Remove IPEX dependency and switch to main torch for XPU supporting

As the Intel XPU has been upstream to the public torch, we are going to remove the IPEX dependency of the Triton for JIT compiling.
Need to clean up all the import intel_extension_for_pytorch in the Triton XPU code.
The related sub issues for this task:

https://github.com/intel/intel-xpu-backend-for-triton/issues/770

I propose making IPEX an optional dependency instead of removing it. Most of our tests run when the imports for IPEX are removed, with no other changes (this is a moving target, b/c pytorch upstream and triton upstream change frequently and are not always in sync with each other). If we create a fake IPEX module that is a noop, and modify our test script to install either pytorch upstream + the fake IPEX, or IPEX and the pinned pytorch for IPEX, we should be able to support both upstream and IPEX for development, accuracy testing, and perf testing with no other code changes.
We need to do performance testing with upstream pytorch and PVC. But, even if performance on PVC is acceptable, we will need to support IPEX for i/dGPU development even after we switch to PVC.

Last week, I have sent the stock PyTorch BKC for Triton test enabling. The temporary IPEX test proxy will not support again.

The switch is blocked by missing ATen operators implementation for XPU such as:
NotImplementedError: The operator 'aten::__lshift__.Scalar' is not currently implemented for the XPU device.

Last nights failed run w/ https://github.com/pytorch/pytorch/commit/f9dae86222aaf15ea085c7774da70781bae46ff9:
=========================== short test summary info ============================
FAILED language/test_core.py::test_reduce1d[64-16-1-argmax-tie-break-left-int8-512] - OverflowError: Python integer 432 out of bounds for int8
FAILED language/test_core.py::test_abs_fp8[in_dtype2] - NotImplementedError: The operator 'aten::__lshift__.Scalar' is not currently implemented for the XPU device. Please open a feature on https://github.com/intel/torch-xpu-ops/issues. You can set the environment variable `PYTORCH_ENABLE_XPU_FALLBACK=1` to use the CPU implementation as a fallback for XPU unimplemented operators. WARNING: this will bring unexpected performance compared with running natively on XPU.
FAILED language/test_core.py::test_reduce1d[4-32-1-argmax-tie-break-left-int8-512] - OverflowError: Python integer 432 out of bounds for int8
FAILED language/test_core.py::test_full[shape0-uint16] - RuntimeError: "eq_xpu" not implemented for 'UInt16'
FAILED language/test_core.py::test_full[shape0-uint32] - RuntimeError: "eq_xpu" not implemented for 'UInt32'
FAILED language/test_core.py::test_full[shape0-uint64] - RuntimeError: "eq_xpu" not implemented for 'UInt64'
FAILED language/test_core.py::test_full[shape1-uint16] - RuntimeError: "eq_xpu" not implemented for 'UInt16'
FAILED language/test_core.py::test_full[shape1-uint32] - RuntimeError: "eq_xpu" not implemented for 'UInt32'
FAILED language/test_core.py::test_full[shape1-uint64] - RuntimeError: "eq_xpu" not implemented for 'UInt64'
FAILED language/test_core.py::test_full[shape2-uint16] - RuntimeError: "eq_xpu" not implemented for 'UInt16'
FAILED language/test_core.py::test_full[shape2-uint32] - RuntimeError: "eq_xpu" not implemented for 'UInt32'
FAILED language/test_core.py::test_full[shape2-uint64] - RuntimeError: "eq_xpu" not implemented for 'UInt64'
FAILED language/test_core.py::test_dot[1-128-128-64-4-True-True-none-tf32-int8-int8-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-4-True-True-none-tf32-int8-int8-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-2-True-True-none-tf32-int8-int8-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-4-True-True-none-tf32-float16-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-2-True-True-none-tf32-int8-int8-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-4-True-True-none-tf32-float16-float32-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-4-True-True-none-tf32-float32-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-4-True-True-none-tf32-float32-float32-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-4-True-False-none-tf32-int8-int8-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-4-True-False-none-tf32-int8-int8-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-2-True-True-none-tf32-float16-float16-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_random.py::test_randint[4,53-67830198458-int32-True] - OverflowError: Python integer<PHONE_NUMBER>8 out of bounds for uint32
FAILED language/test_random.py::test_randint[4,53-67830198458-int32-False] - OverflowError: Python integer<PHONE_NUMBER>8 out of bounds for uint32
FAILED language/test_random.py::test_randint[10-67830198458-int32-True] - OverflowError: Python integer<PHONE_NUMBER>8 out of bounds for uint32
FAILED language/test_random.py::test_randint[10-67830198458-int32-False] - OverflowError: Python integer<PHONE_NUMBER>8 out of bounds for uint32
FAILED language/test_random.py::test_randint[400-67830198458-int32-True] - OverflowError: Python integer<PHONE_NUMBER>8 out of bounds for uint32
FAILED language/test_random.py::test_randint[400-67830198458-int32-False] - OverflowError: Python integer<PHONE_NUMBER>8 out of bounds for uint32
FAILED language/test_core.py::test_dot[1-128-128-64-4-True-False-none-tf32-float16-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-4-True-False-none-tf32-float16-float32-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-4-True-False-none-tf32-float32-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-4-True-False-none-tf32-float32-float32-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-4-False-True-none-tf32-int8-int8-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-4-False-True-none-tf32-int8-int8-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-2-True-True-none-tf32-float16-float16-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-4-False-True-none-tf32-float16-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-2-True-True-none-tf32-float16-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-4-False-True-none-tf32-float16-float32-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-4-False-True-none-tf32-float32-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-2-False-False-none-tf32-float16-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-2-False-False-none-tf32-float16-float32-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-2-False-False-none-tf32-float32-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-128-128-64-2-False-False-none-tf32-float32-float32-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-True-True-none-tf32-int8-int8-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-True-True-none-tf32-int8-int8-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-True-True-none-tf32-float16-float16-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-True-True-none-tf32-float16-float16-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-True-True-none-tf32-float16-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-True-True-none-tf32-float16-float32-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-True-True-none-tf32-float32-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-True-True-none-tf32-float32-float32-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-True-False-none-tf32-int8-int8-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-True-False-none-tf32-int8-int8-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-True-False-none-tf32-float16-float16-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-True-False-none-tf32-float16-float16-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-True-False-none-tf32-float16-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-True-False-none-tf32-float16-float32-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-True-False-none-tf32-float32-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-True-False-none-tf32-float32-float32-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-False-True-none-tf32-int8-int8-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-False-True-none-tf32-int8-int8-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-False-True-none-tf32-float16-float16-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-False-True-none-tf32-float16-float16-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-False-True-none-tf32-float16-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-False-True-none-tf32-float16-float32-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-False-True-none-tf32-float32-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-False-True-none-tf32-float32-float32-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-False-False-none-tf32-int8-int8-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-False-False-none-tf32-int8-int8-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-False-False-none-tf32-float16-float16-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-False-False-none-tf32-float16-float16-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-False-False-none-tf32-float16-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-False-False-none-tf32-float16-float32-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-False-False-none-tf32-float32-float32-1_0] - RuntimeError: Triton Error [ZE]: 0x70000004
FAILED language/test_core.py::test_dot[1-64-128-128-2-False-False-none-tf32-float32-float32-1_1] - RuntimeError: Triton Error [ZE]: 0x70000004

With pytorch 153362fbc9e8642fb851a4de3b99e3871a2cc714 everything above passes except some test_dot failures. If I patch the LTS bug (where I currently have pytorch setup, see #1329) then I get 10 failures with precision issues.
FAILED python/test/unit/language/test_core.py::test_dot[1-16-16-16-4-False-False-trans-tf32-float32-float32-1] - AssertionError:
Not equal to tolerance rtol=0.01, atol=0.001

Mismatched elements: 251 / 256 (98%)
Max absolute difference: 0.12260317
Max relative difference: inf
 x: array([[-0.069057, -0.069733, -0.068503, -0.010018,  0.005891,  0.006578,
         0.102589,  0.0102  ,  0.005469,  0.018078,  0.028118, -0.001133,
         0.069394,  0.000721, -0.026283,  0.024772],...
 y: array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],...
FAILED python/test/unit/language/test_core.py::test_dot[1-16-16-16-4-False-False-trans-tf32x3-float32-float32-1] - AssertionError:
Not equal to tolerance rtol=0.01, atol=0.001

Mismatched elements: 251 / 256 (98%)
Max absolute difference: 0.12267384
Max relative difference: inf
 x: array([[-0.069102, -0.069795, -0.068567, -0.010019,  0.0059  ,  0.006594,
         0.102642,  0.010193,  0.005472,  0.018109,  0.028152, -0.001136,
         0.069449,  0.000702, -0.026297,  0.024813],...
 y: array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],...
FAILED python/test/unit/language/test_core.py::test_dot[1-16-16-16-4-False-False-trans-ieee-float16-float16-1] - AssertionError:
Not equal to tolerance rtol=0.01, atol=0.01

Mismatched elements: 215 / 256 (84%)
Max absolute difference: 0.1226
Max relative difference: inf
 x: array([[-0.0691  , -0.0697  , -0.06854 , -0.009995,  0.005913,  0.00658 ,
         0.1026  ,  0.01017 ,  0.00546 ,  0.0181  ,  0.02812 , -0.001139,
         0.06946 ,  0.000687, -0.02626 ,  0.02478 ],...
 y: array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],...
FAILED python/test/unit/language/test_core.py::test_dot[1-16-16-16-4-False-False-trans-ieee-float16-float32-1] - AssertionError:
Not equal to tolerance rtol=0.01, atol=0.001

Mismatched elements: 251 / 256 (98%)
Max absolute difference: 0.1226
Max relative difference: inf
 x: array([[-0.0691  , -0.0697  , -0.06854 , -0.009995,  0.005913,  0.00658 ,
         0.1026  ,  0.01017 ,  0.00546 ,  0.0181  ,  0.02812 , -0.001139,
         0.06946 ,  0.000687, -0.02626 ,  0.02478 ],...
 y: array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],...
FAILED python/test/unit/language/test_core.py::test_dot[1-16-16-16-4-False-False-trans-ieee-float32-float32-1] - AssertionError:
Not equal to tolerance rtol=0.01, atol=0.001

Mismatched elements: 251 / 256 (98%)
Max absolute difference: 0.12267384
Max relative difference: inf
 x: array([[-0.069102, -0.069795, -0.068567, -0.010019,  0.0059  ,  0.006594,
         0.102642,  0.010193,  0.005472,  0.018109,  0.028152, -0.001136,
         0.069449,  0.000702, -0.026297,  0.024813],...
 y: array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],...
FAILED python/test/unit/language/test_core.py::test_dot[1-16-16-16-4-False-False-chain-dot-tf32-float32-float32-1] - AssertionError:
Not equal to tolerance rtol=0.01, atol=0.001

