Chi_Liu AmosLewis
AmosLewis
/ distillgpt2.py
Last active
January 25, 2023 19:33
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| from transformers import AutoTokenizer, AutoModelForSequenceClassification | |
| import torch | |
| from torch.fx.experimental.proxy_tensor import make_fx | |
| from torch._decomp import get_decompositions | |
| import tempfile | |
| import torch_mlir | |
| def prepare_sentence_tokens(hf_model: str, sentence: str): | |
| tokenizer = AutoTokenizer.from_pretrained(hf_model) |
AmosLewis
/ deberta_tosa.mlir
Created
December 19, 2022 07:08
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| module attributes {torch.debug_module_name = "_lambda"} { | |
| func.func @forward(%arg0: tensor<1x128xi64>) -> tensor<1x2xf32> { | |
| %0 = "tosa.const"() {value = dense<[[65536, 512, 1]]> : tensor<1x3xi32>} : () -> tensor<1x3xi32> | |
| %1 = "tosa.const"() {value = dense_resource<__elided__> : tensor<2x768xf32>} : () -> tensor<2x768xf32> | |
| %2 = "tosa.const"() {value = dense_resource<__elided__> : tensor<768x768xf32>} : () -> tensor<768x768xf32> | |
| %3 = "tosa.const"() {value = dense_resource<__elided__> : tensor<768xf32>} : () -> tensor<768xf32> | |
| %4 = "tosa.const"() {value = dense_resource<__elided__> : tensor<768x3072xf32>} : () -> tensor<768x3072xf32> | |
| %5 = "tosa.const"() {value = dense_resource<__elided__> : tensor<3072xf32>} : () -> tensor<3072xf32> | |
| %6 = "tosa.const"() {value = dense_resource<__elided__> : tensor<3072x768xf32>} : () -> tensor<3072x768xf32> | |
| %7 = "tosa.const"() {value = dense<-3.40282347E+38> : tensor<f32>} : () -> tensor<f32> |
AmosLewis
/ gather_dynamic.mlir
Created
December 17, 2022 20:36
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| func.func @torch.aten.gather(%arg0: !torch.vtensor<[?,?,?],f32>, %arg1: !torch.vtensor<[?,?,?,?],si64>) -> !torch.vtensor<[?,?,?],f32> { | |
| %int-1 = torch.constant.int -1 | |
| %false = torch.constant.bool false | |
| %0 = torch.aten.gather %arg0, %int-1, %arg1, %false : !torch.vtensor<[?,?,?],f32>, !torch.int, !torch.vtensor<[?,?,?,?],si64>, !torch.bool -> !torch.vtensor<[?,?,?],f32> | |
| return %0 : !torch.vtensor<[?,?,?],f32> | |
| } |
AmosLewis
/ deberta_tosa_stateofart_fail.mlir
Created
December 16, 2022 21:37
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| ➜ deberta git:(main) ✗ torch-mlir-opt -pass-pipeline='builtin.module(torch-backend-to-tosa-backend-pipeline)' /tmp/_lambda.mlir --mlir-print-ir-after-failure -mlir-disable-threading | |
| <eval_with_key>.2:8:54: error: failed to legalize operation 'torch.constant.int' | |
| <eval_with_key>.2:8:54: note: see current operation: %1 = "torch.constant.int"() {value = 0 : i64} : () -> !torch.int | |
| // -----// IR Dump After FinalizingBackendTypeConversion Failed (torch-finalizing-backend-type-conversion) //----- // | |
| func.func @forward(%arg0: tensor<1x128xi64>) -> tensor<1x2xf32> { | |
| %0 = "tosa.const"() {value = dense<[[65536, 512, 1]]> : tensor<1x3xi32>} : () -> tensor<1x3xi32> | |
| %int0 = torch.constant.int 0 | |
| %1 = "tosa.const"() {value = dense_resource<__elided__> : tensor<2x768xf32>} : () -> tensor<2x768xf32> | |
| %2 = "tosa.const"() {value = dense_resource<__elided__> : tensor<768x768xf32>} : () -> tensor<768x768xf32> | |
| %3 = "tosa.const"() {value = dense_resource<__elided__> : tensor<768xf32>} : () -> tensor<768xf32> |
