}

dependencies {
    testImplementation 'junit:junit:4.13'
}

// tag::test-filtering[]
test {
    filter {
        //include specific method in any of the tests
        includeTestsMatching "*UiCheck"

        //include all tests from package
        includeTestsMatching "org.gradle.internal.*"

        //include all integration tests
        includeTestsMatching "*IntegTest"
    }
}

}

dependencies {
    testImplementation("junit:junit:4.13")
}

// tag::test-filtering[]
tasks.test {
    filter {
        //include specific method in any of the tests
        includeTestsMatching("*UiCheck")

        //include all tests from package
        includeTestsMatching("org.gradle.internal.*")

        //include all integration tests
        includeTestsMatching("*IntegTest")
    }
}

# RUN: not tf-mlir-translate -graphdef-to-mlir -tf-enable-shape-inference-on-import=false %s -tf-input-arrays=input -tf-input-data-types=DT_FLOAT -tf-input-shapes='' -tf-output-arrays=input:1 -o - 2>&1 | FileCheck %s

# CHECK: Invalid output index 1 specified for node: input

node {
  name: "input"
  op: "Placeholder"
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer --emit-stablehlo-ops=true %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir --disable-vhlo-to-stablehlo=true - -o - | FileCheck %s
// test stablehlo roundtrip

module {
func.func @main(%arg0: tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32> {
  %0 = "vhlo.logistic_v1"(%arg0) : (tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32>
  %1 = "tfl.exp"(%0) : (tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32> loc("exp")

// RUN: tf-opt %s -split-input-file -tf-verify-for-export -verify-diagnostics | FileCheck %s

module {
  func.func @failsNoIslands() {
    // expected-error @+1 {{functions must be of a single Graph with single op Islands: first op in function is not a tf_executor.graph}}
    func.return
  }
}

// -----

module {
  // CHECK-LABEL: func @passesSingleIslandOp
  func.func @passesSingleIslandOp() {
    // CHECK: _class = ["loc:@class"]

# RUN: tf-mlir-translate -graphdef-to-mlir -tf-enable-shape-inference-on-import=false %s -o - | FileCheck %s

node {
  name: "unnamed"
  op: "foo"
  attr {
    key: "_output_shapes"
    value {
      list {
        shape {
        }
      }
    }
  }
  attr {
    key: "_disable_call_shape_inference"
    value {
      b: true
    }
  }
  experimental_debug_info {
  }
}
node {
  name: "unnamed1"

// RUN: tf-mlir-translate -mlir-to-graphdef %s -o - | FileCheck %s

module attributes {tf.versions = {bad_consumers = [], min_consumer = 12 : i32, producer = 29 : i32}} {
  func.func @main() {
    tf_executor.graph {
      %0 = tf_executor.island wraps "tf.PartitionedCall"() {Tin = [], Tout = [], config = "", config_proto = "", device = "", executor_type = "", f = @foo, name = "Call_foo"} : () -> ()
      tf_executor.fetch
    }
    func.return
  }

// RUN: tf-opt %s -split-input-file -verify-diagnostics | FileCheck %s

// Tests for TensorFlow TFRT ops with custom verifiers.

//===--------------------------------------------------------------------===//
//  Test TF operations (tf.*)
//===--------------------------------------------------------------------===//

// CHECK-LABEL: func @testPwStreamResults
func.func @testPwStreamResults(%arg0: tensor<f32>, %arg1: tensor<f32>) {

// RUN: tf-opt --tfl-legalize-tf-while %s -o - | flatbuffer_translate -mlir-to-tflite-flatbuffer - -o -  | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s

// CHECK-LABEL: main
func.func @main(%arg0: tensor<*xf32>) -> tensor<*xf32> {
  // CHECK:     %{{.*}} = tfl.add %{{.*}}, %{{.*}} {fused_activation_function = "NONE"} : tensor<*xf32>
  // CHECK:     return %{{.*}} : tensor<*xf32>

// RUN: odml-to-stablehlo-opt %s -tfl-parse-stablehlo-ops | FileCheck -dump-input always %s

module {
  func.func @main() -> tensor<1xi64> {
  %0 = "tfl.custom"() {custom_code = "stablehlo.constant", custom_option = #tfl<const_bytes : "0x76616C75650001020109010101062C022401">} : () -> tensor<1xi64>
  func.return %0 : tensor<1xi64>
  }
}

// CHECK:  module {
// CHECK-NEXT:    func @main() -> tensor<1xi64> {