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| author | Étienne Simon <esimon@esimon.eu> | 2015-07-14 07:58:20 -0400 |
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| committer | Étienne Simon <esimon@esimon.eu> | 2015-07-14 07:58:20 -0400 |
| commit | 87fc87384e6d9b7d88ca622a17dac7b8bc15cacb (patch) | |
| tree | a4577b0d27f298a7221e99ca7e0edb37ee991bc7 /README.md | |
| parent | c97af300b17ac042c52cfc54f43d4f01fd61fbe9 (diff) | |
| download | taxi-87fc87384e6d9b7d88ca622a17dac7b8bc15cacb.tar.gz taxi-87fc87384e6d9b7d88ca622a17dac7b8bc15cacb.zip | |
Add note about PYTHONPATH in README
Diffstat (limited to 'README.md')
| -rw-r--r-- | README.md | 2 |
1 files changed, 2 insertions, 0 deletions
@@ -40,6 +40,8 @@ Here is a brief description of the Python files in the archive: ## How to reproduce the winning results? There is an helper script `prepare.sh` which might helps you (by performing step 1-6 and some other checks), but if you encounter an error, the script will re-execute all the steps from the beginning (before the actual training, step 2, 4 and 5 are quite long). + +Note that some script expect the repository to be in your PYTHONPATH (go to the root of the repository and type `export PYTHONPATH="$PWD:$PYTHONPATH"`). 1. Set the `TAXI_PATH` environment variable to the path of the folder containing the CSV files. 2. Run `data/csv_to_hdf5.py "$TAXI_PATH" "$TAXI_PATH/data.hdf5"` to generate the HDF5 file (which is generated in `TAXI_PATH`, along the CSV files). This takes around 20 minutes on our machines. |