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https://github.com/saymrwulf/pytorch.git
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e3b3431c42
Summary: There were two problems with the HistogramObserver: 1. It does not work when someone passes a batch_size 1, tensor_size 1 data-point. 2. The Histogram doesn't seem to actually update if the range of the new x falls within the old one These issues were both fixed. On top of this, I greatly simplified the logic for the histogram updating. Now, it doesn't do the downsampling anymore, which saves a ton of memory and code. The accuracy can still be controlled with the upsampling ratio. This ratio was also too high for the accuracy we generally need here, I reduced the default for this. Also the code is cleaner now, much easier to follow what's happening. test_histogram_observer_same_inputs was likely wrong - If I pass 0s and 1s to my histogramobserver, I want them to actually count! The current test now thinks it's good to discard and ignore these values. Test Plan: You can run the included tests. Differential Revision: D58931336 Pull Request resolved: https://github.com/pytorch/pytorch/pull/129387 Approved by: https://github.com/jerryzh168 |
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| .. | ||
| experimental | ||
| __init__.py | ||
| test_backend_config.py | ||
| test_docs.py | ||
| test_quantized_functional.py | ||
| test_quantized_module.py | ||
| test_quantized_op.py | ||
| test_quantized_tensor.py | ||
| test_top_level_apis.py | ||
| test_utils.py | ||
| test_workflow_module.py | ||
| test_workflow_ops.py | ||