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| // Binary Search Tree - Implemenation in C++ | |
| // Simple program to create a BST of integers and search an element in it | |
| #include<iostream> | |
| using namespace std; | |
| //Definition of Node for Binary search tree | |
| struct BstNode { | |
| int data; | |
| BstNode* left; | |
| BstNode* right; | |
| }; |
pashu123
/ memref_exec.py
Created
March 27, 2021 19:33
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| import numpy as np | |
| import ctypes | |
| import gc, sys | |
| from mlir.ir import * | |
| from mlir.passmanager import * | |
| from mlir.execution_engine import * | |
| class MemRefDescriptor(ctypes.Structure): | |
| """ Creates a ctype struct for memref descriptor""" |
pashu123
/ torch_ops_count.py
Created
December 9, 2021 13:50
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| import pandas as pd | |
| import re | |
| import numpy as np | |
| from sys import argv | |
| # `xls_file` and `td files` are total_ops and generatedAtenOps.td file | |
| # respectively. | |
| xls_file = argv[1] | |
| td_file = argv[2] |
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| from transformers import ( | |
| AutoConfig, | |
| AutoModelForCausalLM, | |
| AutoModelForMaskedLM, | |
| AutoModelForSeq2SeqLM, | |
| ReformerConfig, | |
| BigBirdConfig, | |
| BertConfig, | |
| ) | |
| import transformers |
pashu123
/ backward.mlir
Created
February 9, 2022 18:30
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| module attributes {torch.debug_module_name = "GraphModule"} { | |
| func private @__torch__.torch.fx.graph_module.___torch_mangle_2.GraphModule.forward(%arg0: !torch.nn.Module<"__torch__.torch.fx.graph_module.___torch_mangle_2.GraphModule">, %arg1: !torch.tensor {torch.type_bound = !torch.vtensor<[4,512,768],f32>}, %arg2: !torch.tensor {torch.type_bound = !torch.vtensor<[4,512,1],f32>}, %arg3: !torch.tensor {torch.type_bound = !torch.vtensor<[768],f32>}, %arg4: !torch.tensor {torch.type_bound = !torch.vtensor<[4,512,1],f32>}, %arg5: !torch.tensor {torch.type_bound = !torch.vtensor<[4,12,512,512],f32>}, %arg6: !torch.tensor {torch.type_bound = !torch.vtensor<[4,512,768],f32>}, %arg7: !torch.tensor {torch.type_bound = !torch.vtensor<[768,3072],f32>}, %arg8: !torch.tensor {torch.type_bound = !torch.vtensor<[4,512,1],f32>}, %arg9: !torch.tensor {torch.type_bound = !torch.vtensor<[2048,768],f32>}, %arg10: !torch.tensor {torch.type_bound = !torch.vtensor<[4,12,512,512],f32>}, %arg11: !torch.tensor {torch.type_bound = ! |
pashu123
/ forward.mlir
Created
February 9, 2022 18:30
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| module attributes {torch.debug_module_name = "GraphModule"} { | |
| func private @__torch__.torch.fx.graph_module.___torch_mangle_0.GraphModule.forward(%arg0: !torch.nn.Module<"__torch__.torch.fx.graph_module.___torch_mangle_0.GraphModule">, %arg1: !torch.tensor {torch.type_bound = !torch.vtensor<[768],f32>}, %arg2: !torch.tensor {torch.type_bound = !torch.vtensor<[768],f32>}, %arg3: !torch.tensor {torch.type_bound = !torch.vtensor<[512,768],f32>}, %arg4: !torch.tensor {torch.type_bound = !torch.vtensor<[2,768],f32>}, %arg5: !torch.tensor {torch.type_bound = !torch.vtensor<[30522,768],f32>}, %arg6: !torch.tensor {torch.type_bound = !torch.vtensor<[768],f32>}, %arg7: !torch.tensor {torch.type_bound = !torch.vtensor<[768],f32>}, %arg8: !torch.tensor {torch.type_bound = !torch.vtensor<[768],f32>}, %arg9: !torch.tensor {torch.type_bound = !torch.vtensor<[768,768],f32>}, %arg10: !torch.tensor {torch.type_bound = !torch.vtensor<[768],f32>}, %arg11: !torch.tensor {torch.type_bound = !torch.vtensor<[768,768],f32>}, %arg1 |
