_net/torch/__init__.py index 2fc126c2c..eaafa4497 100644 --- a/graph_net/torch/__init__.py +++ b/graph_net/torch/__init__.py @@ -3,5 +3,6 @@ """ from .extractor import extract +from .samples_util import get_default_samples_directory -__all__ = ['extract'] \ No newline at end of file +__all__ = ['extract', 'get_default_samples_directory'] diff --git a/graph_net/torch/check_redundant_incrementally.py b/graph_net/torch/check_redundant_incrementally.py new file mode 100644 index 000000000..d07686f03 --- /dev/null +++ b/graph_net/torch/check_redundant_incrementally.py @@ -0,0 +1,64 @@ +from . import utils +import argparse +import importlib.util +import inspect +import torch +from pathlib import Path +from typing import Type, Any +import sys +import os +import os.path +from dataclasses import dataclass +from contextlib import contextmanager +import time +import glob + +def get_recursively_model_pathes(root_dir): + if is_single_model_dir(root_dir): + yield root_dir + return + for sub_dir in get_immediate_subdirectory_paths(root_dir): + if is_single_model_dir(sub_dir): + yield sub_dir + else: + yield from get_recursively_model_pathes(sub_dir) + +def get_immediate_subdirectory_paths(parent_dir): + return [ + sub_dir + for name in os.listdir(parent_dir) + for sub_dir in [os.path.join(parent_dir, name)] + if os.path.isdir(sub_dir) + ] + +def is_single_model_dir(model_dir): + return os.path.isfile(f"{model_dir}/graph_net.json") + +def main(args): + assert os.path.isdir(args.model_path) + assert os.path.isdir(args.graph_net_samples_path) + current_model_graph_hash_pathes = set( + graph_hash_path + for model_path in get_recursively_model_pathes(args.model_path) + for graph_hash_path in [f"{model_path}/graph_hash.txt"] + ) + graph_hash2graph_net_model_path = { + graph_hash:graph_hash_path + for model_path in get_recursively_model_pathes(args.graph_net_samples_path) + for graph_hash_path in [f"{model_path}/graph_hash.txt"] + if os.path.isfile(graph_hash_path) + if graph_hash_path not in current_model_graph_hash_pathes + for graph_hash in [open(graph_hash_path).read()] + } + for current_model_graph_hash_path in current_model_graph_hash_pathes: + graph_hash = open(current_model_graph_hash_path).read() + assert graph_hash not in graph_hash2graph_net_model_path, f"Redundant models detected. old-model-path:{current_model_graph_hash_path}, new-model-path:{graph_hash2graph_net_model_path[graph_hash]}." + +if __name__ == '__main__': + parser = argparse.ArgumentParser(description="Test compiler performance.") + parser.add_argument("--model-path", type=str, required=True, + help="Path to model file(s), each subdirectory containing graph_net.json will be regarded as a model") + parser.add_argument("--graph-net-samples-path", type=str, required=False, default='default', + help="Path to GraphNet samples") + args = parser.parse_args() + main(args=args) diff --git a/graph_net/torch/extractor.py b/graph_net/torch/extractor.py index 744221236..535f99fde 100644 --- a/graph_net/torch/extractor.py +++ b/graph_net/torch/extractor.py @@ -5,7 +5,7 @@ from . import utils -def extract(name, dynamic=True): +def extract(name, dynamic=True, mut_graph_codes=None, placeholder_auto_rename=False): """ A decorator for PyTorch functions to capture the computation graph. @@ -30,16 +30,31 @@ def extractor(gm: torch.fx.GraphModule, sample_inputs): # 2. Get full params params = {} input_idx = 0 + unique_id = 0 + def try_rename_placeholder(node): + assert node.op == "placeholder" + if not placeholder_auto_rename: + return + nonlocal unique_id + node.target = f"v{unique_id}" + unique_id += 1 + node.name = f"v{unique_id}" + unique_id += 1 for node in gm.graph.nodes: if node.op == "placeholder": + try_rename_placeholder(node) input = sample_inputs[input_idx] if isinstance(input, torch.SymInt): input = torch.tensor(4) params[node.target] = input input_idx += 1 assert input_idx == len(sample_inputs) + if mut_graph_codes is not None: + assert isinstance(mut_graph_codes, list) + mut_graph_codes.append(gm.code) # 3. Generate and save model code base_code = gm.code + # gm.graph.print_tabular() write_code = utils.apply_templates(base_code) with open(os.path.join(model_path, "model.py"), "w") as fp: fp.write(write_code) diff --git a/graph_net/torch/remove_redundant_incrementally.py b/graph_net/torch/remove_redundant_incrementally.py new file mode 100644 index 000000000..2cf8e137f --- /dev/null +++ b/graph_net/torch/remove_redundant_incrementally.py @@ -0,0 +1,69 @@ +from . import utils +import argparse +import importlib.util +import inspect +import torch +from pathlib import Path +from typing import Type, Any +import sys +import os +import os.path +from dataclasses import dataclass +from contextlib import contextmanager +import time +import glob +import shutil + +def get_recursively_model_pathes(root_dir): + if is_single_model_dir(root_dir): + yield root_dir + return + for sub_dir in get_immediate_subdirectory_paths(root_dir): + if is_single_model_dir(sub_dir): + yield sub_dir + else: + yield from get_recursively_model_pathes(sub_dir) + +def get_immediate_subdirectory_paths(parent_dir): + return [ + sub_dir + for name in os.listdir(parent_dir) + for sub_dir in [os.path.join(parent_dir, name)] + if os.path.isdir(sub_dir) + ] + +def is_single_model_dir(model_dir): + return os.path.isfile(f"{model_dir}/graph_net.json") + +def main(args): + assert os.path.isdir(args.model_path) + assert os.path.isdir(args.graph_net_samples_path) + current_model_graph_hash_pathes = set( + graph_hash_path + for model_path in get_recursively_model_pathes(args.model_path) + for graph_hash_path in [f"{model_path}/graph_hash.txt"] + ) + graph_hash2graph_net_model_path = { + graph_hash:graph_hash_path + for model_path in get_recursively_model_pathes(args.graph_net_samples_path) + for graph_hash_path in [f"{model_path}/graph_hash.txt"] + if os.path.isfile(graph_hash_path) + if graph_hash_path not in current_model_graph_hash_pathes + for graph_hash in [open(graph_hash_path).read()] + } + for current_model_graph_hash_path in current_model_graph_hash_pathes: + graph_hash = open(current_model_graph_hash_path).read() + if graph_hash not in graph_hash2graph_net_model_path: + continue + directory = os.path.dirname(current_model_graph_hash_path) + shutil.rmtree(directory) + os.makedirs(directory, exist_ok=True) + +if __name__ == '__main__': + parser = argparse.ArgumentParser(description="Test compiler performance.") + parser.add_argument("--model-path", type=str, required=True, + help="Path to model file(s), each subdirectory containing graph_net.json will be regarded as a model") + parser.add_argument("--graph-net-samples-path", type=str, required=False, default='default', + help="Path to GraphNet samples") + args = parser.parse_args() + main(args=args) diff --git a/graph_net/torch/samples_util.py b/graph_net/torch/samples_util.py new file mode 100644 index 000000000..3fa7ea910 --- /dev/null +++ b/graph_net/torch/samples_util.py @@ -0,0 +1,5 @@ +import graph_net +import os + +def get_default_samples_directory(): + return f"{os.path.dirname(graph_net.__file__)}/../samples" diff --git a/graph_net/torch/single_device_runner.py b/graph_net/torch/single_device_runner.py index aedf3aeaf..732d9a881 100644 --- a/graph_net/torch/single_device_runner.py +++ b/graph_net/torch/single_device_runner.py @@ -7,6 +7,8 @@ from typing import Type, Any import sys from graph_net.torch.extractor import extract +import hashlib +from contextlib import contextmanager def load_class_from_file(file_path: str, class_name: str) -> Type[torch.nn.Module]: @@ -15,32 +17,61 @@ def load_class_from_file(file_path: str, class_name: str) -> Type[torch.nn.Modul spec.loader.exec_module(unnamed) model_class = getattr(unnamed, class_name, None) return model_class + +def _get_sha_hash(content): + m = hashlib.sha256() + m.update(content.encode()) + return m.hexdigest() -def main(args): - model_path = args.model_path - model_class = load_class_from_file(f"{model_path}/model.py", class_name="GraphModule") - assert model_class is not None - model = model_class() - print(f'{model_path=}') - if args.enable_extract: - assert args.extract_name is not None - model = extract(name=args.extract_name)(model) - - inputs_params = utils.load_converted_from_text(f'{model_path}') - params = inputs_params["weight_info"] - state_dict = { - k: utils.replay_tensor(v) for k, v in params.items() +def _save_to_model_path(dump_dir, hash_text): + file_path = f"{dump_dir}/graph_hash.txt" + with open(file_path, 'w') as f: + f.write(hash_text) + +@contextmanager +def _dump_graph_hash_key_ctx(cmd_args): + if not cmd_args.dump_graph_hash_key: + yield {} + return + mut_graph_codes = [] + extractor_kwarg = { + 'placeholder_auto_rename': True, + 'mut_graph_codes': mut_graph_codes } - - y = model(**state_dict)[0] + yield extractor_kwarg + if len(mut_graph_codes) > 0: + assert len(mut_graph_codes) == 1, f"{len(mut_graph_codes)=}" + _save_to_model_path(cmd_args.model_path, _get_sha_hash(mut_graph_codes[0])) + + +def main(args): + with _dump_graph_hash_key_ctx(args) as dump_graph_options: + model_path = args.model_path + model_class = load_class_from_file(f"{model_path}/model.py", class_name="GraphModule") + assert model_class is not None + model = model_class() + print(f'{model_path=}') + if args.enable_extract: + assert args.extract_name is not None + kwargs = dict(name=args.extract_name, **dump_graph_options) + model = extract(**kwargs)(model) + + inputs_params = utils.load_converted_from_text(f'{model_path}') + params = inputs_params["weight_info"] + state_dict = { + k: utils.replay_tensor(v) for k, v in params.items() + } + + y = model(**state_dict)[0] - print(torch.argmin(y), torch.argmax(y)) - print(y.shape) + print(torch.argmin(y), torch.argmax(y)) + print(y.shape) if __name__ == '__main__': parser = argparse.ArgumentParser(description="load and run model") parser.add_argument("--model-path", type=str, required=True, help="Path to folder e.g '../../samples/torch/resnet18'") + parser.add_argument("--dump-graph-hash-key", action='store_true', default=False, help="Dump graph hash key") parser.add_argument("--enable-extract", type=bool, required=False, default=False, help="Enable extract") parser.add_argument("--extract-name", type=str, required=False, default=None, help="Extracted graph's name") args = parser.parse_args() diff --git a/graph_net/torch/validate.py b/graph_net/torch/validate.py index f6c7c6824..7da67ccf0 100644 --- a/graph_net/torch/validate.py +++ b/graph_net/torch/validate.py @@ -3,6 +3,7 @@ import tempfile import sys import contextlib +import graph_net @contextlib.contextmanager def temp_workspace(): @@ -17,12 +18,21 @@ def main(args): model_path = args.model_path with temp_workspace() as tmp_dir_name: extract_name = "temp" - cmd = f'{sys.executable} -m graph_net.torch.single_device_runner --model-path {model_path} --enable-extract True --extract-name {extract_name}' + print("Check extractability ...") + cmd = f'{sys.executable} -m graph_net.torch.single_device_runner --model-path {model_path} --enable-extract True --extract-name {extract_name} --dump-graph-hash-key True' cmd_ret = os.system(cmd) assert cmd_ret == 0, f'{cmd_ret=}, {cmd=}' cmd = f'{sys.executable} -m graph_net.torch.single_device_runner --model-path {tmp_dir_name}/{extract_name}' cmd_ret = os.system(cmd) assert cmd_ret == 0, f'{cmd_ret=}, {cmd=}' + if not args.no_check_redundancy: + print("Check redundancy ...") + graph_net_samples_path = graph_net.torch.samples_util.get_default_samples_directory() + cmd = f"{sys.executable} -m graph_net.torch.check_redundant_incrementally --model-path {args.model_path} --graph-net-samples-path {graph_net_samples_path}" + cmd_ret = os.system(cmd) + rm_cmd = f"{sys.executable} -m graph_net.torch.remove_redundant_incrementally --model-path {args.model_path} --graph-net-samples-path {graph_net_samples_path}" + assert cmd_ret == 0, f"\nPlease use the following command to remove redundant model directories:\n\n{rm_cmd}\n" + print(f'Validation success, {model_path=}') @@ -30,6 +40,8 @@ def main(args): parser = argparse.ArgumentParser(description="load and run model") parser.add_argument("--model-path", type=str, required=True, help="Path to folder e.g '../../samples/torch/resnet18'") + parser.add_argument("--no-check-redundancy", action='store_true', + help="whether check model graph redundancy") args = parser.parse_args() main(args=args) diff --git a/samples/torchvision/alexnet/graph_hash.txt b/samples/torchvision/alexnet/graph_hash.txt new file mode 100644 index 000000000..582f90575 --- /dev/null +++ b/samples/torchvision/alexnet/graph_hash.txt @@ -0,0 +1 @@ +9f9d4addeb6cb388deab98fdc9c7b23a86972575b2b40c616a0ad944cd6bc1fe \ No newline at end of file diff --git a/samples/torchvision/convnext_base/graph_hash.txt b/samples/torchvision/convnext_base/graph_hash.txt new file mode 100644 index 000000000..9ef960a15 --- /dev/null +++ b/samples/torchvision/convnext_base/graph_hash.txt @@ -0,0 +1 @@ +714c33398060d08f52081e798ab9f9644b5199e72ef4693df17edbd55a81b8df \ No newline at end of file diff --git a/samples/torchvision/convnext_large/graph_hash.txt b/samples/torchvision/convnext_large/graph_hash.txt new file mode 100644 index 000000000..49f0694a1 --- /dev/null +++ b/samples/torchvision/convnext_large/graph_hash.txt @@ -0,0 +1 @@ +701eb1e25733659c94cf2125568e8703fd1b318acd496b2ed6d87b77ad89f027 \ No newline at end of file diff --git a/samples/torchvision/convnext_small/graph_hash.txt b/samples/torchvision/convnext_small/graph_hash.txt new file mode 100644 index 000000000..47a487c12 --- /dev/null +++ b/samples/torchvision/convnext_small/graph_hash.txt @@ -0,0 +1 @@ +e5b3c7e5c7f50a53d4d1b898f88506f01398347c7244cee9d75bbb401de35104 \ No newline at end of file diff --git a/samples/torchvision/convnext_tiny/graph_hash.txt b/samples/torchvision/convnext_tiny/graph_hash.txt new file mode 100644 index 000000000..97ca97502 --- /dev/null +++ b/samples/torchvision/convnext_tiny/graph_hash.txt @@ -0,0 +1 @@ +a254270566b45214bf8de7994ad9692f326484bd15db6ce08ec55eb2dea35411 \ No newline at end of file diff --git a/samples/torchvision/densenet121/graph_hash.txt b/samples/torchvision/densenet121/graph_hash.txt new file mode 100644 index 000000000..21678187e --- /dev/null +++ b/samples/torchvision/densenet121/graph_hash.txt @@ -0,0 +1 @@ +a218d776dfc4fc897dcb36c2bac96153bcb468cd581cd1b5f53e24b0365eb130 \ No newline at end of file diff --git a/samples/torchvision/densenet161/graph_hash.txt b/samples/torchvision/densenet161/graph_hash.txt new file mode 100644 index 000000000..2bbe1ffdf --- /dev/null +++ b/samples/torchvision/densenet161/graph_hash.txt @@ -0,0 +1 @@ +a0e6158f429c8206b59e2b7afd58728ca151216a7eb03a0c84a0111bb5ab7a11 \ No newline at end of file diff --git a/samples/torchvision/densenet169/graph_hash.txt b/samples/torchvision/densenet169/graph_hash.txt new file mode 100644 index 000000000..17f7b1e1c --- /dev/null +++ b/samples/torchvision/densenet169/graph_hash.txt @@ -0,0 +1 @@ +bdfb22fd4a337e568baab559647b72d3da717cb978154eec316ef8969910c77f \ No newline at end of file diff --git a/samples/torchvision/densenet201/graph_hash.txt b/samples/torchvision/densenet201/graph_hash.txt new file mode 100644 index 000000000..124b07737 --- /dev/null +++ b/samples/torchvision/densenet201/graph_hash.txt @@ -0,0 +1 @@ +973964bc7dd5bc2d33b009de4ba19d87034d74292ac9859757a9ffc678b18caf \ No newline at end of file diff --git a/samples/torchvision/efficientnet_b0/graph_hash.txt b/samples/torchvision/efficientnet_b0/graph_hash.txt new file mode 100644 index 000000000..76d24228e --- /dev/null +++ b/samples/torchvision/efficientnet_b0/graph_hash.txt @@ -0,0 +1 @@ +c2cae9c443d22d14ae37dd70f233030e2d20d0c132e0282dabd6de45c0f678a8 \ No newline at end of file diff --git a/samples/torchvision/efficientnet_b1/graph_hash.txt b/samples/torchvision/efficientnet_b1/graph_hash.txt new file mode 100644 index 000000000..d45814531 --- /dev/null +++ b/samples/torchvision/efficientnet_b1/graph_hash.txt @@ -0,0 +1 @@ +104b21c6844482eb728ea323f0c01e279f1bb0b89f68870d10ae7e9238fa6130 \ No newline at end of file diff --git a/samples/torchvision/googlenet/graph_hash.txt b/samples/torchvision/googlenet/graph_hash.txt new file mode 100644 index 000000000..b751047aa --- /dev/null +++ b/samples/torchvision/googlenet/graph_hash.txt @@ -0,0 +1 @@ +67ae6c6cd0497cba3ab8549b012eb711f4278e1f1c7d6be58e41ff5064238ea4 \ No newline at end of file diff --git a/samples/torchvision/inception_v3/graph_hash.txt b/samples/torchvision/inception_v3/graph_hash.txt new file mode 100644 index 000000000..bbdbae6ee --- /dev/null +++ b/samples/torchvision/inception_v3/graph_hash.txt @@ -0,0 +1 @@ +cd9047b1958d5f9bc0638965adb73847bdd997418c4f269a02857f7c44286c69 \ No newline at end of file diff --git a/samples/torchvision/mnasnet0_5/graph_hash.txt b/samples/torchvision/mnasnet0_5/graph_hash.txt new file mode 100644 index 000000000..844df4185 --- /dev/null +++ b/samples/torchvision/mnasnet0_5/graph_hash.txt @@ -0,0 +1 @@ +bf4e7567be3a21c38277b12adb46fe2122b713f897b88a5050f0138c852fb537 \ No newline at end of file diff --git a/samples/torchvision/mnasnet0_75/graph_hash.txt b/samples/torchvision/mnasnet0_75/graph_hash.txt new file mode 100644 index 000000000..f5687c39e --- /dev/null +++ b/samples/torchvision/mnasnet0_75/graph_hash.txt @@ -0,0 +1 @@ +f306d203bfef03a0dc879ed0064f9c9a11ae40d89e49d21a162ba86b2ffe4f67 \ No newline at end of file diff --git a/samples/torchvision/mnasnet1_0/graph_hash.txt