pashu123
/ _lambda.mlir
Created
October 10, 2022 18:04
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| #loc0 = loc(unknown) | |
| module attributes {torch.debug_module_name = "_lambda"} { | |
| 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<[2,4,64,64],f32>} loc(unknown), %arg2: !torch.tensor {torch.type_bound = !torch.vtensor<[],si64>} loc(unknown), %arg3: !torch.tensor {torch.type_bound = !torch.vtensor<[2,77,768],f32>} loc(unknown)) -> !torch.tensor { | |
| %3919 = torch.tensor_static_info_cast %arg1 : !torch.tensor to !torch.tensor<[2,4,64,64],f32> loc(#loc0) | |
| %3920 = torch.tensor_static_info_cast %arg2 : !torch.tensor to !torch.tensor<[],si64> loc(#loc0) | |
| %3921 = torch.tensor_static_info_cast %arg3 : !torch.tensor to !torch.tensor<[2,77,768],f32> loc(#loc0) | |
| %3922 = torch.prim.GetAttr %arg0["_param_constant365"] : !torch.nn.Module<"__torch__.torch.fx.graph_module._lambda"> -> !torch.tensor loc(#loc0) | |
| %3923 = torch.prim.GetAttr %arg0["_param_constant3 |
pashu123
/ unet_script.py
Created
October 11, 2022 13:04
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| import torch | |
| import numpy as np | |
| from shark.shark_inference import SharkInference | |
| from shark.shark_importer import SharkImporter | |
| from shark.shark_downloader import download_torch_model | |
| mlir_model, func_name, inputs, golden_out = download_torch_model( | |
| "stable_diff_quant", tank_url="gs://shark_tank/prashant_nod" | |
| ) |
pashu123
/ unet_script.py
Created
October 11, 2022 13:21
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| import numpy as np | |
| from shark.shark_inference import SharkInference | |
| from shark.shark_importer import SharkImporter | |
| from shark.shark_downloader import download_torch_model | |
| mlir_model, func_name, inputs, golden_out = download_torch_model( | |
| "stable_diff_quant", tank_url="gs://shark_tank/prashant_nod" | |
| ) | |
| shark_module = SharkInference(mlir_model, func_name, mlir_dialect="linalg", device="vulkan") |
pashu123
/ elided.mlir
Created
October 11, 2022 17:32
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| #map0 = affine_map<() -> ()> | |
| #map1 = affine_map<(d0) -> (0)> | |
| #map2 = affine_map<(d0) -> (d0)> | |
| #map3 = affine_map<(d0) -> ()> | |
| #map4 = affine_map<(d0, d1) -> (d0, 0)> | |
| #map5 = affine_map<(d0, d1) -> (0, d1)> | |
| #map6 = affine_map<(d0, d1) -> (d0, d1)> | |
| #map7 = affine_map<(d0, d1) -> ()> | |
| #map8 = affine_map<(d0, d1) -> (d1, d0)> | |
| #map9 = affine_map<(d0, d1) -> (d1)> |
pashu123
/ resnet_50_fp16.py
Last active
October 13, 2022 17:42
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| import numpy as np | |
| from shark.shark_inference import SharkInference | |
| from shark.shark_importer import SharkImporter | |
| from shark.shark_downloader import download_torch_model | |
| mlir_model, func_name, inputs, golden_out = download_torch_model( | |
| "resnet_50_fp16_torch", tank_url="gs://shark_tank/prashant_nod" | |
| ) | |
| shark_module = SharkInference(mlir_model, func_name, mlir_dialect="linalg") |
pashu123
/ resnet_50_fp16.py
Created
October 13, 2022 17:50
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| import numpy as np | |
| from shark.shark_inference import SharkInference | |
| from shark.shark_importer import SharkImporter | |
