Move lib/ to src/compute_graph_vectorize/

Author: Neumann, Jan

benchmark.py

@@ -9,28 +9,28 @@
 
 import click
 import torch
-from lib.benchmarks.runnables.neuralogic_cpu import NeuraLogicCPURunnable
-from lib.benchmarks.runnables.neuralogic_vectorized import (
+from compute_graph_vectorize.benchmarks.runnables.neuralogic_cpu import NeuraLogicCPURunnable
+from compute_graph_vectorize.benchmarks.runnables.neuralogic_vectorized import (
     NeuralogicVectorizedTorchRunnable,
     PrebuiltNeuralogicVectorizedTorchRunnable,
 )
-from lib.benchmarks.runnables.pyg import PytorchGeometricRunnable
-from lib.benchmarks.runner import measure_backward, measure_forward
-from lib.datasets.dataset import MyDataset
-from lib.datasets.mutagenesis import MutagenesisSource, MutagenesisTemplate, MyMutagenesis
-from lib.datasets.tu_molecular import MyTUDataset, TUDatasetSource, TUDatasetTemplate
-from lib.engines.torch.settings import Compilation, TorchModuleSettings, TorchReduceMethod
-from lib.sources.neuralogic_settings import NeuralogicSettings
-from lib.utils import dataclass_to_shorthand, iter_empty, serialize_dataclass
-from lib.vectorize.model.op_network import VectorizedOpSeqNetwork
-from lib.vectorize.pipeline.other.reduce_op_network_value import (
+from compute_graph_vectorize.benchmarks.runnables.pyg import PytorchGeometricRunnable
+from compute_graph_vectorize.benchmarks.runner import measure_backward, measure_forward
+from compute_graph_vectorize.datasets.dataset import MyDataset
+from compute_graph_vectorize.datasets.mutagenesis import MutagenesisSource, MutagenesisTemplate, MyMutagenesis
+from compute_graph_vectorize.datasets.tu_molecular import MyTUDataset, TUDatasetSource, TUDatasetTemplate
+from compute_graph_vectorize.engines.torch.settings import Compilation, TorchModuleSettings, TorchReduceMethod
+from compute_graph_vectorize.sources.neuralogic_settings import NeuralogicSettings
+from compute_graph_vectorize.utils import dataclass_to_shorthand, iter_empty, serialize_dataclass
+from compute_graph_vectorize.vectorize.model.op_network import VectorizedOpSeqNetwork
+from compute_graph_vectorize.vectorize.pipeline.other.reduce_op_network_value import (
     count_gather_items,
     count_gathers,
     sum_op_network_values,
 )
-from lib.vectorize.pipeline.other.replace_tensors_with_shapes import replace_tensors_with_shapes
-from lib.vectorize.settings import VectorizeSettings
-from lib.vectorize.settings_presets import VectorizeSettingsPresets, iterate_vectorize_settings_presets
+from compute_graph_vectorize.vectorize.pipeline.other.replace_tensors_with_shapes import replace_tensors_with_shapes
+from compute_graph_vectorize.vectorize.settings import VectorizeSettings
+from compute_graph_vectorize.vectorize.settings_presets import VectorizeSettingsPresets, iterate_vectorize_settings_presets
 from tqdm.std import tqdm
 
 Device = Literal["mps", "cuda", "cpu", "ipu"]

buildnet.py

@@ -1,17 +1,18 @@
 import torch
-from lib.benchmarks.runnables.neuralogic_vectorized import NeuralogicVectorizedTorchRunnable
-from lib.datasets.tu_molecular import MyTUDataset
-from lib.engines.torch.settings import TorchModuleSettings
-from lib.sources.neuralogic_settings import NeuralogicSettings
-from lib.vectorize.settings import (
+from compute_graph_vectorize.benchmarks.runnables.neuralogic_vectorized import NeuralogicVectorizedTorchRunnable
+from compute_graph_vectorize.datasets.mutagenesis import MyMutagenesis
+from compute_graph_vectorize.datasets.tu_molecular import MyTUDataset
+from compute_graph_vectorize.engines.torch.settings import TorchModuleSettings
+from compute_graph_vectorize.sources.neuralogic_settings import NeuralogicSettings
+from compute_graph_vectorize.vectorize.settings import (
     LinearsSymmetriesSettings,
     OptimizeSingleUseGathersSettings,
     OptimizeTailRefsSettings,
     VectorizeSettings,
 )
 
 if __name__ == "__main__":
-    debug = False
+    debug = True
     device = "cpu"
 
     n_settings = NeuralogicSettings()
@@ -43,8 +44,8 @@
         granularize_by_weight=False,
     )
 
-    # dataset = MyMutagenesis(n_settings, "simple", "original")
-    dataset = MyTUDataset(n_settings, "mutag", "gsage")
+    dataset = MyMutagenesis(n_settings, "original", "simple")
+    # dataset = MyTUDataset(n_settings, "mutag", "gsage")
 
     print("Dataset:", dataset)
     print("Device:", device)

conftest.py

@@ -1,5 +1,6 @@
 [pytest]
 addopts = --doctest-modules --doctest-continue-on-failure --strict-markers
+pythonpath = src
 markers =
     long: marks tests as long
     extended: marks tests as extended

lib/sources/minimal_api/network_and_ordinals.py

@@ -1,8 +1,8 @@
 import argparse
 
-from lib.facts.duplicator import DatasetDuplicator
-from lib.facts.parser import parse_file
-from lib.facts.printer import DatasetPrinter
+from compute_graph_vectorize.facts.duplicator import DatasetDuplicator
+from compute_graph_vectorize.facts.parser import parse_file
+from compute_graph_vectorize.facts.printer import DatasetPrinter
 
 if __name__ == "__main__":
     parser = argparse.ArgumentParser()

lib/tests/conftest.py

@@ -1,8 +1,8 @@
 from neuralogic.core.builder.builder import NeuralSample
 
-from lib.benchmarks.runnables.runnable import Runnable
-from lib.benchmarks.utils.timer import Timer
-from lib.datasets.dataset import BuiltDatasetInstance
+from compute_graph_vectorize.benchmarks.runnables.runnable import Runnable
+from compute_graph_vectorize.benchmarks.utils.timer import Timer
+from compute_graph_vectorize.datasets.dataset import BuiltDatasetInstance
 
 
 class NeuraLogicCPURunnable(Runnable):