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/external/tensorflow/tensorflow/compiler/mlir/tensorflow/tests/
Dtf_executor_ops.mlir3 // CHECK-LABEL: func private @control_type() -> !tf_executor.control
4 func private @control_type() -> !tf_executor.control
6 // CHECK-LABEL: func private @token_type() -> !tf_executor.token
7 func private @token_type() -> !tf_executor.token
11 tf_executor.graph {
15 // CHECK: tf_executor.graph {
16 // CHECK-NEXT: tf_executor.fetch
23 %result = tf_executor.graph {
24 tf_executor.fetch %0 : tensor<*xf32>
31 %result = tf_executor.graph {
[all …]
Dexecutor_island_coarsening.mlir8 %0 = tf_executor.graph {
9 %1:2 = tf_executor.island {
11 tf_executor.yield %3 : tensor<i1>
13 %2:2 = tf_executor.island(%1#1) {
15 tf_executor.yield %4 : tensor<f32>
17 tf_executor.fetch %2#0 : tensor<f32>
22 // CHECK: %[[ISLAND:.*]], %[[ISLAND_control:.*]] = tf_executor.island {
25 // CHECK-NEXT: tf_executor.yield %[[OP_B]] : tensor<f32>
26 // CHECK: tf_executor.fetch %[[ISLAND]] : tensor<f32>
33 %0 = tf_executor.graph {
[all …]
Dtf_executor_ops_invalid.mlir3 func @invalid_type() -> !tf_executor.foobar
4 // expected-error@-1 {{unknown tf_executor type: foobar}}
8 // Check that tf_executor.graph does not accept any operand.
10 "tf_executor.graph" (%arg0) ({}) : (tensor<*xf32>) -> ()
11 // expected-error@-1 {{'tf_executor.graph' op requires zero operands}}
19 "tf_executor.graph" () ({
20 // expected-error@-1 {{'tf_executor.graph' op region #0 ('body') failed to verify constraint: regio…
29 "tf_executor.graph" () ({
30 // expected-error@-1 {{'tf_executor.graph' op expects a non-empty block}}
38 // Check that only tf_executor operations can be present in a tf_executor.graph.
[all …]
Dparallel_execute_to_islands.mlir5 tf_executor.graph {
6 tf_executor.island() {
12 tf_executor.yield
14 tf_executor.fetch
19 // CHECK: [[ISLAND_0_CTRL:%.+]] = tf_executor.island {
20 // CHECK: tf_executor.yield
21 // CHECK: [[ISLAND_1_CTRL:%.+]] = tf_executor.island {
22 // CHECK: tf_executor.yield
23 // CHECK: tf_executor.fetch [[ISLAND_0_CTRL]], [[ISLAND_1_CTRL]] :
29 %0:2 = tf_executor.graph {
[all …]
Dgraph_pruning.mlir9 %0 = tf_executor.graph {
10 %1:2 = tf_executor.island {
11 tf_executor.yield %arg0 : i32
13 %2:2 = tf_executor.island {
14 tf_executor.yield %1#0 : i32
16 tf_executor.fetch %2#0 : i32
24 // CHECK: tf_executor.island
25 // CHECK-NOT: tf_executor.island
26 %0 = tf_executor.graph {
27 %1:2 = tf_executor.island {
[all …]
Dbreakup-islands.mlir11 %graph:2 = tf_executor.graph {
12 %island:3 = tf_executor.island {
15 tf_executor.yield %add1, %add2 : tensor<*xi32>, tensor<*xi32>
17 tf_executor.fetch %island#0, %island#1 : tensor<*xi32>, tensor<*xi32>
23 // CHECK: %[[GRAPH:.*]]:2 = tf_executor.graph {
24 // CHECK: %[[ADD1:.*]], %[[ADD1_control:.*]] = tf_executor.island wraps "tf.Add"(%arg0, %arg1)
25 // CHECK: %[[ADD2:.*]], %[[ADD2_control:.*]] = tf_executor.island wraps "tf.Add"(%[[ADD1]], %ar…
26 // CHECK: tf_executor.fetch %[[ADD1]], %[[ADD2]] :
32 %graph:2 = tf_executor.graph {
33 %island1:3 = tf_executor.island {
[all …]
Dexecutor_canonicalize.mlir8 tf_executor.graph {
9 %1:2 = tf_executor.island {
12 tf_executor.yield %3 : tensor<i1>
14 tf_executor.fetch
28 %0:3 = tf_executor.graph {