| from shark.shark_downloader import download_torch_model | |
| mlir_model, func_name, inputs, golden_out = download_torch_model( | |
| "resnet_50_fp16_old", tank_url="gs://shark_tank/prashant_nod" | |
| ) | |
| shark_module = SharkInference(mlir_model, func_name, mlir_dialect="linalg") |
pashu123
/ stable_diff_f16_elided.mlir
Created
October 14, 2022 14:16
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| #map0 = affine_map<(d0) -> (0)> | |
| #map1 = affine_map<(d0) -> (d0)> | |
| #map2 = affine_map<(d0) -> ()> | |
| #map3 = affine_map<() -> ()> | |
| #map4 = affine_map<(d0, d1) -> ()> | |
| #map5 = affine_map<(d0, d1) -> (d0, d1)> | |
| #map6 = affine_map<(d0, d1) -> (d0, 0)> | |
| #map7 = affine_map<(d0, d1) -> (0, d1)> | |
| #map8 = affine_map<(d0, d1) -> (d1, d0)> | |
| #map9 = affine_map<(d0, d1) -> (d1)> |
pashu123
/ err.dispatch
Created
October 14, 2022 17:39
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| stable_diff_f16_elided.mlir:1730:12: error: failed to legalize operation 'vector.transfer_read' that was explicitly marked illegal | |
| %261 = linalg.generic {indexing_maps = [#map16, #map16, #map16], iterator_types = ["parallel", "parallel", "parallel"]} ins(%expanded_770, %209 : tensor<2x4096x320xf16>, tensor<2x4096x320xf16>) outs(%156 : tensor<2x4096x320xf16>) { | |
| ^ | |
| stable_diff_f16_elided.mlir:25:3: note: called from | |
| func.func @forward(%arg0: tensor<2x4x64x64xf16>, %arg1: tensor<1xf16>, %arg2: tensor<2x77x768xf16>) -> tensor<2x4x64x64xf16> { | |
| ^ | |
| stable_diff_f16_elided.mlir:1730:12: note: see current operation: %710 = "vector.transfer_read"(%58, %709, %45) {in_bounds = [true], operand_segment_sizes = array<i32: 1, 1, 1, 0>, permutation_map = affine_map<(d0) -> (d0)>} : (memref<320xf16>, index, f16) -> vector<16xf16> loc(callsite("stable_diff_f16_elided.mlir":1730:12 at "stable_diff_f16_elided.mlir":25:3)) | |
| %261 = linalg.generic {indexing_maps = [#map16, #map16, #map16], iterator_types = ["paral |
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| #map0 = affine_map<(d0, d1) -> (d0, d1)> | |
| #map1 = affine_map<(d0, d1) -> (d1, d0)> | |
| #map2 = affine_map<(d0, d1) -> (d1)> | |
| #map3 = affine_map<(d0, d1, d2) -> (d0, d1, d2)> | |
| module { | |
| func.func @forward(%arg0: tensor<2x4096x320xf16>, %arg1: tensor<2x4096x320xf16>) -> tensor<2x4096x320xf16> { | |
| %cst = arith.constant 0.000000e+00 : f16 | |
| %cst_0 = arith.constant 0.000000e+00 : f16 | |
| %0 = tensor.empty() : tensor<2x4096x320xf16> | |
| %1 = linalg.fill ins(%cst : f16) outs(%0 : tensor<2x4096x320xf16>) -> tensor<2x4096x320xf16> |
pashu123
/ _lambda.mlir
Created
October 19, 2022 06:20
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| #loc0 = loc(unknown) | |
| module attributes {torch.debug_module_name = "_lambda"} { | |
| func.func @forward(%arg0: !torch.vtensor<[2,4,64,64],f16> loc(unknown), %arg1: !torch.vtensor<[],si64> loc(unknown), %arg2: !torch.vtensor<[2,77,768],f16> loc(unknown)) -> !torch.vtensor<[2,4,64,64],f16> { | |
| %int64 = torch.constant.int 64 loc(#loc1) | |
| %int320 = torch.constant.int 320 loc(#loc1) | |
| %int2 = torch.constant.int 2 loc(#loc1) | |
| %int40960 = torch.constant.int 40960 loc(#loc1) | |
| %int4096 = torch.constant.int 4096 loc(#loc1) | |
| %int10 = torch.constant.int 10 loc(#loc1) | |
| %int32 = torch.constant.int 32 loc(#loc1) |