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tensorflow/compiler/mlir/tensorflow/tests/mlir2graphdef/graph-as-function.mlir
func.func @main(%arg0: tensor<*x!tf_type.resource>, %arg1: tensor<*x!tf_type.resource<tensor<3x3x1x32xf32>>>, %arg2: tensor<*xf32>, %arg3: tensor<2x4x6x8xi32>) -> (tensor<f32>, tensor<f32>) attributes {tf.entry_function = {inputs = "args_0,args_1,args_2,args_3", outputs = "rets_0_RetVal,rets_1_RetVal"}} { %graph:2 = tf_executor.graph {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 25 12:28:56 UTC 2022 - 3.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/shape-attrs.pbtxt
type: DT_INT32 type: DT_INT64 } } } } node { name: "MultiDeviceIteratorGetNextFromShard" op: "MultiDeviceIteratorGetNextFromShard" input: "args_2" input: "args_3" input: "args_4" attr { key: "output_shapes" value { list { shape { dim { size: 5 } dim { size: 40
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Dec 04 18:02:53 UTC 2020 - 5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/graph-as-function.pbtxt
# CHECK-SAME: allow_soft_placement # CHECK-SAME: control_outputs = "" # CHECK-SAME: inputs = "args_0,args_1,args_2,args_3" # CHECK-SAME: outputs = "rets_0,rets_1" # CHECK: %[[ISLAND_0:.*]], %[[ISLAND_0_control:.*]] = tf_executor.island wraps "tf.Const" # CHECK: %[[ISLAND_1:.*]], %[[ISLAND_1_control:.*]] = tf_executor.island wraps "tf.Identity"(%[[ISLAND_0]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 24 00:18:34 UTC 2023 - 5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/decompose_reduce_dataset.mlir
// CHECK-NEXT: "tf.MakeIterator"(%[[ARG_0]], %[[ANON_ITER]]) // CHECK-NEXT: %[[COND:.*]] = "tf.Const" // CHECK-NEXT: %[[WHILE:[0-9]*]]:5 = "tf.WhileRegion"(%[[COND]], %[[ARG_1]], %[[ARG_2]], %[[ARG_3]], %[[ARG_4]]) // CHECK-NEXT: ^bb0(%[[ARG_5:.*]]: tensor<i1>, %[[ARG_6:.*]]: tensor<i64>, %[[ARG_7:.*]]: tensor<i32>, %[[ARG_8:.*]]: tensor<!tf_type.resource<tensor<64xf32>>>, %[[ARG_9:.*]]: tensor<!tf_type.resource<tensor<128xf32>>>)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Aug 18 17:16:34 UTC 2022 - 9.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/shape_inference.mlir
%arg2: tensor<i32> {tf._user_specified_name = "args_2"}, %arg3: tensor<i32> {tf._user_specified_name = "args_3"}, %arg4: tensor<?x!tf_type.string> {tf._user_specified_name = "args_4"}, %arg5: tensor<?x!tf_type.string> {tf._user_specified_name = "args_5"}, %arg6: tensor<?x!tf_type.string> {tf._user_specified_name = "args_6"}, %arg7: tensor<?x?x512xf32> {tf._user_specified_name = "args_7"}, %arg8: tensor<?x?xf32> {tf._user_specified_name = "args_8"}, %arg9: tensor<?x300xi32> {tf._user_specified_name = "args_9"},...
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jan 23 17:24:10 UTC 2024 - 167.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/sparsecore/embedding_pipelining.cc
// Start step 0 C_0 = cond(args_0) N_0 = non_tpu(args_0) if (C_0) { F_0 = forward(args_0, N_0) T_0 = core_tpu(args_0, N_0, F_0) // B_0 = backward() is not evaluated here. } args_1 = update_args(args_0, N_0, T_0) // Start step 1 C_1 = cond(args_1) N_1 = non_tpu(args_1) if (C_1) { F_1 = forward(args_1, N_1) // T_1 = core_tpu() is not evaluated here.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 92.9K bytes - Viewed (0) -
src/cmd/vendor/golang.org/x/arch/arm64/arm64asm/tables.go
// FMADD <Sd>, <Sn>, <Sm>, <Sa> {0xffe08000, 0x1f000000, FMADD, instArgs{arg_Sd, arg_Sn, arg_Sm, arg_Sa}, nil}, // FMADD <Dd>, <Dn>, <Dm>, <Da> {0xffe08000, 0x1f400000, FMADD, instArgs{arg_Dd, arg_Dn, arg_Dm, arg_Da}, nil}, // FMAX <Sd>, <Sn>, <Sm> {0xffe0fc00, 0x1e204800, FMAX, instArgs{arg_Sd, arg_Sn, arg_Sm}, nil}, // FMAX <Dd>, <Dn>, <Dm>
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Wed Aug 16 17:57:48 UTC 2017 - 211.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/device-arg-retval-attr.pbtxt
# Verify arg and ret devices are added as arg and ret attributes. # CHECK-LABEL: func @main # CHECK-SAME: (%[[ARG_0:[a-z0-9]+]]: tensor<*xf32> {tf.device = "/CPU:0"}, %[[ARG_1:[a-z0-9]+]]: tensor<2x4x6x8xi32>) -> (tensor<*xf32>, tensor<*xi32> {tf.device = "/CPU:1"}) node { name: "args_0" op: "_Arg" device: "/CPU:0" attr { key: "T" value { type: DT_FLOAT } } attr {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Dec 07 17:45:22 UTC 2020 - 1.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/mlir2graphdef/device-arg-retval-attr.mlir
func.func @main(%arg0: tensor<*xf32> {tf.device = "/CPU:0"}, %arg1: tensor<2x4x6x8xi32>) -> (tensor<*xf32>, tensor<2x4x6x8xi32> {tf.device = "/CPU:1"}) attributes {tf.entry_function = {inputs = "args_0,args_1", outputs = "rets_0,rets_1"}} { %0:2 = tf_executor.graph {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 25 12:28:56 UTC 2022 - 1.8K bytes - Viewed (0) -
src/cmd/vendor/golang.org/x/arch/arm/armasm/decode.go
continue Search } var args Args for j, aop := range f.args { if aop == 0 { break } arg := decodeArg(aop, x) if arg == nil { // cannot decode argument continue Search } args[j] = arg } decoderCover[i] = true inst = Inst{ Op: op, Args: args, Enc: x, Len: 4, } priority = f.priority
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Tue Nov 22 17:16:14 UTC 2022 - 12.6K bytes - Viewed (0)