}

// CHECK-LABEL:   func @maximum(
// CHECK-SAME:                  %[[VAL_0:.*]]: tensor<4xf32>,
// CHECK-SAME:                  %[[VAL_1:.*]]: tensor<4xf32>) -> tensor<4xf32> {
// CHECK:           %[[VAL_2:.*]] = "tf.Maximum"(%[[VAL_0]], %[[VAL_1]]) : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32>
// CHECK:           return %[[VAL_2]] : tensor<4xf32>
// CHECK:         }

	// and the context associated with the call was canceled or expired.
	return call.ctx.Err() != nil
}

// Buffer chunks are allocated from a pool to reduce pressure on GC.
// The maximum wasted space per dataBuffer is 2x the largest size class,
// which happens when the dataBuffer has multiple chunks and there is
// one unread byte in both the first and last chunks. We use a few size

            "schema": {
              "type": "string",
              "uniqueItems": true
            }
          },
          {

            "schema": {
              "type": "string",
              "uniqueItems": true
            }
          },
          {

conditions that must be met for a request to be sent to this webhook. Match conditions filter requests that have already been matched by the rules, namespaceSelector, and objectSelector. An empty list of matchConditions matches all requests. There are a maximum of 64 match conditions allowed.\n\nThe exact matching logic is (in order):\n  1. If ANY matchCondition evaluates to FALSE, the webhook is skipped.\n  2. If ALL matchConditions evaluate to TRUE, the webhook is called.\n  3. If any matchCondition evaluates...

        "description": "VolumeNodeResources is a set of resource limits for scheduling of volumes.",
        "properties": {
          "count": {

		[6]*argField{ap_VecReg_6_10, ap_VecReg_11_15, ap_VecReg_16_20}},
	{VMAXSB, 0xfc0007ff00000000, 0x1000010200000000, 0x0, // Vector Maximum Signed Byte VX-form (vmaxsb VRT,VRA,VRB)
		[6]*argField{ap_VecReg_6_10, ap_VecReg_11_15, ap_VecReg_16_20}},
	{VMAXSH, 0xfc0007ff00000000, 0x1000014200000000, 0x0, // Vector Maximum Signed Halfword VX-form (vmaxsh VRT,VRA,VRB)

                        use the same port, subject to the Listener compatibility rules.
                        \n Support: Core"
                      format: int32
                      maximum: 65535
                      minimum: 1
                      type: integer
                    protocol:
                      description: "Protocol specifies the network protocol this listener

  %249 = "tf.BroadcastTo"(%248, %221) {device = ""} : (tensor<?xi32>, tensor<1xi32>) -> tensor<?xi32>
  %250 = "tf.Max"(%249, %15) {device = "", keep_dims = false} : (tensor<?xi32>, tensor<1xi32>) -> tensor<i32>
  %251 = "tf.Maximum"(%14, %250) {device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i32>
  %252 = "tf.Range"(%14, %251, %7) {device = ""} : (tensor<i32>, tensor<i32>, tensor<i32>) -> tensor<?xi32>

  %0 = "tfl.mul"(%arg0, %alpha) {fused_activation_function = "NONE"} : (tensor<2x3xf32>, tensor<f32>) -> tensor<2x3xf32>
  %1 = "tfl.maximum"(%0, %arg0) : (tensor<2x3xf32>, tensor<2x3xf32>) -> tensor<2x3xf32>
  func.return %1 : tensor<2x3xf32>

  // CHECK: %[[RESULT:[0-9].*]] = "tfl.maximum"
}

// CHECK-LABEL: prelu_fusion
func.func @prelu_fusion(%arg0: tensor<2x3xf32>) -> tensor<2x3xf32> {