@tf_export('math.argmax', 'argmax', v1=[])
def argmax_v2(input, axis=None, output_type=dtypes.int64, name=None):
    'Returns the index with the largest value across axes of a tensor.\n\n  Note that in case of ties the identity of the return value is not guaranteed.\n\n  Args:\n    input: A `Tensor`. Must be one of the following types: `float32`, `float64`,\n    `int32`, `uint8`, `int16`, `int8`, `complex64`, `int64`, `qint8`, `quint8`,\n    `qint32`, `bfloat16`, `uint16`, `complex128`, `half`, `uint32`, `uint64`.\n    axis: A `Tensor`. Must be one of the following types: `int32`, `int64`.\n      int32 or int64, must be in the range `-rank(input), rank(input))`.\n      Describes which axis of the input Tensor to reduce across. For vectors,\n      use axis = 0.\n    output_type: An optional `tf.DType` from: `tf.int32, tf.int64`.\n      Defaults to `tf.int64`.\n    name: A name for the operation (optional).\n\n  Returns:\n    A `Tensor` of type `output_type`.\n  '
    if (axis is None):
        axis = 0
    return gen_math_ops.arg_max(input, axis, name=name, output_type=output_type)
Returns the index with the largest value across axes of a tensor.

Note that in case of ties the identity of the return value is not guaranteed.

Args:
  input: A `Tensor`. Must be one of the following types: `float32`, `float64`,
  `int32`, `uint8`, `int16`, `int8`, `complex64`, `int64`, `qint8`, `quint8`,
  `qint32`, `bfloat16`, `uint16`, `complex128`, `half`, `uint32`, `uint64`.
  axis: A `Tensor`. Must be one of the following types: `int32`, `int64`.
    int32 or int64, must be in the range `-rank(input), rank(input))`.
    Describes which axis of the input Tensor to reduce across. For vectors,
    use axis = 0.
  output_type: An optional `tf.DType` from: `tf.int32, tf.int64`.
    Defaults to `tf.int64`.
  name: A name for the operation (optional).

Returns:
  A `Tensor` of type `output_type`.
@tf_export('math.argmax', 'argmax', v1=[])
def argmax_v2(input, axis=None, output_type=dtypes.int64, name=None):
    'Returns the index with the largest value across axes of a tensor.\n\n  Note that in case of ties the identity of the return value is not guaranteed.\n\n  Args:\n    input: A `Tensor`. Must be one of the following types: `float32`, `float64`,\n    `int32`, `uint8`, `int16`, `int8`, `complex64`, `int64`, `qint8`, `quint8`,\n    `qint32`, `bfloat16`, `uint16`, `complex128`, `half`, `uint32`, `uint64`.\n    axis: A `Tensor`. Must be one of the following types: `int32`, `int64`.\n      int32 or int64, must be in the range `-rank(input), rank(input))`.\n      Describes which axis of the input Tensor to reduce across. For vectors,\n      use axis = 0.\n    output_type: An optional `tf.DType` from: `tf.int32, tf.int64`.\n      Defaults to `tf.int64`.\n    name: A name for the operation (optional).\n\n  Returns:\n    A `Tensor` of type `output_type`.\n  '
    if (axis is None):
        axis = 0
    return gen_math_ops.arg_max(input, axis, name=name, output_type=output_type)