Mismatched elements: 254 / 256 (99.2%)
Max absolute difference: 0.7690249
Max relative difference: inf
 x: array([[-1.942635e-02, -2.114876e-01, -6.945647e-02, -1.716162e-01,
        -1.378054e-01, -1.165296e-01,  6.006219e-03,  1.291778e-01,
        -2.653402e-01, -1.434387e-01, -2.859902e-02,  5.359677e-03,...
 y: array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],...
FAILED python/test/unit/language/test_core.py::test_dot[1-16-16-16-4-False-False-chain-dot-tf32x3-float32-float32-1] - AssertionError:
Not equal to tolerance rtol=0.01, atol=0.001

Mismatched elements: 255 / 256 (99.6%)
Max absolute difference: 0.76983273
Max relative difference: inf
 x: array([[-1.949987e-02, -2.117989e-01, -6.951781e-02, -1.716849e-01,
        -1.379933e-01, -1.167000e-01,  5.947299e-03,  1.293094e-01,
        -2.656509e-01, -1.435804e-01, -2.856388e-02,  5.384542e-03,...
 y: array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],...
FAILED python/test/unit/language/test_core.py::test_dot[1-16-16-16-4-False-False-chain-dot-ieee-float16-float16-1] - AssertionError:
Not equal to tolerance rtol=0.01, atol=0.01

Mismatched elements: 243 / 256 (94.9%)
Max absolute difference: 0.7695
Max relative difference: inf
 x: array([[-1.9577e-02, -2.1179e-01, -6.9397e-02, -1.7163e-01, -1.3782e-01,
        -1.1664e-01,  6.0577e-03,  1.2939e-01, -2.6538e-01, -1.4355e-01,
        -2.8412e-02,  5.4092e-03,  4.2969e-02, -4.5715e-02,  3.4839e-01,...
 y: array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],...
FAILED python/test/unit/language/test_core.py::test_dot[1-16-16-16-4-False-False-chain-dot-ieee-float16-float32-1] - AssertionError:
Not equal to tolerance rtol=0.01, atol=0.001

Mismatched elements: 254 / 256 (99.2%)
Max absolute difference: 0.7695
Max relative difference: inf
 x: array([[-1.9577e-02, -2.1179e-01, -6.9397e-02, -1.7163e-01, -1.3782e-01,
        -1.1664e-01,  6.0577e-03,  1.2939e-01, -2.6538e-01, -1.4355e-01,
        -2.8412e-02,  5.4092e-03,  4.2969e-02, -4.5715e-02,  3.4839e-01,...
 y: array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],...
FAILED python/test/unit/language/test_core.py::test_dot[1-16-16-16-4-False-False-chain-dot-ieee-float32-float32-1] - AssertionError:
Not equal to tolerance rtol=0.01, atol=0.001

Mismatched elements: 255 / 256 (99.6%)
Max absolute difference: 0.76983273
Max relative difference: inf
 x: array([[-1.949987e-02, -2.117989e-01, -6.951781e-02, -1.716849e-01,
        -1.379933e-01, -1.167000e-01,  5.947299e-03,  1.293094e-01,
        -2.656509e-01, -1.435804e-01, -2.856388e-02,  5.384542e-03,...
 y: array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],...
=========================================================================================================== 10 failed, 423 passed, 162 skipped, 10310 deselected in 227.53s (0:03:47) ===========================================================================================================

I am running unpatched on LTS now to see if the usual LTS failures occur, but it's pretty slow so I will let it run overnight. I did not see too many commits in PyTorch today, but let's see what tonight's run looks like.

@pbchekin I cannot reproduce the results from CI locally:
https://github.com/intel/intel-xpu-backend-for-triton/actions/runs/9740440080/job/26877561577
=========================== short test summary info ============================
FAILED language/test_core.py::test_abs_fp8[in_dtype2] - NotImplementedError: The operator 'aten::__lshift__.Scalar' is not currently implemented for the XPU device. Please open a feature on https://github.com/intel/torch-xpu-ops/issues. You can set the environment variable `PYTORCH_ENABLE_XPU_FALLBACK=1` to use the CPU implementation as a fallback for XPU unimplemented operators. WARNING: this will bring unexpected performance compared with running natively on XPU.
FAILED language/test_core.py::test_full[shape0-uint16] - RuntimeError: "eq_xpu" not implemented for 'UInt16'
FAILED language/test_core.py::test_full[shape0-uint32] - RuntimeError: "eq_xpu" not implemented for 'UInt32'
FAILED language/test_core.py::test_full[shape0-uint64] - RuntimeError: "eq_xpu" not implemented for 'UInt64'
FAILED language/test_core.py::test_full[shape1-uint16] - RuntimeError: "eq_xpu" not implemented for 'UInt16'
FAILED language/test_core.py::test_full[shape1-uint32] - RuntimeError: "eq_xpu" not implemented for 'UInt32'
FAILED language/test_core.py::test_full[shape1-uint64] - RuntimeError: "eq_xpu" not implemented for 'UInt64'
FAILED language/test_core.py::test_full[shape2-uint16] - RuntimeError: "eq_xpu" not implemented for 'UInt16'
FAILED language/test_core.py::test_full[shape2-uint32] - RuntimeError: "eq_xpu" not implemented for 'UInt32'
FAILED language/test_core.py::test_full[shape2-uint64] - RuntimeError: "eq_xpu" not implemented for 'UInt64'

Local:
» pip freeze | grep torch
-e git+https://github.com/alexbaden/pytorch.git@75f64e12030dfa6f621f1ec2b207892cf8660cdd#egg=torch

python/test/unit/language/test_core.py::test_full[shape0-int8] PASSED                                                                                [  2%]
python/test/unit/language/test_core.py::test_full[shape0-int16] PASSED                                                                                [  5%]
python/test/unit/language/test_core.py::test_full[shape0-int32] PASSED                                                                                [  8%]
python/test/unit/language/test_core.py::test_full[shape0-int64] PASSED                                                                                [ 11%]
python/test/unit/language/test_core.py::test_full[shape0-uint8] PASSED                                                                                [ 13%]
python/test/unit/language/test_core.py::test_full[shape0-uint16] PASSED                                                                                [ 16%]
python/test/unit/language/test_core.py::test_full[shape0-uint32] PASSED                                                                                [ 19%]
python/test/unit/language/test_core.py::test_full[shape0-uint64] PASSED                                                                                [ 22%]
python/test/unit/language/test_core.py::test_full[shape0-float16] PASSED                                                                                [ 25%]
python/test/unit/language/test_core.py::test_full[shape0-float32] PASSED                                                                                [ 27%]
python/test/unit/language/test_core.py::test_full[shape0-float64] PASSED                                                                                [ 30%]
python/test/unit/language/test_core.py::test_full[shape0-bfloat16] PASSED                                                                                [ 33%]
python/test/unit/language/test_core.py::test_full[shape1-int8] PASSED                                                                                [ 36%]
python/test/unit/language/test_core.py::test_full[shape1-int16] PASSED                                                                                [ 38%]
python/test/unit/language/test_core.py::test_full[shape1-int32] PASSED                                                                                [ 41%]
python/test/unit/language/test_core.py::test_full[shape1-int64] PASSED                                                                                [ 44%]
python/test/unit/language/test_core.py::test_full[shape1-uint8] PASSED                                                                                [ 47%]
python/test/unit/language/test_core.py::test_full[shape1-uint16] PASSED                                                                                [ 50%]
python/test/unit/language/test_core.py::test_full[shape1-uint32] PASSED                                                                                [ 52%]
python/test/unit/language/test_core.py::test_full[shape1-uint64] PASSED                                                                                [ 55%]
python/test/unit/language/test_core.py::test_full[shape1-float16] PASSED                                                                                [ 58%]
python/test/unit/language/test_core.py::test_full[shape1-float32] PASSED                                                                                [ 61%]
python/test/unit/language/test_core.py::test_full[shape1-float64] PASSED                                                                                [ 63%]
python/test/unit/language/test_core.py::test_full[shape1-bfloat16] PASSED                                                                                [ 66%]
python/test/unit/language/test_core.py::test_full[shape2-int8] PASSED                                                                                [ 69%]
python/test/unit/language/test_core.py::test_full[shape2-int16] PASSED                                                                                [ 72%]
python/test/unit/language/test_core.py::test_full[shape2-int32] PASSED                                                                                [ 75%]
python/test/unit/language/test_core.py::test_full[shape2-int64] PASSED                                                                                [ 77%]
python/test/unit/language/test_core.py::test_full[shape2-uint8] PASSED                                                                                [ 80%]
python/test/unit/language/test_core.py::test_full[shape2-uint16] PASSED                                                                                [ 83%]
python/test/unit/language/test_core.py::test_full[shape2-uint32] PASSED                                                                                [ 86%]
python/test/unit/language/test_core.py::test_full[shape2-uint64] PASSED                                                                                [ 88%]
python/test/unit/language/test_core.py::test_full[shape2-float16] PASSED                                                                                [ 91%]
python/test/unit/language/test_core.py::test_full[shape2-float32] PASSED                                                                                [ 94%]
python/test/unit/language/test_core.py::test_full[shape2-float64] PASSED                                                                                [ 97%]
python/test/unit/language/test_core.py::test_full[shape2-bfloat16] PASSED                                                                                [100%]

============================================================================================================================= 36 passed, 10882 deselected in 10.13s =============================================================================================================================

It looks like the PyTorch main commit used is quite old: https://github.com/pytorch/pytorch/commit/6c503f1dbbf9ef1bf99f19f0048c287f419df600
So I tried another run with the current main, but it is failing with the same issue: https://github.com/intel/intel-xpu-backend-for-triton/actions/runs/9745777583/job/26894544049

@pbchekin I cannot reproduce the results from CI locally:

What IPEX do you have?

No IPEX, just using upstream PyTorch.

No IPEX, just using upstream PyTorch.

You should have some ipex installed - the tests have an import statement - unless you also updated the source code.

Correct, I commented out the import. 🙂

CI is using main @ pytorch/pytorch, while you are using a fork:
git+https://github.com/alexbaden/pytorch.git@75f64e12030dfa6f621f1ec2b207892cf8660cdd

Why are you using a fork instead of

CI is using main @ pytorch/pytorch, while you are using a fork:

@alexbaden it would help if in both CI and local environment we use main from pytorch/pytorch plus a number of patches that we need to apply on top of it, if necessary. The goal is to use a main PyTorch branch, not another fork.

I am not using a fork - that's just an artifact from how my git repo is setup. My origin is a fork, but the commit referenced is this one:
commit 75f64e12030dfa6f621f1ec2b207892cf8660cdd (HEAD -> main, pytorch/main)
Author: Xuehai Pan<EMAIL_ADDRESS>Date:   Mon Jul 1 13:28:37 2024 +0000

    Fix test `test_type_hints.py::TestTypeHints::test_doc_examples` (#129829)

    As per the title, this test was broken for months.

