Random shuffle before dropping the last few samples #123
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tongzhoumu
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* Add files via upload * Add files via upload * Add files via upload * Rename eval_benchmark_1_correctness.py to eval_benchmark_correctness.py * Rename eval_benchmark_2_detailed_orientation.py to eval_benchmark_detailed_orientation.py * Rename eval_benchmark_3_context.py to eval_benchmark_context.py * Rename eval_benchmark_4_temporal.py to eval_benchmark_temporal.py * Rename eval_benchmark_5_consistency.py to eval_benchmark_consistency.py * Update eval_all.sh * Update eval_all.sh * Update eval_all.sh * Create run_vila_benchmark.sh * Update slurm_run_all.sh * Update eval_all.sh * Update eval_all.sh * Create eval_vila_benchmark_gpt4.sh * Update eval_vila_benchmark_gpt4.sh * Update eval_all.sh * Update eval_all.sh * Delete llava/eval/video/convert_pred_to_json.py * Update model_vqa_videodemo_benchmark.py * Update eval_all.sh * Update run_vila_benchmark.sh * Update slurm_run_all_sharded.sh * Update slurm_run_all.sh
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I noticed a bug in the data sampler. In the original implementation, the same elements will be dropped in every epoch.
For example, assume the dataset size is 900, and the batch size is 200, then the same 100 samples are dropped every time, which means they are never used in training