# tf.nn.conv3d

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.14.0/tensorflow/python/ops/nn_ops.py#L3236-L3248) |

Computes a 3-D convolution given 5-D `input` and `filters` tensors.

    tf.nn.conv3d(
        input,
        filters,
        strides,
        padding,
        data_format='NDHWC',
        dilations=None,
        name=None
    )

In signal processing, cross-correlation is a measure of similarity of
two waveforms as a function of a time-lag applied to one of them. This
is also known as a sliding dot product or sliding inner-product.

Our Conv3D implements a form of cross-correlation.

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| ## Args ||
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| `input` | A `Tensor`. Must be one of the following types: `half`, `bfloat16`, `float32`, `float64`. Shape `[batch, in_depth, in_height, in_width, in_channels]`. |
| `filters` | A `Tensor`. Must have the same type as `input`. Shape `[filter_depth, filter_height, filter_width, in_channels, out_channels]`. `in_channels` must match between `input` and `filters`. |
| `strides` | A list of `ints` that has length `>= 5`. 1-D tensor of length 5. The stride of the sliding window for each dimension of `input`. Must have `strides[0] = strides[4] = 1`. |
| `padding` | A `string` from: `"SAME", "VALID"`. The type of padding algorithm to use. |
| `data_format` | An optional `string` from: `"NDHWC", "NCDHW"`. Defaults to `"NDHWC"`. The data format of the input and output data. With the default format "NDHWC", the data is stored in the order of: \[batch, in_depth, in_height, in_width, in_channels\]. Alternatively, the format could be "NCDHW", the data storage order is: \[batch, in_channels, in_depth, in_height, in_width\]. |
| `dilations` | An optional list of `ints`. Defaults to `[1, 1, 1, 1, 1]`. 1-D tensor of length 5. The dilation factor for each dimension of `input`. If set to k \> 1, there will be k-1 skipped cells between each filter element on that dimension. The dimension order is determined by the value of `data_format`, see above for details. Dilations in the batch and depth dimensions must be 1. |
| `name` | A name for the operation (optional). |

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| ## Returns ||
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| A `Tensor`. Has the same type as `input`. ||

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