experiments/STT-tensorflow
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NFC: Remove unnecessary CHECK-EMPTY lines.

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These don't test anything useful in these tests.

PiperOrigin-RevId: 257279580
This commit is contained in:
A. Unique TensorFlower 2019-07-09 15:05:43 -07:00 committed by TensorFlower Gardener
parent ac6a943173
commit 449c70062f
7 changed files with 13 additions and 26 deletions
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3
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/graph-device-retval.pbtxt
View File

@ -91,8 +91,7 @@ versions {
# CHECK-NEXT: %0:2 = "_tf.PartitionedCall"() {Tin = [], Tout = ["tfdtype$DT_INT32"], config = "", config_proto = "", device = "", executor_type = "", f = @foo0, name = "PartitionedCall"} : () -> (tensor<*xi32>, !_tf.control)
# CHECK-NEXT: return
# CHECK-NEXT: }
# CHECK-EMPTY:
# CHECK-NEXT: func @foo0() -> tensor<i32>
# CHECK: func @foo0() -> tensor<i32>
# CHECK-NEXT: attributes {tf.experimental_ints_on_device = true} {
# CHECK-NEXT: %0:2 = "_tf.Const"() {device = "", dtype = "tfdtype$DT_INT32", name = "Const", value = dense<5> : tensor<i32>} : () -> (tensor<i32>, !_tf.control)
# CHECK-NEXT: %1:2 = "_tf.Identity"(%0#0) {T = "tfdtype$DT_INT32", device = "", name = "Identity"} : (tensor<i32>) -> (tensor<i32>, !_tf.control)

6
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/graph-func-attr.pbtxt
View File

@ -157,13 +157,11 @@ versions {
# CHECK-NEXT: %1:2 = "_tf.Case"(%0#0) {Tin = [], Tout = ["tfdtype$DT_FLOAT"], branches = [@foo0, @bar0], device = "", name = "Case", output_shapes = []} : (tensor<i32>) -> (tensor<*xf32>, !_tf.control)
# CHECK-NEXT: return
# CHECK-NEXT: }
# CHECK-EMPTY:
# CHECK-NEXT: func @foo0() -> tensor<10xf32> {
# CHECK: func @foo0() -> tensor<10xf32> {
# CHECK-NEXT: %0:2 = "_tf.Const"() {device = "", dtype = "tfdtype$DT_FLOAT", name = "const_1", value = dense<1.000000e+00> : tensor<10xf32>} : () -> (tensor<10xf32>, !_tf.control)
# CHECK-NEXT: return %0#0 : tensor<10xf32>
# CHECK-NEXT: }
# CHECK-EMPTY:
# CHECK-NEXT: func @bar0() -> tensor<10xf32> {
# CHECK: func @bar0() -> tensor<10xf32> {
# CHECK-NEXT: %0:2 = "_tf.Const"() {device = "", dtype = "tfdtype$DT_FLOAT", name = "const_2", value = dense<2.000000e+00> : tensor<10xf32>} : () -> (tensor<10xf32>, !_tf.control)
# CHECK-NEXT: return %0#0 : tensor<10xf32>
# CHECK-NEXT: }

6
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/graph-function-defs.pbtxt
View File

@ -526,14 +526,12 @@ versions {
# CHECK-NEXT: %18:2 = "_tf.Identity"(%17#0, %6) {T = "tfdtype$DT_INT32", device = "", name = "output_1_shard_0"} : (tensor<*xi32>, !_tf.control) -> (tensor<*xi32>, !_tf.control)
# CHECK-NEXT: return
# CHECK-NEXT: }
# CHECK-EMPTY:
# CHECK-NEXT: func @cond_false0(%arg0: tensor<*xi32>, %arg1: tensor<*xi32>) -> (tensor<*xi32>, tensor<*xi32>) {
# CHECK: func @cond_false0(%arg0: tensor<*xi32>, %arg1: tensor<*xi32>) -> (tensor<*xi32>, tensor<*xi32>) {
# CHECK-NEXT: %0:2 = "_tf.Identity"(%arg0) {T = "tfdtype$DT_INT32", device = "", name = "Identity"} : (tensor<*xi32>) -> (tensor<*xi32>, !_tf.control)
# CHECK-NEXT: %1:2 = "_tf.Identity"(%arg1) {T = "tfdtype$DT_INT32", device = "", name = "Identity_1"} : (tensor<*xi32>) -> (tensor<*xi32>, !_tf.control)
# CHECK-NEXT: return %1#0, %0#0 : tensor<*xi32>, tensor<*xi32>
# CHECK-NEXT: }
# CHECK-EMPTY:
# CHECK-NEXT: func @cond_true0(%arg0: tensor<*xi32>, %arg1: tensor<*xi32>) -> (tensor<*xi32>, tensor<*xi32>) {
# CHECK: func @cond_true0(%arg0: tensor<*xi32>, %arg1: tensor<*xi32>) -> (tensor<*xi32>, tensor<*xi32>) {
# CHECK-NEXT: %0:2 = "_tf.Identity"(%arg0) {T = "tfdtype$DT_INT32", device = "", name = "Identity"} : (tensor<*xi32>) -> (tensor<*xi32>, !_tf.control)
# CHECK-NEXT: %1:2 = "_tf.Identity"(%arg1) {T = "tfdtype$DT_INT32", device = "", name = "Identity_1"} : (tensor<*xi32>) -> (tensor<*xi32>, !_tf.control)
# CHECK-NEXT: return %0#0, %1#0 : tensor<*xi32>, tensor<*xi32>

