Repository: microsoft/DeepSpeed
File: op_builder/fp_quantizer.py (Python)

Code before:
            sys_cuda_major, _ = installed_cuda_version()
            torch_cuda_major = int(torch.version.cuda.split('.')[0])
            cuda_capability = torch.cuda.get_device_properties(0).major  #ignore-cuda
            if cuda_capability < 8:
                if verbose:
                    self.warning("NVIDIA Inference is only supported on Ampere and newer architectures")
                cuda_okay = False
            if cuda_capability >= 8:
                if torch_cuda_major < 11 or sys_cuda_major < 11:
                    if verbose:
                        self.warning("On Ampere and higher architectures please use CUDA 11+")
                    cuda_okay = False

        try:
            import triton
        except ImportError:
            if verbose:
                self.warning(f"please install triton==2.3.0,  2.3.1 or 3.0.0 if you want to use the FP Quantizer Kernels")
            return False

        # triton 2.3.{0,1} and 3.0.0 are ok.
        allowed_versions = ("2.3", "3.0")
        if pkg_version:
            allowed = (pkg_version.parse(v) for v in allowed_versions)
            installed_triton = pkg_version.parse(triton.__version__)
            triton_mismatch = all(installed_triton.major != a.major or installed_triton.minor != a.minor for a in allowed)
        else:
            installed_triton = triton.__version__
            major, minor, _ = installed_triton.split(".")
            allowed = (v.split(".") for v in allowed_versions)
            triton_mismatch = all(major != a[0] or minor != a[1] for v in allowed)

        if triton_mismatch:
            if verbose:
                self.warning(
                    f"FP Quantizer is using an untested triton version ({installed_triton}), only 2.3.{0,1} and 3.0.0 are known to be compatible with these kernels"
                )
            return False

        return super().is_compatible(verbose) and cuda_okay

    def filter_ccs(self, ccs):
        ccs_retained = []
        ccs_pruned = []
        for cc in ccs:
            if int(cc[0]) >= 8:
                ccs_retained.append(cc)
            else:
                ccs_pruned.append(cc)
        if len(ccs_pruned) > 0:
            self.warning(f"Filtered compute capabilities {ccs_pruned}")

Review comment (bug):
Hi @siddartha-RE - could you run the pre-commit formatter to pass the formatting checks?

```
pre-commit run --all-files
```

It looks like it is failing on this line and perhaps another

Code after:
            sys_cuda_major, _ = installed_cuda_version()
            torch_cuda_major = int(torch.version.cuda.split('.')[0])
            cuda_capability = torch.cuda.get_device_properties(0).major  #ignore-cuda
            if cuda_capability < 8:
                if verbose:
                    self.warning("NVIDIA Inference is only supported on Ampere and newer architectures")
                cuda_okay = False
            if cuda_capability >= 8:
                if torch_cuda_major < 11 or sys_cuda_major < 11:
                    if verbose:
                        self.warning("On Ampere and higher architectures please use CUDA 11+")
                    cuda_okay = False

        try:
            import triton
        except ImportError:
            if verbose:
                self.warning(
                    f"please install triton==2.3.0, 2.3.1 or 3.0.0 if you want to use the FP Quantizer Kernels")
            return False

        # triton 2.3.{0,1} and 3.0.0 are ok.
        allowed_versions = ("2.3", "3.0")
        if pkg_version:
            allowed = (pkg_version.parse(v) for v in allowed_versions)
            installed_triton = pkg_version.parse(triton.__version__)
            triton_mismatch = all(installed_triton.major != a.major or installed_triton.minor != a.minor
                                  for a in allowed)
        else:
            installed_triton = triton.__version__
            major, minor, _ = installed_triton.split(".")
            allowed = (v.split(".") for v in allowed_versions)
            triton_mismatch = all(major != v[0] or minor != v[1] for v in allowed)

        if triton_mismatch:
            if verbose:
                self.warning(
                    f"FP Quantizer is using an untested triton version ({installed_triton}), only 2.3.{0,1} and 3.0.0 are known to be compatible with these kernels"
                )
            return False

        return super().is_compatible(verbose) and cuda_okay

    def filter_ccs(self, ccs):
        ccs_retained = []
        ccs_pruned = []
        for cc in ccs:
            if int(cc[0]) >= 8:
                ccs_retained.append(cc)
            else:
                ccs_pruned.append(cc)