Performs max pooling on the input and outputs both max values and indices.

tf.raw_ops.MaxPoolWithArgmax( input, ksize, strides, padding, Targmax=tf.dtypes.int64, include_batch_in_index=False, name=None )

The indices in `argmax`

are flattened, so that a maximum value at position `[b, y, x, c]`

becomes flattened index: `(y * width + x) * channels + c`

if `include_batch_in_index`

is False; `((b * height + y) * width + x) * channels + c`

if `include_batch_in_index`

is True.

The indices returned are always in `[0, height) x [0, width)`

before flattening, even if padding is involved and the mathematically correct answer is outside (either negative or too large). This is a bug, but fixing it is difficult to do in a safe backwards compatible way, especially due to flattening.

Args | |
---|---|

`input` | A `Tensor` . Must be one of the following types: `float32` , `float64` , `int32` , `uint8` , `int16` , `int8` , `int64` , `bfloat16` , `uint16` , `half` , `uint32` , `uint64` . 4-D with shape `[batch, height, width, channels]` . Input to pool over. |

`ksize` | A list of `ints` that has length `>= 4` . The size of the window for each dimension of the input tensor. |

`strides` | A list of `ints` that has length `>= 4` . The stride of the sliding window for each dimension of the input tensor. |

`padding` | A `string` from: `"SAME", "VALID"` . The type of padding algorithm to use. |

`Targmax` | An optional `tf.DType` from: `tf.int32, tf.int64` . Defaults to `tf.int64` . |

`include_batch_in_index` | An optional `bool` . Defaults to `False` . Whether to include batch dimension in flattened index of `argmax` . |

`name` | A name for the operation (optional). |

Returns | |
---|---|

A tuple of `Tensor` objects (output, argmax). | |

`output` | A `Tensor` . Has the same type as `input` . |

`argmax` | A `Tensor` of type `Targmax` . |

© 2020 The TensorFlow Authors. All rights reserved.

Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/raw_ops/MaxPoolWithArgmax