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#!/bin/bash
RUN=3
MEMORY_LENGTH=30
MODEL_TYPE="lstm"
Q_NUM_REPEATS_PER_INPUT=10
LOG_DIR="logs/qamnist/run${RUN}/${MODEL_TYPE}_${Q_NUM_REPEATS_PER_INPUT}"
SEED=$((RUN - 1))
python -m tasks.qamnist.train \
--log_dir $LOG_DIR \
--seed $SEED \
--memory_length $MEMORY_LENGTH \
--model_type $MODEL_TYPE \
--q_num_images 3 \
--q_num_images_delta 2 \
--q_num_repeats_per_input $Q_NUM_REPEATS_PER_INPUT \
--q_num_operations 3 \
--q_num_operations_delta 2 \
--q_num_answer_steps 10 \
--n_test_batches 20 \
--d_model 875 \
--d_input 64 \
--n_synch_out 32 \
--n_synch_action 32 \
--synapse_depth 1 \
--heads 4 \
--memory_hidden_dims 16 \
--dropout 0.0 \
--deep_memory \
--no-do_normalisation \
--weight_decay 0.0 \
--use_scheduler \
--scheduler_type "cosine" \
--milestones 0 0 0 \
--gamma 0 \
--batch_size 64 \
--batch_size_test 256 \
--lr=0.0001 \
--training_iterations 300001 \
--warmup_steps 500 \
--track_every 1000 \
--save_every 10000 \
--no-reload \
--no-reload_model_only \
--device 0 \
--no-use_amp \
--neuron_select_type "random" |