Merge pull request #1 from riga/master

Initial commit with CNN-based energy regression and ID tf model.

.gitignore

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+*.sublime-project
+*.sublime-workspace
+*.pyc
+*.log
+*.DS_Store
+*.pkl
+*.egg-info
+*.pdf
+*.png
+__pycache__
+dist
+build
+tmp
+data
+

README.md

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+# Data for the CMSSW [RecoHGCal/TICL](https://github.com/cms-sw/cmssw/tree/master/RecoHGCal/TICL) package
+
+### Quicklinks
+
+- TICL:
+  - [Reconstruction example](http://hgcal.web.cern.ch/hgcal/Reconstruction/TICL/)
+- TensorFlow:
+  - [C++ docs](https://www.tensorflow.org/api_docs/cc)
+  - [CMSSW interface](https://gitlab.cern.ch/mrieger/CMSSW-DNN)
+  - [PhysicsTools/TensorFlow](https://github.com/cms-sw/cmssw/tree/master/PhysicsTools/TensorFlow)
+
+### Models
+
+- `tf_models/energy_id_v*.pb`: TensorFlow model for trackster energy regression and particle ID.
+  - `v0`: Simple CNN-based approach. The neutral pion, neutral hadron, ambiguous and unknown probabilities are set to a constant value of 0. See the [talk at the Reco/AT meeting](https://indico.cern.ch/event/841640/contributions/3534140/attachments/1896780/3129591/2019-08-23_rieger_hgcal_ticl_eid.pdf) for more info. Input and output tensors:
+    - `"input"`: Input tensor with dimension `batch x 50 (layers) x 10 (clusters) x 3 (features)`.
+    - `"output/id_probabilities"`: Output tensor with dimension `batch x 8` representing particle ID "probabilities" (from a softmax output). The probabiltities refer to photon, electron, muon, neutral pion, charged hadron, neutral hadron, ambiguous and unknown cases (in that order).
+    - `"output/regressed_energy"`: Output tensor with dimension `batch x 1` representing the regressed energy value for the trackster.