| op { |
| graph_op_name: "DenseBincount" |
| in_arg { |
| name: "input" |
| description: <<END |
| 1D or 2D int `Tensor`. |
| END |
| } |
| in_arg { |
| name: "size" |
| description: <<END |
| non-negative int scalar `Tensor`. |
| END |
| } |
| in_arg { |
| name: "weights" |
| description: <<END |
| is an int32, int64, float32, or float64 `Tensor` with the same |
| shape as `arr`, or a length-0 `Tensor`, in which case it acts as all weights |
| equal to 1. |
| END |
| } |
| out_arg { |
| name: "output" |
| description: <<END |
| 1D `Tensor` with length equal to `size` or 2D `Tensor` with [batch_size, `size`]. |
| The counts or summed weights for each value in the range [0, size). |
| END |
| } |
| attr { |
| name: "binary_output" |
| description: <<END |
| bool; Whether the kernel should count the appearance or number of occurrences. |
| END |
| } |
| summary: "Counts the number of occurrences of each value in an integer array." |
| description: <<END |
| Outputs a vector with length `size` and the same dtype as `weights`. If |
| `weights` are empty, then index `i` stores the number of times the value `i` is |
| counted in `arr`. If `weights` are non-empty, then index `i` stores the sum of |
| the value in `weights` at each index where the corresponding value in `arr` is |
| `i`. |
| |
| Values in `arr` outside of the range [0, size) are ignored. |
| END |
| } |