performed instead:

```python
tf.cumsum([a, b, c], exclusive=True)  # => [0, a, a + b]
```

By setting the `reverse` kwarg to `True`, the cumsum is performed in the
opposite direction:

```python
tf.cumsum([a, b, c], reverse=True)  # => [a + b + c, b + c, c]
```

This is more efficient than using separate `tf.reverse` ops.

    "tf.Yield"(%arg1) : (tensor<f32>) -> ()
  }) {is_stateless = false} : (tensor<i32>) -> tensor<i1>
  func.return
}

// -----

// Test valid tf.Cumsum
func.func @testCumsum(%arg: tensor<8x16xf32>, %axis: tensor<i32>) -> tensor<8x16xf32> {
  %0 = "tf.Cumsum"(%arg, %axis) : (tensor<8x16xf32>, tensor<i32>) -> tensor<8x16xf32>
  func.return %0 : tensor<8x16xf32>
}

// -----

// CHECK-DAG:       %[[VAL_2:.*]] = "tf.Const"() <{value = dense<0> : tensor<i64>}> : () -> tensor<i64>
// CHECK:           %[[VAL_3:.*]] = "tf.Cumsum"(%[[VAL_0]], %[[VAL_2]]) <{exclusive = false, reverse = false}> : (tensor<4x12xf32>, tensor<i64>) -> tensor<4x12xf32>
// CHECK:           return %[[VAL_3]] : tensor<4x12xf32>
// CHECK:         }

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*   GPU
    *   GPU acceleration now supports quantized models by default
*   `DynamicBuffer::AddJoinedString()` will now add a separator if the first
    string to be joined is empty.
*   Adds support for cumulative sum (cumsum), both as builtin op and MLIR
    conversion.

### `TensorRT`

*   Issues a warning when the `session_config` parameter for the TF1 converter

    if (result.getType() != op.getType())
      result = rewriter.create<tensor::CastOp>(loc, op.getType(), result);
    rewriter.replaceOp(op, result);
    return success();
  }
};

// Converts the Cumsum or Cumprod TensorFlow op to the HLO ReduceWindow op by
// setting appropriate window dimensions, with the given aggregation op as the
// reduction function. The input tensor needs to have a static shape, and 'axis'

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    "NON_MAX_SUPPRESSION_V4",
    "NON_MAX_SUPPRESSION_V5",
    "SCATTER_ND",
    "SELECT_V2",
    "DENSIFY",
    "SEGMENT_SUM",
    "BATCH_MATMUL",
    "PLACEHOLDER_FOR_GREATER_OP_CODES",
    "CUMSUM",
    "CALL_ONCE",
    "BROADCAST_TO",
    "RFFT2D",
    "CONV_3D",
    "IMAG",
    "REAL",
    "COMPLEX_ABS",
    "HASHTABLE",
    "HASHTABLE_FIND",
    "HASHTABLE_IMPORT",