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tensorflow/compiler/mlir/tf2xla/transforms/tf2xla_rewriter.h
#include "tensorflow/compiler/mlir/op_or_arg_name_mapper.h" #include "tensorflow/compiler/tf2xla/xla_context.h" #include "tensorflow/compiler/tf2xla/xla_expression.h" #include "xla/client/xla_builder.h" #include "xla/client/xla_computation.h" #include "xla/mlir_hlo/mhlo/IR/hlo_ops.h" #include "tensorflow/core/common_runtime/device_mgr.h" #include "tensorflow/core/framework/op_kernel.h" namespace mlir { namespace mhlo {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:16:07 UTC 2024 - 5K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_compiler_options_util.cc
#include "tensorflow/compiler/jit/xla_compiler_options_util.h" #include "xla/pjrt/pjrt_client.h" #include "tensorflow/core/framework/function.h" #include "tsl/framework/device_id_utils.h" namespace tensorflow { namespace { using XlaDeviceCompiler = DeviceCompiler<xla::LocalExecutable, xla::LocalClient>; using PjRtDeviceCompiler = DeviceCompiler<xla::PjRtLoadedExecutable, xla::PjRtClient>;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 09:53:30 UTC 2024 - 6.4K bytes - Viewed (0) -
tensorflow/compiler/jit/compilability_check_util.h
#include "tensorflow/compiler/tf2xla/const_analysis.h" #include "tensorflow/compiler/tf2xla/resource_operation_table.h" #include "tensorflow/compiler/tf2xla/xla_op_registry.h" #include "xla/service/graphcycles/graphcycles.h" #include "xla/statusor.h" #include "xla/union_find.h" #include "xla/util.h" #include "tensorflow/core/common_runtime/function.h" #include "tensorflow/core/common_runtime/graph_constructor.h" #include "tensorflow/core/framework/attr_value.pb.h"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Sep 06 19:12:29 UTC 2023 - 14.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/decompose_resource_ops.td
$resource, (TF_SubOp (CreateTFReadVariableOp $src_op, $value, $resource), $value ), (CreateConstBoolAttrFalse) ) >; // This decomposition is only correct inside XLA as it ignores use_locking // attribute. def DecomposeResourceApplyGradientDescentOp : Pat< (TF_ResourceApplyGradientDescentOp:$src_op $resource, $alpha, $delta, BoolAttr:$_), (TF_AssignVariableOp $resource,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 22 19:47:48 UTC 2024 - 20.7K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_device.h
// The XlaDevice executes a TensorFlow graph using the XLA linear algebra // runtime. // // Operators assigned to an XlaDevice are compiled into XLA computations. // Tensors on an XlaDevice are thin wrappers around XLA ScopedShapedBuffers. // // XlaDevice is instantiated separately for each XLA backend (e.g., CPU or GPU), // under different names (e.g., XLA_CPU or XLA_GPU).
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 09:53:30 UTC 2024 - 13.4K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_launch_util_test.cc
EXPECT_EQ(exec_args.size(), 2); std::shared_ptr<xla::Literal> literal1 = *exec_args[0]->ToLiteralSync(); EXPECT_TRUE(xla::LiteralTestUtil::Equal( *literal1, xla::LiteralUtil::CreateR2<int32_t>({{1, 2, 3}}))); std::shared_ptr<xla::Literal> literal2 = *exec_args[1]->ToLiteralSync(); EXPECT_TRUE(xla::LiteralTestUtil::Equal( *literal2, xla::LiteralUtil::CreateR2<int32_t>({{4, 5, 6}}))); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 09:53:30 UTC 2024 - 28.8K bytes - Viewed (0) -
tensorflow/compiler/jit/get_compiler_ir.cc
#include "tensorflow/compiler/jit/xla_platform_info.h" #include "tensorflow/compiler/tf2xla/xla_compiler.h" #include "xla/client/executable_build_options.h" #include "xla/client/local_client.h" #include "xla/service/hlo_graph_dumper.h" #include "xla/status_macros.h" #include "xla/stream_executor/host/host_platform_id.h" #include "xla/stream_executor/platform.h" #include "tensorflow/core/common_runtime/eager/tensor_handle.h"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 06:59:07 UTC 2024 - 19K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v1/compile_mlir_util.h
// eliminates the use of resource variables. // . Legalizes the operations to XLA HLO operations. // . Canonicalizes the XLA HLO operations. // // device_type: XLA JIT device to use for compilation such as "XLA_CPU_JIT", // "XLA_GPU_JIT" or "XLA_TPU_JIT". // use_tuple_args: when this is true, always create a tuple argument for the // entry computation.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 17:24:39 UTC 2024 - 10.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v1/BUILD
"@local_xla//xla/client:xla_computation", "@local_xla//xla/hlo/ir:hlo", "@local_xla//xla/mlir_hlo", "@local_xla//xla/mlir_hlo:hlo_dialect_registration", "@local_xla//xla/mlir_hlo:mhlo_passes", "@local_xla//xla/translate/mhlo_to_hlo:layout_util", "@local_xla//xla/translate/mhlo_to_hlo:mlir_hlo_to_hlo", "@local_xla//xla/translate/mhlo_to_hlo:type_to_shape",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 22:19:26 UTC 2024 - 12.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/utils/tf_xla_mlir_translate.cc
for (mlir::BlockArgument& arg : block.getArguments()) { auto num = arg.getArgNumber(); xla::Shape shape = xla::TypeToShape(arg.getType()); xla::XlaOp argop = xla::Parameter(&builder, num, shape, absl::StrCat("Arg_", num)); xla_params.push_back(argop); } std::vector<xla::XlaOp> returns(1); TF_RETURN_IF_ERROR(BuildHloFromTf(module_op, builder, xla_params, returns,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 18.8K bytes - Viewed (0)