29 %1:4 = tf_executor.island {
33 tf_executor.yield %3, %5, %4 : tensor<i1>, tensor<i1>, tensor<i1>
35 tf_executor.fetch %1#1, %1#0, %1#2 : tensor<i1>, tensor<i1>, tensor<i1>
50 %0:3 = tf_executor.graph {
51 %1:4 = tf_executor.island {
[all …]
Dreplicate_to_island.mlir7 tf_executor.graph {
8 %1 = tf_executor.ControlTrigger {}
9 %2 = tf_executor.ControlTrigger {}
10 %3 = tf_executor.island(%1, %2) {
14 tf_executor.yield
16 tf_executor.fetch
21 // CHECK: %[[CT_0:.*]] = tf_executor.ControlTrigger
22 // CHECK: %[[CT_1:.*]] = tf_executor.ControlTrigger
23 // CHECK: %{{.*}} = tf_executor.island(%[[CT_0]], %[[CT_1]])
24 // CHECK: %{{.*}} = tf_executor.island(%[[CT_0]], %[[CT_1]])
[all …]
Dgraph_pruning_preserve_ops.mlir7 tf_executor.graph {
8 %0 = tf_executor.ControlTrigger {}
10 %1 = tf_executor.island wraps "tf.NoOp"() : () -> ()
12 …%2 = tf_executor.island(%1) wraps "tf.TPUReplicateMetadata"() {allow_soft_placement = false, compu…
13 tf_executor.fetch %0 : !tf_executor.control
20 tf_executor.graph {
21 %0 = tf_executor.ControlTrigger {}
23 %1 = tf_executor.island wraps "tf.NoOp"() : () -> ()
25 %2, %3 = tf_executor.island(%1) wraps "tf.TPUCompilationResult"() : () -> tensor<!tf.string>
26 tf_executor.fetch %0 : !tf_executor.control
[all …]
Dtf-functional-to-executor.mlir11 // CHECK: %[[GRAPH_RESULT:.*]]:2 = tf_executor.graph {
12 // CHECK: %[[ISLAND_RESULT:.*]]:2, {{.*}} = tf_executor.island {
15 // CHECK: tf_executor.yield %[[ADD1]], %[[ADD2]] : tensor<*xi32>, tensor<*xi32>
17 // CHECK: tf_executor.fetch %[[ISLAND_RESULT]]#0, %[[ISLAND_RESULT]]#1 : tensor<*xi32>, tensor<…
26 // CHECK: tf_executor.graph {
27 // CHECK: %[[CONTROL:.*]] = tf_executor.island {
28 // CHECK: tf_executor.yield
30 // CHECK: tf_executor.fetch %[[CONTROL]] : !tf_executor.control
35 tf_executor.graph {
36 %control = tf_executor.island {
[all …]
Dresource-device-inference.mlir12 tf_executor.graph {
13 // CHECK: tf_executor.island
14 %island = tf_executor.island {
32 tf_executor.yield
34 tf_executor.fetch %island : !tf_executor.control
48 tf_executor.graph {
49 // CHECK: tf_executor.island
50 %island = tf_executor.island {
65 tf_executor.yield
67 tf_executor.fetch %island : !tf_executor.control
[all …]
Dtf-executor-to-functional.mlir4 tf_executor.graph {
5 …/ expected-error@+1 {{'tf_executor.ControlTrigger' op is not supported for lifting out of tf_execu…
6 %control = tf_executor.ControlTrigger {}
7 tf_executor.fetch
17 tf_executor.graph {
18 tf_executor.fetch
26 tf_executor.graph {
27 %control = tf_executor.island {
28 tf_executor.yield
30 tf_executor.fetch
[all …]
Dtpu_device_propagation.mlir9 %0 = tf_executor.graph {
10 tf_executor.fetch %arg0 : tensor<i64>
21 %0 = tf_executor.graph {
24 %1:2 = tf_executor.island wraps "tf.Identity"(%arg0) : (tensor<i64>) -> tensor<i64>
25 tf_executor.fetch %1#0 : tensor<i64>
34 %0:2 = tf_executor.graph {
37 …%1:3 = tf_executor.island wraps "tf.IdentityN"(%arg0, %arg1) : (tensor<i64>, tensor<i32>) -> (tens…
38 tf_executor.fetch %1#0, %1#1 : tensor<i64>, tensor<i32>
47 %0 = tf_executor.graph {
50 %1:2 = tf_executor.island wraps "tf.Shape"(%arg0) : (tensor<*xi64>) -> tensor<?xi64>
[all …]
Dtf_executor_ops_printer.mlir3 // Tests printer for tf_executor.island "wraps" short form.
