run_lm.sh

#!/bin/bash

DATA_PATH="/nmt/data"
INPUT_DATA_PATH="/data"
OUTPUT_DATA_PATH="/output"
PROJECT_DIR="/nmt"

# Let's keep here pathes for local testing and comment them out
PROJECT_DIR="."
DATA_PATH="data"
INPUT_DATA_PATH="data"
OUTPUT_DATA_PATH="data"

MODEL_NAME="transformer"
HP_FILE_PATH="$PROJECT_DIR/hp_files/lm_fitted.json"
BATCH_SIZE_FOR_INFERENCE=32
MAX_TIME_SECONDS=18000
VALIDATE_EVERY=3000
MAX_EPOCHS=50000
USE_EARLY_STOPPING=True
EARLY_STOPPING_LAST_N=5

# What the hack is this?
cd "$PROJECT_DIR"

# Preparing data
#$PROJECT_DIR/tokenize.sh "$PROJECT_DIR" "$INPUT_DATA_PATH"

# Training the model
#PYTHONPATH="$PROJECT_DIR" python3.6 "$PROJECT_DIR/src/train.py" "$MODEL_NAME" \
#            --data_path="$DATA_PATH" \
#            --hp_file_path="$HP_FILE_PATH" \
#            --validate_every="$VALIDATE_EVERY" \
#            --max_time_seconds="$MAX_TIME_SECONDS" \
#            --batch_size_for_inference="$BATCH_SIZE_FOR_INFERENCE" \
#            --use_early_stopping="$USE_EARLY_STOPPING" \
#            --early_stopping_last_n="$EARLY_STOPPING_LAST_N" \
#            --max_epochs="$MAX_EPOCHS" \
#            --target_lm_path="trained_models/pretrained_lm_lang2-24999" \
#            --src_lm_path="trained_models/pretrained_lm_lang1-13499"

# Running the model
PYTHONPATH="$PROJECT_DIR" python3.6 "$PROJECT_DIR/src/run.py" "$MODEL_NAME" \
            --data_path="$DATA_PATH" \
            --model_path="$PROJECT_DIR/trained_models/$MODEL_NAME/model.npz" \
            --input_path="$DATA_PATH/bpe_input.txt" \
            --output_path="$OUTPUT_DATA_PATH/output.txt" \
            --hp_file_path="$HP_FILE_PATH" \
            --batch_size_for_inference="$BATCH_SIZE_FOR_INFERENCE"