# tf.raw_ops.Conv3DBackpropInputV2

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Computes the gradients of 3-D convolution with respect to the input.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.raw_ops.Conv3DBackpropInputV2`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/Conv3DBackpropInputV2)

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    tf.raw_ops.Conv3DBackpropInputV2(
        input_sizes,
        filter,
        out_backprop,
        strides,
        padding,
        data_format='NDHWC',
        dilations=[1, 1, 1, 1, 1],
        name=None
    )

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| ## Args ||
|---|---|
| `input_sizes` | A `Tensor`. Must be one of the following types: `int32`, `int64`. An integer vector representing the tensor shape of `input`, where `input` is a 5-D `[batch, depth, rows, cols, in_channels]` tensor. |
| `filter` | A `Tensor`. Must be one of the following types: `half`, `bfloat16`, `float32`, `float64`. Shape `[depth, rows, cols, in_channels, out_channels]`. `in_channels` must match between `input` and `filter`. |
| `out_backprop` | A `Tensor`. Must have the same type as `filter`. Backprop signal of shape `[batch, out_depth, out_rows, out_cols, out_channels]`. |
| `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 ||
|---|---|
| A `Tensor`. Has the same type as `filter`. ||

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