7 tf_executor.graph {
8 // CHECK: tf_executor.island wraps "tf.IdentityN"
9 %0:3 = tf_executor.island {
11 tf_executor.yield %1#0, %1#1 : tensor<i32>, tensor<f32> loc("identity@some_function")
13 tf_executor.fetch
20 tf_executor.graph {
21 // CHECK: tf_executor.island
23 %0:3 = tf_executor.island {
25 tf_executor.yield %1#1, %1#0 : tensor<f32>, tensor<i32> loc("identity@some_function")
[all …]
Dtf_executor_ops_location_roundtrip.mlir16 // This test case exercises the "tf_executor.island wraps" syntax.
18 // tf_executor.island, tf.Identity, and tf_executor.yield).
21 // CHECK: "tf_executor.graph"() ( {
22 // CHECK-NEXT: "tf_executor.island"() ( {
24 // CHECK-NEXT: "tf_executor.yield"(%{{.*}}) : (tensor<f32>) -> () loc("identity@some_functio…
25 // CHECK-NEXT: }) : () -> (tensor<f32>, !tf_executor.control) loc("identity@some_function")
26 // CHECK-NEXT: "tf_executor.fetch"(%{{.*}}) : (tensor<f32>) -> () loc(unknown)
32 %0 = "tf_executor.graph"() ( {
33 %1:2 = "tf_executor.island"() ( {
35 "tf_executor.yield"(%2) : (tensor<f32>) -> () loc("identity@some_function")
[all …]
Dlaunch_to_device_attribute.mlir8 tf_executor.graph {
9 %0:5 = tf_executor.island {
16 … tf_executor.yield %a, %launch#0, %launch#1, %c : tensor<i1>, tensor<f32>, tensor<i32>, tensor<i1>
18 tf_executor.fetch
28 // CHECK: tf_executor.yield %[[A]], %[[B]]#1, %[[B]]#0, %[[C]]
35 tf_executor.graph {
36 %0:5 = tf_executor.island {
44 … tf_executor.yield %a, %launch#0, %launch#1, %d : tensor<i1>, tensor<f32>, tensor<i32>, tensor<i1>
46 tf_executor.fetch
58 // CHECK: tf_executor.yield %[[A]], %[[C]], %[[B]], %[[D]]
[all …]
Dfunctionalize-if-fail.mlir7 tf_executor.graph {
8 …%0 = tf_executor.island wraps "tf._TPUReplicate"() {computation = @foo, Tinputs = [], Tbroadcast_i…
9 tf_executor.fetch
15 tf_executor.graph {
16 …%0:2 = tf_executor.island wraps "tf.Const"() {device = "", dtype = "tfdtype$DT_INT32", value = den…
17 …%1:2 = tf_executor.island wraps "tf.Const"() {device = "", dtype = "tfdtype$DT_BOOL", value = dens…
18 …%2:3 = tf_executor.Switch %0#0, %1#0 : (tensor<i32>, tensor<i1>) -> (tensor<i32>, tensor<i32>, !tf…
19 …%3:2 = tf_executor.island wraps "tf.Add"(%2#0, %2#1) {T = "tfdtype$DT_INT32", device = ""} : (tens…
20 …%4:2 = tf_executor.island wraps "tf.Mul"(%2#1, %2#0) {T = "tfdtype$DT_INT32", device = ""} : (tens…
21 …%5:3 = tf_executor.Merge %3#0, %4#0 : tensor<i32> {device = "", N = 2, T = "tfdtype$DT_INT32"} loc…
[all …]
/external/tensorflow/tensorflow/compiler/mlir/tensorflow/tests/mlir2graphdef/
Dswitchn.mlir5 "tf_executor.graph"() ( {
6 %outputs, %control = "tf_executor.island"() ( {
8 "tf_executor.yield"(%0) : (tensor<i32>) -> ()
9 }) : () -> (tensor<i32>, !tf_executor.control)
10 …tf_executor._SwitchN"(%outputs, %outputs) {T = i32, device = "", num_outs = 3 : i64} : (tensor<i32…
11 %outputs_2, %control_3 = "tf_executor.island"() ( {
13 "tf_executor.yield"(%0) : (tensor<*xi32>) -> ()
14 }) : () -> (tensor<*xi32>, !tf_executor.control)
15 %outputs_4, %control_5 = "tf_executor.island"(%control_3) ( {
17 "tf_executor.yield"(%0) : (tensor<f32>) -> ()
[all …]
Dinvalid_input.mlir22 … must be of a single Graph with single op Islands: first op in function is not a tf_executor.graph.
