quantize_per_tensor(torch.tensor([-1.0, 0.0, 1.0, 2.0]), 0.1, 10, torch.quint8).int_repr() tensor([ 0, 10, 20, 30], dtype=torch.uint8) >>> torch.quantize_per_tensor([torch.tensor([-1.0, 0.0]), torch.tensor([-2.0
quantize_per_tensor(r, scale=scale, zero_point=zero_point, dtype=dtype) @@ -705,8 +746,6 @@ def test_qtensor_view(self): # torch.equal is not supported for the cuda backend if device == 'cpu': self.assertFalse(torch.equal(b, c)) else: self.assertRaises(RuntimeError, lambda: ...
what(): expected ) but found 'ident' here: quantized::fake_quantize_per_tensor_affine_forward(Tensor X, float scale, int zero_point, int num_bits = 8, int quant_delay = 0, int iter = 0) -> Tensor ~~~ <--- HERE Expected behavior no error Environment PyTorch version: 1.1.0 Is ...
torch.fake_quantize_per_tensor_affine(input, scale, zero_point, quant_min, quant_max) → Tensor 参数: input(Tensor) -torch.float32中的输入值。 scale(双倍的或者Tensor) -量化尺度 zero_point(整数64或者Tensor) -量化zero_point quant_min(整数64) -量化域的下界 quant_max(整数64) -量化域的上限...
buck2 test 'fbcode//mode/dev-nosan' fbcode//caffe2/test/quantization:test_quantization -- --exact 'caffe2/test/quantization:test_quantization - test_forward_per_tensor_cachemask_cpu (caffe2.test.quantization.core.test_workflow_ops.TestFakeQuantizeOps)' buck2 test 'fbcode//mode/dev-nosan'...
check-labels.yml on: pull_request_target Check labels 2s Oh hello! Nice to see you. Made with ️ by humans.txt Annotations 2 errors Check labels Canceling since a higher priority waiting request for 'Check Labels-139306-false' exists Check labels The operation was canceled....
For more info: https://github.blog/changelog/2024-03-07-github-actions-all-actions-will-run-on-node20-instead-of-node16-by-default/ Show more
For more info: https://github.blog/changelog/2024-03-07-github-actions-all-actions-will-run-on-node20-instead-of-node16-by-default/ Show more
Tensors and Dynamic neural networks in Python with strong GPU acceleration - Add bfloat16 support for per tensor/channel cpu/cuda fake quantize ops · pytorch/pytorch@5c6d354