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Add a CPU nbit to float dequantization op that supports torch.quintMxN type and QuantizedCPU backend #2995
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This pull request was exported from Phabricator. Differential Revision: D61305979 |
This pull request was exported from Phabricator. Differential Revision: D61305979 |
…N type and QuantizedCPU backend (pytorch#2995) Summary: Pull Request resolved: pytorch#2995 X-link: facebookresearch/FBGEMM#87 Add a CPU nbit to float dequantization operator `torch.ops.fbgemm.FusedNBitRowwiseQuantizedSBHalfFrontToFloat` to support dequantization of int4 / int2 tensors which are of `torch.quintMxN` dtype and `QuantizedCPU` backend. This is to support D61305982 Differential Revision: D61305979
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This pull request was exported from Phabricator. Differential Revision: D61305979 |
…N type and QuantizedCPU backend (pytorch#2995) Summary: Pull Request resolved: pytorch#2995 X-link: facebookresearch/FBGEMM#87 Add a CPU nbit to float dequantization operator `torch.ops.fbgemm.FusedNBitRowwiseQuantizedSBHalfFrontToFloat` to support dequantization of int4 / int2 tensors which are of `torch.quintMxN` dtype and `QuantizedCPU` backend. This is to support D61305982 Differential Revision: D61305979
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…N type and QuantizedCPU backend (pytorch#2995) Summary: Pull Request resolved: pytorch#2995 X-link: facebookresearch/FBGEMM#87 Add a CPU nbit to float dequantization operator `torch.ops.fbgemm.FusedNBitRowwiseQuantizedSBHalfFrontToFloat` to support dequantization of int4 / int2 tensors which are of `torch.quintMxN` dtype and `QuantizedCPU` backend. This is to support D61305982 Differential Revision: D61305979
This pull request was exported from Phabricator. Differential Revision: D61305979 |
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This pull request was exported from Phabricator. Differential Revision: D61305979 |
…N type and QuantizedCPU backend (pytorch#2995) Summary: Pull Request resolved: pytorch#2995 X-link: facebookresearch/FBGEMM#87 Add a CPU nbit to float dequantization operator `torch.ops.fbgemm.FusedNBitRowwiseQuantizedSBHalfFrontToFloat` to support dequantization of int4 / int2 tensors which are of `torch.quintMxN` dtype and `QuantizedCPU` backend. This is to support D61305982 Differential Revision: D61305979
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This pull request was exported from Phabricator. Differential Revision: D61305979 |
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…N type and QuantizedCPU backend (pytorch#2995) Summary: Pull Request resolved: pytorch#2995 X-link: facebookresearch/FBGEMM#87 Add a CPU nbit to float dequantization operator `torch.ops.fbgemm.FusedNBitRowwiseQuantizedSBHalfFrontToFloat` to support dequantization of int4 / int2 tensors which are of `torch.quintMxN` dtype and `QuantizedCPU` backend. This is to support D61305982 Reviewed By: sryap Differential Revision: D61305979
This pull request was exported from Phabricator. Differential Revision: D61305979 |
…N type and QuantizedCPU backend (pytorch#2995) Summary: Pull Request resolved: pytorch#2995 X-link: facebookresearch/FBGEMM#87 Add a CPU nbit to float dequantization operator `torch.ops.fbgemm.FusedNBitRowwiseQuantizedSBHalfFrontToFloat` to support dequantization of int4 / int2 tensors which are of `torch.quintMxN` dtype and `QuantizedCPU` backend. This is to support D61305982 Reviewed By: sryap Differential Revision: D61305979
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This pull request was exported from Phabricator. Differential Revision: D61305979 |
…N type and QuantizedCPU backend (pytorch#2995) Summary: Pull Request resolved: pytorch#2995 X-link: facebookresearch/FBGEMM#87 Add a CPU nbit to float dequantization operator `torch.ops.fbgemm.FusedNBitRowwiseQuantizedSBHalfFrontToFloat` to support dequantization of int4 / int2 tensors which are of `torch.quintMxN` dtype and `QuantizedCPU` backend. This is to support D61305982 Reviewed By: sryap Differential Revision: D61305979
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This pull request was exported from Phabricator. Differential Revision: D61305979 |