27 tf_executor.graph {
28 tf_executor.fetch
30 tf_executor.graph {
31 tf_executor.fetch
36 …f a single Graph with single op Islands: function does not only contain a single tf_executor.graph.
41 tf_executor.graph {
42 %0 = tf_executor.island {
43 tf_executor.yield
45 tf_executor.fetch
[all …]
Dwhile-loop.mlir11 tf_executor.graph {
12 …%0:3 = tf_executor.NextIteration.Source : tensor<*xi32> {device = "", T = "tfdtype$DT_INT32"} loc(…
13 …%1:2 = tf_executor.island wraps "tf.VariableV2"() {device = "", dtype = "tfdtype$DT_INT32", value …
14 …%2:2 = tf_executor.Enter %1#0 frame "while/while_context" parallel_iterations 10 : (tensor<i32>) -…
15 …%3:3 = tf_executor.Merge %2#0, %0#0 : tensor<*xi32> {device = "", N = 2, T = "tfdtype$DT_INT32"} l…
16 …%4:2 = tf_executor.island(%3#2) wraps "tf.Const"() {device = "", dtype = "tfdtype$DT_INT32", value…
17 …%5:2 = tf_executor.island wraps "tf.Less"(%3#0, %4#0) {device = "", T = "tfdtype$DT_INT32"} : (ten…
18 …%6:2 = tf_executor.LoopCond %5#0 : (tensor<*xi1>) -> (tensor<*xi1>, !tf_executor.control) {device …
19 …%7:3 = tf_executor.Switch %3#0, %6#0 : (tensor<*xi32>, tensor<*xi1>) -> (tensor<*xi32>, tensor<*xi…
20 …%8:2 = tf_executor.Exit %7#1 : tensor<*xi32> {device = "", T = "tfdtype$DT_INT32"} loc("while/Exit…
[all …]
Dref-while-loop.mlir10 tf_executor.graph {
11 …%0:3 = tf_executor.NextIteration.Source : tensor<*x!tf.int32ref> {device = "", T = "tfdtype$DT_INT…
12 …%1:2 = tf_executor.island wraps "tf.VariableV2"() {device = "", dtype = "tfdtype$DT_INT32", value …
13 …%2:2 = tf_executor.Enter %1#0 frame "while/while_context" parallel_iterations 10 : (tensor<!tf.int…
14 …%3:3 = tf_executor.Merge %2#0, %0#0 : tensor<*x!tf.int32ref> {device = "", N = 2, T = "tfdtype$DT_…
15 …%4:2 = tf_executor.island(%3#2) wraps "tf.Const"() {device = "", dtype = "tfdtype$DT_INT32", value…
16 …%5:2 = tf_executor.island(%3#2) wraps "tf.Const"() {device = "", dtype = "tfdtype$DT_BOOL", value …
17 …%6:2 = tf_executor.LoopCond %5#0 : (tensor<i1>) -> (tensor<i1>, !tf_executor.control) {device = ""…
18 …%7:3 = tf_executor.Switch %3#0, %6#0 : (tensor<*x!tf.int32ref>, tensor<i1>) -> (tensor<*x!tf.int32…
19 …%8:2 = tf_executor.Exit %7#1 : tensor<*x!tf.int32ref> {device = "", T = "tfdtype$DT_INT32"} loc("w…
[all …]
Dcase.mlir5 tf_executor.graph {
6 …%outputs, %control = tf_executor.island wraps "tf.Const"() {device = "", value = dense<1> : tensor…
7 …%outputs_0, %control_1 = tf_executor.island wraps "tf.Const"() {device = "", value = dense<0> : te…
8 …%outputs_2, %control_3 = tf_executor.island wraps "tf.Case"(%outputs_0, %outputs) {Tin = [i32], To…
9 …%outputs_4, %control_5 = tf_executor.island wraps "tf.Identity"(%outputs_2) {device = ""} : (tenso…
10 …%outputs_6, %control_7 = tf_executor.island wraps "tf.Case"(%outputs_0, %outputs) {Tin = [i32], To…
11 tf_executor.fetch
17 %0 = tf_executor.graph {