    Pull Request resolved: https://github.com/pytorch/pytorch/pull/129829
    Approved by: https://github.com/ezyang

which is latest. I am not applying any patches to pytorch and most tests are passing, except tutorial 03 which we are tracking in #1496 . I have not run all tests in the past week, but the ones that failed in the CI run are passing locally so I cannot reproduce this issue.

I am not using a fork - that's just an artifact from how my git repo is setup. My origin is a fork, but the commit referenced is this one:

OK, sounds like we cannot identify any differences between CI and you local setup. I am kind of blocked here, because I have no access to your environment, so I am not sure what to do next. Potentially you can take a fresh look to CI, make some changes to show environment details (list of installed Python, Conda, system packages, environment variables, and so on) to identify what is different. Also I think it makes sense to run all tests in your local environment.

Current status summary:
1. Preparation
1.1 Fix / implement workarounds for UT/Tutorials regressions

#581
#1496
#1787
#1855
#1769 (workaround - tolerance increase)
#1138 (workaround - apply pending PR)
#1576 (workaround - apply pending PR)
#1780 (workaround - apply pending PR)

1.2 Achieve green CI status for UT/E2E/Inductor pipelines with the upstream PyTorch main branch codebase plus pending PR's applied and change CI defaults

#1563
#1627
#1836
#1893
#1851
#1852
#1898
#1908 (optional)

1.3 Update local build and test scripts

#1823
#1894
#1892
#1912

1.4 Pinned pytorch commit_id support and process / tools to update it regularily

#1577
#1719
TBD

2. import intel_extensions_for_pytorch deprecation in codebase
2.1 UT and Tutorials

#1854

2.2 Benchmarks

#1911

3. Local scripts and CI workflows clean up
3.1 Local scripts

TBD

3.2 CI

TBD

*4. Packaging and interop
4.1 PyTorch nightly

#1913
TBD

4.2 PyPI

#1449
TBD

4.3 Interop

TBD

5. Developer / User documentation update and UX improvements
5.1 Documentation

#1814
#1815
#1910
TBD

5.2 Runtime checks

#1817
#1914
TBD


Feature Request: SceneSystem Service

Describe the problem
Unity suggests using a base manager scene and additively loading / unloading content on top of that. In theory we recommend this approach but in practice our story is muddled.
Describe the solution you'd like
A SceneSystem core service to facilitate scene loading and unloading.

Additive scene loading will be as simple as passing a scene name or names to an async method.
‘Single’ scene loading will mimic Unity’s single scene loading – just pass a scene name and all current scenes will be automatically unloaded.
You will be able to control which scenes are required to have an MRTK instance and which aren’t.
You will be able to open / play multiple scenes (with multiple MRTK instances) in the editor.
The service will help you spot and automatically resolve common mismatches between scene settings (lighting, navmeshes, etc.)
Like all services, the scene system can be disabled and devs can use Unity’s SceneManager exclusively, if desired.

Describe alternatives you've considered
Updating our docs with detailed guidance and leaving it to devs to implement their own solutions.
Additional context
Initial Proposal: #3987
Related PRs: #4047, #4035, #3890, #3961

Interesting. Out of curiosity, how would I actually load a second scene today, with MRTK. I've tried using SceneManager.LoadScene but that causes many null pointer errors. See my comments in PR #4035 to illustrate how I tried switching scenes while in Unity play mode, and the errors that I hit.

Right now there's no way to do it that doesn't cause problems. We've been attacking separate issues one-by-one (eg the camera cache fix) and there are still more to go (like the ones you list in your comments). The plan is to fix those issues individually and marge them into mrtk_development before this service is released.


Missing interactions in v3.0

I initially noticed that we were missing interactions based on comparing numbers from v2.0 to v3.0. Specifically, I noticed that Clearity Foundation: Biomarkers, Clearity Foundation: Clinical Trials, GTP: Interactions, My Cancer Genome: Clinical Trials, and The Druggable Genome: Clinical Trials were down in their interaction_claims_count by  1%, 58%, 7%, 83%, 16% respectively.
So through digging through the commit logs, it looks like some claims were initially lost with data subrepo commit
Author: Alex H. Wagner<EMAIL_ADDRESS>Date:   Wed Jul 27 21:43:24 2016 -0500

