}

func.func @einsum_fourdreducelast(%arg0: tensor<2x5x7x3xf32>, %arg1: tensor<2x3x5x13xf32>) -> tensor<2x7x5x13xf32> {
  %0 = "tf.Einsum"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", equation = "acbe,aecd->abcd"}: (tensor<2x5x7x3xf32>, tensor<2x3x5x13xf32>) -> tensor<2x7x5x13xf32>
  func.return %0 : tensor<2x7x5x13xf32>
  // CHECK-LABEL: einsum_fourdreducelast

 * and access mask of each ACE. If the SID matches, the allow/deny flags
 * and access mask are considered. If the ACE is a "deny"
 * ACE and <i>any</i> of the desired access bits match bits in the access
 * mask of the ACE, the whole access check fails. If the ACE is an "allow"
 * ACE and <i>all</i> of the bits in the desired access bits match bits in
 * the access mask of the ACE, the access check is successful. Otherwise,

  # Equations only supported for XLA operations.
  @parameterized.parameters(
      testing.parameter_combinations([{
          'equation': ('abc,acd->abd', 'abcd,aecd->acbe'),
          'shape_unknown': (True, False),
          'activation_fn': (None, nn_ops.relu, nn_ops.relu6),
          'has_bias': (True, False),
          'use_kernel': (True, False),
      }])
  )

 * and access mask of each ACE. If the SID matches, the allow/deny flags
 * and access mask are considered. If the ACE is a "deny"
 * ACE and <i>any</i> of the desired access bits match bits in the access
 * mask of the ACE, the whole access check fails. If the ACE is an "allow"
 * ACE and <i>all</i> of the bits in the desired access bits match bits in
 * the access mask of the ACE, the access check is successful. Otherwise,

 * and access mask of each ACE. If the SID matches, the allow/deny flags
 * and access mask are considered. If the ACE is a "deny"
 * ACE and <i>any</i> of the desired access bits match bits in the access
 * mask of the ACE, the whole access check fails. If the ACE is an "allow"
 * ACE and <i>all</i> of the bits in the desired access bits match bits in
 * the access mask of the ACE, the access check is successful. Otherwise,

    %17 = "tf.Sub"(%16, %cst_5) {device = ""} : (tensor<2x6x4x5xi32>, tensor<i32>) -> tensor<2x6x4x5xi32>
    %18 = "tf.Einsum"(%14, %17) {device = "", equation = "abcd,aecd->acbe"} : (tensor<2x3x4x5xi32>, tensor<2x6x4x5xi32>) -> tensor<2x4x3x6xi32>
    %19 = "tf.Cast"(%18) {Truncate = false, device = ""} : (tensor<2x4x3x6xi32>) -> tensor<2x4x3x6xf32>

            """

        """
            $pluginsBlock

            import static com.acme.Flavor.free
            import static com.acme.Flavor.paid
            import static com.acme.BuildType.debug
            import static com.acme.BuildType.release

            def flavor = Attribute.of(com.acme.Flavor)
            def buildType = Attribute.of(com.acme.BuildType)
        """

            def platform = mavenRepo.module("com.acme.foo", "platform", v)
            platform.assertPublished()
            platform.hasGradleMetadataRedirectionMarker()
            platform.parsedModuleMetadata.variant("apiElements") {
                constraint("com.acme.foo:core:$v") {
                    exists()
                }
                constraint("com.acme.foo:lib:$v") {
                    exists()

        where:
        fqn          | src
        'A'          | 'public class A {}'
        'com.acme.A' | '''
                           package com.acme;
                           public class A {}
                       '''
        'com.acme.B' | '''
                           package com.acme;
                           public class B {
                               String getName() { return "foo"; }

    }

    @Override
    protected extractResultsFrom(TestFile projectDir) {
        [
            "org/acme/Test.tokens",
            "org/acme/TestBaseListener.java",
            "org/acme/TestLexer.java",
            "org/acme/TestLexer.tokens",
            "org/acme/TestListener.java",
            "org/acme/TestParser.java",
        ].collect { projectDir.file("build/generated-src/antlr/main/$it").text }.join("\n")
    }