pashu123
/ bert_new.mlir
Created
February 11, 2022 13:08
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| // -----// IR Dump After SymbolDCE //----- // | |
| module attributes {torch.debug_module_name = "GraphModule"} { | |
| func private @__torch__.torch.fx.graph_module.___torch_mangle_0.GraphModule.forward(%arg0: !torch.nn.Module<"__torch__.torch.fx.graph_module.___torch_mangle_0.GraphModule">, %arg1: !torch.tensor {torch.type_bound = !torch.vtensor<[768],f32>}, %arg2: !torch.tensor {torch.type_bound = !torch.vtensor<[768],f32>}, %arg3: !torch.tensor {torch.type_bound = !torch.vtensor<[512,768],f32>}, %arg4: !torch.tensor {torch.type_bound = !torch.vtensor<[2,768],f32>}, %arg5: !torch.tensor {torch.type_bound = !torch.vtensor<[30522,768],f32>}, %arg6: !torch.tensor {torch.type_bound = !torch.vtensor<[768],f32>}, %arg7: !torch.tensor {torch.type_bound = !torch.vtensor<[768],f32>}, %arg8: !torch.tensor {torch.type_bound = !torch.vtensor<[768],f32>}, %arg9: !torch.tensor {torch.type_bound = !torch.vtensor<[768,768],f32>}, %arg10: !torch.tensor {torch.type_bound = !torch.vtensor<[768],f32>}, %arg11: !torch.tensor {torch.type |
pashu123
/ MobilenetV3Module.mlir
Created
February 14, 2022 12:29
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| #loc0 = loc(unknown) | |
| module attributes {torch.debug_module_name = "MobilenetV3Module"} { | |
| func @forward(%arg0: !torch.vtensor<[?,3,?,?],f32> loc(unknown)) -> !torch.vtensor { | |
| %0 = torch.vtensor.literal(dense<0.000000e+00> : tensor<1000xf32>) : !torch.vtensor<[1000],f32> loc(#loc0) | |
| %1 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<1000x1024xf32>) : !torch.vtensor<[1000,1024],f32> loc(#loc0) | |
| %2 = torch.vtensor.literal(dense<0.000000e+00> : tensor<1024xf32>) : !torch.vtensor<[1024],f32> loc(#loc0) | |
| %3 = torch.vtensor.literal(opaque<"elided_large_const", "0xDEADBEEF"> : tensor<1024x576xf32>) : !torch.vtensor<[1024,576],f32> loc(#loc0) | |
| %4 = torch.vtensor.literal(dense<0.000000e+00> : tensor<576xf32>) : !torch.vtensor<[576],f32> loc(#loc0) | |
| %5 = torch.vtensor.literal(dense<1.000000e+00> : tensor<576xf32>) : !torch.vtensor<[576],f32> loc(#loc0) | |
| %none = torch.constant.none loc(#loc1) |
pashu123
/ gist:941bfe8a51d01b37b1c3be5cf0e1a87b
Created
February 14, 2022 13:16
pashu123
/ resnet50.py
Created
February 17, 2022 14:13
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| from PIL import Image | |
| import requests | |
| import torch | |
| import torchvision.models as models | |
| from torchvision import transforms | |
| from torch_mlir.dialects.torch.importer.jit_ir import ClassAnnotator, ModuleBuilder | |
| from torch_mlir.passmanager import PassManager | |
| from torch_mlir_e2e_test.linalg_on_tensors_backends.abc import LinalgOnTensorsBackend |
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