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| // -----// IR Dump After AutoInputConversionPipelinePass (iree-auto-input-conversion) //----- // | |
| module { | |
| util.func public @matmul(%arg0: tensor<64x64xf32>, %arg1: tensor<64x64xf32>) -> tensor<64x64xf32> { | |
| %cst = arith.constant 0.000000e+00 : f32 | |
| %0 = tensor.empty() : tensor<64x64xf32> | |
| %1 = linalg.fill ins(%cst : f32) outs(%0 : tensor<64x64xf32>) -> tensor<64x64xf32> | |
| %2 = linalg.matmul ins(%arg0, %arg1 : tensor<64x64xf32>, tensor<64x64xf32>) outs(%1 : tensor<64x64xf32>) -> tensor<64x64xf32> | |
| util.return %2 : tensor<64x64xf32> | |
| } | |
| } |
pashu123
/ reconcile.txt
Created
September 26, 2024 15:55
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| func.func @matmul_dispatch_2_mmt4d_4x4x64x16x16x1_f32() { | |
| %c1537_i32 = arith.constant 1537 : i32 | |
| %c1_i32 = arith.constant 1 : i32 | |
| %c16_i32 = arith.constant 16 : i32 | |
| %c64 = arith.constant 64 : index | |
| %c1 = arith.constant 1 : index | |
| %c0 = arith.constant 0 : index | |
| %c16384 = arith.constant 16384 : index | |
| %c32768 = arith.constant 32768 : index | |
| %0 = hal.interface.binding.subspan layout(<bindings = [#hal.pipeline.binding<storage_buffer, "ReadOnly|Indirect">, #hal.pipeline.binding<storage_buffer, Indirect>], flags = Indirect>) binding(0) alignment(64) offset(%c0) flags("ReadOnly|Indirect") : memref<4x64x16x1xf32, #hal.descriptor_type<storage_buffer>> |
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| // -----// IR Dump After AutoInputConversionPipelinePass (iree-auto-input-conversion) //----- // | |
| module { | |
| util.func public @matmul(%arg0: tensor<64x64xf32>, %arg1: tensor<64x64xf32>) -> tensor<64x64xf32> { | |
| %cst = arith.constant 0.000000e+00 : f32 | |
| %0 = tensor.empty() : tensor<64x64xf32> | |
| %1 = linalg.fill ins(%cst : f32) outs(%0 : tensor<64x64xf32>) -> tensor<64x64xf32> | |
| %2 = linalg.matmul ins(%arg0, %arg1 : tensor<64x64xf32>, tensor<64x64xf32>) outs(%1 : tensor<64x64xf32>) -> tensor<64x64xf32> | |
| util.return %2 : tensor<64x64xf32> | |
| } | |
| } |
pashu123
/ fill_prob.mlir
Created
September 25, 2024 15:57
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| module { | |
| func.func @_reduce_sum_2x3xi32_dim0_dispatch_0_generic_3x2_i32() attributes {translation_info = #iree_codegen.translation_info<CPUDoubleTilingExpert>} { | |
| %c0 = arith.constant 0 : index | |
| %0 = hal.interface.binding.subspan layout(<bindings = [#hal.pipeline.binding<storage_buffer, "ReadOnly|Indirect">, #hal.pipeline.binding<storage_buffer, "ReadOnly|Indirect">, #hal.pipeline.binding<storage_buffer, Indirect>], flags = Indirect>) binding(0) alignment(64) offset(%c0) flags("ReadOnly|Indirect") : !flow.dispatch.tensor<readonly:tensor<i32>> | |
| %1 = hal.interface.binding.subspan layout(<bindings = [#hal.pipeline.binding<storage_buffer, "ReadOnly|Indirect">, #hal.pipeline.binding<storage_buffer, "ReadOnly|Indirect">, #hal.pipeline.binding<storage_buffer, Indirect>], flags = Indirect>) binding(1) alignment(64) offset(%c0) flags("ReadOnly|Indirect") : !flow.dispatch.tensor<readonly:tensor<2x3xi32>> | |
| %2 = hal.interface.binding.subspan layout(<bindings = [#hal.pipeline.binding<storage_buffer, "ReadOnl |
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| // -----// IR Dump After AutoInputConversionPipelinePass (iree-auto-input-conversion) //----- // | |
| module { | |
| func.func @fully_dynamic_pack_simple() { | |
| %0 = flow.tensor.dynamic_constant dense<[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11], [12, 13, 14, 15]]> : tensor<4x4xi32> -> tensor<?x?xi32> | |
| %c0 = arith.constant 0 : index | |
| %c1 = arith.constant 1 : index | |
| %1 = util.unfoldable_constant 2 : index | |
| %dim = tensor.dim %0, %c0 : tensor<?x?xi32> | |
| %dim_0 = tensor.dim %0, %c1 : tensor<?x?xi32> | |
| %2 = arith.ceildivui %dim, %1 : index |
