TensorFlow 1 version
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View source on GitHub
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Performs max pooling on the input and outputs both max values and indices.
tf.nn.max_pool_with_argmax(
input, ksize, strides, padding, data_format='NHWC',
output_dtype=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 | |
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input
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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.
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ksize
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An int or list of ints that has length 1, 2 or 4.
The size of the window for each dimension of the input tensor.
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strides
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An int or list of ints that has length 1, 2 or 4.
The stride of the sliding window for each dimension of the
input tensor.
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padding
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A string from: "SAME", "VALID".
The type of padding algorithm to use.
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data_format
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An optional string, must be set to "NHWC". Defaults to
"NHWC".
Specify the data format of the input and output data.
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output_dtype
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An optional tf.DType from: tf.int32, tf.int64.
Defaults to tf.int64.
The dtype of the returned argmax tensor.
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include_batch_in_index
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An optional boolean. Defaults to False.
Whether to include batch dimension in flattened index of argmax.
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name
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A name for the operation (optional). |
Returns | |
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A tuple of Tensor objects (output, argmax).
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output
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A Tensor. Has the same type as input.
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argmax
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A Tensor of type output_dtype.
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