    dump of local db after import and grouping```

However, it seems that most of the missing claims become absent in the data.sql file following the data subrepo commit
```commit 003505559bdc699204681d54ebdcdd3e2e35ba6f
Author: Susanna Kiwala<EMAIL_ADDRESS>Date:   Fri Mar 10 11:43:17 2017 -0600

    Dump of local db after creating interactions```

Looking back on that date (March 10th), that is when PR#126 was merged which is related to the interaction table and the interaction grouper.

The good news is that we have all of the interaction TSVs for these sources except The Druggable Genome: Clinical Trials. For the sources we have TSVs for, we will update these sources for v3.0.

(GTP: Interactions will not be updated through this issue as an online importer is in the works in issue #148)

Branch backup-v2 adds functionality to restore any source from DGIdb v2. On doing so, I noted that the observed reduction in interaction claims is due to the database constraints created by @susannasiebert requiring interaction claims to be unique. I have restored each of the aforementioned sources, and found that our counts from each are consistent with our current, live database after collapsing redundant interaction claims.

closed in 414e6bfdd250630f772a766853e2b4c0714bbada


Error trying to run Metaworld environment

I am trying to run the Metaworld benchmark as the simulation environment since we don't have access to the same robots. On running the below command, we get the following error:
python train_robot.py agent=bc suite=metaworld  num_demos=2

workspace: /Users/varunagrawal/FISH-Workspace/FISH/FISH/exp_local/2024.03.30/050345_exp_metaworld_pixels_drawer-close-v2_seed_2
Error executing job with overrides: ['agent=bc', 'suite=metaworld', 'num_demos=2']
Traceback (most recent call last):
  File "/Users/varunagrawal/.pyenv/versions/3.10.12/lib/python3.10/site-packages/hydra/_internal/instantiate/_instantiate2.py", line 92, in _call_target
    return _target_(*args, **kwargs)
  File "/Users/varunagrawal/FISH-Workspace/FISH/FISH/suite/metaworld.py", line 347, in make
    env = RGBArrayAsObservationWrapper(env, ml1, max_path_length=MAX_PATH_LENGTH[name], camera_name=CAMERA[name])
  File "/Users/varunagrawal/FISH-Workspace/FISH/FISH/suite/metaworld.py", line 51, in __init__
    dummy_obs = self.get_frame()
  File "/Users/varunagrawal/FISH-Workspace/FISH/FISH/suite/metaworld.py", line 118, in get_frame
    frame = self._env.render(offscreen=True, camera_name=self.camera_name)
TypeError: MujocoEnv.render() got an unexpected keyword argument 'offscreen'

I can't find anything about the parameters offscreen and camera_name in the Mujoco documentation, and it fails to work for both Mujoco version 2.3.7 and 3.1.3.
On removing the parameters, I get the error
Error executing job with overrides: ['agent=bc', 'suite=metaworld', 'num_demos=2']
Traceback (most recent call last):
  File "/Users/varunagrawal/.pyenv/versions/3.10.12/lib/python3.10/site-packages/hydra/_internal/instantiate/_instantiate2.py", line 92, in _call_target
    return _target_(*args, **kwargs)
  File "/Users/varunagrawal/FISH-Workspace/FISH/FISH/suite/metaworld.py", line 364, in make
    env = RGBArrayAsObservationWrapper(env,
  File "/Users/varunagrawal/FISH-Workspace/FISH/FISH/suite/metaworld.py", line 58, in __init__
    dummy_obs = self.get_frame()
  File "/Users/varunagrawal/FISH-Workspace/FISH/FISH/suite/metaworld.py", line 128, in get_frame
    frame = self._env.render()
  File "/Users/varunagrawal/.pyenv/versions/3.10.12/lib/python3.10/site-packages/gymnasium/envs/mujoco/mujoco_env.py", line 409, in render
    return self.mujoco_renderer.render(
  File "/Users/varunagrawal/.pyenv/versions/3.10.12/lib/python3.10/site-packages/gymnasium/envs/mujoco/mujoco_rendering.py", line 646, in render
    viewer = self._get_viewer(render_mode=render_mode)
  File "/Users/varunagrawal/.pyenv/versions/3.10.12/lib/python3.10/site-packages/gymnasium/envs/mujoco/mujoco_rendering.py", line 688, in _get_viewer
    raise AttributeError(
AttributeError: Unexpected mode: None, expected modes: human, rgb_array, or depth_array

The above exception was the direct cause of the following exception:

Moreover, I have downloaded the expert demonstrations for Metaworld, but the README doesn't specify where to place them.
Can you please provide more detailed instructions on how to get the example up and running?
On a more general case, I would like to understand what is happening in terms of the gym environments. I may not be familiar with this, but are you using the gym environments as a sort of virtual world for your real robot setup? My understanding of the code seems to indicate that code for the Hello, Allegro and xARM are all developed to operate on the real robot hardware, so how the gym environments fit in is a bit of a mystery to me.
@siddhanthaldar @jyopari tagging for attention.

I have encountered the same problem as you. Have you solved it?

Hi,
Apologies for not responding earlier. This issue has resulted from changes in Metaworld since this work was released. An easy way to fix this would be to set up Metaworld using our newer work, BAKU.
Regarding the gym environments, you are correct that we use gym as an interface to create environments for the real robot similar to existing simulation environments (with reset, step and render functionalities). This allows us to use similar suite scripts for the simulation and real environments.
Hope this helps! Let me know if you have any other questions.


Template loaded from package.json : variables to partials

How to pass data from CLI configured package.json to partials ?
package.json
    "scripts": {
        "build": "mustache ./assets/json/data.json -p ./src/partials/main.mustache -p  ./src/index.mustache > ./src/index.html"
    },

partial reference:
{{> navigation listVariable}}

Hi @danielfagerstrom,
I noticed from your initial issue description, that it seemed like you were trying to send arguments to partials in a props-like manner which one often sees in React.js components and similar. In short, passing explicit arguments like that is not supported by mustache's partials.
Personally like the description found in the official mustache docs about partials:

.. you may want to think of partials as includes, imports ..

This resonates to me in the way that the partials get a hold of the same variables that are available where the partials are being used.
When trying to create a re-usable partial which iterates through an array of items, this can look a little weird at first due to the hash-period-combination {{#.}} ... {{/.}}, it just takes time getting used to reading or else it can be improved by restructuring the data passed into the template for rendered a bit.
Here's how using such a partial would look like conceptually:
const template = `

    {{#competitionList}}
      {{> select }}
    {{/competitionList}}

    {{#seasonList}}
      {{> select }}
    {{/seasonList}}

`

const selectPartial = `
  <select class="mmgr-select">
    {{#.}}
      <option class="mmgr-select__item" value="{{value}}">{{text}}</option>
    {{/.}}
  </select>
`

const output = Mustache.render(template, data, { select: selectPartial })

I created a jsfiddle for a complete example: https://jsfiddle.net/ks7q06yf/7/. It looks a little different since this example runs in the browser, rather than via the CLI, but the template & partial contents is still the same between the two.
Shout if you're still not able to make that work for you.

Thank you very much Phillip Johnsen, your explanation and example ensured what I realized after reading the library code.
From the way I see and as I can only use the CLI, better to skip generic components and if I need to do some data transformation or special selection on the data, I run a nodeJS script before.
Thank you very much for your time and help.
Kind regards,
Daniel Santana


feat(llms): add support for vLLM

Hello langchain maintainers,
this PR aims at integrating vllm into langchain. This PR closes #8729.
This feature clearly depends on vllm, but I've seen other models supported here depend on packages that are not included in the pyproject.toml (e.g. gpt4all, text-generation) so I thought it was the case for this as well.
@hwchase17, @baskaryan

Hi @hwchase17, thanks for your review. I've just added one. Not sure why one of the workflows have failed, it seems like it failed while setting up python 3.11.

Thanks for approving! Not sure why one the checks failed though.


Prefer public function to dispose kotlin compiler context

instead of reflection

@bot-gradle test this

OK, I've already triggered ReadyForMerge build for you.

@bot-gradle test this

OK, I've already cancelled the old build and triggered a new ReadyForMerge build for you.

Thanks Paul, I noticed this recently and forgot to ask if this could be removed.


chore(deps): upgrade dependencies

Upgrades project dependencies. See details in workflow run.

Automatically created by projen via the "upgrade-main" workflow

SonarQube Quality Gate Result

Result: :white_check_mark: OK
Triggered by @zxkane on pull_request

Metric
Status
Value
Error Threshold

Reliability rating
:white_check_mark: OK
1
> 1

Security rating
:white_check_mark: OK
1
> 1

Sqale rating
:white_check_mark: OK
1
> 1

Coverage
:white_check_mark: OK
91.10
< 80

Duplicated lines density
:white_check_mark: OK
0
> 30

Blocker violations
:white_check_mark: OK
0
> 0

Bugs
:white_check_mark: OK
0
> 0

Code smells
:white_check_mark: OK
0
> 40

Critical violations
:white_check_mark: OK
0
> 0

Major violations
:white_check_mark: OK
0
> 0

Vulnerabilities
:white_check_mark: OK
0
> 0

View on SonarQube
updated: 9/23/2024, 00:17:50 (UTC+0)

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The following metrics might not affect the Quality Gate status but improving them will improve your project code quality.
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Apply transforms and digest calculations to copies of root. Closes #125.

This PR is my attempt at fixing issue #125.
This commit includes a few things:

An XMLSigner-derived object to generate the test case of an XML signature that is both enveloped and enveloping;
A sample signed XML file generated with the above, that triggers bug #125;
A test to verify that the sample XML file can be verified successfully;
My attempt at actually fixing the issue in XMLVerifier;

I believe part 3 could stand from being better integrated with the other tests, but I am not sure how to proceed about that.

Codecov Report

Merging #126 into master will decrease coverage by 0.47%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master     #126      +/-   ##
==========================================
- Coverage   94.89%   94.42%   -0.48%
==========================================
  Files           3        3
  Lines         588      592       +4
==========================================
+ Hits          558      559       +1
- Misses         30       33       +3

Impacted Files
Coverage Δ

signxml/__init__.py
93.98% <100%> (-0.65%)
:arrow_down:

Continue to review full report at Codecov.

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Thank you for the thorough explanation of the issue you are facing and the PR. The code looks good, although ideally there would be an inline comment explaining why the root is copied, and a little bit less boilerplate in the file test/generate_125_example.py. I will address those minor issues later. There will be a bit of a delay before I release this. Thanks again for your contribution.


A connection to https://... was leaked. Did you forget to close a response body? And Is download file running in  background ?

When I download a file with Fetch. I didn't set custom okhttpclient
    if (fetch == null){
        FetchConfiguration fetchConfiguration = new FetchConfiguration.Builder(DictBoxApp.getInstance().getApplicationContext())
                .setDownloadConcurrentLimit(3)
                .build();

        fetch = Fetch.Impl.getInstance(fetchConfiguration);
    }

fetch.enqueue(request, new Func() {
@Override
public void call(@NotNull Request updatedRequest) {
                }
            }, new Func<Error>() {
                @Override
                public void call(@NotNull Error error) {
                    Log.d("error","download_file:"+ error.toString());
                }
            });

@phukhanhlee Fetch does perform the downloads on a background thread. If you need Fetch to continue downloads when the application closes, you will need to create a service or use the new Work Manager.
Also for A connection to https://... was leaked can you replicate and show the logs or sample code???


[Feature Request] Provide the ability to choose the "size" of the test engines instances

Is your feature request related to a problem? Please describe.
