Chi_Liu AmosLewis
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.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
/ 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
/ distillgpt2_torchscript.mlir
Last active
January 3, 2023 02:05
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| #loc = loc(unknown) | |
| module attributes {torch.debug_module_name = "_lambda"} { | |
| func.func private @__torch__.torch.fx.graph_module._lambda.__code_getter(%arg0: !torch.nn.Module<"__torch__.torch.fx.graph_module._lambda"> loc(unknown)) -> !torch.str { | |
| %96 = torch.prim.GetAttr %arg0["_code"] : !torch.nn.Module<"__torch__.torch.fx.graph_module._lambda"> -> !torch.str loc(#loc) | |
| return %96 : !torch.str loc(#loc) | |
| } loc(#loc) | |
| func.func private @__torch__.torch.fx.graph_module._lambda.forward(%arg0: !torch.nn.Module<"__torch__.torch.fx.graph_module._lambda"> loc(unknown), %arg1: !torch.tensor {torch.type_bound = !torch.vtensor<[1,128],si64>} loc(unknown)) -> !torch.tensor { | |
| %true_0 = torch.constant.bool true loc(#loc1) | |
| %int11 = torch.constant.int 11 loc(#loc2) | |
| %int-2 = torch.constant.int -2 loc(#loc3) |
AmosLewis
/ distillgpt2_torch_delete_decompose_amax_selectint.mlir
Created
December 22, 2022 00:15
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| #loc = loc(unknown) | |
| module attributes {torch.debug_module_name = "_lambda"} { | |
| func.func private @__torch__.torch.fx.graph_module._lambda.__code_getter(%arg0: !torch.nn.Module<"__torch__.torch.fx.graph_module._lambda"> loc(unknown)) -> !torch.str { | |
| %96 = torch.prim.GetAttr %arg0["_code"] : !torch.nn.Module<"__torch__.torch.fx.graph_module._lambda"> -> !torch.str loc(#loc) | |
| return %96 : !torch.str loc(#loc) | |
| } loc(#loc) | |
| func.func private @__torch__.torch.fx.graph_module._lambda.forward(%arg0: !torch.nn.Module<"__torch__.torch.fx.graph_module._lambda"> loc(unknown), %arg1: !torch.tensor {torch.type_bound = !torch.vtensor<[1,128],si64>} loc(unknown)) -> !torch.tensor { | |
| %true_0 = torch.constant.bool true loc(#loc1) | |
| %int11 = torch.constant.int 11 loc(#loc2) | |
| %int-2 = torch.constant.int -2 loc(#loc3) |
AmosLewis
/ distilgpt2_torch_1221.mlir
Created
December 22, 2022 05:55
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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> { | |
| %int1 = torch.constant.int 1 loc(#loc1) | |
| %int0 = torch.constant.int 0 loc(#loc2) | |
| %int-1 = torch.constant.int -1 loc(#loc3) | |
| %true = torch.constant.bool true loc(#loc4) | |
| %none = torch.constant.none loc(#loc) | |
| %false = torch.constant.bool false loc(#loc5) | |
| %int128 = torch.constant.int 128 loc(#loc6) |
AmosLewis
/ distilgpt2_torchtotosa_debug.mlir
Last active
December 22, 2022 07:18
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| func.func @forward(%arg0: !torch.vtensor<[1,128],si64>) -> !torch.vtensor<[1,2],f32> { | |
| %0 = builtin.unrealized_conversion_cast %arg0 : !torch.vtensor<[1,128],si64> to tensor<1x128xi64> | |
| %int1 = torch.constant.int 1 | |
| %1 = builtin.unrealized_conversion_cast %int1 : !torch.int to i64 | |
| %int0 = torch.constant.int 0 | |
| %2 = builtin.unrealized_conversion_cast %int0 : !torch.int to i64 | |
| %int-1 = torch.constant.int -1 | |
| %3 = builtin.unrealized_conversion_cast %int-1 : !torch.int to i64 | |
| %true = torch.constant.bool true | |
| %4 = builtin.unrealized_conversion_cast %true : !torch.bool to i1 |
AmosLewis
/ as_strided.mlir
Last active
January 3, 2023 01:28
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| func.func @torch.aten.as_strided(%arg0: !torch.vtensor<[1,128,2304],f32>) -> !torch.vtensor<[1,128,768],f32> { | |
| %int0 = torch.constant.int 0 | |
| %int1 = torch.constant.int 1 | |
| %int128 = torch.constant.int 128 | |
| %int768 = torch.constant.int 768 | |
| %int2304 = torch.constant.int 2304 | |
| %240 = torch.prim.ListConstruct %int1, %int128, %int768 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> | |
| %241 = torch.prim.ListConstruct %int294912, %int2304, %int1 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> | |
| %242 = torch.aten.as_strided %arg0, %240, %241, %int0 : !torch.vtensor<[1,128,2304],f32>, !torch.list<int>, !torch.list<int>, !torch.int -> !torch.vtensor<[1,128,768],f32> | |
| return %242 : !torch.vtensor<[1,128,768],f32> |
AmosLewis
/ gpt2_torch_tosa_elide_2023.mlir
Created
January 2, 2023 05:15
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| module attributes {torch.debug_module_name = "_lambda"} { | |
| func.func @forward(%arg0: tensor<1x5xi64>) -> tensor<1x5x50257xf32> { | |
| %0 = "tosa.const"() {value = dense<-3.40282347E+38> : tensor<f32>} : () -> tensor<f32> | |
| %1 = "tosa.const"() {value = dense_resource<__elided__> : tensor<1x1x1024x1024xui8>} : () -> tensor<1x1x1024x1024xi8> | |
| %2 = "tosa.const"() {value = dense<8.000000e+00> : tensor<f32>} : () -> tensor<f32> | |
| %3 = "tosa.const"() {value = dense_resource<__elided__> : tensor<50257x768xf32>} : () -> tensor<50257x768xf32> | |
| %4 = "tosa.const"() {value = dense<7.680000e+02> : tensor<1xf32>} : () -> tensor<1xf32> | |
| %5 = "tosa.const"() {value = dense<[0, 2, 1, 3]> : tensor<4xi64>} : () -> tensor<4xi64> | |
| %6 = "tosa.const"() {value = dense<[0, 1, 3, 2]> : tensor<4xi32>} : () -> tensor<4xi32> | |
| %7 = "tosa.const"() {value = dense<0> : tensor<1x1x5x5xi8>} : () -> tensor<1x1x5x5xi8> |
AmosLewis
/ gpt2_torch_raw_elide.mlir
Created
January 2, 2023 05:37
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| module attributes {torch.debug_module_name = "_lambda"} { | |
| func.func private @__torch__.torch.fx.graph_module._lambda.__code_getter(%arg0: !torch.nn.Module<"__torch__.torch.fx.graph_module._lambda">) -> !torch.str { | |
| %186 = torch.prim.GetAttr %arg0["_code"] : !torch.nn.Module<"__torch__.torch.fx.graph_module._lambda"> -> !torch.str | |
| return %186 : !torch.str | |
| } | |
| func.func private @__torch__.torch.fx.graph_module._lambda.forward(%arg0: !torch.nn.Module<"__torch__.torch.fx.graph_module._lambda">, %arg1: !torch.tensor {torch.type_bound = !torch.vtensor<[1,5],si64>}) -> !torch.tensor { | |
| %int11 = torch.constant.int 11 | |
| %int-2 = torch.constant.int -2 | |
| %none_0 = torch.constant.none | |
| %false = torch.constant.bool false |