6
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/graph-function-static-output.pbtxt
View File

@ -145,12 +145,10 @@ versions {
#CHECK-NEXT: %2:2 = "_tf.If"(%0#0, %1#0) {Tcond = "tfdtype$DT_BOOL", Tin = ["tfdtype$DT_INT32"], Tout = ["tfdtype$DT_INT32"], device = "", else_branch = @get_zeros0, name = "If", output_shapes = [], then_branch = @identity0} : (tensor<*xi1>, tensor<*xi32>) -> (tensor<*xi32>, !_tf.control)
#CHECK-NEXT: return
#CHECK-NEXT: }
#CHECK-EMPTY:
#CHECK-NEXT: func @get_zeros0(%arg0: tensor<*xi32>) -> tensor<2xi32> {
#CHECK: func @get_zeros0(%arg0: tensor<*xi32>) -> tensor<2xi32> {
#CHECK-NEXT: %0:2 = "_tf.Const"() {device = "", dtype = "tfdtype$DT_INT32", name = "const", value = dense<[1, 2]> : tensor<2xi32>} : () -> (tensor<2xi32>, !_tf.control)
#CHECK-NEXT: return %0#0 : tensor<2xi32>
#CHECK-NEXT: }
#CHECK-EMPTY:
#CHECK-NEXT: func @identity0(%arg0: tensor<*xi32>) -> tensor<*xi32> {
#CHECK: func @identity0(%arg0: tensor<*xi32>) -> tensor<*xi32> {
#CHECK-NEXT: return %arg0 : tensor<*xi32>
#CHECK-NEXT: }

6
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/graph-functional-while-loop.pbtxt
View File

@ -303,16 +303,14 @@ versions {
# CHECK-NEXT: %3:4 = "_tf.While"(%1#0, %2#0, %0#0) {T = ["tfdtype$DT_INT32", "tfdtype$DT_INT32", "tfdtype$DT_INT32"], _lower_using_switch_merge = true, body = @while_body_60, cond = @while_cond_50, device = "", name = "while", output_shapes = ["tfshape$", "tfshape$", "tfshape$"], parallel_iterations = 10 : i64} : (tensor<i32>, tensor<i32>, tensor<i32>) -> (tensor<i32>, tensor<i32>, tensor<i32>, !_tf.control)
# CHECK-NEXT: return %3#2 : tensor<i32>
# CHECK-NEXT: }
# CHECK-EMPTY:
# CHECK-NEXT: func @while_body_60(%arg0: tensor<*xi32>, %arg1: tensor<*xi32>, %arg2: tensor<*xi32>) -> (tensor<*xi32>, tensor<*xi32>, tensor<*xi32>) {
# CHECK: func @while_body_60(%arg0: tensor<*xi32>, %arg1: tensor<*xi32>, %arg2: tensor<*xi32>) -> (tensor<*xi32>, tensor<*xi32>, tensor<*xi32>) {
# CHECK-NEXT: %0:2 = "_tf.Const"() {device = "", dtype = "tfdtype$DT_INT32", name = "Add/y", value = dense<1> : tensor<i32>} : () -> (tensor<i32>, !_tf.control)
# CHECK-NEXT: %1:2 = "_tf.Const"() {device = "", dtype = "tfdtype$DT_INT32", name = "add_1/y", value = dense<1> : tensor<i32>} : () -> (tensor<i32>, !_tf.control)
# CHECK-NEXT: %2:2 = "_tf.Add"(%arg2, %0#0) {T = "tfdtype$DT_INT32", device = "", name = "Add"} : (tensor<*xi32>, tensor<i32>) -> (tensor<*xi32>, !_tf.control)
# CHECK-NEXT: %3:2 = "_tf.Add"(%arg0, %1#0) {T = "tfdtype$DT_INT32", device = "", name = "add_1"} : (tensor<*xi32>, tensor<i32>) -> (tensor<*xi32>, !_tf.control)
# CHECK-NEXT: return %3#0, %arg1, %2#0 : tensor<*xi32>, tensor<*xi32>, tensor<*xi32>
# CHECK-NEXT: }
# CHECK-EMPTY:
# CHECK-NEXT: func @while_cond_50(%arg0: tensor<*xi32>, %arg1: tensor<*xi32>, %arg2: tensor<*xi32>) -> tensor<*xi1> {
# CHECK: func @while_cond_50(%arg0: tensor<*xi32>, %arg1: tensor<*xi32>, %arg2: tensor<*xi32>) -> tensor<*xi1> {
# CHECK-NEXT: %0:2 = "_tf.Const"() {device = "", dtype = "tfdtype$DT_INT32", name = "Less/y", value = dense<10> : tensor<i32>} : () -> (tensor<i32>, !_tf.control)
# CHECK-NEXT: %1:2 = "_tf.Less"(%arg2, %0#0) {T = "tfdtype$DT_INT32", device = "", name = "Less"} : (tensor<*xi32>, tensor<i32>) -> (tensor<*xi1>, !_tf.control)
# CHECK-NEXT: return %1#0 : tensor<*xi1>