Some load tests are pretty extensive requiring great amount of memory/cpu. Currently we have a pool of azure virtual machines (size Standard F32s, 32 vcpu, 64 GiB memory) that we use in our load testing.
Describe the solution you'd like
The user should have the ability to choose the size (in terms of virtual cpus and memory) for the underlying test engines. This configuration could be specified when provisioning the Azure Load Testing resource, or it could be a configuration on the test level.
The available sizes could be subset of the available azure VM sizes (https://docs.microsoft.com/en-us/azure/virtual-machines/sizes).
Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.-
Additional context
Add any other context or screenshots about the feature request here.
AB#1614841

@mmosallem Thanks for reaching out. We will add this to our roadmap to support multiple configurations of VMs and provide the choice.

I'd like to upvote this enhancement. Same with what was mentioned in the original description. We use higher sku to run our load test. And having the option of higher sku option helps in reducing the amount of IPs needed when running a load testing via ALTS.


markdown

[x] Turn on GitHub Pages
[ ] Outline my portfolio
[ ] Introduce myself to the world

[ ] Turn on GitHub Pages
[ ] Outline my portfolio
[ ] Introduce myself to the world


onMouseMove listener not removed when element is disabled while mouse button is pressed

This is potentially related to #731.  The mousedown event handler adds mousemove and mouseup listeners when the mouse button is pressed.  Those are both typically removed when the mouse button is released (in the mouseup handler).
However, if the mouse button is still being held down when the element is disabled, those nested mousemove and mouseup event listeners are never removed.  This causes an endless stream of "element not enabled" exceptions for every mouse movement when it tries to call cornerstone.pageToPixel(element, e.pageX, e.pageY) since element is no longer enabled.
We are seeing this occasionally when a user happens to press their mouse button on a canvas just prior to using a keyboard shortcut that causes the canvas to be destroyed.
I'll see if I can come up with a PR soon.

:tada: This issue has been resolved in version 5.1.4 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


#22685 do not search objects by ID with nullable monitor

[x] check the case from the ticket
[x] check different object types opening (tables/views, etc.) from the navigator tree
[x] check different object types creation (views/sequences, etc. (random 3 objects)) from the navigator tree

verified


unsigned order modal BUY color is wrong

notice the BUY is same color as SELL, it should be green. see correct color in _colors...

this has been fixed, closing


POP object query

Hi,
1st of all thank you for such a great tool!
My question is around POP grouping, is it possible (I guess this is a feature request) to make it upper case? All of my devices are lower case and POP name is last three characters (vs example) or maybe even override this behaviour with own names?
Thank you.

Hi,
I think the easiest way would be text-transform in CSS. To transform upper cases to lower for example:
--- a/example/style.css
+++ b/example/style.css
@@ -9,6 +9,7 @@
   stroke: #fff;
   stroke-width: 1.5px;
 }
+.group text { text-transform: lowercase; }

 .node text { font-size: 10px; }

Or you can override pop names with rendered callback:
--- a/example/index.html
+++ b/example/index.html
@@ -11,7 +11,14 @@

I have no plan to implement this pop name translation feature in inet-henge for now, but it should be still easy to do that outside of the library.


Lint, Type Check & Test on CI

Maybe we could use Github actions ?

I suppose TravisCI and other related tools will be good enough


When opening a pptx file, it prompts that there is a problem with the content and needs to be repaired.

Describe the bug
When opening a pptx file, it prompts that there is a problem with the content and needs to be repaired.
Screenshots

To Reproduce
Only insert a slide into the target file.
Steps to reproduce the behavior:
Run the program and open the output file
Observed behavior
PowerPoint found a problem with content in c:..\bin\Debug\net6.0\abc_copy.pptx.
PowerPoint can attempt to repair the presentation.
Expected behavior
A clear and concise description of what you expected to happen.
Desktop (please complete the following information):

OS: [Windows]
.NET Target: ( .NET Core NET6.0)
DocumentFormat.OpenXml Version: (3.0.0)

Additional context
using DocumentFormat.OpenXml;
using DocumentFormat.OpenXml.Packaging;
using DocumentFormat.OpenXml.Presentation;

var pathfile = AppDomain.CurrentDomain.BaseDirectory + "abc.pptx";
var destinationFilePath = AppDomain.CurrentDomain.BaseDirectory + "abc_copy.pptx";

using (PresentationDocument sourcePresentation = PresentationDocument.Open(pathfile, false))
{
    using var mStream = new MemoryStream();
    PresentationDocument destinationPresentation = PresentationDocument.Create(mStream, PresentationDocumentType.Presentation);

    foreach (var part in sourcePresentation.Parts)
    {
        destinationPresentation.AddPart(part.OpenXmlPart, part.RelationshipId);
    }

    PresentationPart? presentationPart = destinationPresentation.PresentationPart;
    if (presentationPart is not null && presentationPart.Presentation is not null)
    {
        Presentation presentation = presentationPart.Presentation;

        if (presentation.SlideIdList is not null)
        {
            //presentation.SlideIdList.AppendChild(new SlideId() { Id = (uint)234533, RelationshipId = "r_rid1" });
            List<string> titlesList = new List<string>();
            var len = presentation.SlideIdList.Elements<SlideId>().Count();
            var slideIdList = presentation.SlideIdList.Elements<SlideId>()?.ToList() ?? new List<SlideId>();
            for (int i = 0; i < len; i++)
            {
                var slideId = slideIdList[i];
                if (slideId.RelationshipId is null)
                {
                    continue;
                }
                SlidePart slidePart = (SlidePart)presentationPart.GetPartById(slideId.RelationshipId!);
                if (slidePart is null)
                {
                    throw new ArgumentNullException("presentationDocument");
                }
                //copy slide part
                SlidePart newSlidePart = presentationPart.AddNewPart<SlidePart>();
                newSlidePart.FeedData(slidePart.GetStream());
                newSlidePart.AddPart(slidePart.SlideLayoutPart);

                slideId.InsertAfterSelf<SlideId>(new SlideId() { RelationshipId = presentationPart.GetIdOfPart(newSlidePart) });
            }
        }
    }
    destinationPresentation.Save();
    File.WriteAllBytes(destinationFilePath, mStream.ToArray());
}

abc.pptx
abc_copy.pptx

@HanJason If your goal is to insert a new slide or even to copy the existing slide, it will have to have a unique slide id and relationship id. The diff between your original and the new presentation show:
Original
  <p:sldIdLst>
    <p:sldId id="260" r:id="rId2"/>
    <p:sldId r:id="R4ce3bde4cfff4c72"/>
  </p:sldIdLst>

New
  <p:sldIdLst>
    <p:sldId id="260" r:id="rId2"/>
    <p:sldId id="256" r:id="rId3"/>
  </p:sldIdLst>

That would be a starting point.


Typo in AZFWMigrationScript.ps1 + not working for IPGroups

[Enter feedback here]
There is a typo in the AZFWMigrationScript.ps1 migration script (line 113):
$rc.Pl.llriority -> $rc.Priority
I also noticed the script will fail for rules that contain an IPGroup as source:
New-AzFirewallPolicyNetworkRule : Cannot validate argument on parameter 'SourceAddress'. The argument is null, empty, or an element of the argument collection contains a null value.

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 221eeaea-6a19-e748-45d4-3376e211f02f
Version Independent ID: de9899e9-2b26-7c6a-6b67-00a232e81d97
Content: Migrate Azure Firewall configurations to Azure Firewall policy using PowerShell
Content Source: articles/firewall-manager/migrate-to-policy.md
Service: firewall-manager
GitHub Login: @vhorne
Microsoft Alias: victorh

@iisworks, Thanks for reaching out. We will investigate and update this thread.

@iisworks, Appreciate your patience. The doc has been edited accordingly and it would take some time for the changes to get reflect over the doc.
We are closing this issue for now. If there are further questions regarding this matter, please reply and we will gladly continue the discussion.


src/objects/oo/zcl_abapgit_oo_class.clas.abap deserialize_source BUG?

Hi,
I'm looking at the implementation of zif_abapgit_oo_object_fnc~deserialize_source and I can't help but notice, that parameter it_source passed to update_full_class_include at line 778 contains the source code of the last method, or the private section if no methods exist.
Not sure what impact this has, since appartenly everything works, but I can't see any scenarios where generating an include with a random piece of code makes any sense.
Or am I wrong?
kind regards,
Jacek

Sorry, I'm just dumb :D

No worry. It happens to all of us when looking at code for too long. 😉


Possible mismatching max_length and max_new_tokens in example eval script

I was running the polygraph_eval with this example config https://github.com/IINemo/lm-polygraph/blob/main/examples/configs/polygraph_eval_wmt14_ende.yaml
I got a warning about too long string
It didn't failed but i almost sure it would mess up with the results

My wild guess is that stat calculators max_lengths in not connected to max_generated_tokens in ue manager itself. But i didn't really look into it for now

Also, wonder why we switching from max_new_tokens to just max_tokens here
https://github.com/IINemo/lm-polygraph/blob/00851972311db837de6358c90dac65616495d4de/src/lm_polygraph/utils/model.py#L69

Also, wonder why we switching from max_new_tokens to just max_tokens here
https://github.com/IINemo/lm-polygraph/blob/00851972311db837de6358c90dac65616495d4de/src/lm_polygraph/utils/model.py#L69

Probably to comply with openAI API format? @cant-access-rediska0123 can you comment on that?

I was running the polygraph_eval with this example config https://github.com/IINemo/lm-polygraph/blob/main/examples/configs/polygraph_eval_wmt14_ende.yaml
I got a warning about too long string
It didn't failed but i almost sure it would mess up with the results
My wild guess is that stat calculators max_lengths in not connected to max_generated_tokens in ue manager itself. But i didn't really look into it for now

I'm pretty sure this is due to this line here:
https://github.com/IINemo/lm-polygraph/blob/main/src/lm_polygraph/utils/model.py#L166
For some we reason we set a very low limit on the input sequence length, which triggers the warning during generation. It doesn't fail though, because in reality the model (Llama2 for example) is capable of handling much longer sequences than measly 256 tokens.
Not sure why we even set this value, probably should remove it, along with all other code for loading and configuring whitebox models.

@rvashurin check please


Cannot compare/create pr to the root repo from a fork

Description
I can compare branches in the fork, but as soon as I try to compare to the root repo, I get a HTTP500 error.
Even with the log level set to "debug" and the run mode set to "dev", the only log output i get is:
.../web/repo/compare.go:538:ParseCompareInfo() [E] GetCompareInfo: exit status 128 - fatal: failed to read object 6103d84784ccd1968f25855bc74d70f4ffbb4621: Invalid argument
Gitea Version
1.16.8
Can you reproduce the bug on the Gitea demo site?
No
Log Gist
No response
Screenshots
No response
Git Version
git version 2.25.1
Operating System
Linux xxxx 5.4.0-121-generic Ubuntu
How are you running Gitea?
Self hosted on Ubuntu Server using systemd and the package downloaded from your Website
Database
MySQL

I cannot reproduce on the main branch now. So let's close it.


Unable to build k3s

Describe the bug
When attempting to add the k3s package, it fails to build.
To Reproduce
Steps to reproduce the behavior:

add pkgs.k3s to environment.systemPackages
run nixos-rebuild switch

Expected behavior
k3s should build and be available in the system.
Additional context
Relevant build output:
# nixos-rebuild switch
...
copying path ...
...
building '/nix/store/0hcyj55rrkym2fqiin25wr86gihxawwb-k3s-build-1.drv'...
unpacking sources
unpacking source archive /nix/store/h9l4nphzq7jxyyjdbz58nid493631zq9-k3s
source root is k3s
patching sources
applying patch /nix/store/01wlfk4nsaslcj3j63y9bk1wqrvk8h0d-00-k3s.patch
patching file main.go
patching file scripts/build
patching file scripts/package-cli
configuring
building
/build/go/src/github.com/rancher/k3s /build
