node {
  name: "input0"
  op: "Placeholder"
  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }
}
versions {
  producer: 29
  min_consumer: 12
}

# Verify that functions from the library are properly imported.

# CHECK-LABEL:  func @main() {
# CHECK:    "tf.Placeholder"

    example:

    ```
    TEST_F(ArrayGradTest, IdentityGrad) {
      TensorShape shape({5, 2});
      auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(shape));
      auto y = Identity(scope_, x);
      RunTest(x, shape, y, shape);
    }
    ```

NOTE: There are some ops that require features from the C++ API that are not yet
implemented.

TEST(ClientSessionTest, CallableWithCustomThreadPool) {
  Scope root = Scope::NewRootScope();
  int num_threads = 3;

  TensorShape data_shape({1, 1});
  auto a = Placeholder(root, DT_INT32, Placeholder::Shape(data_shape));
  auto b = Placeholder(root, DT_INT32, Placeholder::Shape(data_shape));
  auto c = BatchMatMul(root, a, b);
  ClientSession session(root);
  std::vector<Tensor> outputs;

  auto inter_op_threadpool =

# CHECK: build_graph(out_dir)
node: {
  name: "x"
  op: "Placeholder"
  attr: {
    key: "shape"
    value: {
      shape: {
        dim: {
          size: -1
        }
      }
    }
  }
  attr: {
    key: "dtype"
    value: {
      type: DT_INT32
    }
  }
}
node: {
  name: "y"
  op: "Placeholder"
  attr: {
    key: "shape"
    value: {
      shape: {

// CHECK: "extra_type_attr"
// CHECK-NEXT:    value
// CHECK-NEXT:      list
// CHECK-NEXT:        type: DT_INT32
// CHECK-NEXT:        type: DT_FLOAT

// CHECK-LABEL: function
// CHECK: name: "plain"
// CHECK: Placeholder
// CHECK: key: "type"
// CHECK: type: DT_INT8

func.func @main(%arg0 : tensor<16xf32>) {
  tf_executor.graph {

        while (matcher.find()) {
            String placeholder = matcher.group(1);
            String replacement = placeholder.startsWith("env.") ? system.getEnv(placeholder.substring(4)) : system.getProperty(placeholder);
            if (replacement == null) {
                throw new CannotLocateLocalMavenRepositoryException(String.format("Cannot resolve placeholder '%s' in value '%s'", placeholder, value));
            }

      label: TensorFlow version
      placeholder: e.g., tf 2.8
    validations:
      required: true
  - type: dropdown
    id: Code
    attributes:
      label: Custom code
      options:
        - "Yes"
        - "No"
    validations:
      required: true
  - type: input
    id: OS
    attributes:
      label: OS platform and distribution
      placeholder: e.g., Linux Ubuntu 16.04
  - type: input

on(a,b){e.attr(a,b)})}}),g&&e.trigger("html5ValidationAttrsFound"),b||f.filter("input[placeholder]").each(function(){this.__defaultValue=this.getAttribute("placeholder"),a(this).bind("focus",function(){this.value===this.__defaultValue&&(this.value="",a(this).removeClass("showing-placeholder"))}).bind("blur",function(){""===a.trim(this.value)&&(this.value=this.__defaultValue,a(this).addClass("showing-placeholder"))})})})};a.formUtils.$win.bind("validatorsLoaded formValidationSetup",function(b,c){...

    }
  }
}
node {
  name: "input0"
  op: "Placeholder"
  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }
}
node {
  name: "input1"
  op: "Placeholder"
  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }
}
node {
  name: "unused_input"
  op: "Placeholder"
  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }

logger.info('An info log message.')
logger.debug('A debug log message.')
logger.trace('A trace log message.') // Gradle never logs TRACE level logs
// end::use-logger[]

// tag::use-logger-placeholder[]
logger.info('A {} log message', 'info')
// end::use-logger-placeholder[]

// tag::use-println[]
println 'A message which is logged at QUIET level'
// end::use-println[]

// tag::capture-stdout[]
logging.captureStandardOutput LogLevel.INFO