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## CTCGreedyDecoder <a name="CTCGreedyDecoder"></a> {#openvino_docs_ops_sequence_CTCGreedyDecoder_1}
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**Versioned name**: *CTCGreedyDecoder-1*
**Category**: *Sequence processing*
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**Short description**: *CTCGreedyDecoder* performs greedy decoding on the logits given in input (best path).
**Detailed description**:
Given an input sequence \f$X\f$ of length \f$T\f$, *CTCGreedyDecoder* assumes the probability of a length \f$T\f$ character sequence \f$C\f$ is given by
\f[
p(C|X) = \prod_{t=1}^{T} p(c_{t}|X)
\f]
Sequences in the batch can have different length. The lengths of sequences are coded as values 1 and 0 in the second input tensor `sequence_mask`. Value `sequence_mask[j, i]` specifies whether there is a sequence symbol at index `i` in the sequence `i` in the batch of sequences. If there is no symbol at `j`-th position `sequence_mask[j, i] = 0`, and `sequence_mask[j, i] = 1` otherwise. Starting from `j = 0`, `sequence_mass[j, i]` are equal to 1 up to the particular index `j = last_sequence_symbol`, which is defined independently for each sequence `i`. For `j > last_sequence_symbol`, values in `sequence_mask[j, i]` are all zeros.
**Note**: Regardless of the value of `ctc_merge_repeated` attribute, if the output index for a given batch and time step corresponds to the `blank_index`, no new element is emitted.
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**Attributes**
* *ctc_merge_repeated*
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* **Description**: *ctc_merge_repeated* is a flag for merging repeated labels during the CTC calculation.
* **Range of values**: `true` or `false`
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* **Type**: `boolean`
* **Default value**: `true`
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* **Required**: *no*
**Inputs**
* **1**: `data` - input tensor with batch of sequences of type *T_F* and shape `[T, N, C]`, where `T` is the maximum sequence length, `N` is the batch size and `C` is the number of classes. **Required.**
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* **2**: `sequence_mask` - input tensor with sequence masks for each sequence in the batch of type *T_F* populated with values `0` and `1` and shape `[T, N]`. **Required.**
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**Output**
* **1**: Output tensor of type *T_F* and shape `[N, T, 1, 1]` which is filled with integer elements containing final sequence class indices. A final sequence can be shorter that the size `T` of the tensor, all elements that do not code sequence classes are filled with `-1`.
**Types**
* *T_F*: any supported floating-point type.
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**Example**
```xml
<layer ... type="CTCGreedyDecoder" ...>
<data ctc_merge_repeated="true" />
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<input>
<port id="0">
<dim>20</dim>
<dim>8</dim>
<dim>128</dim>
</port>
<port id="1">
<dim>20</dim>
<dim>8</dim>
</port>
</input>
<output>
<port id="0">
<dim>8</dim>
<dim>20</dim>
<dim>1</dim>
<dim>1</dim>
</port>
</output>
</layer>
```