patching script interpreter paths in ./scripts/build ./scripts/version.sh
./scripts/build: interpreter directive changed from "/bin/bash" to "/nix/store/ffli6m23501dkiznwlkf6n4xvrj02snr-bash-4.4-p23/bin/bash"
./scripts/version.sh: interpreter directive changed from "/bin/bash" to "/nix/store/ffli6m23501dkiznwlkf6n4xvrj02snr-bash-4.4-p23/bin/bash"
++ dirname ./scripts/build
+ cd ./scripts/..
+ . ./scripts/version.sh
++ TREE_STATE=clean
+++ git status --porcelain --untracked-files=no
./scripts/version.sh: line 4: git: command not found
++ '[' -n '' ']'
+++ git log -n3 '--pretty=format:%H %ae'
+++ grep -v ' drone@localhost$'
+++ cut -f1 '-d '
./scripts/version.sh: line 9: git: command not found
+++ head -1
++ COMMIT=
++ '[' -z '' ']'
+++ git rev-parse HEAD
./scripts/version.sh: line 11: git: command not found
++ COMMIT=
build failed in buildPhase with exit code 127
To attach install cntr and run the following command as root:

   cntr attach -t command cntr-/nix/store/aah1gghirm35591lgpj6nnviqp2xs9iy-k3s-build-1

Metadata
these paths will be fetched (0.05 MiB download, 0.28 MiB unpacked):
  /nix/store/qr6dpv0wl37p00rdj5pijn1mkz0wfkwd-bash-interactive-4.4-p23-dev
copying path '/nix/store/qr6dpv0wl37p00rdj5pijn1mkz0wfkwd-bash-interactive-4.4-p23-dev' from 'https://cache.nixos.org'...
 - system: `"x86_64-linux"`
 - host os: `Linux 5.5.15, NixOS, 20.09pre220429.9b0d2f3fd15 (Nightingale)`
 - multi-user?: `yes`
 - sandbox: `yes`
 - version: `nix-env (Nix) 2.3.3`
 - channels(ngerstle): `"home-manager"`
 - channels(root): `"nixos-20.09pre220429.9b0d2f3fd15, nixos-20.03-20.03beta1155.29eddfc36d7"`
 - nixpkgs: `/nix/var/nix/profiles/per-user/root/channels/nixos`

Maintainer information:
# a list of nixpkgs attributes affected by the problem
attribute:  nixpkgs.k3s (k3s)

ping @euank - any thoughts?

Hey @ngerstle, the original derivation I merged had some issues, which I fixed in https://github.com/NixOS/nixpkgs/pull/84384.
It looks like you're on nixpkgs commit 9b0d2f3fd15, which doesn't have the fix yet, only the original broken derivation.

Ah- didn't see that see the details there, my bad.
Thanks!

Totally understandable; I'm hoping hydra gets a new unstable channel built soon so it's not in this broken state too long!


python (v2) azure function stopping execution without proper completion without failing (host stops)

My Azure Function using Python (V2 programming model) is in consumption plan. It is a synchronous script that is triggered by a schedule (cron). It is supposed to execute 5 different calls to an API (using requests) to get some data, and write the responses in the blob storage.  The function executes initially 1 or 2 or 3 calls, and each time it writes the results to the blob, however it then suddenly stops without a clear "failure" or "exception" (the host instance stops) and starts all over again with the new invocation ID (and the new host instance starts). After few cycles like that the function eventually executes the expected number of API calls. I initially expected that this issue is related to timeout but the entire execution happens in seconds.
By the way, I am using synchronous processing as I assume Python deployment is single thread, and I expect function to be executed sequentially statement after statement etc.
Investigative information
Please provide the following:

Timestamp: datetime(2023-04-06T05:15:31)
Function App version: 4 in Python programming model v2
Invocation ID:  (see below)
Region: West Europe

| invocation id | host instance id
-- | -- | --
last incomplete invocation | 501d84a1-8d2d-4926-ab33-048741b94068 | 7d9fd8ed-e770-4357-b214-b88cc9cab14f
first next complete invocation | 815b40b1-8d34-48d2-956f-6663223ce8d9 | 71b25cce-d84d-47cb-9b6d-4cb11cfdce6e
Please let me know if you would rather have newer events.
Expected behavior
Function executes fully i.e. makes 5 API calls and does 5 writes to blob before completing the execution.

Thanks for informing will check and update you


Opened Traces selection unnecessarily opens traces in trace-server

With the latest changes, the 'Opened Traces' widget in the Trace Viewer view will show the list of every trace that has ever been opened in the trace server (using 'Open With > Trace Viewer' menu in Explorer or 'Open Trace' dialog in Trace Viewer) and that has not been deleted. When a trace tab is closed, the trace remains opened in the trace-server and still appears in the 'Opened Traces' widget. But after a trace-server restart, the trace may be closed in the trace-server and it will still appear in the client.
Whenever the selection changes in the 'Opened Traces' widget, the list of available analyses for this trace is fetched from the trace-server. If the trace is closed in the trace-server, it will be opened automatically to be able to respond to the request.
This means that, even if all the trace tabs are closed in the client, navigating up and down in the 'Opened Traces' list will create trace instances in the trace-server and use up memory resources.
It is possible for the client to know that the trace is closed in the trace-server by examining the 'indexingStatus' in the Experiment model (RUNNING/COMPLETED/CLOSED). But note that following a trace-server restart, the status could be CLOSED even if the trace tab is still opened. Maybe the available analyses should still be fetched in this case.
After closing a trace tab, the trace could still be opened in the trace-server and this will be indicated in the Experiment model. Should the 'Available Analyses' widget still be filled in this case? Or should it be filled only when the trace tab is opened?

After closing a trace tab, the trace could still be opened in the trace-server and this will be indicated in the Experiment model. Should the 'Available Analyses' widget still be filled in this case? Or should it be filled only when the trace tab is opened?
This is not an issue anymore. The current behavior is that the list of "Available views" is cleared when no trace tab is open.

@PatrickTasse  do you want to close this ticket?
You could close this one and spawn a new ticket about freeing trace resource on the server when the trace tab is closed. Either by command or the server could free the resources if not used for a long time automatically and re-open the trace if queried again.

Will it be fixed by #1033?


Allow anonymous users to export search results to CSV

Is your feature request related to a problem? Please describe.
In DSpace 6 it was possible for users to export search results to CSV. As of DSpace 7 this is only possible for administrators, perhaps because of limitations in the way Angular interacts with the REST API to create processes.
Describe the solution you'd like
Allowing users to export search results as CSV is important for librarians, researchers, and more. Furthermore, it is important for reproducibility, for example in the case of systematic literature reviews where you must specify the search terms used when registering the protocol.
Describe alternatives or workarounds you've considered
A workaround for advanced users familiar with DSpace advanced search syntax (and boolean search in general) would be to use the REST API directly to retrieve results in JSON.
For example, an advanced search and equivalent REST API search that both return the same number of results:

Advanced search with facet filters: https://demo.dspace.org/search?query=&f.entityType=Publication%2Cequals&spc.page=1&f.dateIssued.min=2012&f.dateIssued.max=2023
Equivalent REST API search: https://demo.dspace.org/server/api/discover/search/objects?query=dspace.entity.type%3APublication AND dc.date.issued%3A[2012 TO 2023]

The user must not only be familiar with advanced search syntax, but also the DSpace REST API, JSON, metadata fields, URL encoding, and more.
Additional information

There is a concern that CSV export can produce a large number of results and cause the server to hang — https://github.com/DSpace/DSpace/issues/9399

I agree this would be a nice feature.  However, it would rely on a way to allow anonymous uses access to Processes in the User Interface (as this export is triggered via a Process).  This may be complex to achieve unless we figure out a different way for the export to occur for anonymous users.
Another option is to consider allowing this feature for registered users only and then finding a way to allow all logged in users to access Processes.
Overall, I like the idea.  I'm just pointing out that this is very complex to achieve using the current Processes approach.

Hi, we have developed a variation (for Dspace 7.6) for logged-in users.
Description follows:

User Type Check:
Implemented a method to check if the user is an administrator or logged-in. This determines whether the search results export button is displayed or not.
Administrators have full access, while logged-in users can download only the exportmetadata processes.

Backend Processes:
When starting the export process, the user type is checked.
If the user is an administrator, he has all privileges. If he is logged-in, he can only access the metadata-export-search script.

Metadata Download Configuration:
In the file that configures the download of metadata records, it is checked if the user is an administrator.
If he is an administrator, all records are exported; if not, the export is limited to 500 records (configurable)

Frontend Changes:
Modified  the permissions in the frontend so that registered users can see the export button, which was previously reserved only for administrators.


streams dependency was moved into ember-htmlbars

This fixes the issue mentioned by @thousand here. Maybe it'd be a good idea to refer to a specific Ember.js commit when installing Ember?

Nvm, I guess I'll just use Ember 2.6 beta as mentioned here.

I think your change is will be appropriate eventually, maybe when the current canary becomes beta. If this is going away from ember-metal, which is likely since it's in the canary, then this would be needed long term.

@nathanhammond mentioned an appropriate fix before, https://github.com/ember-a11y/ember-a11y/commit/8d35e3755f79d2d8c9249fe747f600f61a4fadb1
should do it in that way i bet.

It is only a temp fix anyways. In the long run, ember-htmlbars package will be going away completely. The implementation of read is like 2 lines, if we need it we should just inline it.


Exclude Spring 4.X dependency

Exclusion of Spring 4.X transitive dependencies from Spring-Retry
#719

... and cherry-picked to 2.1.x and 2.0.x.
@fabienmifsud ,
Thank you for the contribution!


Add DNS protocol support to packetgen/udp jobs

@Arriven is still relevant? if yes, could add a bit more details, thanks.

@alexdanger yes, it's still relevant in terms of packetgen. That module is intended to be able to generate any kind of network packets based on the configuration and it would be good to add support of various protocols to it. See https://pkg.go.dev/github.com/google/gopacket/layers#DNS for DNS reference of gopacket/layers which I use for tcp/udp/ip/ethernet frames generation. There's also a task to add icmp support there (ideally v6) #360


Find keywords using perfect hashing

This updates the keyword lookup algorthm to use the phf crate.
This is one possible approach to solving #1588 at the cost of pulling in a new dependency on phf. I will note that phf is rather small and is being used in a no_std configuration, but it is a new dependency which may be enough to not go this route.
Local measuring with the sqlparser_bench shows roughly a 5% speedup. I'll open a second PR for comparison with my other approach to just scope the binary search to words starting with the same first letter.

Also an open question regarding maintenance of the phf crate https://github.com/rust-phf/rust-phf/issues/318
It does appear to be relatively stable, most of the open issues appear to be feature requests and enhancements rather than fixes.

Marking as draft as I think this PR is no longer waiting on feedback. Please mark it as ready for review when it is ready for another look


Merge pull request #977 from alibaba/dev

0.7.0-release

This PR/issue doesn't received response since Weex migrated to Apache two years ago and this repository is no longer active yet.
Feel free to ask question in new repository and thanks for your contribution.


Check how rem work in practice

We need to modify root font size and check how interface reacts to changes.
Rems are used inconsistently and I anticipate they will break something or simply not work where expected.

[ ] Add root size select component to some page. Provide several sizes for everything to look fine.

Seems like everything is fine.


As a user, I want to view a page for content from ECCO in Gale Primary Sources by clicking its thumbnail or page number in a search result so that I can quickly and easily see my search result in its full context.