AmosLewis
/ deberta_torch.mlir
Created
December 16, 2022 21:35
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| #loc = loc(unknown) | |
| module attributes {torch.debug_module_name = "_lambda"} { | |
| func.func @forward(%arg0: !torch.vtensor<[1,128],si64> loc(unknown)) -> !torch.vtensor<[1,2],f32> { | |
| %int0 = torch.constant.int 0 loc(#loc1) | |
| %int1 = torch.constant.int 1 loc(#loc2) | |
| %true = torch.constant.bool true loc(#loc3) | |
| %float1.000000e00 = torch.constant.float 1.000000e+00 loc(#loc3) | |
| %none = torch.constant.none loc(#loc) | |
| %int11 = torch.constant.int 11 loc(#loc4) | |
| %false = torch.constant.bool false loc(#loc5) |
AmosLewis
/ gathernd_torch_deberta.mlir
Created
December 15, 2022 22:41
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| func.func @torch.aten.gather(%arg0: !torch.vtensor<[12,128,512],f32>, %arg1: !torch.vtensor<[1,128,128],si64>) -> !torch.vtensor<[12,128,128],f32> { | |
| %int-1 = torch.constant.int -1 | |
| %false = torch.constant.bool false | |
| %0 = torch.aten.gather %arg0, %int-1, %arg1, %false : !torch.vtensor<[12,128,512],f32>, !torch.int, !torch.vtensor<[1,128,128],si64>, !torch.bool -> !torch.vtensor<[12,128,128],f32> | |
| return %0 : !torch.vtensor<[12,128,128],f32> | |
| } |
AmosLewis
/ gathernd_torch.mlir
Created
December 15, 2022 21:30
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| func.func @torch.aten.gather(%arg0: !torch.vtensor<[1,4,3],f32>, %arg1: !torch.vtensor<[1,4,2],si64>) -> !torch.vtensor<[1,4,2],f32> { | |
| %int-1 = torch.constant.int -1 | |
| %false = torch.constant.bool false | |
| %0 = torch.aten.gather %arg0, %int-1, %arg1, %false : !torch.vtensor<[1,4,3],f32>, !torch.int, !torch.vtensor<[1,4,2],si64>, !torch.bool -> !torch.vtensor<[1,4,2],f32> | |
| return %0 : !torch.vtensor<[1,4,2],f32> | |
| } |
AmosLewis
/ tosa_concat_example.txt
Last active
December 15, 2022 05:07
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| value1: | |
| vec:[0,0,0,0,0,0,0] | |
| shape: 1*4*2*1 | |
| tosa::getConstTensor | |
| tensor([[ | |
| [ | |
| [0], [0] | |
| ], | |
| [ | |
| [0], [0] |
AmosLewis
/ gathernd_expand_algorithm_explanation.cpp
Last active
December 16, 2022 07:36
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| module { | |
| func.func @torch.aten.gather(%arg0: !torch.vtensor<[1,4,3],f32>, %arg1: !torch.vtensor<[1,4,2,3],i32>) -> !torch.vtensor<[1,4,2],f32> { | |
| %0 = torch_c.to_builtin_tensor %arg0 : !torch.vtensor<[1,4,3],f32> -> tensor<1x4x3xf32> | |
| %0= torch.tensor([[ | |
| [1, 2, 3], | |
| [4, 5, 6], | |
| [7, 8, 9], | |
| [10, 11, 12] | |
| ]]) # 1*4*3 | |
| %1 = torch_c.to_builtin_tensor %arg1 : !torch.vtensor<[1,4,2,3],i32> -> tensor<1x4x2x3xi32> |
AmosLewis
/ gathernd.mlir
Created
December 5, 2022 06:54
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| func.func @torch.aten.gather(%arg0: !torch.vtensor<[1,4,3],f32>, %arg1: !torch.vtensor<[1,4,2,3],si64>) -> !torch.vtensor<[1,4,2],f32> { | |
| %int-1 = torch.constant.int -1 | |
| %false = torch.constant.bool false | |
| %0 = torch.aten.gather %arg0, %int-1, %arg1, %false : !torch.vtensor<[1,4,3],f32>, !torch.int, !torch.vtensor<[1,4,2,3],si64>, !torch.bool -> !torch.vtensor<[1,4,2],f32> | |
| return %0 : !torch.vtensor<[1,4,2],f32> | |
| } |