/*depthwise_multiplier=*/rewriter.getI32IntegerAttr(multiplier));
    } else if (is_transpose_conv) {
      // TODO: b/326332748 - For forward convolution in transpose_conv,
      // IsSamePadding calculation may need to be updated.
      // Reference: https://arxiv.org/pdf/1603.07285.pdf
      // Section 4.6 > Relationship 13 states `stride_dim = dilation + 1`.
      rewriter.replaceOpWithNewOp<TFL::TransposeConvOp>(

    local variables.

    This pass requires that the full shape of the stack can be inferred: 1) the
    maximum size needs to be a constant and 2) a push op can be found with a
    known shape, and all push ops need to have the same shape.

    A stack creation op "tf.StackV2" will be turned in to two zero-initialized
    variables, for the buffer and current size. Each push will be turned into

   * Executor)} or to {@link #catchingAsync(Class, AsyncClosingFunction, Executor)} as long as it
   * meets these conditions:
   *
   * <ul>
   *   <li>It does not need to capture any {@link Closeable} objects by calling {@link
   *       DeferredCloser#eventuallyClose(Object, Executor)}.
   *   <li>It returns a {@link ListenableFuture}.
   * </ul>
   *
   * <p>Example usage:
   *

     Neg<Or<[
       TypeIsPred<"input_to_input_weights", NoneType>,
       TypeIsPred<"recurrent_to_input_weights", NoneType>,
       TypeIsPred<"input_gate_bias", NoneType>]>>]>>;


// TODO(b/137798843): Need to add an additional constraint for both LSTM and
// UnidirectionalSequenceLstm
// For layer norm: if layer norm is false, tensor {20, 21, 22, 23}
// are null; if layer norm is true, tensors {21, 22, 23} are not null; tensor

(Sqrt32 ...) => (FSQRTS ...)

(Min(64|32)F ...) => (FMIN(D|S) ...)
(Max(64|32)F ...) => (FMAX(D|S) ...)

// lowering rotates
// we do rotate detection in generic rules, if the following rules need to be changed, check generic rules first.
(RotateLeft8  <t> x (MOVDconst [c])) => (Or8 (Lsh8x64 <t> x (MOVDconst [c&7])) (Rsh8Ux64 <t> x (MOVDconst [-c&7])))

  %0 = "tfl.random_uniform"(%arg0) {seed = 0 : i64, seed2 = 0 : i64} : (tensor<3xi32>) -> tensor<?x?x?xf32>
  func.return %0 : tensor<?x?x?xf32>
}

// -----

// CHECK-LABEL: testRandomStandardNormal
func.func @testRandomStandardNormal(%arg0: tensor<3xi32>) -> tensor<?x?x?xf32> {
  // CHECK: "tfl.random_standard_normal"(%arg0)

target=\"_blank\">secure</a>,\n    <a href=\"https://istio.io/docs/concepts/traffic-management/\" target=\"_blank\">connect</a>, and \n    <a href=\"https://istio.io/docs/concepts/observability/\" target=\"_blank\">monitor</a> microservices.\n    <br>\n    Need help? <a href=\"https://istio.io/get-involved/\" target=\"_blank\">Join the Istio community</a>.\n  </div>\n</div>","mode":"html"},"pluginVersion":"10.1.5","style":{"font-size":"18pt"},"targets":[{"datasource":{"type":"prometheus","uid":"${datasou...

        ["lib1", "lib2"].each { name ->
            buildFile << withExternalLibDependency(name)
        }

        when:
        executer.requireIsolatedDaemons() // needs to stop daemon
        requireOwnGradleUserHomeDir() // needs its own journal
        succeeds ":app:resolve"

        then:
        def outputDir1 = immutableOutputDir("lib1-1.0.jar", "lib1-1.0.jar.txt").assertExists()

		// the size of the type, up to the size of the size class. This space
		// is safe for the GC to scan since it's zero, and GCBits checks to
		// make sure that's true. But we need to handle the fact that the bitmap
		// may be larger than we expect.
		return
	}
	_, _, line, _ := runtime.Caller(1)
	t.Errorf("line %d: heapBits incorrect for %v\nhave %v\nwant %v", line, typ, heapBits, bits)

  func.return %0 : tensor<10xi64>

// CHECK-LABEL:multinomial_i64
// CHECK: "tfl.multinomial"(%arg0, %arg1) <{seed = 0 : i64, seed2 = 0 : i64}> : (tensor<2xf32>, tensor<1xi32>) -> tensor<10xi64>
}

func.func @multinomial_i32(%arg0: tensor<2xf32>, %arg1: tensor<1xi32>) -> tensor<10xi32> {