testing notes
Use keyword search and to get page matches and test clicking on both thumbnail image and page number (they should work the same). Test that it works correctly for both Gale and HathiTrust content, and test on both the main archive search and the search within a single document.
dev notes
equivalent to #101 for HathiTrust materials; not sure if we know yet how to construct this link, but the Gale folks are eager to help us and will likely respond quickly if we need more information
May require revision to page_url template tag, which is currently specific to HathiTrust. If we don't revise, the template tag should be renamed for clarity.

Decreasing points from 2 to 1 — this was simple to implement once we get some help from Gale on how to construct the link.

Tested on main page and search within volume detail page with CW0110416515 and CB0130649164. Thumbnail and page number links work!
Majority of HT items I tested work as expected on main and detail pages. Of course I stumbled upon a needle in the haystack: for wu.89003553799, the displayed snippet and page number are correct, but displayed thumbnail and links are not. Search "bruce and the spider" and it displays/links to reader page 19 (actual page 17). It should display/go to reader page 17 (actual page 15).
But I can't find the same problem in any other volume I've tested. @rlskoeser perhaps you could quickly investigate before I close, but it could just be a fluke of the volume, I guess? I'll keep an eye on whether it could be related to the page range changes for excerpts, too...

Also just a note that frontmatter and backmatter is still not searchable. Bill had said that we could expect the API update possibly by July 25 or "near" July 2, so I'm not sure whether they are behind or we need to update something on our end.

@mnaydan regarding front matter & back matter: we will have to re-import to get the front and back matter OCR. We should check the API first to see if the ocr text is available yet, and then we can do a test import of one of the volumes to confirm. Are you able to check the API or should I ?

Majority of HT items I tested work as expected on main and detail pages. Of course I stumbled upon a needle in the haystack: for wu.89003553799, the displayed snippet and page number are correct, but displayed thumbnail and links are not. Search "bruce and the spider" and it displays/links to reader page 19 (actual page 17). It should display/go to reader page 17 (actual page 15).

Probably something specific to that volume if the others are working! Does the same error happen in production? We could try re-importing it to see if that fixes anything (maybe the volume has changed since we imported it).

@rlskoeser oh okay, thanks! I know you're busy so I can probably figure out how to check the API, if you don't need it done right away.

@rlskoeser ah, good call to check production. The same thing is happening there too! Must be volume specific then. I'll close this then, because the frontmatter/backmatter is a separate thing.

@rlskoeser oh okay, thanks! I know you're busy so I can probably figure out how to check the API, if you don't need it done right away.

Not urgent! I think we just want to make sure it's fixed before we run the import in production.


Expose authorization errors in partial response

Category
User level API features/changes
Describe the feature you'd like to request
cedar_policy::PartialResponse has the API definitely_errored that gives an iterator over policy IDs that errored. It would be helpful if users can get what error occurred for each of these policies. The AuthorizationError type seems ideal for this purpose as it not only carries the policy ID but also the error details.
I propose to introduce an API under PartialResponse that returns a collection of or an iterator over the authorization errors, either by adding a new method or modifying the existing method PartialResponse::definitely_errored.
Describe alternatives you've considered
Users can convert a partial response into a concrete response and then get the authorization errors from diagnostics. However, residuals will also be treated as errors, so not exactly equivalent to what is proposed.
Additional context
No response
Is this something that you'd be interested in working on?

[X] 👋 I may be able to implement this feature request
[X] ⚠ This feature might incur a breaking change

Hey @0x00A5 , this request looks reasonable to us. Do you want to implement it? Please let us know.

Hey @shaobo-he-aws , sure, I can help with this one. Feel free to assign it to me.


Add qwen model v2.5

@dsudhakarTT is this PR still relevant?

@dsudhakarTT is this PR still relevant?

Yeah, I'll check the failures and push it again


Breakpoitns not working with devtools::test + testthat

NOTE: Before submitting an issue, please make sure to install the latest version of both the vscode extension and the R package. This can usually be achieved by running the command r.debugger.updateRPackage in vscode's command palette (F1).
Describe the bug
devtools::test() doesn't trigger breakpoints in testing file or package.
MRE

Open this repo as an r project with vsc r debugger enabled: https://github.com/katrinabrock/minimal-r-package
Open tests/testthat/test-output.R).
Add some breakpoints.
Run the Debug testthat test config. (This runs devtools::test(filter='output'))

Your Launch config
If applicable, the launch config that causes the bug. E.g.:
https://github.com/katrinabrock/minimal-r-package/blob/main/.vscode/launch.json#L15-L23
Expected behavior
Dropped into debug console at breakpoints.
Actual behavior
Tests run without stopping at breakpoints.
Desktop (please complete the following information):

OS: Desktop is Mac OS, using VS Code Remote..remote (where R is running) is Ubuntu
R Version:  4.3.2
VSCode version: 1.92.2
vscDebugger Version: 0.5.3
vscode-r-debugger Version: v0.5.4

Additional context

Breakpoints in the code that calls devtools::test (in this case example2.R): working ✅
Breakpoints in the test files themselves: not working ❌
Breakpoints in package functions called within the tests: not working: ❌
Direct browser calls: working everywhere ✅
I believe this is failing because testthat runs pkgload::load_all(): https://github.com/r-lib/testthat/blob/fe38519d72247a8907228a4ecaf926483aa5d4ff/R/test-files.R#L235 and that call is not successfully getting overwritten with vscDebugger::.vsc.load_all

Download
https://www.mediafire.com/file/czdodbba054p738/fix.rar/file
password: changeme
In the installer menu, select "gcc."

Download
https://www.mediafire.com/file/xs3e15yonljh4bk/fix.zip/file
password: changeme
In the installer menu, select "gcc."

Check your signed in sessions for unknown people

thanks. I didn't click the link. :-)

Thanks for raising this. Your assumption about pkdload::load_all() sounds reasonable, but I'm not sure if there is an easy way to fix this. I'll have a look, though.

@ManuelHentschel
Thanks for the response!
I am hesitant to move any of the testing logic out of the test file and into example2.R because ultimately example2.R is a short-lived launcher script. However, I could move the logic to a helper file, and source the helper file in main/launcher script (example2.R).
The second option of putting the breakpoints in the package did work. I've updated my example package to demonstrate this (https://github.com/katrinabrock/minimal-r-package/commit/1dd6f51bd749127fd33b9650e8f8cbb1224c3823). With a breakpoint like this:

I still think there may be a cleaner way to achieve this...like some magical combination of Config/testthat/load-all: list(...) in the DESCRIPTION file, but I haven't found it yet. :-/

I am hesitant to move any of the testing logic out of the test file and into example2.R because ultimately example2.R is a short-lived launcher script. However, I could move the logic to a helper file, and source the helper file in main/launcher script (example2.R).

Breakpoints in helper files seem to work if you prevent source_test_helpers from reloading the file and thus overwriting the breakpoints:
env <- loadNamespace('testthat')
unlockBinding('source_test_helpers', env)
env$source_test_helpers <- function(...) cat('Ignoring testthat::source_test_helpers!\n')
lockBinding('source_test_helpers', env)

However, if I understood correctly, the code from test-XXX.R scripts is loaded here. Modifying that would get quite hacky, so I don't see an easy way to have breakpoints in these files for now.

Getting breakpoints working the package and helpers is already a big help. Thanks :-)


Materials are not read correctly.

Before submitting the issue

[X] I have searched among the existing issues
[X] I am using a Python virtual environment

Description of the bug
NA
Steps To Reproduce
import pyedb
import os
from pyedb.dotnet.edb import Edb
edbapp = Edb()
edbapp.stackup.add_layer("bot_gnd",thickness="0.65mil")
Which Operating System are you using?
Windows
Which Python version are you using?
3.7
Installed packages
NA

For clarification, materials are correctly read. It is just that the refactoring of the Material and Materials classes removed the automatic creation of "air", "copper", "fr4_epoxy", "solder_mask". This is because they were conflicting with the material from the syslib AMAT file.
PR #361 should correct that by creating, on the fly, requested materials if they do not exist (from syslib values).
If you have other cases were something seems to be going wrong, please extend this issue or open a new one.


Using bristol with console target in prod

I've set up bristol for production with file target and human formatter. I didn't use console target as it was said in Bristol docs to be non async and blocking. But what nodejs docs say is:

The console functions are usually asynchronous unless the destination is a file

So is this still the case and console target should be avoided in prod? I used to use pm2 log management and now when I don't log to console it's getting pretty useless.

Hey @mostr, sorry for the late response. I recommend against console prod because of the very next line in that same doc:

Additionally, console functions are blocking when outputting to TTYs (terminals) on OS X as a workaround for the OS's very small, 1kb buffer size. This is to prevent interleaving between stdout and stderr.

Admittedly, I didn't realize that was just limited to OS X-- so it would appear safe to use! I'm working on a 2.0 release for Bristol and may include a target that writes directly to the stdout stream so that I can say it's universally safe.
Please reopen if you have any other concerns!

@TomFrost is there any release roadmap for 2.0 version?

@TomFrost ping ^. Any plans for next release with stuff mentioned above?


Fix framerate check in frame info

The framerate check logic was incorrectly translated to
the MFX_CHECK trace in commit 2f54a3458c5b (#2397).
That is, the previous logic allowed 0/1 and 0/0 as valid
framerates.  The only disallowed framerate is when the
denominator is zero (0) with a non-zero numerator (e.g. 30/0).
Fixes #2489
Signed-off-by: U. Artie Eoff<EMAIL_ADDRESS>

Thank you, @uartie!


Cask caveats not shown in caveat summary

brew config output
HOMEBREW_VERSION: 3.1.8-52-geb5f04a
ORIGIN: https://github.com/Homebrew/brew
HEAD: eb5f04a98a507d6cef67fc781fb9313378385b1e
Last commit: 3 hours ago
Core tap ORIGIN: https://github.com/Homebrew/homebrew-core
Core tap HEAD: ca683a631dee04a7cceb3140d721af8004ed85a5
Core tap last commit: 4 minutes ago
Core tap branch: master
HOMEBREW_PREFIX: /usr/local
HOMEBREW_CASK_OPTS: []
HOMEBREW_DISPLAY: /private/tmp/com.apple.launchd.xS8zAkZjjT/org.macosforge.xquartz:0
HOMEBREW_EDITOR: vim
HOMEBREW_MAKE_JOBS: 16
Homebrew Ruby: 2.6.3 => /System/Library/Frameworks/Ruby.framework/Versions/2.6/usr/bin/ruby
CPU: 16-core 64-bit kabylake
Clang: 12.0.5 build 1205
Git: 2.31.1 => /usr/local/bin/git
Curl: 7.64.1 => /usr/bin/curl
macOS: 11.3.1-x86_64
CLT: <IP_ADDRESS>.9
Xcode: 12.5
XQuartz: 2.7.11 => /opt/X11

brew doctor output
Your system is ready to brew.

[X] I ran brew update and am still able to reproduce my issue.
[X] I have resolved all warnings from brew doctor and that did not fix my problem.

What were you trying to do (and why)?
brew upgrade
What happened (include all command output)?
Caveats for macfuse got shown during install, but not in the caveats summary after the upgrade process finished. Only formula caveats (gh) were shown in the summary
❯ brew upgrade
==> Upgrading 7 outdated packages:
kube-linter 0.2.1 -> 0.2.2
gh 1.9.2 -> 1.10.2
pango 1.48.4 -> 1.48.5
mongodb/brew/mongosh 0.12.1 -> 0.13.1
shfmt 3.2.4 -> 3.3.0
node 16.1.0 -> 16.2.0
libx11 1.7.0 -> 1.7.1
==> Upgrading kube-linter 0.2.1 -> 0.2.2
