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Timing the ONNX model, retrain CMS-GNNLSH-TF (jpata#229)
* timing code, retrain CMS-GNNLSH-TF, new multi-particle gun dataset, small hit-based datasets
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,66 @@ | ||
| from pathlib import Path | ||
|
|
||
| import tensorflow as tf | ||
| from utils_edm import ( | ||
| X_FEATURES_CH, | ||
| X_FEATURES_TRK, | ||
| Y_FEATURES, | ||
| generate_examples, | ||
| split_sample, | ||
| ) | ||
|
|
||
| import tensorflow_datasets as tfds | ||
|
|
||
| from qq import _DESCRIPTION, _CITATION | ||
|
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|
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| class ClicEdmQqHitsPf10k(tfds.core.GeneratorBasedBuilder): | ||
| VERSION = tfds.core.Version("1.5.0") | ||
| RELEASE_NOTES = { | ||
| "1.5.0": "Regenerate with ARRAY_RECORD", | ||
| } | ||
| MANUAL_DOWNLOAD_INSTRUCTIONS = """ | ||
| For the raw input files in ROOT EDM4HEP format, please see the citation above. | ||
| The processed tensorflow_dataset can also be downloaded from: | ||
| FIXME | ||
| """ | ||
|
|
||
| def __init__(self, *args, **kwargs): | ||
| kwargs["file_format"] = tfds.core.FileFormat.ARRAY_RECORD | ||
| super(ClicEdmQqHitsPf10k, self).__init__(*args, **kwargs) | ||
|
|
||
| def _info(self) -> tfds.core.DatasetInfo: | ||
| """Returns the dataset metadata.""" | ||
| return tfds.core.DatasetInfo( | ||
| builder=self, | ||
| description=_DESCRIPTION, | ||
| features=tfds.features.FeaturesDict( | ||
| { | ||
| "X": tfds.features.Tensor( | ||
| shape=( | ||
| None, | ||
| max(len(X_FEATURES_TRK), len(X_FEATURES_CH)), | ||
| ), | ||
| dtype=tf.float32, | ||
| ), | ||
| "ygen": tfds.features.Tensor(shape=(None, len(Y_FEATURES)), dtype=tf.float32), | ||
| "ycand": tfds.features.Tensor(shape=(None, len(Y_FEATURES)), dtype=tf.float32), | ||
| } | ||
| ), | ||
| supervised_keys=None, | ||
| homepage="", | ||
| citation=_CITATION, | ||
| metadata=tfds.core.MetadataDict( | ||
| x_features_track=X_FEATURES_TRK, | ||
| x_features_calohit=X_FEATURES_CH, | ||
| y_features=Y_FEATURES, | ||
| ), | ||
| ) | ||
|
|
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| def _split_generators(self, dl_manager: tfds.download.DownloadManager): | ||
| path = dl_manager.manual_dir | ||
| return split_sample(Path(path / "p8_ee_qq_ecm380/"), max_files=100) | ||
|
|
||
| def _generate_examples(self, files): | ||
| return generate_examples(files) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,66 @@ | ||
| from pathlib import Path | ||
|
|
||
| import tensorflow as tf | ||
| from utils_edm import ( | ||
| X_FEATURES_CH, | ||
| X_FEATURES_TRK, | ||
| Y_FEATURES, | ||
| generate_examples, | ||
| split_sample, | ||
| ) | ||
|
|
||
| import tensorflow_datasets as tfds | ||
|
|
||
| from ttbar import _DESCRIPTION, _CITATION | ||
|
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||
|
|
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| class ClicEdmTtbarHitsPf10k(tfds.core.GeneratorBasedBuilder): | ||
| VERSION = tfds.core.Version("1.5.0") | ||
| RELEASE_NOTES = { | ||
| "1.5.0": "Regenerate with ARRAY_RECORD", | ||
| } | ||
| MANUAL_DOWNLOAD_INSTRUCTIONS = """ | ||
| For the raw input files in ROOT EDM4HEP format, please see the citation above. | ||
| The processed tensorflow_dataset can also be downloaded from: | ||
| FIXME | ||
| """ | ||
|
|
||
| def __init__(self, *args, **kwargs): | ||
| kwargs["file_format"] = tfds.core.FileFormat.ARRAY_RECORD | ||
| super(ClicEdmTtbarHitsPf10k, self).__init__(*args, **kwargs) | ||
|
|
||
| def _info(self) -> tfds.core.DatasetInfo: | ||
