# W3cubDocs

/TensorFlow 2.4

Computes the gradient of the crop_and_resize op wrt the input boxes tensor.

Args
`grads` A `Tensor` of type `float32`. A 4-D tensor of shape `[num_boxes, crop_height, crop_width, depth]`.
`image` A `Tensor`. Must be one of the following types: `uint8`, `uint16`, `int8`, `int16`, `int32`, `int64`, `half`, `float32`, `float64`. A 4-D tensor of shape `[batch, image_height, image_width, depth]`. Both `image_height` and `image_width` need to be positive.
`boxes` A `Tensor` of type `float32`. A 2-D tensor of shape `[num_boxes, 4]`. The `i`-th row of the tensor specifies the coordinates of a box in the `box_ind[i]` image and is specified in normalized coordinates `[y1, x1, y2, x2]`. A normalized coordinate value of `y` is mapped to the image coordinate at `y * (image_height - 1)`, so as the `[0, 1]` interval of normalized image height is mapped to `[0, image_height - 1] in image height coordinates. We do allow y1 > y2, in which case the sampled crop is an up-down flipped version of the original image. The width dimension is treated similarly. Normalized coordinates outside the`[0, 1]`range are allowed, in which case we use`extrapolation_value`to extrapolate the input image values. </td> </tr><tr> <td>`box_ind`</td> <td> A`Tensor`of type`int32`. A 1-D tensor of shape`[num_boxes]`with int32 values in`[0, batch)`. The value of`box_ind[i]`specifies the image that the`i`-th box refers to. </td> </tr><tr> <td>`method`</td> <td> An optional`string`from:`"bilinear"`. Defaults to`"bilinear"`. A string specifying the interpolation method. Only 'bilinear' is supported for now. </td> </tr><tr> <td>`name` A name for the operation (optional).
Returns
A `Tensor` of type `float32`.