# tf.nn.max_pool_with_argmax

tf.nn.max_pool_with_argmax(
input,
ksize,
strides,
Targmax=tf.int64,
name=None
)


Defined in generated file: tensorflow/python/ops/gen_nn_ops.py.

See the guide: Neural Network > Pooling

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

The indices in argmax are flattened, so that a maximum value at position [b, y, x, c] becomes flattened index ((b * height + y) * width + x) * channels + c.

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.
• 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.