b/samples/torchvision/mnasnet1_0/graph_hash.txt new file mode 100644 index 000000000..210e5eb69 --- /dev/null +++ b/samples/torchvision/mnasnet1_0/graph_hash.txt @@ -0,0 +1 @@ +c630c94e3b73740215fc2e5621348c7f8b89826018fe8faafe4ed8b3ae860833 \ No newline at end of file diff --git a/samples/torchvision/mnasnet1_3/graph_hash.txt b/samples/torchvision/mnasnet1_3/graph_hash.txt new file mode 100644 index 000000000..54ce079c4 --- /dev/null +++ b/samples/torchvision/mnasnet1_3/graph_hash.txt @@ -0,0 +1 @@ +4b443a19e694bf7409af76dc66ce0bb49154109cf798f1d30fd15f7c878a4a04 \ No newline at end of file diff --git a/samples/torchvision/mobilenet_v2/graph_hash.txt b/samples/torchvision/mobilenet_v2/graph_hash.txt new file mode 100644 index 000000000..5c36dd3cc --- /dev/null +++ b/samples/torchvision/mobilenet_v2/graph_hash.txt @@ -0,0 +1 @@ +c8e857abd33ff165958fc373cad510dd8e9ea5ed85a942c7b127b09c7b96978a \ No newline at end of file diff --git a/samples/torchvision/mobilenet_v3_large/graph_hash.txt b/samples/torchvision/mobilenet_v3_large/graph_hash.txt new file mode 100644 index 000000000..05459c859 --- /dev/null +++ b/samples/torchvision/mobilenet_v3_large/graph_hash.txt @@ -0,0 +1 @@ +e599ad974d8bdf45566ddc3e784f6a380a09c34dc121cadb1340935bf034c712 \ No newline at end of file diff --git a/samples/torchvision/mobilenet_v3_small/graph_hash.txt b/samples/torchvision/mobilenet_v3_small/graph_hash.txt new file mode 100644 index 000000000..c26fe8efb --- /dev/null +++ b/samples/torchvision/mobilenet_v3_small/graph_hash.txt @@ -0,0 +1 @@ +6f069533f581a2a10a2cc5b9744da88fe96a4a2998a5165fdcc12076382b90fd \ No newline at end of file diff --git a/samples/torchvision/r3d_18/graph_hash.txt b/samples/torchvision/r3d_18/graph_hash.txt new file mode 100644 index 000000000..6d0703cec --- /dev/null +++ b/samples/torchvision/r3d_18/graph_hash.txt @@ -0,0 +1 @@ +5d11a010c31a695dc64121c46e16dd33cd9903192a57f60fd90820238d2e5a46 \ No newline at end of file diff --git a/samples/torchvision/regnet_x_16gf/graph_hash.txt b/samples/torchvision/regnet_x_16gf/graph_hash.txt new file mode 100644 index 000000000..eedc9899c --- /dev/null +++ b/samples/torchvision/regnet_x_16gf/graph_hash.txt @@ -0,0 +1 @@ +82d4abbf7ed005f4d4fe451b713f3f90438ab09e0e1b6c93c57ea0b60ede989d \ No newline at end of file diff --git a/samples/torchvision/regnet_x_1_6gf/graph_hash.txt b/samples/torchvision/regnet_x_1_6gf/graph_hash.txt new file mode 100644 index 000000000..4eab7a759 --- /dev/null +++ b/samples/torchvision/regnet_x_1_6gf/graph_hash.txt @@ -0,0 +1 @@ +afe4ad7c79375b6dec61d20b60d346e0a848abbba2f44ab44d81a912653ddb05 \ No newline at end of file diff --git a/samples/torchvision/regnet_x_32gf/graph_hash.txt b/samples/torchvision/regnet_x_32gf/graph_hash.txt new file mode 100644 index 000000000..387d8209a --- /dev/null +++ b/samples/torchvision/regnet_x_32gf/graph_hash.txt @@ -0,0 +1 @@ +c48e822ac367b90e1f6fdd8533d3751606f71fe1bb10959a7a7a0a0d8e4a45ff \ No newline at end of file diff --git a/samples/torchvision/regnet_x_3_2gf/graph_hash.txt b/samples/torchvision/regnet_x_3_2gf/graph_hash.txt new file mode 100644 index 000000000..23cf8eec8 --- /dev/null +++ b/samples/torchvision/regnet_x_3_2gf/graph_hash.txt @@ -0,0 +1 @@ +51079e8fcf3e2c9e4e5422290d693de770b0ba1651b8fda9afc64082006db261 \ No newline at end of file diff --git a/samples/torchvision/regnet_x_400mf/graph_hash.txt b/samples/torchvision/regnet_x_400mf/graph_hash.txt new file mode 100644 index 000000000..e437ad362 --- /dev/null +++ b/samples/torchvision/regnet_x_400mf/graph_hash.txt @@ -0,0 +1 @@ +b9bb661182c5f360458630f6c54c47be4503547feac48c03fdd0995d03647445 \ No newline at end of file diff --git a/samples/torchvision/regnet_x_800mf/graph_hash.txt b/samples/torchvision/regnet_x_800mf/graph_hash.txt new file mode 100644 index 000000000..1820e63da --- /dev/null +++ b/samples/torchvision/regnet_x_800mf/graph_hash.txt @@ -0,0 +1 @@ +3665fd276f34a63a9f1a36b0a8b4d645ed3d82352f1f514cbb4c6bcbb63d4d9e \ No newline at end of file diff --git a/samples/torchvision/regnet_x_8gf/graph_hash.txt b/samples/torchvision/regnet_x_8gf/graph_hash.txt new file mode 100644 index 000000000..879bcaa21 --- /dev/null +++ b/samples/torchvision/regnet_x_8gf/graph_hash.txt @@ -0,0 +1 @@ +0663ed7feea418ff45015f88a1c93402be76b84031cfbbfd6b1d4b66f8f55cda \ No newline at end of file diff --git a/samples/torchvision/regnet_y_128gf/graph_hash.txt b/samples/torchvision/regnet_y_128gf/graph_hash.txt new file mode 100644 index 000000000..b53533d7d --- /dev/null +++ b/samples/torchvision/regnet_y_128gf/graph_hash.txt @@ -0,0 +1 @@ +1513c5f929c4b0557b4020293f3cdd667169ffc8c8d05320a08d8fdb8a50f285 \ No newline at end of file diff --git a/samples/torchvision/resnet101/graph_hash.txt b/samples/torchvision/resnet101/graph_hash.txt new file mode 100644 index 000000000..ef24b0a92 --- /dev/null +++ b/samples/torchvision/resnet101/graph_hash.txt @@ -0,0 +1 @@ +0cbc99e22d6c50c11fb02aca0ded3f01a0f7dd3474d2f65e12f956a11b08b2cb \ No newline at end of file diff --git a/samples/torchvision/resnet152/graph_hash.txt b/samples/torchvision/resnet152/graph_hash.txt new file mode 100644 index 000000000..8778f1e22 --- /dev/null +++ b/samples/torchvision/resnet152/graph_hash.txt @@ -0,0 +1 @@ +e6285a1eea52cf08f0ac621086e773ab4763f2a1d07fe155a1f009e0bebcc272 \ No newline at end of file diff --git a/samples/torchvision/resnet18/graph_hash.txt b/samples/torchvision/resnet18/graph_hash.txt new file mode 100644 index 000000000..a43bbde05 --- /dev/null +++ b/samples/torchvision/resnet18/graph_hash.txt @@ -0,0 +1 @@ +9d1568d6617d5b2d5d3762b24b3c296f63fe423cfecdc27d6ecd425c0290de74 \ No newline at end of file diff --git a/samples/torchvision/resnet34/graph_hash.txt b/samples/torchvision/resnet34/graph_hash.txt new file mode 100644 index 000000000..c47fd8879 --- /dev/null +++ b/samples/torchvision/resnet34/graph_hash.txt @@ -0,0 +1 @@ +ebab7b3df841647c90ec576ffd128b64c04de03a89325407110f3a9e3047fc66 \ No newline at end of file diff --git a/samples/torchvision/resnet50/graph_hash.txt b/samples/torchvision/resnet50/graph_hash.txt new file mode 100644 index 000000000..c4d4c065a --- /dev/null +++ b/samples/torchvision/resnet50/graph_hash.txt @@ -0,0 +1 @@ +87396dbda3e3e3177c581d5b79fe44c45f5dc1fb8432e1d2ea21aee4febe0c4f \ No newline at end of file diff --git a/samples/torchvision/resnext101_32x8d/graph_hash.txt b/samples/torchvision/resnext101_32x8d/graph_hash.txt new file mode 100644 index 000000000..916aa88a0 --- /dev/null +++ b/samples/torchvision/resnext101_32x8d/graph_hash.txt @@ -0,0 +1 @@ +52a11486e82cb4a71b6393d7af95da2218927178f0c60baa8c391825dca9fa44 \ No newline at end of file diff --git a/samples/torchvision/resnext101_64x4d/graph_hash.txt b/samples/torchvision/resnext101_64x4d/graph_hash.txt new file mode 100644 index 000000000..a0407b9f0 --- /dev/null +++ b/samples/torchvision/resnext101_64x4d/graph_hash.txt @@ -0,0 +1 @@ +024a2573cbd5ebb5300cac0faf62b73b682a3651bcb0f6eea089c3eb6683a2a0 \ No newline at end of file diff --git a/samples/torchvision/resnext50_32x4d/graph_hash.txt b/samples/torchvision/resnext50_32x4d/graph_hash.txt new file mode 100644 index 000000000..b4d4c6051 --- /dev/null +++ b/samples/torchvision/resnext50_32x4d/graph_hash.txt @@ -0,0 +1 @@ +2e3e9ce73f4693d66c60727f4285fe8bd8757b4103f5832354a95e750533ab62 \ No newline at end of file diff --git a/samples/torchvision/squeezenet1_0/graph_hash.txt b/samples/torchvision/squeezenet1_0/graph_hash.txt new file mode 100644 index 000000000..813f39966 --- /dev/null +++ b/samples/torchvision/squeezenet1_0/graph_hash.txt @@ -0,0 +1 @@ +9ad67491386ba2cd1b77ac21ef76624e5b9c58f6992b3411f40f2fe9a2153f55 \ No newline at end of file diff --git a/samples/torchvision/squeezenet1_1/graph_hash.txt b/samples/torchvision/squeezenet1_1/graph_hash.txt new file mode 100644 index 000000000..9c2ce5a6c --- /dev/null +++ b/samples/torchvision/squeezenet1_1/graph_hash.txt @@ -0,0 +1 @@ +06ae5589119525532e61d159a8173eb94f56faacd3e823342bd471233c958404 \ No newline at end of file diff --git a/samples/torchvision/vgg11/graph_hash.txt b/samples/torchvision/vgg11/graph_hash.txt new file mode 100644 index 000000000..40f598864 --- /dev/null +++ b/samples/torchvision/vgg11/graph_hash.txt @@ -0,0 +1 @@ +68ad60dba65c7769563ebba85aa8981038338b062af8f913d7bce421284b11ce \ No newline at end of file diff --git a/samples/torchvision/vgg11_bn/graph_hash.txt b/samples/torchvision/vgg11_bn/graph_hash.txt new file mode 100644 index 000000000..1963d3c0a --- /dev/null +++ b/samples/torchvision/vgg11_bn/graph_hash.txt @@ -0,0 +1 @@ +ec7a8669233e90e10dbae7b9fb4d72b7e59edd6564abf418431ed048919e54bd \ No newline at end of file diff --git a/samples/torchvision/vgg13/graph_hash.txt b/samples/torchvision/vgg13/graph_hash.txt new file mode 100644 index 000000000..7b4c7fd09 --- /dev/null +++ b/samples/torchvision/vgg13/graph_hash.txt @@ -0,0 +1 @@ +8b01e935f3fe706b8590e93c8c81a415927115dd7b261424a6b995b1eaec30eb \ No newline at end of file diff --git a/samples/torchvision/vgg13_bn/graph_hash.txt b/samples/torchvision/vgg13_bn/graph_hash.txt new file mode 100644 index 000000000..7db8f1c0e --- /dev/null +++ b/samples/torchvision/vgg13_bn/graph_hash.txt @@ -0,0 +1 @@ +c8c3cf0e5b103707fd6db3bd6caa2da73642ee7b06a788e66e01dcd28d6b815d \ No newline at end of file diff --git a/samples/torchvision/vgg16/graph_hash.txt b/samples/torchvision/vgg16/graph_hash.txt new file mode 100644 index 000000000..f2f2b3354 --- /dev/null +++ b/samples/torchvision/vgg16/graph_hash.txt @@ -0,0 +1 @@ +7877919aec2a5accc5be74c1145585a5b71407d81633ebc919d102ea54781f90 \ No newline at end of file diff --git a/samples/torchvision/vgg16_bn/graph_hash.txt b/samples/torchvision/vgg16_bn/graph_hash.txt new file mode 100644 index 000000000..a80927aa2 --- /dev/null +++ b/samples/torchvision/vgg16_bn/graph_hash.txt @@ -0,0 +1 @@ +95aa20ff842033ee57afd421c4237019307c520a1ae8e62490d3ea298e55607e \ No newline at end of file diff --git a/samples/torchvision/vgg19/graph_hash.txt b/samples/torchvision/vgg19/graph_hash.txt new file mode 100644 index 000000000..7370a3412 --- /dev/null +++ b/samples/torchvision/vgg19/graph_hash.txt @@ -0,0 +1 @@ +3396d4d7859b75da9f131f47d184c885bdfae13c070f2ad80c975b7b118b923c \ No newline at end of file diff --git a/samples/torchvision/vgg19_bn/graph_hash.txt b/samples/torchvision/vgg19_bn/graph_hash.txt new file mode 100644 index 000000000..ca8131ca2 --- /dev/null +++ b/samples/torchvision/vgg19_bn/graph_hash.txt @@ -0,0 +1 @@ +e6c3807886040e406a69dff874a542ce634c00370c84de3672e09b2cd1ae574c \ No newline at end of file diff --git a/samples/transformers-auto-model/distilbert-base-uncased/graph_hash.txt b/samples/transformers-auto-model/distilbert-base-uncased/graph_hash.txt new file mode 100644 index 000000000..2acaca732 --- /dev/null +++ b/samples/transformers-auto-model/distilbert-base-uncased/graph_hash.txt @@ -0,0 +1 @@ +b657cdf3f52b9717c7a8c5a76b380e19be40fddf843fefe4eee488a10429d8e1 \ No newline at end of file From c21cb49e5ca8aa544bd9f3d83ee11a5821d6e5ea Mon Sep 17 00:00:00 2001 From: Xinqi Li Date: Thu, 31 Jul 2025 08:25:19 +0000 Subject: [PATCH 02/10] revert change of vision_model_test --- graph_net/test/vision_model_test.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/graph_net/test/vision_model_test.py b/graph_net/test/vision_model_test.py index 0002cbec6..c2c41c7de 100644 --- a/graph_net/test/vision_model_test.py +++ b/graph_net/test/vision_model_test.py @@ -29,7 +29,7 @@ model.to(device) normalized_input = normalized_input.to(device) - model = graph_net.torch.extract(name="resnet18", placeholder_auto_rename=True)(model) + model = graph_net.torch.extract(name="resnet18")(model) print("Running inference...") print("Input shape:", normalized_input.shape) From ca9017f281c5b535897e7b03e613d606cc52d312 Mon Sep 17 00:00:00 2001 From: Xinqi Li Date: Thu, 31 Jul 2025 08:28:19 +0000 Subject: [PATCH 03/10] reformat python code. --- graph_net/__init__.py | 2 +- graph_net/config.py | 40 ++- graph_net/pack.py | 44 +-- graph_net/status.py | 17 +- graph_net/test/bert_model_test.py | 11 +- graph_net/test/vision_model_test.py | 7 +- graph_net/torch/__init__.py | 2 +- .../torch/check_redundant_incrementally.py | 30 +- graph_net/torch/extractor.py | 2 + .../torch/remove_redundant_incrementally.py | 26 +- graph_net/torch/samples_util.py | 3 +- graph_net/torch/single_device_runner.py | 59 ++-- graph_net/torch/test_compiler.py | 271 ++++++++++-------- graph_net/torch/utils.py | 73 +++-- graph_net/torch/validate.py | 46 +-- graph_net/unpack.py | 25 +- 16 files changed, 400 insertions(+), 258 deletions(-) diff --git a/graph_net/__init__.py b/graph_net/__init__.py index c5d3fb225..0a618d53c 100644 --- a/graph_net/__init__.py +++ b/graph_net/__init__.py @@ -1 +1 @@ -import graph_net.torch as torch \ No newline at end of file +import graph_net.torch as torch diff --git a/graph_net/config.py b/graph_net/config.py index c69014157..b4b72e2a2 100644 --- a/graph_net/config.py +++ b/graph_net/config.py @@ -7,53 +7,51 @@ def load_env_workspace(): - ws = os.environ.get('GRAPH_NET_EXTRACT_WORKSPACE') + ws = os.environ.get("GRAPH_NET_EXTRACT_WORKSPACE") if not ws: - print('Error: GRAPH_NET_EXTRACT_WORKSPACE is not set', file=sys.stderr) + print("Error: GRAPH_NET_EXTRACT_WORKSPACE is not set", file=sys.stderr) sys.exit(1) return ws def write_config(path: str, data: dict): # Ensure parent dir exists - + os.makedirs(os.path.dirname(path), exist_ok=True) - with open(path, 'w', encoding='utf-8') as f: + with open(path, "w", encoding="utf-8") as f: json.dump(data, f, indent=2) - print(f'Config written to {path}') + print(f"Config written to {path}") def main(): parser = argparse.ArgumentParser( - prog='python -m graph_net.config', - description='Set user config for graph_net' + prog="python -m graph_net.config", description="Set user config for graph_net" + ) + parser.add_argument( + "--global", + dest="global_", + action="store_true", + help="Write config globally to ~/.graph_net/config.json", ) - parser.add_argument('--global', dest='global_', action='store_true', - help='Write config globally to ~/.graph_net/config.json') - parser.add_argument('--username', required=True, - help='Username to set in config') - parser.add_argument('--email', required=True, - help='Email to set in config') + parser.add_argument("--username", required=True, help="Username to set in config") + parser.add_argument("--email", required=True, help="Email to set in config") args = parser.parse_args() # Prepare config data - config_data = { - 'username': args.username, - 'email': args.email - } + config_data = {"username": args.username, "email": args.email} if args.global_: # global config - home = os.path.expanduser('~') - config_path = os.path.join(home, '.graph_net', 'config.json') + home = os.path.expanduser("~") + config_path = os.path.join(home, ".graph_net", "config.json") else: # workspace config ws = load_env_workspace() - config_path = os.path.join(ws, 'config.json') + config_path = os.path.join(ws, "config.json") write_config(config_path, config_data) -if __name__ == '__main__': +if __name__ == "__main__": main() diff --git a/graph_net/pack.py b/graph_net/pack.py index a24b5b454..44e6aaa91 100644 --- a/graph_net/pack.py +++ b/graph_net/pack.py @@ -10,7 +10,9 @@ def pack_directory(src_dir: str, output_path: str): Pack all files and subdirectories under src_dir into a ZIP file at output_path. """ src_dir = os.path.normpath(src_dir) - with zipfile.ZipFile(output_path, 'w', compression=zipfile.ZIP_DEFLATED, allowZip64=True) as zf: + with zipfile.ZipFile( + output_path, "w", compression=zipfile.ZIP_DEFLATED, allowZip64=True + ) as zf: for root, _, files in os.walk(src_dir): for fname in files: full_path = os.path.join(root, fname) @@ -31,7 +33,7 @@ def clear_directory(src_dir: str): elif os.path.isdir(path): shutil.rmtree(path) except Exception as e: - print(f'Failed to remove {path}: {e}', file=sys.stderr) + print(f"Failed to remove {path}: {e}", file=sys.stderr) print(f'Cleared contents of "{src_dir}"') @@ -40,44 +42,48 @@ def parse_boolean_flag(value: str) -> bool: Parse a string to boolean, accepting 'True' or 'False' (case-insensitive). """ lower = value.lower() - if lower == 'true': + if lower == "true": return True - if lower == 'false': + if lower == "false": return False - raise argparse.ArgumentTypeError(f"clear_after_pack must be 'True' or 'False', got '{value}'") + raise argparse.ArgumentTypeError( + f"clear_after_pack must be 'True' or 'False', got '{value}'" + ) def main(): parser = argparse.ArgumentParser( - prog='python -m graph_net.pack', - description='Pack the $GRAPH_NET_EXTRACT_WORKSPACE directory into ZIP (clear_after_pack is required)' + prog="python -m graph_net.pack", + description="Pack the $GRAPH_NET_EXTRACT_WORKSPACE directory into ZIP (clear_after_pack is required)", ) parser.add_argument( - '--output', - metavar='OUTPUT_PATH', - help='Specify the output ZIP file path (default is .zip)', + "--output", + metavar="OUTPUT_PATH", + help="Specify the output ZIP file path (default is .zip)", ) parser.add_argument( - '--clear-after-pack', - dest='clear_after_pack', + "--clear-after-pack", + dest="clear_after_pack", required=True, type=parse_boolean_flag, - help="Specify whether to clear workspace after packing: 'True' or 'False'" + help="Specify whether to clear workspace after packing: 'True' or 'False'", ) args = parser.parse_args() - ws = os.environ.get('GRAPH_NET_EXTRACT_WORKSPACE') + ws = os.environ.get("GRAPH_NET_EXTRACT_WORKSPACE") if not ws: - parser.error('Environment variable GRAPH_NET_EXTRACT_WORKSPACE is not set') + parser.error("Environment variable GRAPH_NET_EXTRACT_WORKSPACE is not set") if not os.path.isdir(ws): - parser.error(f'The path specified by GRAPH_NET_EXTRACT_WORKSPACE ("{ws}") is not a valid directory') + parser.error( + f'The path specified by GRAPH_NET_EXTRACT_WORKSPACE ("{ws}") is not a valid directory' + ) # Determine output path if args.output: output_path = args.output else: - base = os.path.basename(ws.rstrip(os.sep)) or 'workspace' + base = os.path.basename(ws.rstrip(os.sep)) or "workspace" output_path = f"{base}.zip" # Perform pack @@ -88,5 +94,5 @@ def main(): clear_directory(ws) -if __name__ == '__main__': - main() \ No newline at end of file +if __name__ == "__main__": + main() diff --git a/graph_net/status.py b/graph_net/status.py index 95953b245..ed8cce15d 100644 --- a/graph_net/status.py +++ b/graph_net/status.py @@ -4,6 +4,7 @@ import sys import argparse + def list_directory(src_dir: str): """ List all files and subdirectories directly under src_dir. @@ -21,20 +22,24 @@ def list_directory(src_dir: str): for name in sorted(entries): print(name) + def main(): parser = argparse.ArgumentParser( - prog='python -m graph_net.status', - description='List contents of the $GRAPH_NET_EXTRACT_WORKSPACE directory (like ls)' + prog="python -m graph_net.status", + description="List contents of the $GRAPH_NET_EXTRACT_WORKSPACE directory (like ls)", ) args = parser.parse_args() - ws = os.environ.get('GRAPH_NET_EXTRACT_WORKSPACE') + ws = os.environ.get("GRAPH_NET_EXTRACT_WORKSPACE") if not ws: - parser.error('Environment variable GRAPH_NET_EXTRACT_WORKSPACE is not set') + parser.error("Environment variable GRAPH_NET_EXTRACT_WORKSPACE is not set") if not os.path.isdir(ws): - parser.error(f'The path specified by GRAPH_NET_EXTRACT_WORKSPACE ("{ws}") is not a valid directory') + parser.error( + f'The path specified by GRAPH_NET_EXTRACT_WORKSPACE ("{ws}") is not a valid directory' + ) list_directory(ws) -if __name__ == '__main__': + +if __name__ == "__main__": main() diff --git a/graph_net/test/bert_model_test.py b/graph_net/test/bert_model_test.py index 71eb5a25f..ab818c647 100644 --- a/graph_net/test/bert_model_test.py +++ b/graph_net/test/bert_model_test.py @@ -1,18 +1,21 @@ import torch from transformers import AutoModel, AutoTokenizer -import graph_net.torch +import graph_net.torch import os + def get_model_name(): return "distilbert-base-uncased" + def create_model(): model = AutoModel.from_pretrained(get_model_name()) model.eval() return model.to(device) -if __name__ == '__main__': - + +if __name__ == "__main__": + tokenizer = AutoTokenizer.from_pretrained(get_model_name()) text = "Hello world" @@ -25,5 +28,5 @@ def create_model(): model = graph_net.torch.extract(name=get_model_name())(model) print("Running inference...") - output = model(**inputs) + output = model(**inputs) print("Inference finished. Output shape:", output.last_hidden_state.shape) diff --git a/graph_net/test/vision_model_test.py b/graph_net/test/vision_model_test.py index c2c41c7de..ea51bc533 100644 --- a/graph_net/test/vision_model_test.py +++ b/graph_net/test/vision_model_test.py @@ -7,11 +7,10 @@ import os import graph_net -if __name__ == '__main__': +if __name__ == "__main__": # Normalization parameters for ImageNet normalize = transforms.Normalize( - mean=[0.485, 0.456, 0.406], - std=[0.229, 0.224, 0.225] + mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225] ) # Create dummy input @@ -28,7 +27,7 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu") model.to(device) normalized_input = normalized_input.to(device) - + model = graph_net.torch.extract(name="resnet18")(model) print("Running inference...") diff --git a/graph_net/torch/__init__.py b/graph_net/torch/__init__.py index eaafa4497..67f7a7120 100644 --- a/graph_net/torch/__init__.py +++ b/graph_net/torch/__init__.py @@ -5,4 +5,4 @@ from .extractor import extract from .samples_util import get_default_samples_directory -__all__ = ['extract', 'get_default_samples_directory'] +__all__ = ["extract", "get_default_samples_directory"] diff --git a/graph_net/torch/check_redundant_incrementally.py b/graph_net/torch/check_redundant_incrementally.py index d07686f03..747a710d4 100644 --- a/graph_net/torch/check_redundant_incrementally.py +++ b/graph_net/torch/check_redundant_incrementally.py @@ -13,6 +13,7 @@ import time import glob + def get_recursively_model_pathes(root_dir): if is_single_model_dir(root_dir): yield root_dir @@ -23,6 +24,7 @@ def get_recursively_model_pathes(root_dir): else: yield from get_recursively_model_pathes(sub_dir) + def get_immediate_subdirectory_paths(parent_dir): return [ sub_dir @@ -31,9 +33,11 @@ def get_immediate_subdirectory_paths(parent_dir): if os.path.isdir(sub_dir) ] + def is_single_model_dir(model_dir): return os.path.isfile(f"{model_dir}/graph_net.json") + def main(args): assert os.path.isdir(args.model_path) assert os.path.isdir(args.graph_net_samples_path) @@ -43,7 +47,7 @@ def main(args): for graph_hash_path in [f"{model_path}/graph_hash.txt"] ) graph_hash2graph_net_model_path = { - graph_hash:graph_hash_path + graph_hash: graph_hash_path for model_path in get_recursively_model_pathes(args.graph_net_samples_path) for graph_hash_path in [f"{model_path}/graph_hash.txt"] if os.path.isfile(graph_hash_path) @@ -52,13 +56,25 @@ def main(args): } for current_model_graph_hash_path in current_model_graph_hash_pathes: graph_hash = open(current_model_graph_hash_path).read() - assert graph_hash not in graph_hash2graph_net_model_path, f"Redundant models detected. old-model-path:{current_model_graph_hash_path}, new-model-path:{graph_hash2graph_net_model_path[graph_hash]}." + assert ( + graph_hash not in graph_hash2graph_net_model_path + ), f"Redundant models detected. old-model-path:{current_model_graph_hash_path}, new-model-path:{graph_hash2graph_net_model_path[graph_hash]}." -if __name__ == '__main__': + +if __name__ == "__main__": parser = argparse.ArgumentParser(description="Test compiler performance.") - parser.add_argument("--model-path", type=str, required=True, - help="Path to model file(s), each subdirectory containing graph_net.json will be regarded as a model") - parser.add_argument("--graph-net-samples-path", type=str, required=False, default='default', - help="Path to GraphNet samples") + parser.add_argument( + "--model-path", + type=str, + required=True, + help="Path to model file(s), each subdirectory containing graph_net.json will be regarded as a model", + ) + parser.add_argument( + "--graph-net-samples-path", + type=str, + required=False, + default="default", + help="Path to GraphNet samples", + ) args = parser.parse_args() main(args=args) diff --git a/graph_net/torch/extractor.py b/graph_net/torch/extractor.py index 535f99fde..9ed82d381 100644 --- a/graph_net/torch/extractor.py +++ b/graph_net/torch/extractor.py @@ -31,6 +31,7 @@ def extractor(gm: torch.fx.GraphModule, sample_inputs): params = {} input_idx = 0 unique_id = 0 + def try_rename_placeholder(node): assert node.op == "placeholder" if not placeholder_auto_rename: @@ -40,6 +41,7 @@ def try_rename_placeholder(node): unique_id += 1 node.name = f"v{unique_id}" unique_id += 1 + for node in gm.graph.nodes: if node.op == "placeholder": try_rename_placeholder(node) diff --git a/graph_net/torch/remove_redundant_incrementally.py b/graph_net/torch/remove_redundant_incrementally.py index 2cf8e137f..81a6b3d90 100644 --- a/graph_net/torch/remove_redundant_incrementally.py +++ b/graph_net/torch/remove_redundant_incrementally.py @@ -14,6 +14,7 @@ import glob import shutil + def get_recursively_model_pathes(root_dir): if is_single_model_dir(root_dir): yield root_dir @@ -24,6 +25,7 @@ def get_recursively_model_pathes(root_dir): else: yield from get_recursively_model_pathes(sub_dir) + def get_immediate_subdirectory_paths(parent_dir): return [ sub_dir @@ -32,9 +34,11 @@ def get_immediate_subdirectory_paths(parent_dir): if os.path.isdir(sub_dir) ] + def is_single_model_dir(model_dir): return os.path.isfile(f"{model_dir}/graph_net.json") + def main(args): assert os.path.isdir(args.model_path) assert os.path.isdir(args.graph_net_samples_path) @@ -44,7 +48,7 @@ def main(args): for graph_hash_path in [f"{model_path}/graph_hash.txt"] ) graph_hash2graph_net_model_path = { - graph_hash:graph_hash_path + graph_hash: graph_hash_path for model_path in get_recursively_model_pathes(args.graph_net_samples_path) for graph_hash_path in [f"{model_path}/graph_hash.txt"] if os.path.isfile(graph_hash_path) @@ -59,11 +63,21 @@ def main(args): shutil.rmtree(directory) os.makedirs(directory, exist_ok=True) -if __name__ == '__main__': + +if __name__ == "__main__": parser = argparse.ArgumentParser(description="Test compiler performance.") - parser.add_argument("--model-path", type=str, required=True, - help="Path to model file(s), each subdirectory containing graph_net.json will be regarded as a model") - parser.add_argument("--graph-net-samples-path", type=str, required=False, default='default', - help="Path to GraphNet samples") + parser.add_argument( + "--model-path", + type=str, + required=True, + help="Path to model file(s), each subdirectory containing graph_net.json will be regarded as a model", + ) + parser.add_argument( + "--graph-net-samples-path", + type=str, + required=False, + default="default", + help="Path to GraphNet samples", + ) args = parser.parse_args() main(args=args) diff --git a/graph_net/torch/samples_util.py b/graph_net/torch/samples_util.py index 3fa7ea910..a6b7870e0 100644 --- a/graph_net/torch/samples_util.py +++ b/graph_net/torch/samples_util.py @@ -1,5 +1,6 @@ import graph_net import os + def get_default_samples_directory(): - return f"{os.path.dirname(graph_net.__file__)}/../samples" + return f"{os.path.dirname(graph_net.__file__)}/../samples" diff --git a/graph_net/torch/single_device_runner.py b/graph_net/torch/single_device_runner.py index 732d9a881..72d89c1f5 100644 --- a/graph_net/torch/single_device_runner.py +++ b/graph_net/torch/single_device_runner.py @@ -17,17 +17,20 @@ def load_class_from_file(file_path: str, class_name: str) -> Type[torch.nn.Modul spec.loader.exec_module(unnamed) model_class = getattr(unnamed, class_name, None) return model_class - + + def _get_sha_hash(content): m = hashlib.sha256() m.update(content.encode()) return m.hexdigest() + def _save_to_model_path(dump_dir, hash_text): file_path = f"{dump_dir}/graph_hash.txt" - with open(file_path, 'w') as f: + with open(file_path, "w") as f: f.write(hash_text) + @contextmanager def _dump_graph_hash_key_ctx(cmd_args): if not cmd_args.dump_graph_hash_key: @@ -35,8 +38,8 @@ def _dump_graph_hash_key_ctx(cmd_args): return mut_graph_codes = [] extractor_kwarg = { - 'placeholder_auto_rename': True, - 'mut_graph_codes': mut_graph_codes + "placeholder_auto_rename": True, + "mut_graph_codes": mut_graph_codes, } yield extractor_kwarg if len(mut_graph_codes) > 0: @@ -47,32 +50,54 @@ def _dump_graph_hash_key_ctx(cmd_args): def main(args): with _dump_graph_hash_key_ctx(args) as dump_graph_options: model_path = args.model_path - model_class = load_class_from_file(f"{model_path}/model.py", class_name="GraphModule") + model_class = load_class_from_file( + f"{model_path}/model.py", class_name="GraphModule" + ) assert model_class is not None model = model_class() - print(f'{model_path=}') + print(f"{model_path=}") if args.enable_extract: assert args.extract_name is not None kwargs = dict(name=args.extract_name, **dump_graph_options) model = extract(**kwargs)(model) - inputs_params = utils.load_converted_from_text(f'{model_path}') + inputs_params = utils.load_converted_from_text(f"{model_path}") params = inputs_params["weight_info"] - state_dict = { - k: utils.replay_tensor(v) for k, v in params.items() - } - + state_dict = {k: utils.replay_tensor(v) for k, v in params.items()} + y = model(**state_dict)[0] print(torch.argmin(y), torch.argmax(y)) print(y.shape) -if __name__ == '__main__': + +if __name__ == "__main__": parser = argparse.ArgumentParser(description="load and run model") - parser.add_argument("--model-path", type=str, required=True, - help="Path to folder e.g '../../samples/torch/resnet18'") - parser.add_argument("--dump-graph-hash-key", action='store_true', default=False, help="Dump graph hash key") - parser.add_argument("--enable-extract", type=bool, required=False, default=False, help="Enable extract") - parser.add_argument("--extract-name", type=str, required=False, default=None, help="Extracted graph's name") + parser.add_argument( + "--model-path", + type=str, + required=True, + help="Path to folder e.g '../../samples/torch/resnet18'", + ) + parser.add_argument( + "--dump-graph-hash-key", + action="store_true", + default=False, + help="Dump graph hash key", + ) + parser.add_argument( + "--enable-extract", + type=bool, + required=False, + default=False, + help="Enable extract", + ) + parser.add_argument( + "--extract-name", + type=str, + required=False, + default=None, + help="Extracted graph's name", + ) args = parser.parse_args() main(args=args) diff --git a/graph_net/torch/test_compiler.py b/graph_net/torch/test_compiler.py index 31e44eaef..15534685e 100644 --- a/graph_net/torch/test_compiler.py +++ b/graph_net/torch/test_compiler.py @@ -18,168 +18,209 @@ def load_class_from_file(file_path: str, class_name: str) -> Type[torch.nn.Modul file = Path(file_path).resolve() module_name = file.stem - with open(file_path, 'r', encoding='utf-8') as f: + with open(file_path, "r", encoding="utf-8") as f: original_code = f.read() - import_stmt= "import torch" + import_stmt = "import torch" modified_code = f"{import_stmt}\n{original_code}" spec = importlib.util.spec_from_loader(module_name, loader=None) module = importlib.util.module_from_spec(spec) sys.modules[module_name] = module - compiled_code = compile(modified_code, filename=file, mode='exec') + compiled_code = compile(modified_code, filename=file, mode="exec") exec(compiled_code, module.__dict__) model_class = getattr(module, class_name, None) return model_class + def get_compiler(args): - assert args.compiler == 'default' - return torch.compile + assert args.compiler == "default" + return torch.compile + def get_synchronizer_func(args): - assert args.compiler == 'default' - return torch.cuda.synchronize + assert args.compiler == "default" + return torch.cuda.synchronize + def get_model(args): - model_class = load_class_from_file(f"{args.model_path}/model.py", class_name="GraphModule") + model_class = load_class_from_file( + f"{args.model_path}/model.py", class_name="GraphModule" + ) return model_class() + def get_input_dict(args): - inputs_params = utils.load_converted_from_text(f'{args.model_path}') + inputs_params = utils.load_converted_from_text(f"{args.model_path}") params = inputs_params["weight_info"] - return { - k: utils.replay_tensor(v) for k, v in params.items() - } + return {k: utils.replay_tensor(v) for k, v in params.items()} + @dataclass class DurationBox: - value: int - + value: int + + @contextmanager def naive_timer(duration_box, get_synchronizer_func): - get_synchronizer_func() - start = time.time() - yield - get_synchronizer_func() - end = time.time() - duration_box.value = end - start + get_synchronizer_func() + start = time.time() + yield + get_synchronizer_func() + end = time.time() + duration_box.value = end - start + def test_single_model(args): - compiler = get_compiler(args) - synchronizer_func = get_synchronizer_func(args) - input_dict = get_input_dict(args) - model = get_model(args) - compiled_model = compiler(model) - - # eager - eager_duration_box = DurationBox(-1) - with naive_timer(eager_duration_box, synchronizer_func): - expected_out = model(**input_dict) - - # warmup - for _ in range(args.warmup if args.warmup > 0 else 0): - compiled_model(**input_dict) - - # compiled - compiled_duration_box = DurationBox(-1) - with naive_timer(compiled_duration_box, synchronizer_func): - compiled_out = compiled_model(**input_dict) - - def print_cmp(key, func, **kwargs): - cmp_ret = func(expected_out, compiled_out, **kwargs) - print(f"{args.log_prompt} {key} model_path:{args.model_path} {cmp_ret}", file=sys.stderr) - - print_cmp("cmp.equal", get_cmp_equal) - print_cmp("cmp.all_close_atol8_rtol8", get_cmp_all_close, atol=1e-8, rtol=1e-8) - print_cmp("cmp.all_close_atol8_rtol5", get_cmp_all_close, atol=1e-8, rtol=1e-5) - print_cmp("cmp.all_close_atol5_rtol5", get_cmp_all_close, atol=1e-5, rtol=1e-5) - print_cmp("cmp.all_close_atol3_rtol2", get_cmp_all_close, atol=1e-3, rtol=1e-2) - print_cmp("cmp.all_close_atol2_rtol1", get_cmp_all_close, atol=1e-2, rtol=1e-1) - print_cmp("cmp.max_diff", get_cmp_max_diff) - print_cmp("cmp.mean_diff", get_cmp_mean_diff) - print_cmp("cmp.diff_count_atol8_rtol8", get_cmp_diff_count, atol=1e-8, rtol=1e-8) - print_cmp("cmp.diff_count_atol8_rtol5", get_cmp_diff_count, atol=1e-8, rtol=1e-5) - print_cmp("cmp.diff_count_atol5_rtol5", get_cmp_diff_count, atol=1e-5, rtol=1e-5) - print_cmp("cmp.diff_count_atol3_rtol2", get_cmp_diff_count, atol=1e-3, rtol=1e-2) - print_cmp("cmp.diff_count_atol2_rtol1", get_cmp_diff_count, atol=1e-2, rtol=1e-1) - - print(f"{args.log_prompt} duration model_path:{args.model_path} eager:{eager_duration_box.value} compiled:{compiled_duration_box.value}", file=sys.stderr) + compiler = get_compiler(args) + synchronizer_func = get_synchronizer_func(args) + input_dict = get_input_dict(args) + model = get_model(args) + compiled_model = compiler(model) + + # eager + eager_duration_box = DurationBox(-1) + with naive_timer(eager_duration_box, synchronizer_func): + expected_out = model(**input_dict) + + # warmup + for _ in range(args.warmup if args.warmup > 0 else 0): + compiled_model(**input_dict) + + # compiled + compiled_duration_box = DurationBox(-1) + with naive_timer(compiled_duration_box, synchronizer_func): + compiled_out = compiled_model(**input_dict) + + def print_cmp(key, func, **kwargs): + cmp_ret = func(expected_out, compiled_out, **kwargs) + print( + f"{args.log_prompt} {key} model_path:{args.model_path} {cmp_ret}", + file=sys.stderr, + ) + + print_cmp("cmp.equal", get_cmp_equal) + print_cmp("cmp.all_close_atol8_rtol8", get_cmp_all_close, atol=1e-8, rtol=1e-8) + print_cmp("cmp.all_close_atol8_rtol5", get_cmp_all_close, atol=1e-8, rtol=1e-5) + print_cmp("cmp.all_close_atol5_rtol5", get_cmp_all_close, atol=1e-5, rtol=1e-5) + print_cmp("cmp.all_close_atol3_rtol2", get_cmp_all_close, atol=1e-3, rtol=1e-2) + print_cmp("cmp.all_close_atol2_rtol1", get_cmp_all_close, atol=1e-2, rtol=1e-1) + print_cmp("cmp.max_diff", get_cmp_max_diff) + print_cmp("cmp.mean_diff", get_cmp_mean_diff) + print_cmp("cmp.diff_count_atol8_rtol8", get_cmp_diff_count, atol=1e-8, rtol=1e-8) + print_cmp("cmp.diff_count_atol8_rtol5", get_cmp_diff_count, atol=1e-8, rtol=1e-5) + print_cmp("cmp.diff_count_atol5_rtol5", get_cmp_diff_count, atol=1e-5, rtol=1e-5) + print_cmp("cmp.diff_count_atol3_rtol2", get_cmp_diff_count, atol=1e-3, rtol=1e-2) + print_cmp("cmp.diff_count_atol2_rtol1", get_cmp_diff_count, atol=1e-2, rtol=1e-1) + + print( + f"{args.log_prompt} duration model_path:{args.model_path} eager:{eager_duration_box.value} compiled:{compiled_duration_box.value}", + file=sys.stderr, + ) + def get_cmp_equal(expected_out, compiled_out): - return " ".join( - str(int(torch.equal(a, b))) - for a, b in zip(expected_out, compiled_out) - ) + return " ".join( + str(int(torch.equal(a, b))) for a, b in zip(expected_out, compiled_out) + ) + def get_cmp_all_close(expected_out, compiled_out, atol, rtol): - return " ".join( - str(int(torch.allclose(a, b, atol=atol, rtol=rtol))) - for a, b in zip(expected_out, compiled_out) - ) + return " ".join( + str(int(torch.allclose(a, b, atol=atol, rtol=rtol))) + for a, b in zip(expected_out, compiled_out) + ) + def get_cmp_max_diff(expected_out, compiled_out): - return " ".join( - str(torch.max(torch.abs(a - b)).item()) - for a, b in zip(expected_out, compiled_out) - ) + return " ".join( + str(torch.max(torch.abs(a - b)).item()) + for a, b in zip(expected_out, compiled_out) + ) + def get_cmp_mean_diff(expected_out, compiled_out): - return " ".join( - str(torch.mean(torch.abs(a - b)).item()) - for a, b in zip(expected_out, compiled_out) - ) + return " ".join( + str(torch.mean(torch.abs(a - b)).item()) + for a, b in zip(expected_out, compiled_out) + ) + def get_cmp_diff_count(expected_out, compiled_out, atol, rtol): - return " ".join( - str(torch.sum(~torch.isclose(a, b, atol=atol, rtol=rtol)).item()) - for a, b in zip(expected_out, compiled_out) - ) + return " ".join( + str(torch.sum(~torch.isclose(a, b, atol=atol, rtol=rtol)).item()) + for a, b in zip(expected_out, compiled_out) + ) + def test_multi_models(args): - for model_path in get_recursively_model_path(args.model_path): - cmd = "".join([ - sys.executable, - "-m graph_net.torch.test_compiler", - f"--model-path {model_path}", - f"--compiler {args.compiler}", - f"--warmup {args.warmup}", - f"--log-prompt {args.log_prompt}", - ]) - cmd_ret = os.system(cmd) - assert cmd_ret == 0, f"{cmd_ret=}, {cmd=}" + for model_path in get_recursively_model_path(args.model_path): + cmd = "".join( + [ + sys.executable, + "-m graph_net.torch.test_compiler", + f"--model-path {model_path}", + f"--compiler {args.compiler}", + f"--warmup {args.warmup}", + f"--log-prompt {args.log_prompt}", + ] + ) + cmd_ret = os.system(cmd) + assert cmd_ret == 0, f"{cmd_ret=}, {cmd=}" + def get_recursively_model_path(root_dir): - for sub_dir in get_immediate_subdirectory_paths(root_dir): - if is_single_model_dir(sub_dir): - yield sub_dir - else: - yield from get_recursively_model_path(sub_dir) + for sub_dir in get_immediate_subdirectory_paths(root_dir): + if is_single_model_dir(sub_dir): + yield sub_dir + else: + yield from get_recursively_model_path(sub_dir) + def get_immediate_subdirectory_paths(parent_dir): return [ - sub_dir - for name in os.listdir(parent_dir) - for sub_dir in [os.path.join(parent_dir, name)] - if os.path.isdir(sub_dir) - ] + sub_dir + for name in os.listdir(parent_dir) + for sub_dir in [os.path.join(parent_dir, name)] + if os.path.isdir(sub_dir) + ] + def is_single_model_dir(model_dir): - return os.path.isfile(f"{model_dir}/graph_net.json") + return os.path.isfile(f"{model_dir}/graph_net.json") + def main(args): - assert os.path.isdir(args.model_path) - if is_single_model_dir(args.model_path): - test_single_model(args) - else: - test_multi_models(args) - - -if __name__ == '__main__': + assert os.path.isdir(args.model_path) + if is_single_model_dir(args.model_path): + test_single_model(args) + else: + test_multi_models(args) + + +if __name__ == "__main__": parser = argparse.ArgumentParser(description="Test compiler performance.") - parser.add_argument("--model-path", type=str, required=True, - help="Path to model file(s), each subdirectory containing graph_net.json will be regarded as a model") - parser.add_argument("--compiler", type=str, required=False, default='default', - help="Path to customized compiler python file") - parser.add_argument("--warmup", type=int, required=False, default=5, help="Number of warmup steps") - parser.add_argument("--log-prompt", type=str, required=False, default="graph-net-test-compiler-log", help="Log prompt for performance log filtering.") + parser.add_argument( + "--model-path", + type=str, + required=True, + help="Path to model file(s), each subdirectory containing graph_net.json will be regarded as a model", + ) + parser.add_argument( + "--compiler", + type=str, + required=False, + default="default", + help="Path to customized compiler python file", + ) + parser.add_argument( + "--warmup", type=int, required=False, default=5, help="Number of warmup steps" + ) + parser.add_argument( + "--log-prompt", + type=str, + required=False, + default="graph-net-test-compiler-log", + help="Log prompt for performance log filtering.", + ) args = parser.parse_args() main(args=args) diff --git a/graph_net/torch/utils.py b/graph_net/torch/utils.py index 7d951dffc..370ab8f1f 100644 --- a/graph_net/torch/utils.py +++ b/graph_net/torch/utils.py @@ -9,16 +9,19 @@ import importlib import inspect + def apply_templates(forward_code: str) -> str: tab = " " forward_code = f"\n{tab}".join(forward_code.split("\n")) return f"import torch\n\nclass GraphModule(torch.nn.Module):\n{tab}{forward_code}" + def get_limited_precision_float_str(value): if not isinstance(value, float): return value return f"{value:.3f}" + def convert_state_and_inputs_impl(state_dict, example_inputs): def tensor_info(tensor): is_float = tensor.dtype.is_floating_point @@ -39,7 +42,11 @@ def process_tensor(tensor): info = tensor_info(tensor) if tensor.dtype in [torch.int8, torch.int16, torch.int32, torch.int64]: if tensor.numel() < 1024: - return {"type": "small_int_tensor", "data": tensor.clone(), "info": info} + return { + "type": "small_int_tensor", + "data": tensor.clone(), + "info": info, + } else: return {"type": "big_int_tensor", "data": tensor.clone(), "info": info} elif tensor.numel() < 1024: @@ -64,12 +71,8 @@ def handle_named_tensors(tensor): else: data_type = "big_int_tensor" info = tensor_info(tensor) - return { - "info": info, - "data": data_value, - "type": data_type - } - + return {"info": info, "data": data_value, "type": data_type} + processed_weights = { key: handle_named_tensors(tensor) for key, tensor in state_dict.items() } @@ -78,28 +81,31 @@ def handle_named_tensors(tensor): return { "input_info": processed_inputs, "weight_info": processed_weights, - "dynamic_shapes": None + "dynamic_shapes": None, } + def convert_state_and_inputs(state_dict, example_inputs): return convert_state_and_inputs_impl(state_dict, example_inputs) + def save_constraints_text(converted, file_path): lines = [] if converted["dynamic_shapes"] is not None: raise NotImplementedError("Handling constraints is not implemented yet.") - with open(file_path, 'w') as f: + with open(file_path, "w") as f: f.write("\n".join(lines)) + def save_converted_to_text(converted, file_path): def format_data(data): if data is None: return "None" elif isinstance(data, torch.Tensor): if data.dtype.is_floating_point: - return "[{}]".format(", ".join(f'{x:.6f}' for x in data.tolist())) + return "[{}]".format(", ".join(f"{x:.6f}" for x in data.tolist())) else: - return "[{}]".format(", ".join(f'{x}' for x in data.tolist())) + return "[{}]".format(", ".join(f"{x}" for x in data.tolist())) else: return repr(data) @@ -109,14 +115,16 @@ def process_tensor_info(tensor_info, name_prefix="example_input"): if tensor_info["type"] in ["small_tensor", "small_int_tensor"]: data_list = tensor_info["data"].flatten() elif tensor_info["type"] == "big_int_tensor": - data_list = f'pt-filename:xxx-key' + data_list = f"pt-filename:xxx-key" else: pass else: - if tensor_info["type"] == "small_int_tensor": + if tensor_info["type"] == "small_int_tensor": data_list = tensor_info["data"].flatten() - if tensor_info["type"] == "big_int_tensor": - raise ValueError("Unexpected cases: there are weights in big tensor of int type ") + if tensor_info["type"] == "big_int_tensor": + raise ValueError( + "Unexpected cases: there are weights in big tensor of int type " + ) info = tensor_info.get("info", {}) dtype = info.get("dtype", "torch.float") shape = info.get("shape", []) @@ -128,12 +136,12 @@ def process_tensor_info(tensor_info, name_prefix="example_input"): (f"class {uid}:"), (f"\tname = \"{tensor_info.get('name', '')}\""), (f"\tshape = {shape}"), - (f"\tdtype = \"{dtype}\""), - (f"\tdevice = \"{device}\""), + (f'\tdtype = "{dtype}"'), + (f'\tdevice = "{device}"'), (f"\tmean = {get_limited_precision_float_str(mean)}"), (f"\tstd = {get_limited_precision_float_str(std)}"), (f"\tdata = {format_data(data_list)}"), - ("") + (""), ] input_infos = converted["input_info"] @@ -145,44 +153,52 @@ def process_tensor_info(tensor_info, name_prefix="example_input"): input_info["name"] = f"input_{idx}" input_lines.extend(process_tensor_info(input_info, name_prefix="Program_input")) - with open(f"{file_path}/input_meta.py", 'w') as f: + with open(f"{file_path}/input_meta.py", "w") as f: f.write("\n".join(input_lines)) weight_lines = [] for name, weight_info in converted["weight_info"].items(): weight_info["name"] = name - weight_lines.extend(process_tensor_info(weight_info, name_prefix="Program_weight")) + weight_lines.extend( + process_tensor_info(weight_info, name_prefix="Program_weight") + ) - with open(f"{file_path}/weight_meta.py", 'w') as f: + with open(f"{file_path}/weight_meta.py", "w") as f: f.write("\n".join(weight_lines)) + def load_converted_from_text(file_path): input_info = list(convert_meta_classes_to_tensors(f"{file_path}/input_meta.py")) weight_info = { - data['name']: data + data["name"]: data for data in convert_meta_classes_to_tensors(f"{file_path}/weight_meta.py") } return { "input_info": input_info, "weight_info": weight_info, - "dynamic_shapes": None + "dynamic_shapes": None, } + def convert_meta_classes_to_tensors(file_path): for name, cls in _get_classes(file_path): attrs = { - k: v for k, v in cls.__dict__.items() if not k.startswith('__') and not callable(v) + k: v + for k, v in cls.__dict__.items() + if not k.startswith("__") and not callable(v) } data_value = None - data_type = getattr(torch, attrs.get("dtype", "torch.float").split('.')[-1]) + data_type = getattr(torch, attrs.get("dtype", "torch.float").split(".")[-1]) if attrs.get("data") is not None: if isinstance(attrs.get("data"), str): raise ValueError("Unimplemented") else: - data_value = torch.tensor(attrs["data"], dtype=data_type).reshape(attrs.get("shape"), []) + data_value = torch.tensor(attrs["data"], dtype=data_type).reshape( + attrs.get("shape"), [] + ) yield { "info": { "shape": attrs.get("shape", []), @@ -192,18 +208,21 @@ def convert_meta_classes_to_tensors(file_path): "std": attrs.get("std", 1.0), }, "data": data_value, - "name": attrs.get("name") + "name": attrs.get("name"), } + def _get_classes(file_path): spec = importlib.util.spec_from_file_location("unnamed", file_path) unnamed = importlib.util.module_from_spec(spec) spec.loader.exec_module(unnamed) yield from inspect.getmembers(unnamed, inspect.isclass) + def extract_dynamic_shapes(example_inputs): pass + def replay_tensor(info): device = info["info"]["device"] diff --git a/graph_net/torch/validate.py b/graph_net/torch/validate.py index 7da67ccf0..ba99bd540 100644 --- a/graph_net/torch/validate.py +++ b/graph_net/torch/validate.py @@ -1,17 +1,18 @@ import argparse -import os +import os import tempfile import sys import contextlib import graph_net + @contextlib.contextmanager def temp_workspace(): with tempfile.TemporaryDirectory() as tmp_dir_name: - old = os.environ.get('GRAPH_NET_EXTRACT_WORKSPACE') - os.environ['GRAPH_NET_EXTRACT_WORKSPACE'] = tmp_dir_name + old = os.environ.get("GRAPH_NET_EXTRACT_WORKSPACE") + os.environ["GRAPH_NET_EXTRACT_WORKSPACE"] = tmp_dir_name yield tmp_dir_name - os.environ['GRAPH_NET_EXTRACT_WORKSPACE'] = old + os.environ["GRAPH_NET_EXTRACT_WORKSPACE"] = old def main(args): @@ -19,30 +20,39 @@ def main(args): with temp_workspace() as tmp_dir_name: extract_name = "temp" print("Check extractability ...") - cmd = f'{sys.executable} -m graph_net.torch.single_device_runner --model-path {model_path} --enable-extract True --extract-name {extract_name} --dump-graph-hash-key True' + cmd = f"{sys.executable} -m graph_net.torch.single_device_runner --model-path {model_path} --enable-extract True --extract-name {extract_name} --dump-graph-hash-key True" cmd_ret = os.system(cmd) - assert cmd_ret == 0, f'{cmd_ret=}, {cmd=}' - cmd = f'{sys.executable} -m graph_net.torch.single_device_runner --model-path {tmp_dir_name}/{extract_name}' + assert cmd_ret == 0, f"{cmd_ret=}, {cmd=}" + cmd = f"{sys.executable} -m graph_net.torch.single_device_runner --model-path {tmp_dir_name}/{extract_name}" cmd_ret = os.system(cmd) - assert cmd_ret == 0, f'{cmd_ret=}, {cmd=}' + assert cmd_ret == 0, f"{cmd_ret=}, {cmd=}" if not args.no_check_redundancy: print("Check redundancy ...") - graph_net_samples_path = graph_net.torch.samples_util.get_default_samples_directory() + graph_net_samples_path = ( + graph_net.torch.samples_util.get_default_samples_directory() + ) cmd = f"{sys.executable} -m graph_net.torch.check_redundant_incrementally --model-path {args.model_path} --graph-net-samples-path {graph_net_samples_path}" cmd_ret = os.system(cmd) rm_cmd = f"{sys.executable} -m graph_net.torch.remove_redundant_incrementally --model-path {args.model_path} --graph-net-samples-path {graph_net_samples_path}" - assert cmd_ret == 0, f"\nPlease use the following command to remove redundant model directories:\n\n{rm_cmd}\n" + assert ( + cmd_ret == 0 + ), f"\nPlease use the following command to remove redundant model directories:\n\n{rm_cmd}\n" - print(f'Validation success, {model_path=}') + print(f"Validation success, {model_path=}") -if __name__ == '__main__': +if __name__ == "__main__": parser = argparse.ArgumentParser(description="load and run model") - parser.add_argument("--model-path", type=str, required=True, - help="Path to folder e.g '../../samples/torch/resnet18'") - parser.add_argument("--no-check-redundancy", action='store_true', - help="whether check model graph redundancy") + parser.add_argument( + "--model-path", + type=str, + required=True, + help="Path to folder e.g '../../samples/torch/resnet18'", + ) + parser.add_argument( + "--no-check-redundancy", + action="store_true", + help="whether check model graph redundancy", + ) args = parser.parse_args() main(args=args) - - diff --git a/graph_net/unpack.py b/graph_net/unpack.py index 2faa6127d..12e8b0b2b 100644 --- a/graph_net/unpack.py +++ b/graph_net/unpack.py @@ -13,7 +13,10 @@ def unpack_archive(src_path: str, dest_dir: str): """ # Verify source ZIP exists if not os.path.isfile(src_path): - print(f"Error: archive '{src_path}' does not exist or is not a file", file=sys.stderr) + print( + f"Error: archive '{src_path}' does not exist or is not a file", + file=sys.stderr, + ) sys.exit(1) # Create destination directory if needed @@ -21,12 +24,14 @@ def unpack_archive(src_path: str, dest_dir: str): try: os.makedirs(dest_dir, exist_ok=True) except Exception as e: - print(f"Error: failed to create directory '{dest_dir}': {e}", file=sys.stderr) + print( + f"Error: failed to create directory '{dest_dir}': {e}", file=sys.stderr + ) sys.exit(1) # Extract all contents try: - with zipfile.ZipFile(src_path, 'r') as zf: + with zipfile.ZipFile(src_path, "r") as zf: zf.extractall(dest_dir) except zipfile.BadZipFile: print(f"Error: '{src_path}' is not a valid ZIP archive", file=sys.stderr) @@ -40,18 +45,16 @@ def unpack_archive(src_path: str, dest_dir: str): def main(): parser = argparse.ArgumentParser( - prog='python -m graph_net.unpack', - description='Unpack a ZIP archive into a specified directory' + prog="python -m graph_net.unpack", + description="Unpack a ZIP archive into a specified directory", ) parser.add_argument( - '--src', - required=True, - help='Path to the ZIP archive to unpack' + "--src", required=True, help="Path to the ZIP archive to unpack" ) parser.add_argument( - '--dst', + "--dst", required=True, - help='Destination directory where files will be unpacked' + help="Destination directory where files will be unpacked", ) args = parser.parse_args() @@ -59,5 +62,5 @@ def main(): unpack_archive(args.src, args.dst) -if __name__ == '__main__': +if __name__ == "__main__": main() From 52cc34dc36f224d316a8851f055c8238c8dbc3fc Mon Sep 17 00:00:00 2001 From: Xinqi Li Date: Thu, 31 Jul 2025 08:32:22 +0000 Subject: [PATCH 04/10] reformat bert_model_test.py and utils.py --- graph_net/test/bert_model_test.py | 1 - graph_net/torch/utils.py | 2 -- 2 files changed, 3 deletions(-) diff --git a/graph_net/test/bert_model_test.py b/graph_net/test/bert_model_test.py index ab818c647..7aab7115e 100644 --- a/graph_net/test/bert_model_test.py +++ b/graph_net/test/bert_model_test.py @@ -15,7 +15,6 @@ def create_model(): if __name__ == "__main__": - tokenizer = AutoTokenizer.from_pretrained(get_model_name()) text = "Hello world" diff --git a/graph_net/torch/utils.py b/graph_net/torch/utils.py index 370ab8f1f..8419e5d95 100644 --- a/graph_net/torch/utils.py +++ b/graph_net/torch/utils.py @@ -168,7 +168,6 @@ def process_tensor_info(tensor_info, name_prefix="example_input"): def load_converted_from_text(file_path): - input_info = list(convert_meta_classes_to_tensors(f"{file_path}/input_meta.py")) weight_info = { @@ -224,7 +223,6 @@ def extract_dynamic_shapes(example_inputs): def replay_tensor(info): - device = info["info"]["device"] dtype = info["info"]["dtype"] shape = info["info"]["shape"] From d8c6213b78240150cb93f581505030cc3f7a57c8 Mon Sep 17 00:00:00 2001 From: Xinqi Li Date: Thu, 31 Jul 2025 08:46:15 +0000 Subject: [PATCH 05/10] minor fix --- graph_net/torch/validate.