# tf.raw_ops.Conv2DBackpropInputV2

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Computes the gradients of 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.Conv2DBackpropInputV2`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/Conv2DBackpropInputV2)

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    tf.raw_ops.Conv2DBackpropInputV2(
        input,
        filter,
        out_backprop,
        strides,
        padding,
        use_cudnn_on_gpu=True,
        explicit_paddings=[],
        data_format='NHWC',
        dilations=[1, 1, 1, 1],
        name=None
    )

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| ## Args ||
|---|---|
| `input` | A `Tensor`. Must be one of the following types: `half`, `bfloat16`, `float32`, `float64`, `int32`. 4-D with shape `[batch, in_height, in_width, in_channels]`. Only shape of tensor is used. |
| `filter` | A `Tensor`. Must have the same type as `input`. 4-D with shape `[filter_height, filter_width, in_channels, out_channels]`. |
| `out_backprop` | A `Tensor`. Must have the same type as `input`. 4-D with shape `[batch, out_height, out_width, out_channels]`. Gradients w.r.t. the output of the convolution. |
| `strides` | A list of `ints`. The stride of the sliding window for each dimension of the input of the convolution. Must be in the same order as the dimension specified with format. |
| `padding` | A `string` from: `"SAME", "VALID", "EXPLICIT"`. The type of padding algorithm to use. |
| `use_cudnn_on_gpu` | An optional `bool`. Defaults to `True`. |
| `explicit_paddings` | An optional list of `ints`. Defaults to `[]`. If `padding` is `"EXPLICIT"`, the list of explicit padding amounts. For the ith dimension, the amount of padding inserted before and after the dimension is `explicit_paddings[2 * i]` and `explicit_paddings[2 * i + 1]`, respectively. If `padding` is not `"EXPLICIT"`, `explicit_paddings` must be empty. |
| `data_format` | An optional `string` from: `"NHWC", "NCHW"`. Defaults to `"NHWC"`. Specify the data format of the input and output data. With the default format "NHWC", the data is stored in the order of: \[batch, in_height, in_width, in_channels\]. Alternatively, the format could be "NCHW", the data storage order of: \[batch, in_channels, in_height, in_width\]. |
| `dilations` | An optional list of `ints`. Defaults to `[1, 1, 1, 1]`. 1-D tensor of length 4. 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 `input`. ||

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