6
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/graph-gradient-def.pbtxt
View File

@ -279,14 +279,12 @@ versions {
# CHECK-NEXT: %5:2 = "_tf.SymbolicGradient"(%0#0, %4#0) {Tin = ["tfdtype$DT_FLOAT", "tfdtype$DT_FLOAT"], Tout = ["tfdtype$DT_FLOAT"], device = "", f = @foo0, f._disable_call_shape_inference = true, name = "gradients/foo_grad/SymbolicGradient"} : (tensor<f32>, tensor<*xf32>) -> (tensor<f32>, !_tf.control)
# CHECK-NEXT: return
# CHECK-NEXT: }
# CHECK-EMPTY:
# CHECK-NEXT: func @foo_grad0(%arg0: tensor<*xf32>, %arg1: tensor<*xf32>) -> tensor<*xf32>
# CHECK: func @foo_grad0(%arg0: tensor<*xf32>, %arg1: tensor<*xf32>) -> tensor<*xf32>
# CHECK-NEXT: attributes {tf._disable_call_shape_inference = true} {
# CHECK-NEXT: %0:2 = "_tf.Mul"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", device = "", name = "mul_0"} : (tensor<*xf32>, tensor<*xf32>) -> (tensor<*xf32>, !_tf.control)
# CHECK-NEXT: return %0#0 : tensor<*xf32>
# CHECK-NEXT: }
# CHECK-EMPTY:
# CHECK-NEXT: func @foo0(%arg0: tensor<*xf32>) -> tensor<*xf32>
# CHECK: func @foo0(%arg0: tensor<*xf32>) -> tensor<*xf32>
# CHECK-NEXT: attributes {tf._disable_call_shape_inference = true, tf.gradient = @foo_grad0} {
# CHECK-NEXT: %0:2 = "_tf.Exp"(%arg0) {T = "tfdtype$DT_FLOAT", device = "", name = "Exp"} : (tensor<*xf32>) -> (tensor<*xf32>, !_tf.control)
# CHECK-NEXT: %1:2 = "_tf.Neg"(%arg0) {T = "tfdtype$DT_FLOAT", device = "", name = "Neg"} : (tensor<*xf32>) -> (tensor<*xf32>, !_tf.control)

6
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/graph-library.pbtxt
View File

@ -41,12 +41,10 @@ versions {
# CHECK-NEXT: %1 = "_tf.bar0"() {device = "", name = "unnamed1"} : () -> !_tf.control
# CHECK-NEXT: return
# CHECK-NEXT: }
# CHECK-EMPTY:
# CHECK-NEXT: func @foo0() {
# CHECK: func @foo0() {
# CHECK-NEXT: %0 = "_tf.bar0"() {device = "", name = "unnamed"} : () -> !_tf.control
# CHECK-NEXT: return
# CHECK-NEXT: }
# CHECK-EMPTY:
# CHECK-NEXT: func @bar0() {
# CHECK: func @bar0() {
# CHECK-NEXT: return
# CHECK-NEXT: }