18 …%outputs, %control = tf_executor.island wraps "tf.Const"() {device = "", value = dense<1> : tensor…
19 …%outputs_0, %control_1 = tf_executor.island wraps "tf.AddV2"(%arg0, %outputs) {device = ""} : (ten…
[all …]
/external/tensorflow/tensorflow/compiler/mlir/tensorflow/tests/executor_tpuv1_island_coarsening/
Dexecutor_tpuv1_island_coarsening.mlir7 %0 = tf_executor.graph {
8 %1:2 = tf_executor.island {
10 tf_executor.yield %3 : tensor<i1>
12 %2:2 = tf_executor.island(%1#1) {
14 tf_executor.yield %4 : tensor<f32>
21 tf_executor.fetch %2#0 : tensor<f32>
29 tf_executor.graph {
34 …%outputs, %control = tf_executor.island wraps "tf.Const"() {_tpu_replicate = "cluster", value = de…
35 …%outputs_0, %control_1 = tf_executor.island wraps "tf.Const"() {_tpu_replicate = "cluster", value …
36 …%outputs_3, %control_4 = tf_executor.island wraps "tf.AddV2"(%outputs, %outputs_0) {_tpu_replicate…
[all …]
/external/tensorflow/tensorflow/compiler/mlir/tensorflow/g3doc/
Dtf_dialects.md12 the `tf_executor` dialect that represents the execution model of the TensorFlow
18 just the `tf` dialect, allowing us to phase out the `tf_executor` dialect in
82 The `tf_executor` dialect is intended to model the current TensorFlow executor
86 `tf_executor` dialect defines two dialect-specific types:
88 * `!tf_executor.control` to represent control dependencies.
89 * `!tf_executor.token` to represent the pair of operations modeling
92 The `tf_executor` dialect is closed (operations are all known to MLIR) as there
102 return an extra control token as output. Except for `tf_executor.Merge` and
103 `tf_executor.ControlTrigger`, operations are propagating deadness: if any of the
105 non-control) are dead as well. For `tf_executor.Merge`, the output is dead only
[all …]
/external/tensorflow/tensorflow/compiler/mlir/tensorflow/tests/tpu_bridge_v1/
Dend_to_end.mlir9 tf_executor.graph {
10 …%outputs, %control = tf_executor.island wraps "std.constant"() {value = dense<2.000000e+00> : tens…
11 …%outputs_0, %control_1 = tf_executor.island wraps "std.constant"() {value = dense<3.000000e+00> : …
12 …%control_2 = tf_executor.island wraps "tf.TPUReplicateMetadata"() {_tpu_replicate = "cluster", all…
13 …%outputs_3, %control_4 = tf_executor.island wraps "tf.Placeholder"() {device = "", dtype = "tfdtyp…
14 …%outputs_5, %control_6 = tf_executor.island wraps "tf.TPUReplicatedInput"(%outputs_3) {N = 1 : i64…
15 …%outputs_7, %control_8 = tf_executor.island wraps "tf.Identity"(%outputs_5) {T = "tfdtype$DT_FLOAT…
16 …%outputs_9, %control_10 = tf_executor.island wraps "tf.Mul"(%outputs_7, %outputs) {T = "tfdtype$DT…
17 …%outputs_11, %control_12 = tf_executor.island wraps "tf.Placeholder"() {device = "", dtype = "tfdt…
18 …%outputs_13, %control_14 = tf_executor.island wraps "tf.TPUReplicatedInput"(%outputs_11) {N = 1 : …
[all …]

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