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Results 11 - 20 of 24 for xla_tpu_jit (0.14 sec)
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tensorflow/compiler/mlir/tf2xla/tests/tfxla_device_specific_transformations_gpu.mlir
// RUN: tf-opt "--tfxla-device-specific-transforms=device-type=XLA_GPU_JIT" -verify-diagnostics -split-input-file %s | FileCheck -dump-input=fail %s module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 1399 : i32}} { // CHECK-LABEL: stateless_op func.func @stateless_op() -> tensor<i32> { // CHECK: %cst = "tf.Const"() <{value = dense<1> : tensor<i32>}> : () -> tensor<i32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 515 bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/tfxla_device_specific_transformations_cpu.mlir
// RUN: tf-opt "--tfxla-device-specific-transforms=device-type=XLA_CPU_JIT" -verify-diagnostics -split-input-file %s | FileCheck -dump-input=fail %s module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 1399 : i32}} { // CHECK-LABEL: stateless_op func.func @stateless_op() -> tensor<i32> { // CHECK: %cst = "tf.Const"() <{value = dense<1> : tensor<i32>}> : () -> tensor<i32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 515 bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/mlprogram.cc
pm.addPass(mlir::createCanonicalizerPass()); pm.addPass(mlir::createSymbolDCEPass()); pm.addPass(mlir::TF::CreateTFShapeInferencePass()); llvm::StringRef tf2xla_fallback_device_type = "XLA_CPU_JIT"; pm.addPass(mlir::mhlo::createLegalizeTFPass( /*legalize_chlo=*/true, tf2xla_fallback_device_type, /*prefer_tf2xla=*/false)); pm.addPass(mlir::TF::CreateStripTfAttributesPass());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jan 09 22:39:15 UTC 2024 - 3.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-include-tf2xla-fallback.mlir
// RUN: tf-opt "-xla-legalize-tf=use-tf2xla-fallback=true device-type=XLA_CPU_JIT" -verify-diagnostics %s | FileCheck --check-prefix SUPPORTED_FALLBACK_DEVICE %s // RUN: tf-opt "-xla-legalize-tf=use-tf2xla-fallback=true" %s | FileCheck --check-prefix UNSPECIFIED_FALLBACK_DEVICE %s // RUN: tf-opt "-xla-legalize-tf=use-tf2xla-fallback=true device-type=INVALID_DEVICE_TYPE" %s | FileCheck --check-prefix UNSUPPORTED_FALLBACK_DEVICE %s // We run this test four times:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Nov 16 19:04:03 UTC 2023 - 3.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/tf2xla_rewriter_test.cc
explicit Tf2XlaRewriterTestPeer(mlir::Operation* op) : op_builder_(op), empty_rewriter_(op_builder_), tf2xla_rewriter_(op, empty_rewriter_, /*device_type=*/"XLA_CPU_JIT") {} absl::StatusOr<TupleOp> ImportXlaComputationIntoModule( XlaComputation& computation) { return tf2xla_rewriter_.ImportXlaComputation(computation); } private: OpBuilder op_builder_;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:16:07 UTC 2024 - 11.7K bytes - Viewed (0) -
tensorflow/compiler/jit/pjrt_base_device.h
std::string device_name; // The index of the device. int device_ordinal = -1; // The name of the compilation device, also referred to as jit_device_type. // (e.g., "XLA_CPU_JIT"); std::string compilation_device_name; // A vector of ShapeDeterminationFn (i.e., a bundle of LayoutSelectionFn, // ShapeRepresentationFn). Each bundle describes how the on-host shapes of
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 12:19:41 UTC 2024 - 4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/tf_stablehlo_pass.cc
mhlo::PopulateLegalizeTfPatterns(context, &patterns); TF::PopulateTFLoweringBeforeHLOPatterns(context, &patterns); mhlo::Tf2XlaTypeConverter converter; mhlo::PopulateLegalizeTfWithTf2XlaPatterns( "XLA_CPU_JIT", patterns, context, converter, /*prefer_tf2xla=*/false); stablehlo::StablehloToHloTypeConverter hlo_converter; chlo::populateChloToHloPatterns(context, &hlo_converter, &patterns);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 21:49:50 UTC 2024 - 7.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/translate/tf_mlir_translate_registration.cc
static constexpr char kMlirToGraphCompilationCheckName[] = "mlir-to-graph-compilation-check"; // Use CPU arbitrarily in order to check that a graph compiles at all static constexpr char kArbitraryDeviceName[] = "XLA_CPU_JIT"; namespace { inline absl::string_view StringRefToView(llvm::StringRef ref) { return {ref.data(), ref.size()}; } } // namespace static OwningOpRef<mlir::ModuleOp> GraphdefToMlirTranslateFunction(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 22:19:26 UTC 2024 - 7.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/utils/tf_xla_mlir_translate.cc
ParseArgumentShapes(mlir::StringRefToView(input_shapes), arg_shapes); if (!args_status.ok()) { LOG(ERROR) << args_status; return mlir::failure(); } auto device_type = "XLA_CPU_JIT"; llvm::MutableArrayRef<std::unique_ptr<mlir::Pass>> custom_legalization_passes{}; XlaCompilationResult compilation_result; auto compilation_status = via_builder
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 18.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-prefer-tf2xla.mlir
// RUN: tf-opt "-xla-legalize-tf=device-type=XLA_CPU_JIT legalize-chlo=false use-tf2xla-fallback=true prefer-tf2xla=true" %s | FileCheck %s // RUN: tf-opt "-xla-legalize-tf=device-type=XLA_CPU_JIT legalize-chlo=false prefer-tf2xla=true" %s | FileCheck --check-prefix NOFALLBACK %s module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 268 : i32}} { // CHECK-LABEL: @abs func.func @abs(%arg0: tensor<2xf32>) -> tensor<2xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 15.8K bytes - Viewed (0)