…N type and QuantizedCPU backend (pytorch#2995) Summary: Pull Request resolved: pytorch#2995 X-link: facebookresearch/FBGEMM#87 Add a CPU nbit to float dequantization operator `torch.ops.fbgemm.FusedNBitRowwiseQuantizedSBHalfFrontToFloat` to support dequantization of int4 / int2 tensors which are of `torch.quintMxN` dtype and `QuantizedCPU` backend. This is to support D61305982 Reviewed By: sryap Differential Revision: D61305979
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This pull request was exported from Phabricator. Differential Revision: D61305979 |
…N type and QuantizedCPU backend (pytorch#2995) Summary: Pull Request resolved: pytorch#2995 X-link: facebookresearch/FBGEMM#87 Add a CPU nbit to float dequantization operator `torch.ops.fbgemm.FusedNBitRowwiseQuantizedSBHalfFrontToFloat` to support dequantization of int4 / int2 tensors which are of `torch.quintMxN` dtype and `QuantizedCPU` backend. This is to support D61305982 Reviewed By: sryap Differential Revision: D61305979
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This pull request was exported from Phabricator. Differential Revision: D61305979 |
…N type and QuantizedCPU backend (pytorch#2995) Summary: Pull Request resolved: pytorch#2995 X-link: facebookresearch/FBGEMM#87 Add a CPU nbit to float dequantization operator `torch.ops.fbgemm.FusedNBitRowwiseQuantizedSBHalfFrontToFloat` to support dequantization of int4 / int2 tensors which are of `torch.quintMxN` dtype and `QuantizedCPU` backend. This is to support D61305982 Reviewed By: sryap Differential Revision: D61305979
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This pull request was exported from Phabricator. Differential Revision: D61305979 |
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…N type and QuantizedCPU backend (pytorch#2995) Summary: Pull Request resolved: pytorch#2995 X-link: facebookresearch/FBGEMM#87 Add a CPU nbit to float dequantization operator `torch.ops.fbgemm.FusedNBitRowwiseQuantizedSBHalfFrontToFloat` to support dequantization of int4 / int2 tensors which are of `torch.quintMxN` dtype and `QuantizedCPU` backend. This is to support D61305982 Reviewed By: sryap Differential Revision: D61305979
This pull request was exported from Phabricator. Differential Revision: D61305979 |
…N type and QuantizedCPU backend (pytorch#2995) Summary: Pull Request resolved: pytorch#2995 X-link: facebookresearch/FBGEMM#87 Add a CPU nbit to float dequantization operator `torch.ops.fbgemm.FusedNBitRowwiseQuantizedSBHalfFrontToFloat` to support dequantization of int4 / int2 tensors which are of `torch.quintMxN` dtype and `QuantizedCPU` backend. This is to support D61305982 Reviewed By: sryap Differential Revision: D61305979
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This pull request was exported from Phabricator. Differential Revision: D61305979 |
…N type and QuantizedCPU backend (pytorch#2995) Summary: Pull Request resolved: pytorch#2995 X-link: facebookresearch/FBGEMM#87 Add a CPU nbit to float dequantization operator `torch.ops.fbgemm.FusedNBitRowwiseQuantizedSBHalfFrontToFloat` to support dequantization of int4 / int2 tensors which are of `torch.quintMxN` dtype and `QuantizedCPU` backend. This is to support D61305982 Reviewed By: sryap Differential Revision: D61305979
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This pull request was exported from Phabricator. Differential Revision: D61305979 |
…N type and QuantizedCPU backend (pytorch#2995) Summary: Pull Request resolved: pytorch#2995 X-link: facebookresearch/FBGEMM#87 Add a CPU nbit to float dequantization operator `torch.ops.fbgemm.FusedNBitRowwiseQuantizedSBHalfFrontToFloat` to support dequantization of int4 / int2 tensors which are of `torch.quintMxN` dtype and `QuantizedCPU` backend. This is to support D61305982 Reviewed By: sryap Differential Revision: D61305979
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…N type and QuantizedCPU backend (pytorch#2995) Summary: Pull Request resolved: pytorch#2995 X-link: facebookresearch/FBGEMM#87 Add a CPU nbit to float dequantization operator `torch.ops.fbgemm.FusedNBitRowwiseQuantizedSBHalfFrontToFloat` to support dequantization of int4 / int2 tensors which are of `torch.quintMxN` dtype and `QuantizedCPU` backend. This is to support D61305982 Reviewed By: sryap Differential Revision: D61305979
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This pull request has been merged in 986e80c. |
Summary: Add a CPU nbit to float dequantization operator
torch.ops.fbgemm.FusedNBitRowwiseQuantizedSBHalfFrontToFloat
to support dequantization of int4 / int2 tensors which are oftorch.quintMxN
dtype andQuantizedCPU
backend. This is to support D61305982Differential Revision: D61305979