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Results 11 - 20 of 31 for allow_soft_placement (0.3 sec)
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tensorflow/compiler/mlir/tensorflow/tests/end-to-end-tpu-reshard-variables.mlir
%0 = tf_executor.graph { %outputs, %control = tf_executor.island {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Mar 13 21:23:47 UTC 2024 - 4.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/graph_pruning_preserve_ops.mlir
// CHECK: "tf.NoOp" %1 = tf_executor.island wraps "tf.NoOp"() : () -> () // CHECK: "tf.TPUReplicateMetadata"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 28 12:06:33 UTC 2022 - 3.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/convert_tpu_model_to_cpu.mlir
%0 = "tf.Cast"(%arg0) {Truncate = false, device = ""} : (tensor<1x3x4x3xf32>) -> tensor<1x3x4x3xbf16>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 4.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/graph-as-function.pbtxt
# CHECK-SAME: _xla_compile_device_type = "GPU" # 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"
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/tf2xla/internal/passes/clustering_passes.td
%0 = "tf_device.cluster"() ( { %1 = "tf.UnsupportedOp"() : () -> tensor<i32> %2 = "tf.Identity"(%1) : (tensor<i32>) -> tensor<i32> tf_device.return %2 : tensor<i32> }) {allow_soft_placement = true, num_cores_per_replica = 1, topology = "", device_assignment = []} : () -> tensor<i32> return %0 : tensor<i32> } ```
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 02:01:13 UTC 2024 - 19.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/utils/attribute_utils.h
// Whether soft placement is allowed. If true, the marked node is eligible for // outside compilation. inline constexpr llvm::StringRef kAllowSoftPlacementAttr = "allow_soft_placement"; // Marks a node for XLA compilation. The attribute value indicates the // compilation device type. inline constexpr llvm::StringRef kCompileDeviceTypeAttr = "_xla_compile_device_type";
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 22 19:47:48 UTC 2024 - 8.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v2/testdata/outside_compilation.mlir
func.func @main(%arg0: tensor<*x!tf_type.resource> {tf._user_specified_name = "input_1", tf.device = "/job:localhost/replica:0/task:0/device:CPU:0"}) attributes {allow_soft_placement = true, tf.entry_function = {control_outputs = "while,image_sample/write_summary/summary_cond", inputs = "image_sample_write_summary_summary_cond_input_1", outputs = ""}} { tf_executor.graph {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Oct 19 20:19:45 UTC 2023 - 21.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/tf2xla_rewriter_test.cc
module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 1610 : i32}} { func.func @main(%arg0: tensor<3x3x10xbf16>, %arg1: tensor<3xi32>) -> tensor<1x?x4xbf16> attributes {allow_soft_placement = false, tf.entry_function = {control_outputs = "", inputs = "_arg0,_arg1,_arg2", outputs = "_retval0"}} { %cst = "tf.Const"() {value = dense<[1, -1, 4]> : tensor<3xi32>} : () -> tensor<3xi32>
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/mlir/tensorflow/tests/tpu_space_to_depth_pass.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 37.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v2/testdata/func_with_dead_ops.mlir
= "/job:tpu_host_worker/replica:0/task:0/device:CPU:0"}, %arg21: tensor<*x!tf_type.resource<tensor<1024x1xf32>>> {tf._user_specified_name = "939", tf.device = "/job:tpu_host_worker/replica:0/task:0/device:CPU:0"}) -> tensor<i64> attributes {allow_soft_placement = false, tf.entry_function = {control_outputs = "", inputs = "steps,unknown,unknown_0,unknown_1,unknown_2,unknown_3,unknown_4,unknown_5,unknown_6,unknown_7,unknown_8,unknown_9,unknown_10,unknown_11,unknown_12,unknown_13,unknown_14,unknown_...
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 13 23:22:50 UTC 2024 - 15.3K bytes - Viewed (0)