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| // -----// IR Dump After EmptyTensorToAllocTensor (empty-tensor-to-alloc-tensor) //----- // | |
| func.func @_fully_dynamic_pack_simple_dispatch_0_pack_i32() attributes {translation_info = #iree_codegen.translation_info<CPUDataTiling>} { | |
| %c1 = arith.constant 1 : index | |
| %c0 = arith.constant 0 : index | |
| %c3 = arith.constant 3 : index | |
| %c2 = arith.constant 2 : index | |
| %c64 = arith.constant 64 : index | |
| %c32_i64 = arith.constant 32 : i64 | |
| %0 = hal.interface.constant.load layout(<constants = 10, bindings = [#hal.pipeline.binding<storage_buffer, ReadOnly>, #hal.pipeline.binding<storage_buffer, Indirect>], flags = Indirect>) ordinal(0) : i32 | |
| %1 = hal.interface.constant.load layout(<constants = 10, bindings = [#hal.pipeline.binding<storage_buffer, ReadOnly>, #hal.pipeline.binding<storage_buffer, Indirect>], flags = Indirect>) ordinal(1) : i32 |
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| #map = affine_map<(d0)[s0] -> (-d0 + s0, 64)> | |
| #map1 = affine_map<(d0)[s0] -> (d0 * s0)> | |
| #map2 = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> | |
| #pipeline_layout = #hal.pipeline.layout<constants = 10, bindings = [#hal.pipeline.binding<storage_buffer, ReadOnly>, #hal.pipeline.binding<storage_buffer, Indirect>], flags = Indirect> | |
| #translation = #iree_codegen.translation_info<CPUDataTiling> | |
| module { | |
| func.func @_fully_dynamic_pack_simple_dispatch_0_pack_i32() attributes {translation_info = #translation} { | |
| %c1 = arith.constant 1 : index | |
| %c0 = arith.constant 0 : index | |
| %c3 = arith.constant 3 : index |
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| func.func @_fully_dynamic_pack_simple_dispatch_0_pack_i32() attributes {translation_info = #iree_codegen.translation_info<CPUDataTiling>} { | |
| %c1 = arith.constant 1 : index | |
| %c0 = arith.constant 0 : index | |
| %c3 = arith.constant 3 : index | |
| %c2 = arith.constant 2 : index | |
| %c64 = arith.constant 64 : index | |
| %c32_i64 = arith.constant 32 : i64 | |
| %0 = hal.interface.constant.load layout(<constants = 10, bindings = [#hal.pipeline.binding<storage_buffer, ReadOnly>, #hal.pipeline.binding<storage_buffer, Indirect>], flags = Indirect>) ordinal(0) : i32 | |
| %1 = hal.interface.constant.load layout(<constants = 10, bindings = [#hal.pipeline.binding<storage_buffer, ReadOnly>, #hal.pipeline.binding<storage_buffer, Indirect>], flags = Indirect>) ordinal(1) : i32 | |
| %2 = hal.interface.constant.load layout(<constants = 10, bindings = [#hal.pipeline.binding<storage_buffer, ReadOnly>, #hal.pipeline.binding<storage_buffer, Indirect>], flags = Indirect>) ordinal(2) : i32 |
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| // -----// IR Dump After AutoInputConversionPipelinePass (iree-auto-input-conversion) //----- // | |
| #map = affine_map<(d0, d1) -> (d0, d1)> | |
| module { | |
| func.func private @generate_2D_source(%arg0: index, %arg1: index) -> tensor<?x?xi32> { | |
| %0 = tensor.empty(%arg0, %arg1) : tensor<?x?xi32> | |
| %1 = linalg.generic {indexing_maps = [#map], iterator_types = ["parallel", "parallel"]} outs(%0 : tensor<?x?xi32>) { | |
| ^bb0(%out: i32): | |
| %4 = linalg.index 0 : index | |
| %5 = linalg.index 1 : index | |
| %6 = arith.muli %4, %arg1 : index |
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| #!/bin/bash | |
| ################################################################################ | |
| # Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. | |
| # See https://llvm.org/LICENSE.txt for license information. | |
| # SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception | |
| ################################################################################ | |
| # | |
| # This script will install the llvm toolchain on the different | |
| # Debian and Ubuntu versions |