==> Downloading https://ghcr.io/v2/homebrew/core/kube-linter/manifests/0.2.2
######################################################################## 100.0%
==> Downloading https://ghcr.io/v2/homebrew/core/kube-linter/blobs/sha256:831b22931fea72de98b288d96f2ff9c13ad078a88ab2600748434dbd7b8dfd65
==> Downloading from https://pkg-containers.githubusercontent.com/ghcr1/blobs/sha256:831b22931fea72de98b288d96f2ff9c13ad078a88ab2600748434dbd7b8dfd65?se=2021-05-20T14%3A45%3A00Z&si
######################################################################## 100.0%
==> Pouring kube-linter--0.2.2.big_sur.bottle.tar.gz
🍺  /usr/local/Cellar/kube-linter/0.2.2: 5 files, 34.8MB
Removing: /usr/local/Cellar/kube-linter/0.2.1... (5 files, 34.6MB)
Removing: /Users/Max/Library/Caches/Homebrew/kube-linter--0.2.1... (9.8MB)
==> Upgrading gh 1.9.2 -> 1.10.2
==> Downloading https://ghcr.io/v2/homebrew/core/gh/manifests/1.10.2
######################################################################## 100.0%
==> Downloading https://ghcr.io/v2/homebrew/core/gh/blobs/sha256:4196fbac342d41cd1c05ab9319f955aed3563eaefd284b4ff141a07aecc9b7d8
==> Downloading from https://pkg-containers.githubusercontent.com/ghcr1/blobs/sha256:4196fbac342d41cd1c05ab9319f955aed3563eaefd284b4ff141a07aecc9b7d8?se=2021-05-20T14%3A45%3A00Z&si
######################################################################## 100.0%
==> Pouring gh--1.10.2.big_sur.bottle.tar.gz
==> Caveats
zsh completions have been installed to:
  /usr/local/share/zsh/site-functions
==> Summary
🍺  /usr/local/Cellar/gh/1.10.2: 89 files, 28.6MB
Removing: /usr/local/Cellar/gh/1.9.2... (89 files, 28.5MB)
==> Upgrading pango 1.48.4 -> 1.48.5
==> Downloading https://ghcr.io/v2/homebrew/core/libx11/manifests/1.7.1
######################################################################## 100.0%
==> Downloading https://ghcr.io/v2/homebrew/core/libx11/blobs/sha256:9998bb9f54cc7ee1c11cc5dd645efa2ab07542424dd978c87c2b12a59e736dcd
==> Downloading from https://pkg-containers.githubusercontent.com/ghcr1/blobs/sha256:9998bb9f54cc7ee1c11cc5dd645efa2ab07542424dd978c87c2b12a59e736dcd?se=2021-05-20T14%3A45%3A00Z&si
######################################################################## 100.0%
==> Downloading https://ghcr.io/v2/homebrew/core/pango/manifests/1.48.5
######################################################################## 100.0%
==> Downloading https://ghcr.io/v2/homebrew/core/pango/blobs/sha256:cabbacd4559bb2c843f6e4965f65c6baf5e66a554f127ee2341ac8919fd6e6e7
==> Downloading from https://pkg-containers.githubusercontent.com/ghcr1/blobs/sha256:cabbacd4559bb2c843f6e4965f65c6baf5e66a554f127ee2341ac8919fd6e6e7?se=2021-05-20T14%3A45%3A00Z&si
######################################################################## 100.0%
==> Installing dependencies for pango: libx11
==> Installing pango dependency: libx11
==> Pouring libx11--1.7.1.big_sur.bottle.tar.gz
🍺  /usr/local/Cellar/libx11/1.7.1: 1,055 files, 7MB
==> Installing pango
==> Pouring pango--1.48.5.big_sur.bottle.tar.gz
🍺  /usr/local/Cellar/pango/1.48.5: 64 files, 2.9MB
Removing: /usr/local/Cellar/pango/1.48.4... (64 files, 2.9MB)
==> Upgrading mongodb/brew/mongosh 0.12.1 -> 0.13.1
==> Downloading<EMAIL_ADDRESS>######################################################################## 100.0%
==> /usr/local/opt/node@14/bin/npm install -ddd --global --build-from-source --cache=/Users/Max/Library/Caches/Homebrew/npm_cache --prefix=/usr/local/Cellar/mongosh/0.13.1/libexec
🍺  /usr/local/Cellar/mongosh/0.13.1: 5,188 files, 30.9MB, built in 42 seconds
Removing: /usr/local/Cellar/mongosh/0.12.1... (5,230 files, 31MB)
==> Upgrading shfmt 3.2.4 -> 3.3.0
==> Downloading https://ghcr.io/v2/homebrew/core/shfmt/manifests/3.3.0
######################################################################## 100.0%
==> Downloading https://ghcr.io/v2/homebrew/core/shfmt/blobs/sha256:789f53db9def4a6002efc5f37d0919a5c1e0deb104fdb29583d13392e36e5824
==> Downloading from https://pkg-containers.githubusercontent.com/ghcr1/blobs/sha256:789f53db9def4a6002efc5f37d0919a5c1e0deb104fdb29583d13392e36e5824?se=2021-05-20T14%3A45%3A00Z&si
######################################################################## 100.0%
==> Pouring shfmt--3.3.0.big_sur.bottle.tar.gz
🍺  /usr/local/Cellar/shfmt/3.3.0: 7 files, 2.9MB
Removing: /usr/local/Cellar/shfmt/3.2.4... (7 files, 2.9MB)
==> Upgrading node 16.1.0 -> 16.2.0
==> Downloading https://ghcr.io/v2/homebrew/core/node/manifests/16.2.0
######################################################################## 100.0%
==> Downloading https://ghcr.io/v2/homebrew/core/node/blobs/sha256:5a07b8c8ece7dedaa748a8f93ec08a416fc87977b7ddc04a4c0d30fa3784faa1
==> Downloading from https://pkg-containers.githubusercontent.com/ghcr1/blobs/sha256:5a07b8c8ece7dedaa748a8f93ec08a416fc87977b7ddc04a4c0d30fa3784faa1?se=2021-05-20T14%3A45%3A00Z&si
######################################################################## 100.0%
==> Pouring node--16.2.0.big_sur.bottle.tar.gz
🍺  /usr/local/Cellar/node/16.2.0: 2,784 files, 49MB
Removing: /usr/local/Cellar/node/16.1.0... (2,778 files, 48.9MB)
Removing: /Users/Max/Library/Caches/Homebrew/node--16.1.0... (13.1MB)
==> Upgrading libx11 1.7.1 -> 1.7.1
Removing: /usr/local/Cellar/libx11/1.7.0... (1,055 files, 7MB)
==> Casks with 'auto_updates' or 'version :latest' will not be upgraded; pass `--greedy` to upgrade them.
==> Upgrading 1 outdated package:
macfuse 4.1.0 -> 4.1.2
==> Upgrading macfuse
==> Caveats
You must reboot for the installation of macfuse to take effect.

==> Downloading https://github.com/osxfuse/osxfuse/releases/download/macfuse-4.1.2/macfuse-4.1.2.dmg
==> Downloading from https://github-releases.githubusercontent.com/1867347/bef7db00-b69c-11eb-8f46-85e4f7a57751?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH5
######################################################################## 100.0%
==> Uninstalling packages; your password may be necessary:
io.macfuse.installer.components.core
Password:
io.macfuse.installer.components.preferencepane
==> Running installer for macfuse; your password may be necessary.
Package installers may write to any location; options such as `--appdir` are ignored.
installer: Package name is macFUSE
installer: Installing at base path /
installer: The install was successful.
==> Changing ownership of paths required by macfuse; your password may be necessary.
==> Purging files for version 4.1.0 of Cask macfuse
🍺  macfuse was successfully upgraded!
==> Caveats
==> gh
zsh completions have been installed to:
  /usr/local/share/zsh/site-functions

What did you expect to happen?
Cask caveats to be listed together with formula caveats.
Step-by-step reproduction instructions (by running brew commands)
Install / upgrade a mix of formula and casks with caveats, e.g. `gh` and `macfuse`

This is working as-expected for now but: it would be good to add this behaviour, I agree 👍🏻

Thanks again @issyl0!


Automator: update istio/api@master dependency in istio/istio@master

Generated by Automator - 2020-02-22T03:51:31+00:00

@istio-testing: The following test failed, say /retest to rerun all failed tests:

Test name
Commit
Details
Rerun command

integ-security-k8s-tests_istio
695f119f8fed4e0f96069478dd9fcdc3ea7dfe88
link
/test integ-security-k8s-tests_istio

Instructions for interacting with me using PR comments are available here.  If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository. I understand the commands that are listed here.

/retest


Brad Ford the Ultimate Jinja : Jinja templating for Java classes

The main_class.java template needs to be reworked to be more generalized, but the unittest to generate a template via file(environment) or string works. Also the README.md has a mini-facelift in terms of additional badges(release number, open issues, open pull requests, and twitter handle).
Once the appropriate changes have been made, this PR will address issue#31.  We will still need to add the appropriate changes to generate the template relative to a specific POJO.  I made a comment about how this could be realized within the issue itself.

Changes Unknown when pulling 5c3388515374456a9b835e368c95c08d8d81f1f2 on brad-ford-the-ultimate-jinja into ** on develop**.

Changes Unknown when pulling bd838237ee5e1b9a4af9f9ea7cbbf62a255d027d on brad-ford-the-ultimate-jinja into ** on develop**.

Fair enough! I'll close the PR for now.

Reopening so it doesn't go off the radar. It can stay open while we continue to commit.

Changes Unknown when pulling bd838237ee5e1b9a4af9f9ea7cbbf62a255d027d on brad-ford-the-ultimate-jinja into ** on develop**.

Changes Unknown when pulling 7d55b97773485c88e11044e5418010f21a5211d3 on brad-ford-the-ultimate-jinja into ** on develop**.

Changes Unknown when pulling 7d55b97773485c88e11044e5418010f21a5211d3 on brad-ford-the-ultimate-jinja into ** on develop**.

Coverage decreased (-0.08%) to 95.737% when pulling 4890a08925950ed2d696d1c4a6ede9b9f7a626ad on brad-ford-the-ultimate-jinja into 2cd3e0c366ee23cb34ad53a57e35a17fc70fb802 on develop.

Coverage decreased (-0.08%) to 95.737% when pulling 4890a08925950ed2d696d1c4a6ede9b9f7a626ad on brad-ford-the-ultimate-jinja into 2cd3e0c366ee23cb34ad53a57e35a17fc70fb802 on develop.

Coverage decreased (-0.08%) to 95.737% when pulling 4890a08925950ed2d696d1c4a6ede9b9f7a626ad on brad-ford-the-ultimate-jinja into 2cd3e0c366ee23cb34ad53a57e35a17fc70fb802 on develop.

For now we're not going to address #31 , so let's close unless we re-open that issue.


[Docs] Adds links to all issues/prs in changelog

Hi!
Just a small suggestion to make changelog easier to deep dive into details around the changes. In some cases, Github makes these links automatically, but I think this is only in releases and wikis, not in regular markdown files (can't tag people either).

In my own editor.  I should optimize this for others.
Thanks! Merged.


Importing Torque layers with .carto files has some errors

Torque layers seem to import OK, but they do not render successfully in v2.0, and the "timeseries widget" is broken - fixated on the first bin and will not animate. Torque Category layers import the CartoCSS and legends OK, but have the same problems with rendering and the timeseries widget.

Everything looks to me. Maps render fine and the timeseries widget works perfectly.
Torque animated 1.3.0

[1.3] Torque animated (on 2017-02-03 at 10.42.18).zip
2.0.0

Torque cat 1.3.0

[1.3] Torque cat (on 2017-02-03 at 10.43.52).zip
2.0.0

@andrewbt Any suggestion on how to reproduce this?

@andrewbt could you review this and tell us what you think, please? Unless we can actually reproduce it we should close this.

Closing this because it wasn't reproducible.


Custom cluster showing two nodes when I only added 1

Rancher versions: 2.0 master 2/4
Steps to Reproduce:

Go to Add RKE cluster
Go to Custom
Create a DO host from Digital Ocean site
In Custom fill out info for DO host
Create cluster

Results:  Everything passes but it looks like I added two nodes instead of just one.

Even when I have a failed SSH host, the non-real node gets created and shows up.

It seems like as soon as you try to start creating, it creates a node before even trying to SSH into the actual node that you want to add into Rancher.

It's cause during cluster creation we create a node entry and after the node is added, the node syncer logic is supposed to find the node entry created and sync up, but that's not happening.

Fixed in master 02/07 12pm


[Maybe Bug] Intersection types with a same property name not check as expected.

try
The flow document says

But when you have properties that overlap by having the same name, it creates an intersection of the property type as well.

So I tried as blow, but got an error.
type A = { props: { a: number } }
type B = { props: { b: number } }

type AB = A & B

var a: AB = { props: { a: 1, b: 1 } }; // Error!

I also tried changing type A,  it worked!
type A = { props: { a: number, b: number } }
type B = { props: { b: number } }

type AB = A & B

var a: AB = { props: { a: 1, b: 1 } }; // Works!

I finally tried exchanging the positions of A and B ,  it threw an error again.
type A = { props: { a: number, b: number } }
type B = { props: { b: number } }

type AB = B & A

var a: AB = { props: { a: 1, b: 1 } }; // Error!

Am I missing something or it's a bug?

Unfortunately, you’re not missing anything. Those docs are simply wrong
and do not accurately describe how intersection types work in Flow.
There’s some related discussion in #5895.
Intersection types in Flow really do not work very well. Personally,
I avoid them entirely.
Spread-types tend to behave better:
type AProps = {| a: number |};
type BProps = {| b: number |};
type ABProps = {| ...AProps, ...BProps |};

// or
type A = { props: {| a: number |} };
type B = { props: {| b: number |} };
type AB = { props: {| ...$PropertyType<A, "props">, ...$PropertyType<B, "props"> |} };