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/graph_net/torch/validate.py b/graph_net/torch/validate.py index ba99bd540..61469845a 100644 --- a/graph_net/torch/validate.py +++ b/graph_net/torch/validate.py @@ -20,7 +20,7 @@ def main(args): with temp_workspace() as tmp_dir_name: extract_name = "temp" print("Check extractability ...") - cmd = f"{sys.executable} -m graph_net.torch.single_device_runner --model-path {model_path} --enable-extract True --extract-name {extract_name} --dump-graph-hash-key True" + cmd = f"{sys.executable} -m graph_net.torch.single_device_runner --model-path {model_path} --enable-extract True --extract-name {extract_name} --dump-graph-hash-key" cmd_ret = os.system(cmd) assert cmd_ret == 0, f"{cmd_ret=}, {cmd=}" cmd = f"{sys.executable} -m graph_net.torch.single_device_runner --model-path {tmp_dir_name}/{extract_name}" From 6bd1370354a6c0fe7392f485c847ce6d765c3a8c Mon Sep 17 00:00:00 2001 From: Xinqi Li Date: Mon, 4 Aug 2025 06:15:30 +0000 Subject: [PATCH 06/10] fix failed check by comparing directories after os.path.realpath() --- graph_net/torch/check_redundant_incrementally.py | 7 ++++++- graph_net/torch/remove_redundant_incrementally.py | 5 +++++ 2 files changed, 11 insertions(+), 1 deletion(-) diff --git a/graph_net/torch/check_redundant_incrementally.py b/graph_net/torch/check_redundant_incrementally.py index 747a710d4..e784b536a 100644 --- a/graph_net/torch/check_redundant_incrementally.py +++ b/graph_net/torch/check_redundant_incrementally.py @@ -15,8 +15,13 @@ def get_recursively_model_pathes(root_dir): + for sub_dir in _get_recursively_model_pathes(root_dir): + yield os.path.realpath(sub_dir) + + +def _get_recursively_model_pathes(root_dir): if is_single_model_dir(root_dir): - yield root_dir + yield os.path.realpath(root_dir) return for sub_dir in get_immediate_subdirectory_paths(root_dir): if is_single_model_dir(sub_dir): diff --git a/graph_net/torch/remove_redundant_incrementally.py b/graph_net/torch/remove_redundant_incrementally.py index 81a6b3d90..df046b504 100644 --- a/graph_net/torch/remove_redundant_incrementally.py +++ b/graph_net/torch/remove_redundant_incrementally.py @@ -16,6 +16,11 @@ def get_recursively_model_pathes(root_dir): + for sub_dir in _get_recursively_model_pathes(root_dir): + yield os.path.realpath(sub_dir) + + +def _get_recursively_model_pathes(root_dir): if is_single_model_dir(root_dir): yield root_dir return From 165ae4b851cce4309ccd08932ab721c5053fd2e1 Mon Sep 17 00:00:00 2001 From: Xinqi Li Date: Mon, 4 Aug 2025 07:09:56 +0000 Subject: [PATCH 07/10] fix bugs in check_validate.sh --- graph_net/torch/check_redundant_incrementally.py | 2 +- graph_net/torch/validate.py | 11 ++++++++++- tools/ci/check_validate.sh | 4 ++-- 3 files changed, 13 insertions(+), 4 deletions(-) diff --git a/graph_net/torch/check_redundant_incrementally.py b/graph_net/torch/check_redundant_incrementally.py index 2a1c41c82..0c0f70534 100644 --- a/graph_net/torch/check_redundant_incrementally.py +++ b/graph_net/torch/check_redundant_incrementally.py @@ -63,7 +63,7 @@ def main(args): graph_hash = open(current_model_graph_hash_path).read() assert ( graph_hash not in graph_hash2graph_net_model_path - ), f"Redundant models detected. old-model-path:{current_model_graph_hash_path}, new-model-path:{graph_hash2graph_net_model_path[graph_hash]}." + ), f"Redundant models detected. old-model-path:{graph_hash2graph_net_model_path[graph_hash]}, new-model-path:{current_model_graph_hash_path}." if __name__ == "__main__": diff --git a/graph_net/torch/validate.py b/graph_net/torch/validate.py index 61469845a..0e1c63e2e 100644 --- a/graph_net/torch/validate.py +++ b/graph_net/torch/validate.py @@ -29,7 +29,9 @@ def main(args): if not args.no_check_redundancy: print("Check redundancy ...") graph_net_samples_path = ( - graph_net.torch.samples_util.get_default_samples_directory() + (graph_net.torch.samples_util.get_default_samples_directory()) + if args.graph_net_samples_path is None + else args.graph_net_samples_path ) cmd = f"{sys.executable} -m graph_net.torch.check_redundant_incrementally --model-path {args.model_path} --graph-net-samples-path {graph_net_samples_path}" cmd_ret = os.system(cmd) @@ -49,6 +51,13 @@ def main(args): required=True, help="Path to folder e.g '../../samples/torch/resnet18'", ) + parser.add_argument( + "--graph-net-samples-path", + type=str, + required=False, + default=None, + help="Path to GraphNet samples folder. e.g '../../samples'", + ) parser.add_argument( "--no-check-redundancy", action="store_true", diff --git a/tools/ci/check_validate.sh b/tools/ci/check_validate.sh index 89bdc33a1..32681858c 100644 --- a/tools/ci/check_validate.sh +++ b/tools/ci/check_validate.sh @@ -44,7 +44,7 @@ function check_validation() { fail_name=() for model_path in ${MODIFIED_MODEL_PATHS[@]} do - python -m graph_net.torch.validate --model-path ${GRAPH_NET_EXTRACT_WORKSPACE}/${model_path} >&2 + python -m graph_net.torch.validate --model-path ${GRAPH_NET_EXTRACT_WORKSPACE}/${model_path} --graph-net-samples-path ${GRAPH_NET_EXTRACT_WORKSPACE}/samples >&2 [ $? -ne 0 ] && fail_name[${#fail_name[@]}]="${model_path}" done if [ ${#fail_name[@]} -ne 0 ] @@ -76,4 +76,4 @@ function main() { LOG "[INFO] check_validation run success and no error!" } -main \ No newline at end of file +main From 3a75ddd429bf0c02f501ea6da19218d59cb16376 Mon Sep 17 00:00:00 2001 From: Xinqi Li Date: Tue, 5 Aug 2025 13:36:34 +0000 Subject: [PATCH 08/10] set dynamic=False in single_device_runner.py --- graph_net/torch/single_device_runner.py | 2 +- graph_net/torch/validate.py | 5 ++++- samples/torchvision/resnet18/graph_hash.txt | 2 +- 3 files changed, 6 insertions(+), 3 deletions(-) diff --git a/graph_net/torch/single_device_runner.py b/graph_net/torch/single_device_runner.py index 72d89c1f5..ed4ef115e 100644 --- a/graph_net/torch/single_device_runner.py +++ b/graph_net/torch/single_device_runner.py @@ -58,7 +58,7 @@ def main(args): print(f"{model_path=}") if args.enable_extract: assert args.extract_name is not None - kwargs = dict(name=args.extract_name, **dump_graph_options) + kwargs = dict(name=args.extract_name, dynamic=False, **dump_graph_options) model = extract(**kwargs)(model) inputs_params = utils.load_converted_from_text(f"{model_path}") diff --git a/graph_net/torch/validate.py b/graph_net/torch/validate.py index 0e1c63e2e..784525510 100644 --- a/graph_net/torch/validate.py +++ b/graph_net/torch/validate.py @@ -18,8 +18,11 @@ def temp_workspace(): def main(args): model_path = args.model_path with temp_workspace() as tmp_dir_name: - extract_name = "temp" print("Check extractability ...") + cmd = f"{sys.executable} -m graph_net.torch.single_device_runner --model-path {model_path}" + cmd_ret = os.system(cmd) + assert cmd_ret == 0, f"{cmd_ret=}, {cmd=}" + extract_name = "temp" cmd = f"{sys.executable} -m graph_net.torch.single_device_runner --model-path {model_path} --enable-extract True --extract-name {extract_name} --dump-graph-hash-key" cmd_ret = os.system(cmd) assert cmd_ret == 0, f"{cmd_ret=}, {cmd=}" diff --git a/samples/torchvision/resnet18/graph_hash.txt b/samples/torchvision/resnet18/graph_hash.txt index a43bbde05..692ee6ff3 100644 --- a/samples/torchvision/resnet18/graph_hash.txt +++ b/samples/torchvision/resnet18/graph_hash.txt @@ -1 +1 @@ -9d1568d6617d5b2d5d3762b24b3c296f63fe423cfecdc27d6ecd425c0290de74 \ No newline at end of file +6307f5cae7a727aa9c38f51c1b38fc303106c8d7d9f318a74039249efe87f3d4 \ No newline at end of file From 868b686c2ddb80b930d7f949294889fca310a1c6 Mon Sep 17 00:00:00 2001 From: Xinqi Li Date: Wed, 6 Aug 2025 04:51:44 +0000 Subject: [PATCH 09/10] reset graph hash --- graph_net/torch/dump_graph_hash.py | 39 +++++++++++++++++++ .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../cait_s24_224.fb_dist_in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/coat_lite_medium.in1k/graph_hash.txt | 2 +- .../timm/coat_lite_mini.in1k/graph_hash.txt | 2 +- .../timm/coat_lite_small.in1k/graph_hash.txt | 2 +- .../timm/coat_lite_tiny.in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../convmixer_1536_20.in1k/graph_hash.txt | 2 +- .../timm/convmixer_768_32.in1k/graph_hash.txt | 2 +- .../timm/convnext_atto.d2_in1k/graph_hash.txt | 2 +- .../convnext_atto_ols.a2_in1k/graph_hash.txt | 2 +- .../convnext_base.clip_laion2b/graph_hash.txt | 2 +- .../convnext_femto.d1_in1k/graph_hash.txt | 2 +- .../convnext_femto_ols.d1_in1k/graph_hash.txt | 2 +- .../convnext_large.fb_in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../convnext_nano.d1h_in1k/graph_hash.txt | 2 +- .../convnext_nano_ols.d1h_in1k/graph_hash.txt | 2 +- .../timm/convnext_pico.d1_in1k/graph_hash.txt | 2 +- .../convnext_pico_ols.d1_in1k/graph_hash.txt | 2 +- .../convnext_small.fb_in1k/graph_hash.txt | 2 +- .../timm/convnext_tiny.fb_in1k/graph_hash.txt | 2 +- .../convnext_tiny_hnf.a2h_in1k/graph_hash.txt | 2 +- .../convnext_xlarge.fb_in22k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/convnextv2_atto.fcmae/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/convnextv2_base.fcmae/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../convnextv2_femto.fcmae/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/convnextv2_huge.fcmae/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../convnextv2_large.fcmae/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/convnextv2_nano.fcmae/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/convnextv2_pico.fcmae/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/convnextv2_tiny.fcmae/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/crossvit_15_240.in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/crossvit_18_240.in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/crossvit_9_240.in1k/graph_hash.txt | 2 +- .../crossvit_9_dagger_240.in1k/graph_hash.txt | 2 +- .../crossvit_base_240.in1k/graph_hash.txt | 2 +- .../crossvit_small_240.in1k/graph_hash.txt | 2 +- .../crossvit_tiny_240.in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../cs3darknet_l.c2ns_in1k/graph_hash.txt | 2 +- .../cs3darknet_m.c2ns_in1k/graph_hash.txt | 2 +- .../cs3darknet_x.c2ns_in1k/graph_hash.txt | 2 +- .../timm/cs3edgenet_x.c2_in1k/graph_hash.txt | 2 +- .../cs3se_edgenet_x.c2ns_in1k/graph_hash.txt | 2 +- .../cs3sedarknet_l.c2ns_in1k/graph_hash.txt | 2 +- .../cs3sedarknet_x.c2ns_in1k/graph_hash.txt | 2 +- .../timm/cspdarknet53.ra_in1k/graph_hash.txt | 2 +- .../timm/cspresnet50.ra_in1k/graph_hash.txt | 2 +- .../timm/cspresnext50.ra_in1k/graph_hash.txt | 2 +- .../timm/darknet53.c2ns_in1k/graph_hash.txt | 2 +- .../timm/darknetaa53.c2ns_in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/densenet121.ra_in1k/graph_hash.txt | 2 +- .../timm/densenet161.tv_in1k/graph_hash.txt | 2 +- .../timm/densenet169.tv_in1k/graph_hash.txt | 2 +- .../timm/densenet201.tv_in1k/graph_hash.txt | 2 +- .../densenetblur121d.ra_in1k/graph_hash.txt | 2 +- samples/timm/dla102.in1k/graph_hash.txt | 2 +- samples/timm/dla102x.in1k/graph_hash.txt | 2 +- samples/timm/dla102x2.in1k/graph_hash.txt | 2 +- samples/timm/dla169.in1k/graph_hash.txt | 2 +- samples/timm/dla34.in1k/graph_hash.txt | 2 +- samples/timm/dla46_c.in1k/graph_hash.txt | 2 +- samples/timm/dla46x_c.in1k/graph_hash.txt | 2 +- samples/timm/dla60.in1k/graph_hash.txt | 2 +- samples/timm/dla60x.in1k/graph_hash.txt | 2 +- samples/timm/dla60x_c.in1k/graph_hash.txt | 2 +- samples/timm/dpn107.mx_in1k/graph_hash.txt | 2 +- samples/timm/dpn131.mx_in1k/graph_hash.txt | 2 +- samples/timm/dpn68.mx_in1k/graph_hash.txt | 2 +- samples/timm/dpn68b.mx_in1k/graph_hash.txt | 2 +- samples/timm/dpn92.mx_in1k/graph_hash.txt | 2 +- samples/timm/dpn98.mx_in1k/graph_hash.txt | 2 +- .../eca_resnet33ts.ra2_in1k/graph_hash.txt | 2 +- .../eca_resnext26ts.ch_in1k/graph_hash.txt | 2 +- .../ecaresnet101d.miil_in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../ecaresnet269d.ra2_in1k/graph_hash.txt | 2 +- .../timm/ecaresnet26t.ra2_in1k/graph_hash.txt | 2 +- .../ecaresnet50d.miil_in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/ecaresnet50t.a1_in1k/graph_hash.txt | 2 +- .../ecaresnetlight.miil_in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../efficientnet_b1.ft_in1k/graph_hash.txt | 2 +- .../efficientnet_b2.ra_in1k/graph_hash.txt | 2 +- .../efficientnet_b3.ra2_in1k/graph_hash.txt | 2 +- .../efficientnet_b4.ra2_in1k/graph_hash.txt | 2 +- .../efficientnet_b5.sw_in12k/graph_hash.txt | 2 +- .../efficientnet_el.ra_in1k/graph_hash.txt | 2 +- .../efficientnet_em.ra2_in1k/graph_hash.txt | 2 +- .../efficientnet_es.ra_in1k/graph_hash.txt | 2 +- .../efficientnet_lite0.ra_in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../ese_vovnet19b_dw.ra_in1k/graph_hash.txt | 2 +- .../timm/ese_vovnet39b.ra_in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- samples/timm/fasternet_l.in1k/graph_hash.txt | 2 +- samples/timm/fasternet_m.in1k/graph_hash.txt | 2 +- samples/timm/fasternet_s.in1k/graph_hash.txt | 2 +- samples/timm/fasternet_t0.in1k/graph_hash.txt | 2 +- samples/timm/fasternet_t1.in1k/graph_hash.txt | 2 +- samples/timm/fasternet_t2.in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../fastvit_t8.apple_dist_in1k/graph_hash.txt | 2 +- .../timm/fbnetc_100.rmsp_in1k/graph_hash.txt | 2 +- .../timm/fbnetv3_b.ra2_in1k/graph_hash.txt | 2 +- .../timm/fbnetv3_d.ra2_in1k/graph_hash.txt | 2 +- .../timm/fbnetv3_g.ra2_in1k/graph_hash.txt | 2 +- .../focalnet_base_lrf.ms_in1k/graph_hash.txt | 2 +- .../focalnet_base_srf.ms_in1k/graph_hash.txt | 2 +- .../focalnet_huge_fl3.ms_in22k/graph_hash.txt | 2 +- .../focalnet_huge_fl4.ms_in22k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../focalnet_small_lrf.ms_in1k/graph_hash.txt | 2 +- .../focalnet_small_srf.ms_in1k/graph_hash.txt | 2 +- .../focalnet_tiny_lrf.ms_in1k/graph_hash.txt | 2 +- .../focalnet_tiny_srf.ms_in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/gernet_l.idstcv_in1k/graph_hash.txt | 2 +- .../timm/gernet_m.idstcv_in1k/graph_hash.txt | 2 +- .../timm/gernet_s.idstcv_in1k/graph_hash.txt | 2 +- samples/timm/ghostnet_100.in1k/graph_hash.txt | 2 +- .../gmixer_24_224.ra3_in1k/graph_hash.txt | 2 +- .../timm/gmlp_s16_224.ra3_in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/hgnet_base.ssld_in1k/graph_hash.txt | 2 +- .../hgnet_small.paddle_in1k/graph_hash.txt | 2 +- .../hgnet_tiny.paddle_in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/hrnet_w18.ms_aug_in1k/graph_hash.txt | 2 +- .../hrnet_w18_small.gluon_in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../hrnet_w18_ssld.paddle_in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/inception_resnet_v2/graph_hash.txt | 2 +- .../inception_v3.gluon_in1k/graph_hash.txt | 2 +- .../timm/inception_v4.tf_in1k/graph_hash.txt | 2 +- samples/timm/inception_v4/graph_hash.txt | 2 +- .../timm/lcnet_050.ra2_in1k/graph_hash.txt | 2 +- .../timm/lcnet_075.ra2_in1k/graph_hash.txt | 2 +- .../timm/lcnet_100.ra2_in1k/graph_hash.txt | 2 +- .../timm/legacy_senet154.in1k/graph_hash.txt | 2 +- .../legacy_seresnet101.in1k/graph_hash.txt | 2 +- .../legacy_seresnet152.in1k/graph_hash.txt | 2 +- .../legacy_seresnet18.in1k/graph_hash.txt | 2 +- .../legacy_seresnet34.in1k/graph_hash.txt | 2 +- .../legacy_seresnet50.in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../legacy_xception.tf_in1k/graph_hash.txt | 2 +- .../timm/mambaout_base.in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/mambaout_femto.in1k/graph_hash.txt | 2 +- .../timm/mambaout_kobe.in1k/graph_hash.txt | 2 +- .../timm/mambaout_small.in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../timm/mambaout_tiny.in1k/graph_hash.txt | 2 +- .../mixer_b16_224.goog_in21k/graph_hash.txt | 2 +- .../mixer_l16_224.goog_in21k/graph_hash.txt | 2 +- samples/timm/mixnet_l.ft_in1k/graph_hash.txt | 2 +- samples/timm/mixnet_m.ft_in1k/graph_hash.txt | 2 +- samples/timm/mixnet_s.ft_in1k/graph_hash.txt | 2 +- samples/timm/mixnet_xl.ra_in1k/graph_hash.txt | 2 +- .../timm/mnasnet_100.rmsp_in1k/graph_hash.txt | 2 +- .../mnasnet_small.lamb_in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../mobilenetv2_050.lamb_in1k/graph_hash.txt | 2 +- .../mobilenetv2_100.ra_in1k/graph_hash.txt | 2 +- .../mobilenetv2_110d.ra_in1k/graph_hash.txt | 2 +- .../mobilenetv2_120d.ra_in1k/graph_hash.txt | 2 +- .../mobilenetv2_140.ra_in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../mobilenetv3_rw.rmsp_in1k/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../mobileone_s0.apple_in1k/graph_hash.txt | 2 +- .../mobileone_s1.apple_in1k/graph_hash.txt | 2 +- .../mobileone_s2.apple_in1k/graph_hash.txt | 2 +- .../mobileone_s3.apple_in1k/graph_hash.txt | 2 +- .../mobileone_s4.apple_in1k/graph_hash.txt | 2 +- .../timm/nf_resnet50.ra2_in1k/graph_hash.txt | 2 +- .../poolformer_m36.sail_in1k/graph_hash.txt | 2 +- .../poolformer_m48.sail_in1k/graph_hash.txt | 2 +- .../poolformer_s12.sail_in1k/graph_hash.txt | 2 +- .../poolformer_s24.sail_in1k/graph_hash.txt | 2 +- .../poolformer_s36.sail_in1k/graph_hash.txt | 2 +- .../poolformerv2_m36.sail_in1k/graph_hash.txt | 2 +- .../poolformerv2_m48.sail_in1k/graph_hash.txt | 2 +- .../poolformerv2_s12.sail_in1k/graph_hash.txt | 2 +- .../poolformerv2_s24.sail_in1k/graph_hash.txt | 2 +- .../poolformerv2_s36.sail_in1k/graph_hash.txt | 2 +- .../timm/rdnet_base.nv_in1k/graph_hash.txt | 2 +- .../timm/rdnet_large.nv_in1k/graph_hash.txt | 2 +- .../timm/rdnet_small.nv_in1k/graph_hash.txt | 2 +- .../timm/rdnet_tiny.nv_in1k/graph_hash.txt | 2 +- .../timm/regnetv_040.ra3_in1k/graph_hash.txt | 2 +- .../timm/regnetv_064.ra3_in1k/graph_hash.txt | 2 +- .../regnetx_002.pycls_in1k/graph_hash.txt | 2 +- .../regnetx_004.pycls_in1k/graph_hash.txt | 2 +- .../regnetx_004_tv.tv2_in1k/graph_hash.txt | 2 +- .../regnetx_006.pycls_in1k/graph_hash.txt | 2 +- .../regnetx_008.pycls_in1k/graph_hash.txt | 2 +- .../regnetx_016.pycls_in1k/graph_hash.txt | 2 +- .../regnetx_032.pycls_in1k/graph_hash.txt | 2 +- .../regnetx_040.pycls_in1k/graph_hash.txt | 2 +- .../regnetx_064.pycls_in1k/graph_hash.txt | 2 +- .../regnetx_080.pycls_in1k/graph_hash.txt | 2 +- .../regnetx_120.pycls_in1k/graph_hash.txt | 2 +- .../regnetx_160.pycls_in1k/graph_hash.txt | 2 +- .../regnetx_320.pycls_in1k/graph_hash.txt | 2 +- .../regnety_002.pycls_in1k/graph_hash.txt | 2 +- .../regnety_004.pycls_in1k/graph_hash.txt | 2 +- .../regnety_006.pycls_in1k/graph_hash.txt | 2 +- .../regnety_008.pycls_in1k/graph_hash.txt | 2 +- .../regnety_008_tv.tv2_in1k/graph_hash.txt | 2 +- .../regnety_016.pycls_in1k/graph_hash.txt | 2 +- .../regnety_032.pycls_in1k/graph_hash.txt | 2 +- .../regnety_040.pycls_in1k/graph_hash.txt | 2 +- .../regnety_064.pycls_in1k/graph_hash.txt | 2 +- .../regnety_080.pycls_in1k/graph_hash.txt | 2 +- .../regnety_080_tv.tv2_in1k/graph_hash.txt | 2 +- samples/timm/res2net101_26w_4s/graph_hash.txt | 2 +- samples/timm/res2net101d/graph_hash.txt | 2 +- samples/timm/resnet18/graph_hash.txt | 2 +- samples/timm/resnetblur50d/graph_hash.txt | 2 +- .../convtasnet_base_libri2mix/graph_hash.txt | 2 +- samples/torchaudio/hubert_base/graph_hash.txt | 2 +- .../torchaudio/hubert_large/graph_hash.txt | 2 +- .../torchaudio/squim_objective/graph_hash.txt | 2 +- .../squim_subjective/graph_hash.txt | 2 +- .../torchaudio/wav2vec2_base/graph_hash.txt | 2 +- .../torchaudio/wav2vec2_large/graph_hash.txt | 2 +- .../wav2vec2_xlsr_300m/graph_hash.txt | 2 +- samples/torchvision/alexnet/graph_hash.txt | 2 +- .../torchvision/convnext_base/graph_hash.txt | 2 +- .../torchvision/convnext_large/graph_hash.txt | 2 +- .../torchvision/convnext_small/graph_hash.txt | 2 +- .../torchvision/convnext_tiny/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../deeplabv3_resnet101/graph_hash.txt | 2 +- .../deeplabv3_resnet50/graph_hash.txt | 2 +- .../torchvision/densenet121/graph_hash.txt | 2 +- .../torchvision/densenet161/graph_hash.txt | 2 +- .../torchvision/densenet169/graph_hash.txt | 2 +- .../torchvision/densenet201/graph_hash.txt | 2 +- .../efficientnet_b0/graph_hash.txt | 2 +- .../efficientnet_b1/graph_hash.txt | 2 +- .../efficientnet_b2/graph_hash.txt | 2 +- .../efficientnet_b3/graph_hash.txt | 2 +- .../efficientnet_b4/graph_hash.txt | 2 +- .../efficientnet_b5/graph_hash.txt | 2 +- .../efficientnet_b6/graph_hash.txt | 2 +- .../efficientnet_b7/graph_hash.txt | 2 +- .../efficientnet_v2_l/graph_hash.txt | 2 +- .../efficientnet_v2_m/graph_hash.txt | 2 +- .../efficientnet_v2_s/graph_hash.txt | 2 +- samples/torchvision/googlenet/graph_hash.txt | 2 +- .../torchvision/inception_v3/graph_hash.txt | 2 +- samples/torchvision/mnasnet0_5/graph_hash.txt | 2 +- .../torchvision/mnasnet0_75/graph_hash.txt | 2 +- samples/torchvision/mnasnet1_0/graph_hash.txt | 2 +- samples/torchvision/mnasnet1_3/graph_hash.txt | 2 +- .../torchvision/mobilenet_v2/graph_hash.txt | 2 +- .../mobilenet_v3_large/graph_hash.txt | 2 +- .../mobilenet_v3_small/graph_hash.txt | 2 +- samples/torchvision/r3d_18/graph_hash.txt | 2 +- .../torchvision/regnet_x_16gf/graph_hash.txt | 2 +- .../torchvision/regnet_x_1_6gf/graph_hash.txt | 2 +- .../torchvision/regnet_x_32gf/graph_hash.txt | 2 +- .../torchvision/regnet_x_3_2gf/graph_hash.txt | 2 +- .../torchvision/regnet_x_400mf/graph_hash.txt | 2 +- .../torchvision/regnet_x_800mf/graph_hash.txt | 2 +- .../torchvision/regnet_x_8gf/graph_hash.txt | 2 +- .../torchvision/regnet_y_128gf/graph_hash.txt | 2 +- .../torchvision/regnet_y_16gf/graph_hash.txt | 2 +- .../torchvision/regnet_y_1_6gf/graph_hash.txt | 2 +- .../torchvision/regnet_y_32gf/graph_hash.txt | 2 +- .../torchvision/regnet_y_3_2gf/graph_hash.txt | 2 +- .../torchvision/regnet_y_400mf/graph_hash.txt | 2 +- .../torchvision/regnet_y_800mf/graph_hash.txt | 2 +- .../torchvision/regnet_y_8gf/graph_hash.txt | 2 +- samples/torchvision/resnet101/graph_hash.txt | 2 +- samples/torchvision/resnet152/graph_hash.txt | 2 +- samples/torchvision/resnet34/graph_hash.txt | 2 +- samples/torchvision/resnet50/graph_hash.txt | 2 +- .../resnext101_32x8d/graph_hash.txt | 2 +- .../resnext101_64x4d/graph_hash.txt | 2 +- .../resnext50_32x4d/graph_hash.txt | 2 +- .../shufflenet_v2_x0_5/graph_hash.txt | 2 +- .../shufflenet_v2_x1_0/graph_hash.txt | 2 +- .../shufflenet_v2_x1_5/graph_hash.txt | 2 +- .../shufflenet_v2_x2_0/graph_hash.txt | 2 +- .../torchvision/squeezenet1_0/graph_hash.txt | 2 +- .../torchvision/squeezenet1_1/graph_hash.txt | 2 +- samples/torchvision/vgg11/graph_hash.txt | 2 +- samples/torchvision/vgg11_bn/graph_hash.txt | 2 +- samples/torchvision/vgg13/graph_hash.txt | 2 +- samples/torchvision/vgg13_bn/graph_hash.txt | 2 +- samples/torchvision/vgg16/graph_hash.txt | 2 +- samples/torchvision/vgg16_bn/graph_hash.txt | 2 +- samples/torchvision/vgg19/graph_hash.txt | 2 +- samples/torchvision/vgg19_bn/graph_hash.txt | 2 +- .../wide_resnet101_2/graph_hash.txt | 2 +- .../wide_resnet50_2/graph_hash.txt | 2 +- .../Qwen2.5-0.5B/graph_hash.txt | 2 +- .../distilbert-base-uncased/graph_hash.txt | 2 +- .../graph_hash.txt | 2 +- .../microsoft_resnet-50/graph_hash.txt | 2 +- 389 files changed, 427 insertions(+), 388 deletions(-) create mode 100644 graph_net/torch/dump_graph_hash.py diff --git a/graph_net/torch/dump_graph_hash.py b/graph_net/torch/dump_graph_hash.py new file mode 100644 index 000000000..01cba0162 --- /dev/null +++ b/graph_net/torch/dump_graph_hash.py @@ -0,0 +1,39 @@ +import argparse +import os +import tempfile +import sys +import contextlib +import graph_net + + +@contextlib.contextmanager +def temp_workspace(): + with tempfile.TemporaryDirectory() as tmp_dir_name: + old = os.environ.get("GRAPH_NET_EXTRACT_WORKSPACE") + os.environ["GRAPH_NET_EXTRACT_WORKSPACE"] = tmp_dir_name + yield tmp_dir_name + os.environ["GRAPH_NET_EXTRACT_WORKSPACE"] = old + + +def main(args): + model_path = args.model_path + with temp_workspace() as tmp_dir_name: + print("dump-graph-hash ...") + extract_name = "temp" + cmd = f"{sys.executable} -m graph_net.torch.single_device_runner --model-path {model_path} --enable-extract True --extract-name {extract_name} --dump-graph-hash-key" + cmd_ret = os.system(cmd) + assert cmd_ret == 0, f"{cmd_ret=}, {cmd=}" + + print(f"dump-graph-hash success, {model_path=}") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="load and run model") + parser.add_argument( + "--model-path", + type=str, + required=True, + help="Path to folder e.g '../../samples/torch/resnet18'", + ) + args = parser.parse_args() + main(args=args) diff --git a/samples/timm/aimv2_1b_patch14_224.apple_pt/graph_hash.txt b/samples/timm/aimv2_1b_patch14_224.apple_pt/graph_hash.txt index 856fd6ca0..448ee18cf 100644 --- a/samples/timm/aimv2_1b_patch14_224.apple_pt/graph_hash.txt +++ b/samples/timm/aimv2_1b_patch14_224.apple_pt/graph_hash.txt @@ -1 +1 @@ -ff10075e46eeae7615c783a3970e04ae79c1ea3f5b6020b167bec1e19489372f \ No newline at end of file +e60ac9dbcc0fa9f62855f67503f5c2bca67f9e53f3439e9804197df7ddf048eb \ No newline at end of file diff --git a/samples/timm/aimv2_3b_patch14_224.apple_pt/graph_hash.txt b/samples/timm/aimv2_3b_patch14_224.apple_pt/graph_hash.txt index 6eb601bbf..f9edc4be1 100644 --- a/samples/timm/aimv2_3b_patch14_224.apple_pt/graph_hash.txt +++ b/samples/timm/aimv2_3b_patch14_224.apple_pt/graph_hash.txt @@ -1 +1 @@ -60bb6d0dc13811c3e1ded64bb218dc7c0d655cf6f734a78d49d2f9bb22641c34 \ No newline at end of file +dcf892a92d59aa3c8a317e4362bd66dee86cef616cdd0b5454934416f0e3d3a2 \ No newline at end of file diff --git a/samples/timm/aimv2_huge_patch14_224.apple_pt/graph_hash.txt b/samples/timm/aimv2_huge_patch14_224.apple_pt/graph_hash.txt index 644cdd433..20506936e 100644 --- a/samples/timm/aimv2_huge_patch14_224.apple_pt/graph_hash.txt +++ b/samples/timm/aimv2_huge_patch14_224.apple_pt/graph_hash.txt @@ -1 +1 @@ -d10372439b472d0f72f1ff88c60f8fbaf8b8dc0d8a0773c79e34ddee6c2cc78d \ No newline at end of file +085338002b2237e13b39c245d576213233f245692298d2f8eb9d6b96b41b1444 \ No newline at end of file diff --git a/samples/timm/aimv2_large_patch14_224.apple_pt/graph_hash.txt b/samples/timm/aimv2_large_patch14_224.apple_pt/graph_hash.txt index fec1e0b25..68f65e5c7 100644 --- a/samples/timm/aimv2_large_patch14_224.apple_pt/graph_hash.txt +++ b/samples/timm/aimv2_large_patch14_224.apple_pt/graph_hash.txt @@ -1 +1 @@ -b3d1b0a0f52857e51f4dddd46b99a86dfb3d43e77e14d5859924120583f5a244 \ No newline at end of file +a57e75386c28bd03050a2c2fa255baaf8cf2208025254f16ec55140f8efdb05a \ No newline at end of file diff --git a/samples/timm/beit3_base_patch16_224.in22k_ft_in1k/graph_hash.txt b/samples/timm/beit3_base_patch16_224.in22k_ft_in1k/graph_hash.txt index 88da88ab8..1daa3b7a5 100644 --- a/samples/timm/beit3_base_patch16_224.in22k_ft_in1k/graph_hash.txt +++ b/samples/timm/beit3_base_patch16_224.in22k_ft_in1k/graph_hash.txt @@ -1 +1 @@ -49efabd40a93e856c10a3cf40aef7d7ad7e6f9fcfed3fc57f883ebd0e7d3f938 \ No newline at end of file +5bed5358ccacb86df0f4d76edc532e700cd0fa462a66a42f4e662ad1b9e3458f \ No newline at end of file diff --git a/samples/timm/beit3_large_patch16_224.in22k_ft_in1k/graph_hash.txt b/samples/timm/beit3_large_patch16_224.in22k_ft_in1k/graph_hash.txt index 44b074954..58663aee3 100644 --- a/samples/timm/beit3_large_patch16_224.in22k_ft_in1k/graph_hash.txt +++ b/samples/timm/beit3_large_patch16_224.in22k_ft_in1k/graph_hash.txt @@ -1 +1 @@ -a79caac738b040f293c01cd92e1770f312f059371fd757fa138f608c37b3cf6e \ No newline at end of file +d4b3165a1b0f2088dc8940ec3d195f2334556cee7aa596c518de6d43a74ac492 \ No newline at end of file diff --git a/samples/timm/cait_s24_224.fb_dist_in1k/graph_hash.txt b/samples/timm/cait_s24_224.fb_dist_in1k/graph_hash.txt index 2bea99094..3c48ee044 100644 --- a/samples/timm/cait_s24_224.fb_dist_in1k/graph_hash.txt +++ b/samples/timm/cait_s24_224.fb_dist_in1k/graph_hash.txt @@ -1 +1 @@ -1e2932070cfe79b2301a5dcbf8822c085d0b27f1952820dec3236ec25dee50e4 \ No newline at end of file +027b94d67fd23c273464fd1fa774dc8e5bb71e3fa553f420a34384219e56b54d \ No newline at end of file diff --git a/samples/timm/cait_xxs24_224.fb_dist_in1k/graph_hash.txt b/samples/timm/cait_xxs24_224.fb_dist_in1k/graph_hash.txt index 2810dae27..a7d899410 100644 --- a/samples/timm/cait_xxs24_224.fb_dist_in1k/graph_hash.txt +++ b/samples/timm/cait_xxs24_224.fb_dist_in1k/graph_hash.txt @@ -1 +1 @@ -5e480860975c00b127e98aacc223c6966c3aa932ab913bbc461632d495e346df \ No newline at end of file +d9317c14b15f471b1130cd5da638dc8f0f3a1393f7bc4cebec0d62c0d057b123 \ No newline at end of file diff --git a/samples/timm/cait_xxs36_224.fb_dist_in1k/graph_hash.txt b/samples/timm/cait_xxs36_224.fb_dist_in1k/graph_hash.txt index 834859863..7c1292913 100644 --- a/samples/timm/cait_xxs36_224.fb_dist_in1k/graph_hash.txt +++ b/samples/timm/cait_xxs36_224.fb_dist_in1k/graph_hash.txt @@ -1 +1 @@ -630243af3229385eb616e6637b54dc563056dc16fd00c309d948e10aec3e8c0e \ No newline at end of file +2cf2c1412978939d42c8ad657643776644fec366153bc0b0bc5cff199c9c33fa \ No newline at end of file diff --git a/samples/timm/coat_lite_medium.in1k/graph_hash.txt b/samples/timm/coat_lite_medium.in1k/graph_hash.txt index 00c332427..53cd736bf 100644 --- a/samples/timm/coat_lite_medium.in1k/graph_hash.txt +++ b/samples/timm/coat_lite_medium.in1k/graph_hash.txt @@ -1 +1 @@ -89c00326da6b2b9930919a98f8db1c2b3d4a880a204269070dd51b4ddf3793a1 \ No newline at end of file +ac8b6252762329ce5fd6393b40f22a69a7e4c388d864a6efd106473fdd1ec06f \ No newline at end of file diff --git a/samples/timm/coat_lite_mini.in1k/graph_hash.txt b/samples/timm/coat_lite_mini.in1k/graph_hash.txt index de0390b93..4cec2096c 100644 --- a/samples/timm/coat_lite_mini.in1k/graph_hash.txt +++ b/samples/timm/coat_lite_mini.in1k/graph_hash.txt @@ -1 +1 @@ -731518653d5bd2112ff4d03f41383bfd9ada5b116521be8ee6ff2a86b0651993 \ No newline at end of file +09f130edf7e4d6f99c58bc7ab8f86aca05d482a868698e036c3722e19f51c604 \ No newline at end of file diff --git a/samples/timm/coat_lite_small.in1k/graph_hash.txt b/samples/timm/coat_lite_small.in1k/graph_hash.txt index 4b3af640e..8fffa4514 100644 --- a/samples/timm/coat_lite_small.in1k/graph_hash.txt +++ b/samples/timm/coat_lite_small.in1k/graph_hash.txt @@ -1 +1 @@ -490850194b83b142b6f65c861665b9cd1b46288297fdafeeb5a8eec6473a0f99 \ No newline at end of file +f84ba35d9b5a53c57b9534f4ac3371388037091fc75303cfca1c923baf3803af \ No newline at end of file diff --git a/samples/timm/coat_lite_tiny.in1k/graph_hash.txt b/samples/timm/coat_lite_tiny.in1k/graph_hash.txt index 2aed4edee..3532470a0 100644 --- a/samples/timm/coat_lite_tiny.in1k/graph_hash.txt +++ b/samples/timm/coat_lite_tiny.in1k/graph_hash.txt @@ -1 +1 @@ -0f835b2acd918ac86f94f98d8976832e84263a568562660d3fe87debf158b23d \ No newline at end of file +1e1877c5433b6390deac93ed25adf7e7caf3dc7e0e96311d4f28b472e9fda7b6 \ No newline at end of file diff --git a/samples/timm/convmixer_1024_20_ks9_p14.in1k/graph_hash.txt b/samples/timm/convmixer_1024_20_ks9_p14.in1k/graph_hash.txt index 8c7797f1b..2c50d640f 100644 --- a/samples/timm/convmixer_1024_20_ks9_p14.in1k/graph_hash.txt +++ b/samples/timm/convmixer_1024_20_ks9_p14.in1k/graph_hash.txt @@ -1 +1 @@ -278547c85ed73465aeb4a413847ac5ebf20507ba3921a16f80994470a9d0c746 \ No newline at end of file +984f526a9bb9fe9a4b11e43bf59e743abff3cde3649ee2d6b16bf45ea936cc2d \ No newline at end of file diff --git a/samples/timm/convmixer_1536_20.in1k/graph_hash.txt b/samples/timm/convmixer_1536_20.in1k/graph_hash.txt index c75062cf4..3e4c1c8d1 100644 --- a/samples/timm/convmixer_1536_20.in1k/graph_hash.txt +++ b/samples/timm/convmixer_1536_20.in1k/graph_hash.txt @@ -1 +1 @@ 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40fb26dcd..b08355e4b 100644 --- a/samples/timm/deit_base_patch16_224.fb_in1k/graph_hash.txt +++ b/samples/timm/deit_base_patch16_224.fb_in1k/graph_hash.txt @@ -1 +1 @@ -1d0ef300e50462f683e3b88ea3674a392cb6ecc17bc7dd39f8e2c65367e829a5 \ No newline at end of file +fef00359aa4c6ed9f7d578fb22b791e6705be9f392811109c0b9b36c171f2f49 \ No newline at end of file diff --git a/samples/timm/deit_small_distilled_patch16_224.fb_in1k/graph_hash.txt b/samples/timm/deit_small_distilled_patch16_224.fb_in1k/graph_hash.txt index f602a0660..2504f8a18 100644 --- a/samples/timm/deit_small_distilled_patch16_224.fb_in1k/graph_hash.txt +++ b/samples/timm/deit_small_distilled_patch16_224.fb_in1k/graph_hash.txt @@ -1 +1 @@ -a6fd91eca0badc635ce20aead25e47f6b7aaeef35de34742b760572723b41494 \ No newline at end of file +34c33a14579eb842ab70ec33a84298b292b3f209e61383a3bfd7ab4b82ea706c \ No newline at end of file diff --git a/samples/timm/deit_small_patch16_224.fb_in1k/graph_hash.txt b/samples/timm/deit_small_patch16_224.fb_in1k/graph_hash.txt index 4d06412e6..e2c682f0e 100644 --- a/samples/timm/deit_small_patch16_224.fb_in1k/graph_hash.txt +++ b/samples/timm/deit_small_patch16_224.fb_in1k/graph_hash.txt @@ -1 +1 @@ -dd39f4fd656faad35082e94c9b6536c58e6fa1fde59fbf16b0e8d53977453a6f \ No newline at end of file +15788b84a7dfa0aebdf8a0ea7a23e47e2cdaf9aaea0657e5d56a5fb15f50a236 \ No newline at end of file diff --git a/samples/timm/deit_tiny_distilled_patch16_224.fb_in1k/graph_hash.txt b/samples/timm/deit_tiny_distilled_patch16_224.fb_in1k/graph_hash.txt index 9c0d5dce4..d9be1597e 100644 --- a/samples/timm/deit_tiny_distilled_patch16_224.fb_in1k/graph_hash.txt +++ b/samples/timm/deit_tiny_distilled_patch16_224.fb_in1k/graph_hash.txt @@ -1 +1 @@ -8f0e9cfd2900cb44268638505c1031a525ea15e20dbf26a3feddfa71f0f303b5 \ No newline at end of file +41ee5da1820cb95751efdee74b194e58ba2bfcba3b2cf136bbe098cfea174820 \ No newline at end of file diff --git a/samples/timm/deit_tiny_patch16_224.fb_in1k/graph_hash.txt b/samples/timm/deit_tiny_patch16_224.fb_in1k/graph_hash.txt index b269f0719..43d0612d8 100644 --- a/samples/timm/deit_tiny_patch16_224.fb_in1k/graph_hash.txt +++ b/samples/timm/deit_tiny_patch16_224.fb_in1k/graph_hash.txt @@ -1 +1 @@ -280ac56eaaf4721e2023e2a905b9645fb0eea6be3fa203adaded06373c53b6b5 \ No newline at end of file +caad3c48b1fd1c10f91a295d69f51209329c634840743d3f988f90095fcf1480 \ No newline at end of file diff --git a/samples/timm/densenet121.ra_in1k/graph_hash.txt b/samples/timm/densenet121.ra_in1k/graph_hash.txt index 4aefe5c6c..656175394 100644 --- a/samples/timm/densenet121.ra_in1k/graph_hash.txt +++ b/samples/timm/densenet121.ra_in1k/graph_hash.txt @@ -1 +1 @@ -7d877cb38ecbe22220db7dc1f7b2d0cf9438bfb4f70998ecee1ae10941e4eeb2 \ No newline at end of file +5198c49014aecfb4d1cbb1f558abc3ce09579544dedf22480e8909262a72e0f8 \ No newline at end of file diff --git a/samples/timm/densenet161.tv_in1k/graph_hash.txt b/samples/timm/densenet161.tv_in1k/graph_hash.txt index 5b716bb92..e0200ce34 100644 --- a/samples/timm/densenet161.tv_in1k/graph_hash.txt +++ b/samples/timm/densenet161.tv_in1k/graph_hash.txt @@ -1 +1 @@ -4cef2f10705d139d718cf68cff2ac72ea0f705b85b19a9b403273b7308adb826 \ No newline at end of file +98508a8807a7fab8ec5345be8ed599bef9c9a0df666a6a5664133fb328167b82 \ No newline at end of file diff --git a/samples/timm/densenet169.tv_in1k/graph_hash.txt b/samples/timm/densenet169.tv_in1k/graph_hash.txt index 9ccec065d..0be0d4afe 100644 --- a/samples/timm/densenet169.tv_in1k/graph_hash.txt +++ b/samples/timm/densenet169.tv_in1k/graph_hash.txt @@ -1 +1 @@ -20ec56b7a5ce2dcf23a0114ba99191eaa451499b4406b1eec91ea0b1bd44dfac \ No newline at end of file +397b69b7fdf694ac4d5d6eeedee3e0ff26a907beed7069fc0c95cd169248bbc4 \ No newline at end of file diff --git a/samples/timm/densenet201.tv_in1k/graph_hash.txt b/samples/timm/densenet201.tv_in1k/graph_hash.txt index d8dae0872..b29e49019 100644 --- a/samples/timm/densenet201.tv_in1k/graph_hash.txt +++ b/samples/timm/densenet201.tv_in1k/graph_hash.txt @@ -1 +1 @@ -36ec146b47b470780e08cd74b50727801ccadde5421d7ed89ea47ca7ff326e59 \ No newline at end of file +3318ce417de91b969e3ddcb0328661de43cea94d1a45bc7aeb4753cb6360e35c \ No newline at end of file diff --git a/samples/timm/densenetblur121d.ra_in1k/graph_hash.txt b/samples/timm/densenetblur121d.ra_in1k/graph_hash.txt index f267737c7..ccdfa8187 100644 --- a/samples/timm/densenetblur121d.ra_in1k/graph_hash.txt +++ b/samples/timm/densenetblur121d.ra_in1k/graph_hash.txt @@ -1 +1 @@ -c19519861ce0a98446d72201993ea0c8e7662560a288da6ea9997a3e4ddae2c2 \ No newline at end of file +88c767cbfacc855fa44a1b3b8d540a56f61a7b53edfd30424aabfa73d2152c86 \ No newline at end of file diff --git a/samples/timm/dla102.in1k/graph_hash.txt b/samples/timm/dla102.in1k/graph_hash.txt index a94fe6bb0..e42323702 100644 --- a/samples/timm/dla102.in1k/graph_hash.txt +++ b/samples/timm/dla102.in1k/graph_hash.txt @@ 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\ No newline at end of file diff --git a/samples/timm/ese_vovnet57b.ra4_e3600_r256_in1k/graph_hash.txt b/samples/timm/ese_vovnet57b.ra4_e3600_r256_in1k/graph_hash.txt index 3998bda63..631642711 100644 --- a/samples/timm/ese_vovnet57b.ra4_e3600_r256_in1k/graph_hash.txt +++ b/samples/timm/ese_vovnet57b.ra4_e3600_r256_in1k/graph_hash.txt @@ -1 +1 @@ -f64ae305f83ac5587e5dd04d30760947de280fe8512254bff7a19fba062511a8 \ No newline at end of file +10daec45f2ec01a0dfea68c1fc20ccf67d3a253a8595aa1400e67fe389562929 \ No newline at end of file diff --git a/samples/timm/eva02_base_patch14_224.mim_in22k/graph_hash.txt b/samples/timm/eva02_base_patch14_224.mim_in22k/graph_hash.txt index 9af3b0d56..63c77d046 100644 --- a/samples/timm/eva02_base_patch14_224.mim_in22k/graph_hash.txt +++ b/samples/timm/eva02_base_patch14_224.mim_in22k/graph_hash.txt @@ -1 +1 @@ -5cab81a5de7c87c8f2cdae781e504bfc5185c6ef49244ecb949d02766ccdabf4 \ No newline at end of file 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--git a/samples/timm/lcnet_100.ra2_in1k/graph_hash.txt b/samples/timm/lcnet_100.ra2_in1k/graph_hash.txt index 1c17242f3..6d29ea607 100644 --- a/samples/timm/lcnet_100.ra2_in1k/graph_hash.txt +++ b/samples/timm/lcnet_100.ra2_in1k/graph_hash.txt @@ -1 +1 @@ -7ba8f65ff3fffa3731926d8b55ac4d8773c358b7acb48adee377e289cddc930f \ No newline at end of file +e780b115584bcabd4b318e6fa3defd1bbe232017808351f8728f0b32e12f2377 \ No newline at end of file diff --git a/samples/timm/legacy_senet154.in1k/graph_hash.txt b/samples/timm/legacy_senet154.in1k/graph_hash.txt index c89b39032..7066427ef 100644 --- a/samples/timm/legacy_senet154.in1k/graph_hash.txt +++ b/samples/timm/legacy_senet154.in1k/graph_hash.txt @@ -1 +1 @@ -5ac5fdc5b8e29e098f6052a5645612c94de61fb30566e1b8c0b9aadd78ee89c8 \ No newline at end of file +afc3a19cde953702a8a24013c4f38fccc8f5723b89b4bc2abb34e5c444d740d8 \ No newline at end of file diff --git a/samples/timm/legacy_seresnet101.in1k/graph_hash.txt 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a/samples/timm/legacy_xception.tf_in1k/graph_hash.txt +++ b/samples/timm/legacy_xception.tf_in1k/graph_hash.txt @@ -1 +1 @@ -be236a3880db2da18b846edd55caa69cc61d7e705bb52e5ba5b3407fd33d6ae8 \ No newline at end of file +bf1673216067fc6c3504afa577e95fd61726b929c8386c02d18670c021bfd36c \ No newline at end of file diff --git a/samples/timm/mambaout_base.in1k/graph_hash.txt b/samples/timm/mambaout_base.in1k/graph_hash.txt index 22a068db7..f36623120 100644 --- a/samples/timm/mambaout_base.in1k/graph_hash.txt +++ b/samples/timm/mambaout_base.in1k/graph_hash.txt @@ -1 +1 @@ -86a681e7719ccaa7616c07af301aa7517bc740801f2d0b4c61bb4804d70d9f6e \ No newline at end of file +691333f891aa92fdb6f8d786dbcdef29d07c269060f10d6b7119bf26d95e440e \ No newline at end of file diff --git a/samples/timm/mambaout_base_plus_rw.sw_e150_in12k/graph_hash.txt b/samples/timm/mambaout_base_plus_rw.sw_e150_in12k/graph_hash.txt index 5786ce93b..c84ac0e34 100644 --- a/samples/timm/mambaout_base_plus_rw.sw_e150_in12k/graph_hash.txt +++ b/samples/timm/mambaout_base_plus_rw.sw_e150_in12k/graph_hash.txt @@ -1 +1 @@ -8138d4c68e47fd2d252c83fb18955da37e06897031ab9dea2417f6f908c574bc \ No newline at end of file +630512ac217a527e0739a31a2fe2f834e1c14d2f678bdbf27492aa7af1bd27b6 \ No newline at end of file diff --git a/samples/timm/mambaout_base_short_rw.sw_e500_in1k/graph_hash.txt b/samples/timm/mambaout_base_short_rw.sw_e500_in1k/graph_hash.txt index 5342b685b..e1db72e92 100644 --- a/samples/timm/mambaout_base_short_rw.sw_e500_in1k/graph_hash.txt +++ b/samples/timm/mambaout_base_short_rw.sw_e500_in1k/graph_hash.txt @@ -1 +1 @@ -9a24773a8832535e9dc52596d5172e6896e1d0cfbebf8bdd6ec38b4ab3b19574 \ No newline at end of file +428329684dd690b5447b35813480773542d531393a508e8c0c9134dd4b738e66 \ No newline at end of file diff --git a/samples/timm/mambaout_base_tall_rw.sw_e500_in1k/graph_hash.txt b/samples/timm/mambaout_base_tall_rw.sw_e500_in1k/graph_hash.txt index 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a/samples/torchvision/regnet_y_800mf/graph_hash.txt b/samples/torchvision/regnet_y_800mf/graph_hash.txt index 1a2651feb..d0775d1e6 100644 --- a/samples/torchvision/regnet_y_800mf/graph_hash.txt +++ b/samples/torchvision/regnet_y_800mf/graph_hash.txt @@ -1 +1 @@ -c4dd99794123b0821bae1050d45eb3b041330a106e2131bb878df2d9af5a353a \ No newline at end of file +efae752d45ab1d0e4deb85e3f66c1164b7d562288dc9ae38363ae1d68e196902 \ No newline at end of file diff --git a/samples/torchvision/regnet_y_8gf/graph_hash.txt b/samples/torchvision/regnet_y_8gf/graph_hash.txt index fea591ee8..55cac8c0c 100644 --- a/samples/torchvision/regnet_y_8gf/graph_hash.txt +++ b/samples/torchvision/regnet_y_8gf/graph_hash.txt @@ -1 +1 @@ -f05d0aa03279bedb22fe513eade90b92bb34aae6a69f49b2004d03bd9416dff2 \ No newline at end of file +7f00db7b0d28d1a70aedac6367ce8aa84edcf34e89ca29cc1ec7cd2034b1b7d3 \ No newline at end of file diff --git a/samples/torchvision/resnet101/graph_hash.txt b/samples/torchvision/resnet101/graph_hash.txt index ef24b0a92..220117ee6 100644 --- a/samples/torchvision/resnet101/graph_hash.txt +++ b/samples/torchvision/resnet101/graph_hash.txt @@ -1 +1 @@ -0cbc99e22d6c50c11fb02aca0ded3f01a0f7dd3474d2f65e12f956a11b08b2cb \ No newline at end of file +22b59c265c3bb922439d4226a1126847188787443aee4acdf348869ef049ca36 \ No newline at end of file diff --git a/samples/torchvision/resnet152/graph_hash.txt b/samples/torchvision/resnet152/graph_hash.txt index 8778f1e22..091d9e158 100644 --- a/samples/torchvision/resnet152/graph_hash.txt +++ b/samples/torchvision/resnet152/graph_hash.txt @@ -1 +1 @@ -e6285a1eea52cf08f0ac621086e773ab4763f2a1d07fe155a1f009e0bebcc272 \ No newline at end of file +fb79990d19df5738aaf4d0231b603f24fe0bf301d51aea89dbf5efe33d0491a6 \ No newline at end of file diff --git a/samples/torchvision/resnet34/graph_hash.txt b/samples/torchvision/resnet34/graph_hash.txt index c47fd8879..4af620315 100644 --- a/samples/torchvision/resnet34/graph_hash.txt +++ b/samples/torchvision/resnet34/graph_hash.txt @@ -1 +1 @@ -ebab7b3df841647c90ec576ffd128b64c04de03a89325407110f3a9e3047fc66 \ No newline at end of file +c8122acb24e569d860ab6b11a31c023355c59255286995cc7b52099e52229c36 \ No newline at end of file diff --git a/samples/torchvision/resnet50/graph_hash.txt b/samples/torchvision/resnet50/graph_hash.txt index c4d4c065a..744992a96 100644 --- a/samples/torchvision/resnet50/graph_hash.txt +++ b/samples/torchvision/resnet50/graph_hash.txt @@ -1 +1 @@ -87396dbda3e3e3177c581d5b79fe44c45f5dc1fb8432e1d2ea21aee4febe0c4f \ No newline at end of file +9be6c6a66a943feb004723199356af14dd5b0a65c0dbb3e1203d0b7da91c28c9 \ No newline at end of file diff --git a/samples/torchvision/resnext101_32x8d/graph_hash.txt b/samples/torchvision/resnext101_32x8d/graph_hash.txt index 916aa88a0..27f697808 100644 --- a/samples/torchvision/resnext101_32x8d/graph_hash.txt +++ b/samples/torchvision/resnext101_32x8d/graph_hash.txt @@ -1 +1 @@ -52a11486e82cb4a71b6393d7af95da2218927178f0c60baa8c391825dca9fa44 \ No newline at end of file +371c6399a2b1527ac99fe1ba423c0a60bde0035328da56d207c7dd3f50a45b49 \ No newline at end of file diff --git a/samples/torchvision/resnext101_64x4d/graph_hash.txt b/samples/torchvision/resnext101_64x4d/graph_hash.txt index a0407b9f0..9b9c2412d 100644 --- a/samples/torchvision/resnext101_64x4d/graph_hash.txt +++ b/samples/torchvision/resnext101_64x4d/graph_hash.txt @@ -1 +1 @@ -024a2573cbd5ebb5300cac0faf62b73b682a3651bcb0f6eea089c3eb6683a2a0 \ No newline at end of file +8c542c63a7ebd8721efac3a6c910caaf2522a3077d21204d62b13f54382dc801 \ No newline at end of file diff --git a/samples/torchvision/resnext50_32x4d/graph_hash.txt b/samples/torchvision/resnext50_32x4d/graph_hash.txt index b4d4c6051..3fd2c6702 100644 --- a/samples/torchvision/resnext50_32x4d/graph_hash.txt +++ b/samples/torchvision/resnext50_32x4d/graph_hash.txt @@ -1 +1 @@ -2e3e9ce73f4693d66c60727f4285fe8bd8757b4103f5832354a95e750533ab62 \ No newline at end of file +1fdf16652d85ec444964a73eaafb1699c525715a6258d2cb510c9520e8412864 \ No newline at end of file diff --git a/samples/torchvision/shufflenet_v2_x0_5/graph_hash.txt b/samples/torchvision/shufflenet_v2_x0_5/graph_hash.txt index bc670ee96..f6a9192d9 100644 --- a/samples/torchvision/shufflenet_v2_x0_5/graph_hash.txt +++ b/samples/torchvision/shufflenet_v2_x0_5/graph_hash.txt @@ -1 +1 @@ -cfd71f4404d6803c46cddb92552d8c89ef6cae25506efcfc762a24b75682b545 \ No newline at end of file +dfbd5228081bc360d9c7b5cc53155cbe1bc95777d4b5fc70fc81b0b6eae3d6bc \ No newline at end of file diff --git a/samples/torchvision/shufflenet_v2_x1_0/graph_hash.txt b/samples/torchvision/shufflenet_v2_x1_0/graph_hash.txt index 28c8f6198..d5e6a165e 100644 --- a/samples/torchvision/shufflenet_v2_x1_0/graph_hash.txt +++ b/samples/torchvision/shufflenet_v2_x1_0/graph_hash.txt @@ -1 +1 @@ -34a83b5adacddfcbfc4ad2e6be2092b36ce537d80ba45d57aaea0ccb83fac88d \ No newline at end of file +38a773fea7f9fe68fdfe6c05f733c2473930ae822a5831a30d861d4e972488ab \ No newline at end of file diff --git a/samples/torchvision/shufflenet_v2_x1_5/graph_hash.txt b/samples/torchvision/shufflenet_v2_x1_5/graph_hash.txt index 86a736fcf..27fbadb4c 100644 --- a/samples/torchvision/shufflenet_v2_x1_5/graph_hash.txt +++ b/samples/torchvision/shufflenet_v2_x1_5/graph_hash.txt @@ -1 +1 @@ -20eed391b1be5e6cec6d31e0c192b31edea281a3b2b87741ffdade1d93740c79 \ No newline at end of file +79ba31834877dcef81fc35c00e87659a41327be787db5b70ddbb5fd6b5d77432 \ No newline at end of file diff --git a/samples/torchvision/shufflenet_v2_x2_0/graph_hash.txt b/samples/torchvision/shufflenet_v2_x2_0/graph_hash.txt index edfd01da1..568b87fa9 100644 --- a/samples/torchvision/shufflenet_v2_x2_0/graph_hash.txt +++ b/samples/torchvision/shufflenet_v2_x2_0/graph_hash.txt @@ -1 +1 @@ -e45637f6b1f52d2c4a3792f3a9944f343c3ca6be0d98e87d47b838c061aeb8dd \ No newline at end of file +883618131feefef72b64c232d4c47326fb06f7c15b74be38a8ab1369723cf551 \ No newline at end of file diff --git a/samples/torchvision/squeezenet1_0/graph_hash.txt b/samples/torchvision/squeezenet1_0/graph_hash.txt index 813f39966..0d227e328 100644 --- a/samples/torchvision/squeezenet1_0/graph_hash.txt +++ b/samples/torchvision/squeezenet1_0/graph_hash.txt @@ -1 +1 @@ -9ad67491386ba2cd1b77ac21ef76624e5b9c58f6992b3411f40f2fe9a2153f55 \ No newline at end of file +5ed2d2a828e234e500809fe6681ca45d1016a3ebcb43f21cd7e68642483c972e \ No newline at end of file diff --git a/samples/torchvision/squeezenet1_1/graph_hash.txt b/samples/torchvision/squeezenet1_1/graph_hash.txt index 9c2ce5a6c..993aa184b 100644 --- a/samples/torchvision/squeezenet1_1/graph_hash.txt +++ b/samples/torchvision/squeezenet1_1/graph_hash.txt @@ -1 +1 @@ -06ae5589119525532e61d159a8173eb94f56faacd3e823342bd471233c958404 \ No newline at end of file +e362e4050a3a4c3494e64eedda299e072ff68c88e03a4257e003fbce8303a1ad \ No newline at end of file diff --git a/samples/torchvision/vgg11/graph_hash.txt b/samples/torchvision/vgg11/graph_hash.txt index 40f598864..743184938 100644 --- a/samples/torchvision/vgg11/graph_hash.txt +++ b/samples/torchvision/vgg11/graph_hash.txt @@ -1 +1 @@ -68ad60dba65c7769563ebba85aa8981038338b062af8f913d7bce421284b11ce \ No newline at end of file +737e5b699fda5f5e484cb5cd20af64524f2265bda786820ba8f5ad6fce8359b3 \ No newline at end of file diff --git a/samples/torchvision/vgg11_bn/graph_hash.txt b/samples/torchvision/vgg11_bn/graph_hash.txt index 1963d3c0a..31c64b826 100644 --- a/samples/torchvision/vgg11_bn/graph_hash.txt +++ b/samples/torchvision/vgg11_bn/graph_hash.txt @@ -1 +1 @@ -ec7a8669233e90e10dbae7b9fb4d72b7e59edd6564abf418431ed048919e54bd \ No newline at end of file +66b46131f75b3a0110ea64ab33868e4d255f62106ce8f7f535d2484e12836bb9 \ No newline at end of file diff --git a/samples/torchvision/vgg13/graph_hash.txt b/samples/torchvision/vgg13/graph_hash.txt index 7b4c7fd09..a35489b05 100644 --- a/samples/torchvision/vgg13/graph_hash.txt +++ b/samples/torchvision/vgg13/graph_hash.txt @@ -1 +1 @@ -8b01e935f3fe706b8590e93c8c81a415927115dd7b261424a6b995b1eaec30eb \ No newline at end of file +cb72168e568ce8753ff0693b9d96414d4ad10b7958c54c53024641761fcaa139 \ No newline at end of file diff --git a/samples/torchvision/vgg13_bn/graph_hash.txt b/samples/torchvision/vgg13_bn/graph_hash.txt index 7db8f1c0e..131219882 100644 --- a/samples/torchvision/vgg13_bn/graph_hash.txt +++ b/samples/torchvision/vgg13_bn/graph_hash.txt @@ -1 +1 @@ -c8c3cf0e5b103707fd6db3bd6caa2da73642ee7b06a788e66e01dcd28d6b815d \ No newline at end of file +fc353a850f899724576f9035e7a7b8543f6bedf4f29f77bf170809b91c7b5134 \ No newline at end of file diff --git a/samples/torchvision/vgg16/graph_hash.txt b/samples/torchvision/vgg16/graph_hash.txt index f2f2b3354..b758dc4d9 100644 --- a/samples/torchvision/vgg16/graph_hash.txt +++ b/samples/torchvision/vgg16/graph_hash.txt @@ -1 +1 @@ -7877919aec2a5accc5be74c1145585a5b71407d81633ebc919d102ea54781f90 \ No newline at end of file +523658bbf628de004b0c545d4bd4668f7cafc561825565a5ae2d01d54a49fd8a \ No newline at end of file diff --git a/samples/torchvision/vgg16_bn/graph_hash.txt b/samples/torchvision/vgg16_bn/graph_hash.txt index a80927aa2..393bd3e4c 100644 --- a/samples/torchvision/vgg16_bn/graph_hash.txt +++ b/samples/torchvision/vgg16_bn/graph_hash.txt @@ -1 +1 @@ -95aa20ff842033ee57afd421c4237019307c520a1ae8e62490d3ea298e55607e \ No newline at end of file +354014f582fccfe9fe4b401de131a9e7c601128b57ed351bbe9f2d1b96cbd63b \ No newline at end of file diff --git a/samples/torchvision/vgg19/graph_hash.txt b/samples/torchvision/vgg19/graph_hash.txt index 7370a3412..4cbde2b7b 100644 --- a/samples/torchvision/vgg19/graph_hash.txt +++ b/samples/torchvision/vgg19/graph_hash.txt @@ -1 +1 @@ -3396d4d7859b75da9f131f47d184c885bdfae13c070f2ad80c975b7b118b923c \ No newline at end of file +cd89ecaa7d909f1ff974395b42b49eee60c9c9c980f11d54b0ef163866f0f5bb \ No newline at end of file diff --git a/samples/torchvision/vgg19_bn/graph_hash.txt b/samples/torchvision/vgg19_bn/graph_hash.txt index ca8131ca2..eabfa7902 100644 --- a/samples/torchvision/vgg19_bn/graph_hash.txt +++ b/samples/torchvision/vgg19_bn/graph_hash.txt @@ -1 +1 @@ -e6c3807886040e406a69dff874a542ce634c00370c84de3672e09b2cd1ae574c \ No newline at end of file +b710b3e4f3b828d1592029ab52d1b989ba8eba9853475c44e863db79db8291ca \ No newline at end of file diff --git a/samples/torchvision/wide_resnet101_2/graph_hash.txt b/samples/torchvision/wide_resnet101_2/graph_hash.txt index 91ea43163..220117ee6 100644 --- a/samples/torchvision/wide_resnet101_2/graph_hash.txt +++ b/samples/torchvision/wide_resnet101_2/graph_hash.txt @@ -1 +1 @@ -37cee721064cf2d138dc2cae9cae0bd3d0118972fa7aa98e124eb18b96415e23 \ No newline at end of file +22b59c265c3bb922439d4226a1126847188787443aee4acdf348869ef049ca36 \ No newline at end of file diff --git a/samples/torchvision/wide_resnet50_2/graph_hash.txt b/samples/torchvision/wide_resnet50_2/graph_hash.txt index 8904c1c89..744992a96 100644 --- a/samples/torchvision/wide_resnet50_2/graph_hash.txt +++ b/samples/torchvision/wide_resnet50_2/graph_hash.txt @@ -1 +1 @@ -e79573ae5503db817b51151bff1f784bea0c90014ebf763b0f480c00d5edefb6 \ No newline at end of file +9be6c6a66a943feb004723199356af14dd5b0a65c0dbb3e1203d0b7da91c28c9 \ No newline at end of file diff --git a/samples/transformers-auto-model/Qwen2.5-0.5B/graph_hash.txt b/samples/transformers-auto-model/Qwen2.5-0.5B/graph_hash.txt index bcf55efe8..c84a917ee 100644 --- a/samples/transformers-auto-model/Qwen2.5-0.5B/graph_hash.txt +++ b/samples/transformers-auto-model/Qwen2.5-0.5B/graph_hash.txt @@ -1 +1 @@ -3eee572d55c6ad1c30c1778c4d83453e27050706a3688ca177cc44f82b53fa95 \ No newline at end of file +4bd91a3dcc08517dc4ac39602b20245aba8452907e56b5111bccfe53a5c1c0bf \ No newline at end of file diff --git a/samples/transformers-auto-model/distilbert-base-uncased/graph_hash.txt b/samples/transformers-auto-model/distilbert-base-uncased/graph_hash.txt index 2acaca732..8e360a554 100644 --- a/samples/transformers-auto-model/distilbert-base-uncased/graph_hash.txt +++ b/samples/transformers-auto-model/distilbert-base-uncased/graph_hash.txt @@ -1 +1 @@ -b657cdf3f52b9717c7a8c5a76b380e19be40fddf843fefe4eee488a10429d8e1 \ No newline at end of file +e0fb785effe6aead329f6c5e99780276972c6c6b47d0c5ee93907814a70a3a2b \ No newline at end of file diff --git a/samples/transformers-auto-model/google_vit-base-patch16-224/graph_hash.txt b/samples/transformers-auto-model/google_vit-base-patch16-224/graph_hash.txt index 95cd74fd1..410b2aeb5 100644 --- a/samples/transformers-auto-model/google_vit-base-patch16-224/graph_hash.txt +++ b/samples/transformers-auto-model/google_vit-base-patch16-224/graph_hash.txt @@ -1 +1 @@ -5d1eb3b61f5aea2262dfa275b5b6ec799ef6855efb686bdd75eb2f8039d49b14 \ No newline at end of file +0c533ab27d190b1bf8656c194ed55b558f1c3a6f143108d5cf2de1155da7bafd \ No newline at end of file diff --git a/samples/transformers-auto-model/microsoft_resnet-50/graph_hash.txt b/samples/transformers-auto-model/microsoft_resnet-50/graph_hash.txt index 9201ede58..20aeac967 100644 --- a/samples/transformers-auto-model/microsoft_resnet-50/graph_hash.txt +++ b/samples/transformers-auto-model/microsoft_resnet-50/graph_hash.txt @@ -1 +1 @@ -c05f6c016eaefabe6f35278d0beaa25f6f3ab32601149736ec2370f368d02566 \ No newline at end of file +6496b398d7e2ea4c08026ec10560cd0b9ca9be81dfd72a8c4b48aa35deb43f0d \ No newline at end of file From f8524bbd6eb325090a5fee83ad274167c6f69b74 Mon Sep 17 00:00:00 2001 From: Xinqi Li Date: Sat, 6 Sep 2025 08:32:09 +0000 Subject: [PATCH 10/10] backup code for multi_dim_size --- graph_net/torch/constraint_util.py | 54 +++++++ .../generate_constraint_proposal_file.py | 140 ++++++++++++++++++ graph_net/torch/hash_util.py | 7 + graph_net/torch/imp_util.py | 17 +++ graph_net/torch/record_util.py | 31 ++++ graph_net/torch/single_device_runner.py | 49 +++++- graph_net/torch/test_compiler.py | 4 +- graph_net/torch/utils.py | 35 +++-- samples/torchvision/resnet18/shape_patch.py | 8 + 9 files changed, 320 insertions(+), 25 deletions(-) create mode 100644 graph_net/torch/constraint_util.py create mode 100644 graph_net/torch/generate_constraint_proposal_file.py create mode 100644 graph_net/torch/hash_util.py create mode 100644 graph_net/torch/imp_util.py create mode 100644 graph_net/torch/record_util.py create mode 100644 samples/torchvision/resnet18/shape_patch.py diff --git a/graph_net/torch/constraint_util.py b/graph_net/torch/constraint_util.py new file mode 100644 index 000000000..a4b29dacd --- /dev/null +++ b/graph_net/torch/constraint_util.py @@ -0,0 +1,54 @@ +import copy + + +def get_all_symbol_names(constraint_attrs_list): + unique_symbol_names = [] + for constraint_attrs in constraint_attrs_list: + for dim in constraint_attrs["shape"]: + if isinstance(dim, int): + continue + assert isinstance(dim, dict) + if dim["symbol_name"] in unique_symbol_names: + continue + unique_symbol_names.append(dim["symbol_name"]) + + return unique_symbol_names + + +def reify_symboli_dims(constraint_attrs_list, symbol_names): + def try_reify_dim(dim): + if isinstance(dim, int): + return dim + assert isinstance(dim, dict) + if dim["symbol_name"] not in symbol_names: + return dim + return dim["example_value"] + + constraint_attrs_list = copy.deepcopy(constraint_attrs_list) + for constraint_attrs in constraint_attrs_list: + constraint_attrs["shape"] = [ + try_reify_dim(dim) for dim in constraint_attrs["shape"] + ] + return constraint_attrs_list + + +def modify_dim_example_value(constraint_attrs_list, symbol_name, modifier): + def modify_dim(dim): + if isinstance(dim, int): + return + assert isinstance(dim, dict) + dim["example_value"] = modifier(dim["example_value"]) + + constraint_attrs_list = copy.deepcopy(constraint_attrs_list) + for constraint_attrs in constraint_attrs_list: + for dim in constraint_attrs["shape"]: + modify_dim(dim) + return constraint_attrs_list + + +def symbolic_dims_all_reified(constraint_attrs_list): + for constraint_attrs in constraint_attrs_list: + for dim in constraint_attrs["shape"]: + if not isinstance(dim, int): + return False + return True diff --git a/graph_net/torch/generate_constraint_proposal_file.py b/graph_net/torch/generate_constraint_proposal_file.py new file mode 100644 index 000000000..9cb7a1cd0 --- /dev/null +++ b/graph_net/torch/generate_constraint_proposal_file.py @@ -0,0 +1,140 @@ +from graph_net.torch import utils +import argparse +import torch +import logging +from pathlib import Path +from typing import Type, Any +import sys +from graph_net.torch.imp_util import load_class_from_file +import hashlib +from contextlib import contextmanager +import json +import inspect +import imp_util +import record_util +import copy + + +def main(args): + model_path = args.model_path + name2input_param_attrs = _get_name2input_param_attrs(model_path) + name_and_annotation_types = _get_name_and_annotation_types(model_path) + input_name_and_meta_attrs = _get_input_name_and_meta_attrs( + name2input_param_attrs, name_and_annotation_types + ) + input_name_and_constraint_attrs = _get_input_name_and_constraint_attrs( + input_name_and_meta_attrs + ) + _dump_input_name_and_constraint_attrs( + input_name_and_constraint_attrs, args.output_path + ) + + +def _dump_input_name_and_constraint_attrs(input_name_and_constraint_attrs, output_path): + py_code = record_util.serialize_to_py_code( + [attr for _, attr in input_name_and_constraint_attrs], + class_prefix="ProgramInputConstraint", + ) + print(f"{output_path=}") + with open(output_path, "w") as f: + f.write(py_code) + + +def _get_input_name_and_constraint_attrs(input_name_and_meta_attrs): + seq_no = 0 + dim2seq = {} + + def find_or_new_seq(dim): + nonlocal seq_no + nonlocal dim2seq + if dim in dim2seq: + return dim2seq[dim] + ret = seq_no + dim2seq[dim] = ret + seq_no += 1 + return ret + + def make_symoblic_shape(shape): + return type(shape)( + [ + symbolic_dim_desc + for dim in shape + for dim_seq_no in [find_or_new_seq(dim)] + for symbolic_dim_desc in [ + {"symbol_name": f"s{dim_seq_no}", "example_value": dim} + ] + ] + ) + + def make_constraint_attrs(attrs): + attrs = copy.deepcopy(attrs) + attrs["shape"] = make_symoblic_shape(attrs["shape"]) + return attrs + + return [ + (name, symbolic_attrs) + for name, attrs in input_name_and_meta_attrs + for symbolic_attrs in [make_constraint_attrs(attrs)] + ] + + +def _get_input_name_and_meta_attrs(name2input_param_attrs, name_and_annotation_types): + def constructed_from_self(name): + return name.find("self_") != -1 + + def is_tensor_type(annotation_type): + return annotation_type is torch.Tensor + + ret = [ + (name, meta_attr) + for name, annotation_type in name_and_annotation_types + if is_tensor_type(annotation_type) + if not constructed_from_self(name) + for meta_attr in [name2input_param_attrs[name]] + ] + assert len(ret) > 0 + return ret + + +def _get_name_and_annotation_types(model_path): + model_class = load_class_from_file( + f"{model_path}/model.py", class_name="GraphModule" + ) + annotations = inspect.getfullargspec(model_class.forward).annotations + return [(k, v) for k, v in annotations.items()] + + +def _get_name2input_param_attrs(model_path): + def get_classes(): + input_meta_file = f"{model_path}/input_meta.py" + for _, cls in imp_util.load_name_and_classes_from_file(input_meta_file): + yield cls + + weight_meta_file = f"{model_path}/weight_meta.py" + for _, cls in imp_util.load_name_and_classes_from_file(weight_meta_file): + yield cls + + return { + name: attr + for cls in get_classes() + for attr in [record_util.make_attrs_from_class(cls)] + for name in [attr["name"]] + } + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="generate constraint proposal file") + parser.add_argument( + "--model-path", + type=str, + required=True, + help="Path to folder e.g '../../samples/torch/resnet18'", + ) + parser.add_argument( + "--output-path", + type=str, + required=True, + help="output file path", + ) + args = parser.parse_args() + main(args=args) diff --git a/graph_net/torch/hash_util.py b/graph_net/torch/hash_util.py new file mode 100644 index 000000000..a8780470d --- /dev/null +++ b/graph_net/torch/hash_util.py @@ -0,0 +1,7 @@ +import hashlib + + +def get_sha_hash(content): + m = hashlib.sha256() + m.update(content.encode()) + return m.hexdigest() diff --git a/graph_net/torch/imp_util.py b/graph_net/torch/imp_util.py new file mode 100644 index 000000000..233c58c8e --- /dev/null +++ b/graph_net/torch/imp_util.py @@ -0,0 +1,17 @@ +import importlib.util +import inspect + + +def load_class_from_file(file_path: str, class_name: str): + spec = importlib.util.spec_from_file_location("unnamed", file_path) + unnamed = importlib.util.module_from_spec(spec) + spec.loader.exec_module(unnamed) + model_class = getattr(unnamed, class_name, None) + return model_class + + +def load_name_and_classes_from_file(file_path): + spec = importlib.util.spec_from_file_location("unnamed", file_path) + unnamed = importlib.util.module_from_spec(spec) + spec.loader.exec_module(unnamed) + yield from inspect.getmembers(unnamed, inspect.isclass) diff --git a/graph_net/torch/record_util.py b/graph_net/torch/record_util.py new file mode 100644 index 000000000..c48882231 --- /dev/null +++ b/graph_net/torch/record_util.py @@ -0,0 +1,31 @@ +import hash_util + + +def make_attrs_from_class(cls): + return { + k: v + for k, v in cls.__dict__.items() + if not k.startswith("__") and not callable(v) + } + + +def serialize_to_py_code(attrs, class_prefix): + assert isinstance(attrs, (tuple, list)) + + ret = "\n".join( + _serialize_one_attr_to_py_code(attr, class_prefix) for attr in attrs + ) + return ret + + +def _serialize_one_attr_to_py_code(attr, class_prefix): + hash_str = hash_util.get_sha_hash(str(attr)) + hash_str = hash_str[:32] + indent = " " * 4 + ret = "\n".join( + [ + f"class {class_prefix}{hash_str}:", + *[f"{indent}{name} = {repr(value)}" for name, value in attr.items()], + ] + ) + return f"{ret}\n\n" diff --git a/graph_net/torch/single_device_runner.py b/graph_net/torch/single_device_runner.py index 784e092d8..5afed3863 100644 --- a/graph_net/torch/single_device_runner.py +++ b/graph_net/torch/single_device_runner.py @@ -1,4 +1,4 @@ -from . import utils +from graph_net.torch import utils import argparse import importlib.util import inspect @@ -10,6 +10,10 @@ from graph_net.torch.extractor import extract import hashlib from contextlib import contextmanager +import json +import record_util +import imp_util +import os def load_class_from_file(file_path: str, class_name: str) -> Type[torch.nn.Module]: @@ -62,9 +66,14 @@ def main(args): kwargs = dict(name=args.extract_name, dynamic=False, **dump_graph_options) model = extract(**kwargs)(model) - inputs_params = utils.load_converted_from_text(f"{model_path}") + inputs_params = utils.make_input_and_param_tensors_from_model_path( + f"{model_path}" + ) params = inputs_params["weight_info"] - state_dict = {k: utils.replay_tensor(v) for k, v in params.items()} + shape_modifier = _get_shape_modifier(args) + state_dict = { + k: utils.replay_tensor(v, shape_modifier) for k, v in params.items() + } explain = torch._dynamo.explain(model)(**state_dict) if explain.graph_count != 1 or len(explain.break_reasons) != 0: @@ -76,10 +85,31 @@ def main(args): f"Graph extraction failed. The resulting graph is incomplete, broken into {explain.graph_count} subgraphs." ) - y = model(**state_dict)[0] + model(**state_dict) + + +def _get_shape_modifier(cli_args): + """ + yield shape modifier from shape_modifiers.json in directory cli_args.model_path + """ + if not cli_args.enable_shape_patch: + return lambda name, shape: shape + shape_patch_file_path = f"{cli_args.model_path}/shape_patch.py" + if not os.path.exists(shape_patch_file_path): + return lambda name, shape: shape + shape_modifier_data = [ + attrs + for name, cls in imp_util.load_name_and_classes_from_file(shape_patch_file_path) + for attrs in [record_util.make_attrs_from_class(cls)] + ] + assert isinstance(shape_modifier_data, list) + return _make_shape_modifier_impl(shape_modifier_data) - print(torch.argmin(y), torch.argmax(y)) - print(y.shape) + +def _make_shape_modifier_impl(shape_modifier_data): + name2new_shape = {attrs["name"]: attrs["shape"] for attrs in shape_modifier_data} + print(f"{name2new_shape=}") + return lambda name, shape: name2new_shape[name] if name in name2new_shape else shape if __name__ == "__main__": @@ -110,5 +140,12 @@ def main(args): default=None, help="Extracted graph's name", ) + parser.add_argument( + "--enable-shape-patch", + type=bool, + required=False, + default=False, + help="Enable extra inputs", + ) args = parser.parse_args() main(args=args) diff --git a/graph_net/torch/test_compiler.py b/graph_net/torch/test_compiler.py index e6ed03717..f8e8cc85b 100644 --- a/graph_net/torch/test_compiler.py +++ b/graph_net/torch/test_compiler.py @@ -86,7 +86,9 @@ def get_model(args): def get_input_dict(args): - inputs_params = utils.load_converted_from_text(f"{args.model_path}") + inputs_params = utils.make_input_and_param_tensors_from_model_path( + f"{args.model_path}" + ) params = inputs_params["weight_info"] return { k: utils.replay_tensor(v).to(torch.device(args.device)) diff --git a/graph_net/torch/utils.py b/graph_net/torch/utils.py index 35fa1ad0a..f543b722b 100644 --- a/graph_net/torch/utils.py +++ b/graph_net/torch/utils.py @@ -9,6 +9,8 @@ import importlib import inspect import math +import graph_net.torch.imp_util as imp_util +import graph_net.torch.record_util as record_util kLiteralTensorSize = 64 @@ -195,6 +197,10 @@ def process_tensor_info(tensor_info, name_prefix="example_input"): def load_converted_from_text(file_path): + return make_input_and_param_tensors_from_model_path(file_path) + + +def make_input_and_param_tensors_from_model_path(file_path): input_info = list(convert_meta_classes_to_tensors(f"{file_path}/input_meta.py")) weight_info = { @@ -209,13 +215,14 @@ def load_converted_from_text(file_path): } +def convert_tensor_meta_file_to_attrs(file_path): + for name, cls in imp_util.load_name_and_classes_from_file(file_path): + attrs = record_util.make_attrs_from_class(cls) + yield attrs + + def convert_meta_classes_to_tensors(file_path): - for name, cls in _get_classes(file_path): - attrs = { - k: v - for k, v in cls.__dict__.items() - if not k.startswith("__") and not callable(v) - } + for attrs in convert_tensor_meta_file_to_attrs(file_path): data_value = None data_type = getattr(torch, attrs.get("dtype", "torch.float").split(".")[-1]) shape = attrs.get("shape", []) @@ -247,21 +254,13 @@ def convert_meta_classes_to_tensors(file_path): } -def _get_classes(file_path): - spec = importlib.util.spec_from_file_location("unnamed", file_path) - unnamed = importlib.util.module_from_spec(spec) - spec.loader.exec_module(unnamed) - yield from inspect.getmembers(unnamed, inspect.isclass) - - -def extract_dynamic_shapes(example_inputs): - pass - - -def replay_tensor(info): +def replay_tensor(info, shape_modifier=None): device = info["info"]["device"] dtype = info["info"]["dtype"] shape = info["info"]["shape"] + if shape_modifier is None: + shape_modifier = lambda name, shape: shape + shape = shape_modifier(info["name"], shape) mean = info["info"]["mean"] std = info["info"]["std"] diff --git a/samples/torchvision/resnet18/shape_patch.py b/samples/torchvision/resnet18/shape_patch.py new file mode 100644 index 000000000..532aecb28 --- /dev/null +++ b/samples/torchvision/resnet18/shape_patch.py @@ -0,0 +1,8 @@ +class Program_weight_tensor_meta_L_x_: + name = "L_x_" + shape = [2, 3, 224, 224] + dtype = "torch.float32" + device = "cuda:0" + mean = 0.500 + std = 0.289 + data = None