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vivekgoe
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May 29, 2025
| CODE = {"nf4": _NF4_QUANT_TABLE, "fp4": _FP4_QUANT_TABLE} | ||
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| def get_habana_frameworks_version(): |
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Maybe better to change this to "get_gaudi_sw_version".
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| def get_habana_frameworks_version(): | ||
| """ | ||
| Returns the installed version of SynapseAI. |
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Returns the installed version of Gaudi SW.
| return version.parse(output.stdout.split("\n")[0].split()[-1]) | ||
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| HABANA_VERSION = get_habana_frameworks_version() |
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Replace HABANA_VERSION by GAUDI_SW_VER
| ) -> torch.Tensor: | ||
| torch._check_is_size(blocksize) | ||
| torch._check(quant_type == "nf4", lambda: f"quant_type must be nf4 or fp4, got {quant_type}") | ||
| torch._check(dtype == torch.bfloat16, lambda: f"4bit dequantization only supports bf16, but got {dtype}") |
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We support torch.float32 also, better to include that also in this check).
| if torch.xpu.is_available(): | ||
| from .backends.xpu import ops as xpu_ops | ||
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| if hasattr(torch, "hpu") and torch.hpu.is_available(): |
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In Line-29 above, can we make it "Intel Gaudi".
vivekgoe
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May 29, 2025
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updates the assertion message Co-authored-by: Matthew Douglas <38992547+matthewdouglas@users.noreply.github.com>
Co-authored-by: Matthew Douglas <38992547+matthewdouglas@users.noreply.github.com>
Fix lint issue
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This PR enables the support of bitsandbytes for HPU (Intel Gaudi) devices.
These changes add support for single and double NF4 quantization/dequantization using Intel Gaudi hardware.