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Mingshan/Adding resnet50 validation script #478
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…naSystems/ngraph-tf into mingshan/validate_resnet50
…naSystems/ngraph-tf into mingshan/validate_resnet50
sayantan-nervana
suggested changes
Apr 17, 2019
| def check_validation_results(norm_dict, metric): | ||
| test_pass = True | ||
| for norm in norm_dict: | ||
| if norm_dict[norm] > 0.1: |
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so if we get ref accuracy = 75, and ng accuracy = 75.3, then is it a failure?
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This script is not comparing the accuracy. It compares the training loss value at every iteration
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Same thing for loss. If ref loss is 1, and we get 0.8, is the test passing?
| return total_loss, top1_acc, top5_acc | ||
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| def parse_reference_file(filename): |
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parse_reference_file and parse_training_output can be a single function... I think they are separate because one parses a file, and the other parses string. Maybe we keep the string parsing function and just read the file into a string and reuse.
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This PR added the validation script for resnet50 training with both synthetic data and real data.
The tf result references under tfGPU/ folder is collected running the same command in the script on TF GPU.
The patch to make the data loader for real data deterministic is also included, and also the patch to eliminate the average_loss encapsulates in the training graph.