pytorch

12ea1d74 - Add missing functions and methods for channelwise quantization (#24934)

Add missing functions and methods for channelwise quantization (#24934) Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/24934 1) Functions and methods to get scales and zero_points for channelwise quantization were missing. Adding these. 2) Correctly print quantized tensors for channelwise quantization. ghstack-source-id: 88868339 Test Plan: buck test mode/dev caffe2/test:quantized -- 'test_qtensor\ \(test_quantized_tensor.TestQuantizedTensor\)' --print-passing-details ``` Running 1 tests Started new test run: https://our.intern.facebook.com/intern/testinfra/testrun/1970324844629541 ✓ caffe2/test:quantized - test_qtensor (test_quantized_tensor.TestQuantizedTensor) 0.161 1/1 (passed) Test output: > test_qtensor (test_quantized_tensor.TestQuantizedTensor) ... ok > > ---------------------------------------------------------------------- > Ran 1 test in 0.161s > > OK Finished test run: https://our.intern.facebook.com/intern/testinfra/testrun/1970324844629541 Summary (total time 6.61s): PASS: 1 FAIL: 0 SKIP: 0 FATAL: 0 TIMEOUT: 0 OMIT: 0 ``` To be added in a followup diff. Current output for printing qtensors: print(W_q.int_repr()) print(W_q) ``` > tensor([[[[-3, 0, 0], > [ 4, -2, -4], > [-1, -3, -2]], > > [[-3, 1, 3], > [-3, -3, 3], > [-3, -5, -1]]], > > > [[[ 4, -3, -4], > [ 4, -3, -3], > [ 4, -1, -1]], > > [[ 2, -3, 0], > [ 3, 1, 1], > [ 2, -4, 0]]]], dtype=torch.int8) > tensor([[[[-0.9273, -0.2318, -0.2318], > [ 0.6955, -0.6955, -1.1592], > [-0.4637, -0.9273, -0.6955]], > > [[-0.9273, 0.0000, 0.4637], > [-0.9273, -0.9273, 0.4637], > [-0.9273, -1.3910, -0.4637]]], > > > [[[ 0.3938, -0.1575, -0.2363], > [ 0.3938, -0.1575, -0.1575], > [ 0.3938, 0.0000, 0.0000]], > > [[ 0.2363, -0.1575, 0.0788], > [ 0.3150, 0.1575, 0.1575], > [ 0.2363, -0.2363, 0.0788]]]], size=(2, 2, 3, 3), dtype=torch.qint8, > quantization_scheme=torch.per_channel_affine, > scale=tensor([0.2318, 0.0788]), zero_point=tensor([ 1, -1])) ``` Differential Revision: D16659715 fbshipit-source-id: f8d3eeaff8f618aa0cca4fd076db73318e6df946