%0 = "tf.XlaConvV2"(%lhs, %rhs, %strides, %padding, %lhs_dilation, %rhs_dilation, %feature_group_count) {dimension_numbers = "\18\03 \042\03\00\01\02@\04P\04Z\03\01\02\03b\03\01\02\03", precision_config = ""} : (tensor<8x?x?x?x16xf32>, tens...

  %0 = "tf.XlaConvV2"(%arg0, %arg1, %strides, %padding, %lhs_dilation, %rhs_dilation, %feature_group_count) {
      batch_group_count = 1 : i64,
      dimension_numbers = "\18\03 \042\03\00\01\02@\04P\04Z\03\01\02\03b\03\01\02\03",
      precision_config = ""} : (tensor<8x4x16x16x16xf32>, tensor<4x3x3x16x16xf32>, tensor<3xi32>,
         tensor<3x2xi32>, tensor<3xi32>, tensor<3xi32>, tensor<i32>) -> tensor<8x4x14x14x16xf32>

DATA K_XMM_AR<>+0x7c(SB)/4,$0xca62c1d6
GLOBL K_XMM_AR<>(SB),RODATA,$128

DATA BSWAP_SHUFB_CTL<>+0x00(SB)/4,$0x00010203
DATA BSWAP_SHUFB_CTL<>+0x04(SB)/4,$0x04050607
DATA BSWAP_SHUFB_CTL<>+0x08(SB)/4,$0x08090a0b
DATA BSWAP_SHUFB_CTL<>+0x0c(SB)/4,$0x0c0d0e0f
DATA BSWAP_SHUFB_CTL<>+0x10(SB)/4,$0x00010203
DATA BSWAP_SHUFB_CTL<>+0x14(SB)/4,$0x04050607
DATA BSWAP_SHUFB_CTL<>+0x18(SB)/4,$0x08090a0b

      tf_executor.fetch %outputs_16, %outputs_18, %outputs_8, %outputs_12 : tensor<*xi32>, tensor<*xi32>, tensor<*xi32>, tensor<*x!tf_type.variant>
    }
    return %0#0, %0#1, %0#2, %0#3 : tensor<*xi32>, tensor<*xi32>, tensor<*xi32>, tensor<*x!tf_type.variant>
  }

		b.StopTimer()
	}
}

// Issue 9124.
// %x on bytes couldn't handle non-space bytes terminating the scan.
func TestHexBytes(t *testing.T) {
	var a, b []byte
	n, err := Sscanf("00010203", "%x", &a)
	if n != 1 || err != nil {
		t.Errorf("simple: got count, err = %d, %v; expected 1, nil", n, err)
	}
	check := func(msg string, x []byte) {
		if len(x) != 4 {

  // CHECK: return %[[SHAPE0]], %[[SHAPE13]]#0, %[[SHAPE2]], %[[SHAPE13]]#1
  func.return %0#0, %0#1, %0#2, %0#3 : tensor<0xi64>, tensor<3xi64>, tensor<4xi64>, tensor<?xi64>
}

// CHECK-LABEL: func @testShapeNOneDynamic

  %1 = "tf.Const"() {value = dense<[1, 9, 23, 768]> : tensor<4xi32>} : () -> tensor<4xi32>
  %2 = "tf.XlaGather"(%arg0, %0, %1) {device = "", dimension_numbers = "\0A\04\00\01\02\03\1A\01\02", indices_are_sorted = false} : (tensor<1x9x104x768xf32>, tensor<1xi32>, tensor<4xi32>) -> tensor<?x?x?x?xf32>
  func.return %2 : tensor<?x?x?x?xf32>

  %0 = "tf.XlaConvV2"(%lhs, %rhs, %strides, %padding, %lhs_dilation, %rhs_dilation, %feature_group_count) {dimension_numbers = "\18\03 \042\03\00\01\02@\04P\04Z\03\01\02\03b\03\01\02\03", precision_config = ""} : (tensor<8x4x16x16x16xf32>, tensor<4x3x3x16x16xf32>, tensor<3xi32>, tensor<3x2xi32>, tensor<3xi32>, tensor<3xi32>, tensor<2xi32>) -> tensor<8x4x14x14x16xf32>
  func.return %0 : tensor<8x4x14x14x16xf32>
}

  // CHECK: "tf.XlaConvV2"(%arg0, %arg1, %cst_3, %cst_2, %cst_0, %cst_1, %cst) <{batch_group_count = 1 : i64, dimension_numbers = "\18\03 \042\03\00\01\02@\04P\04Z\03\01\02\03b\03\01\02\03", precision_config = ""}> {device = "/job:localhost/replica:0/task:0/device:GPU:0"} : (tensor<8x4x16x16x16xf32>, tensor<4x3x3x16x16xf32>, tensor<3xi32>, tensor<3x2xi32>, tensor<3xi32>, tensor<3xi32>, tensor<i32>) -> tensor<8x4x14x14x16xf32>

    }) {device_assignment = [], num_cores_per_replica = 1 : i64, topology = ""} : () -> (tensor<?x3xi32>, tensor<?x3xi32>, tensor<3x!tf_type.string>, tensor<3x!tf_type.string>)
    return %0#0, %0#1, %0#2, %0#3 : tensor<?x3xi32>, tensor<?x3xi32>, tensor<3x!tf_type.string>, tensor<3x!tf_type.string>
  }
}
// -----

// Tests that a an error is reported when the pass results in a cluster output