| """Returns the dataset metadata.""" | ||
| return tfds.core.DatasetInfo( | ||
| builder=self, | ||
| description=_DESCRIPTION, | ||
| features=tfds.features.FeaturesDict( | ||
| { | ||
| "X": tfds.features.Tensor( | ||
| shape=( | ||
| None, | ||
| max(len(X_FEATURES_TRK), len(X_FEATURES_CH)), | ||
| ), | ||
| dtype=tf.float32, | ||
| ), | ||
| "ygen": tfds.features.Tensor(shape=(None, len(Y_FEATURES)), dtype=tf.float32), | ||
| "ycand": tfds.features.Tensor(shape=(None, len(Y_FEATURES)), dtype=tf.float32), | ||
| } | ||
| ), | ||
| supervised_keys=None, | ||
| homepage="", | ||
| citation=_CITATION, | ||
| metadata=tfds.core.MetadataDict( | ||
| x_features_track=X_FEATURES_TRK, | ||
| x_features_calohit=X_FEATURES_CH, | ||
| y_features=Y_FEATURES, | ||
| ), | ||
| ) | ||
|
|
||
| def _split_generators(self, dl_manager: tfds.download.DownloadManager): | ||
| path = dl_manager.manual_dir | ||
| return split_sample(Path(path / "p8_ee_tt_ecm380/"), max_files=100) | ||
|
|
||
| def _generate_examples(self, files): | ||
| return generate_examples(files) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,62 @@ | ||
| """CMS PF SinglePi dataset.""" | ||
| import cms_utils | ||
| import tensorflow as tf | ||
|
|
||
| import tensorflow_datasets as tfds | ||
|
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| X_FEATURES = cms_utils.X_FEATURES | ||
| Y_FEATURES = cms_utils.Y_FEATURES | ||
|
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| _DESCRIPTION = """ | ||
| Dataset generated with CMSSW and full detector sim. | ||
| Multi-particle gun events. | ||
| """ | ||
|
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| # TODO(cms_pf): BibTeX citation | ||
| _CITATION = """ | ||
| """ | ||
|
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|
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| class CmsPfMultiParticleGun(tfds.core.GeneratorBasedBuilder): | ||
| """DatasetBuilder for cms_pf_multi_particle_gun dataset.""" | ||
|
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| VERSION = tfds.core.Version("1.6.0") | ||
| RELEASE_NOTES = { | ||
| "1.6.0": "Initial release", | ||
| } | ||
| MANUAL_DOWNLOAD_INSTRUCTIONS = """ | ||
| rsync -r --progress lxplus.cern.ch:/eos/user/j/jpata/mlpf/cms/MultiParticlePFGun_cfi data/ | ||
| """ | ||
|
|
||
| def __init__(self, *args, **kwargs): | ||
| kwargs["file_format"] = tfds.core.FileFormat.ARRAY_RECORD | ||
| super(CmsPfMultiParticleGun, self).__init__(*args, **kwargs) | ||
|
|
||
| def _info(self) -> tfds.core.DatasetInfo: | ||
| """Returns the dataset metadata.""" | ||
| # TODO(cms_pf): Specifies the tfds.core.DatasetInfo object | ||
| return tfds.core.DatasetInfo( | ||
| builder=self, | ||
| description=_DESCRIPTION, | ||
| features=tfds.features.FeaturesDict( | ||
| { | ||
| "X": tfds.features.Tensor(shape=(None, len(X_FEATURES)), dtype=tf.float32), | ||
| "ygen": tfds.features.Tensor(shape=(None, len(Y_FEATURES)), dtype=tf.float32), | ||
| "ycand": tfds.features.Tensor(shape=(None, len(Y_FEATURES)), dtype=tf.float32), | ||
| } | ||
| ), | ||
| supervised_keys=("X", "ycand"), | ||
| homepage="", | ||
| citation=_CITATION, | ||
| metadata=tfds.core.MetadataDict(x_features=X_FEATURES, y_features=Y_FEATURES), | ||
| ) | ||
|
|
||
| def _split_generators(self, dl_manager: tfds.download.DownloadManager): | ||
| """Returns SplitGenerators.""" | ||
| path = dl_manager.manual_dir | ||
| sample_dir = "MultiParticlePFGun50_cfi" | ||
| return cms_utils.split_sample(path / sample_dir / "raw") | ||
|
|
||
| def _generate_examples(self, files): | ||
| return cms_utils.generate_examples(files) |
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