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Make tests to use levelzero_runtime (#512)
Co-authored-by: [email protected] <Nishant Patel>
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test/PlaidML/CppEdsl.ConvI8.mlir

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// RUN: %gpu_skip || %python_executable %imex_runner -i %s --pass-pipeline-file=%p/linalg-to-llvm.pp \
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// RUN: --runner mlir-cpu-runner -e main \
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// RUN: --entry-point-result=void \
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// RUN: --shared-libs=%mlir_runner_utils,%mlir_c_runner_utils,%sycl_runtime | FileCheck %s
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// RUN: --shared-libs=%mlir_runner_utils,%mlir_c_runner_utils,%levelzero_runtime | FileCheck %s
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#map0 = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)>
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#map1 = affine_map<(d0, d1, d2, d3, d4, d5, d6) -> (d0, d1 + d4, d2 + d5, d6)>
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#map2 = affine_map<(d0, d1, d2, d3, d4, d5, d6) -> (d4, d5, d6, d3)>

test/PlaidML/CppEdsl.Convolution.mlir

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// RUN: %gpu_skip || %python_executable %imex_runner -i %s --pass-pipeline-file=%p/linalg-to-llvm.pp \
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// RUN: --runner mlir-cpu-runner -e main \
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// RUN: --entry-point-result=void \
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// RUN: --shared-libs=%mlir_runner_utils,%mlir_c_runner_utils,%sycl_runtime | FileCheck %s
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// RUN: --shared-libs=%mlir_runner_utils,%mlir_c_runner_utils,%levelzero_runtime | FileCheck %s
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#map0 = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)>
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#map1 = affine_map<(d0, d1, d2, d3, d4, d5, d6) -> (d0, d1 + d4, d2 + d5, d6)>
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#map2 = affine_map<(d0, d1, d2, d3, d4, d5, d6) -> (d4, d5, d6, d3)>

test/PlaidML/CppEdsl.DefractLong.mlir

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// RUN: %gpu_skip || %python_executable %imex_runner -i %s --pass-pipeline-file=%p/linalg-to-llvm.pp \
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// RUN: --runner mlir-cpu-runner -e main \
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// RUN: --entry-point-result=void \
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// RUN: --shared-libs=%mlir_runner_utils,%mlir_c_runner_utils,%sycl_runtime | FileCheck %s
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// RUN: --shared-libs=%mlir_runner_utils,%mlir_c_runner_utils,%levelzero_runtime | FileCheck %s
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#map0 = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)>
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#map1 = affine_map<(d0, d1, d2, d3, d4, d5, d6, d7, d8, d9, d10) -> (d1, -d0 + d3 + d8 + 1, -d0 + d4 + d5 + d9, d10)>
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#map2 = affine_map<(d0, d1, d2, d3, d4, d5, d6, d7, d8, d9, d10) -> (d0 * 4 + d2 * 2 + d7 - d8 * 2, d0 * 4 + d2 - d4 + d7 - d9 * 2 + 3, d6, d10)>

test/PlaidML/CppEdsl.DoubleDot.mlir

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// RUN: %gpu_skip || %python_executable %imex_runner -i %s --pass-pipeline-file=%p/linalg-to-llvm.pp \
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// RUN: --runner mlir-cpu-runner -e main \
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// RUN: --entry-point-result=void \
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// RUN: --shared-libs=%mlir_runner_utils,%mlir_c_runner_utils,%sycl_runtime | FileCheck %s
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// RUN: --shared-libs=%mlir_runner_utils,%mlir_c_runner_utils,%levelzero_runtime | FileCheck %s
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#map0 = affine_map<(d0, d1, d2) -> (d0, d2)>
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#map1 = affine_map<(d0, d1, d2) -> (d2, d1)>
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#map2 = affine_map<(d0, d1, d2) -> (d0, d1)>

test/PlaidML/CppEdsl.DupOut.mlir

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// RUN: %gpu_skip || %python_executable %imex_runner -i %s --pass-pipeline-file=%p/linalg-to-llvm.pp \
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// RUN: --runner mlir-cpu-runner -e main \
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// RUN: --entry-point-result=void \
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// RUN: --shared-libs=%mlir_runner_utils,%mlir_c_runner_utils,%sycl_runtime | FileCheck %s
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// RUN: --shared-libs=%mlir_runner_utils,%mlir_c_runner_utils,%levelzero_runtime | FileCheck %s
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#map0 = affine_map<(d0, d1, d2) -> (d0, d2)>
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#map1 = affine_map<(d0, d1, d2) -> (d2, d1)>
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#map2 = affine_map<(d0, d1, d2) -> (d0, d1)>

test/PlaidML/OpTest.Matmul.mlir

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// RUN-GPU: %python_executable %imex_runner -i %s --pass-pipeline-file=%p/linalg-to-llvm.pp \
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// RUN-GPU: --runner mlir-cpu-runner -e main \
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// RUN-GPU: --entry-point-result=void \
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// RUN-GPU: --shared-libs=%mlir_runner_utils,%sycl_runtime | FileCheck %s
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// RUN-GPU: --shared-libs=%mlir_runner_utils,%levelzero_runtime | FileCheck %s
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module @linalg_matmul{
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func.func @matmul(%arg0: tensor<5x3xf32>, %arg1: tensor<3x2xf32>) -> (tensor<5x2xf32>) {

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