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tensorflow/compiler/mlir/tensorflow/tests/stack_ops_decomposition.mlir
%max_size = "tf.Const"() {value = dense<10> : tensor<i32>} : () -> tensor<i32> %stack = "tf.StackV2"(%max_size) {elem_type = f32, stack_name = "s"} : (tensor<i32>) -> tensor<!tf_type.resource> %stack2 = "tf.StackV2"(%max_size) {elem_type = f32, stack_name = "s2"} : (tensor<i32>) -> tensor<!tf_type.resource> %if_op = "tf.If"(%arg0, %stack, %stack2) {then_branch = @if_then, else_branch = @if_else, is_stateless = false}
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 25.8K bytes - Viewed (0) -
src/runtime/testdata/testprogcgo/stackswitch.c
// allocation won't accidentally count as in bounds of the first stack #define STACK_SIZE (64ull << 10) static ucontext_t uctx_save, uctx_switch; extern void stackSwitchCallback(void); char *stack2; static void *stackSwitchThread(void *arg) { // Simple test: callback works from the normal system stack. stackSwitchCallback(); // Next, verify that switching stacks doesn't break callbacks.
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu Oct 26 15:17:33 UTC 2023 - 3.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/convert_control_to_data_outputs.mlir
// Tests loop with resource that is unique per iteration. // // In cases where a resource-allocating op creates a new unique resource per // loop iteration (ops with `TF_UniqueResourceAllocation` trait, in this case: // `tf.StackV2`), make sure that we don't create data dependencies between // different iterations for such resources. This is in line with the behavior // for the same loop unrolled. In this particular case, no data chain and token
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 18:35:00 UTC 2024 - 68.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/canonicalize.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/side-effect-analysis-test.mlir
// expected-remark@above {{ID: 5}} // expected-remark@above {{Successors: {6}}} %stack_handle1 = "tf.StackV2"(%arg0) {elem_type = f32, stack_name = "s"} : (tensor<i32>) -> tensor<!tf_type.resource> // expected-remark@above {{ID: 0}} %stack_handle2 = "tf.StackV2"(%arg0) {elem_type = f32, stack_name = "s"} : (tensor<i32>) -> tensor<!tf_type.resource> // expected-remark@above {{ID: 1}}
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 20 04:39:18 UTC 2023 - 129.7K bytes - Viewed (0) -
tensorflow/compiler/jit/mark_for_compilation_pass.cc
"SpaceToBatch", "SpaceToBatchND", "SpaceToDepth", "SparseMatMul", "SparseToDense", "StackCloseV2", "StackPopV2", "StackPushV2", "StackV2", "StatefulPartitionedCall", "StatefulStandardNormalV2", "StatefulTruncatedNormal", "StatefulUniform", "StatefulUniformFullInt", "StatefulUniformInt",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 12:19:41 UTC 2024 - 85.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.td
maximum size needs to be a constant and 2) a push op can be found with a known shape, and all push ops need to have the same shape. A stack creation op "tf.StackV2" will be turned in to two zero-initialized variables, for the buffer and current size. Each push will be turned into ```mlir %old_val = "tf.ReadVariableOp"(%buffer) %old_size = "tf.ReadVariableOp"(%size)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:18:05 UTC 2024 - 99.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
let results = (outs Res<TF_Tensor, [{The same tensor as the input 'elem'.}]>:$output ); TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<1>; } def TF_StackV2Op : TF_Op<"StackV2", [TF_UniqueResourceAllocation]> { let summary = "A stack that produces elements in first-in last-out order."; let arguments = (ins
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0)