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CTCGreedyDecoder operation specification refactoring (#5885)

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* CTCGreedyDecoder spec refactored against explicit type indication.

* Add backticks to output tensor description.
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Jozef Daniecki 2021-06-01 12:58:45 +02:00 committed by GitHub
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docs/ops/sequence/CTCGreedyDecoder_1.md
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@ -7,9 +7,6 @@
**Short description**: *CTCGreedyDecoder* performs greedy decoding on the logits given in input (best path).
**Detailed description**:
This operation is similar [Reference](https://www.tensorflow.org/api_docs/python/tf/nn/ctc_greedy_decoder)
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)
@ -24,20 +21,23 @@ Sequences in the batch can have different length. The lengths of sequences are c
* *ctc_merge_repeated*
* **Description**: *ctc_merge_repeated* is a flag for merging repeated labels during the CTC calculation.
* **Range of values**: true or false
* **Range of values**: `true` or `false`
* **Type**: `boolean`
* **Default value**: true
* **Default value**: `true`
* **Required**: *no*
**Inputs**
* **1**: `data` - Input tensor with a batch of sequences. Type of elements is any supported floating point type. Shape of the tensor is `[T, N, C]`, where `T` is the maximum sequence length, `N` is the batch size and `C` is the number of classes. Required.
* **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.**
* **2**: `sequence_mask` - 2D input floating point tensor with sequence masks for each sequence in the batch. Populated with values 0 and 1. Shape of this input is `[T, N]`. Required.
* **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.**
**Output**
* **1**: Output tensor with shape `[N, T, 1, 1]` and 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. Type of elements is floating point, but all values are integers.
* **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.
**Example**