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- /**
- * Copyright 2019-2020 Huawei Technologies Co., Ltd
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
- #ifndef GE_OP_CTC_OPS_H
- #define GE_OP_CTC_OPS_H
-
- #include "graph/operator.h"
- #include "graph/operator_reg.h"
-
- namespace ge {
-
- /**
- *@brief Calculates the CTC Loss (log probability) for each batch entry. \n
- Also calculates the gradient.
-
- *@par Inputs:
- *@li inputs: 3-D, shape: `(max_time x batch_size x num_classes)`, the logits.
- *@li labels_indices: The indices of a `SparseTensor<int32, 2>`. \n
- `labels_indices(i, :) == [b, t]` means `labels_values(i)` stores the id for \n
- `(batch b, time t)`.
- *@li labels_values: The values (labels) associated with the given batch and time.
- *@li sequence_length: A vector containing sequence lengths (batch).
-
- *@par Outputs:
- *@li loss: A vector (batch) containing log-probabilities.
- *@li gradient: The gradient of `loss`. 3-D, shape: `(max_time x \n
- batch_size x num_classes)`.
-
- *@par Attributes:
- *@li preprocess_collapse_repeated: Scalar, if true then repeated labels are collapsed prior to \n
- the CTC calculation.If not specified, defaults to false
- *@li ctc_merge_repeated: Scalar. If set to false, *during* CTC calculation \n
- repeated non-blank labels will not be merged and are interpreted as \n
- individual labels. This is a simplified version of CTC. \n
- If not specified, defaults to true
-
- *@par Third-party framework compatibility
- * Compatible with TensorFlow CTCLoss operator.
- */
-
- REG_OP(CTCLoss)
- .INPUT(inputs, TensorType({DT_FLOAT, DT_DOUBLE}))
- .INPUT(labels_indices, TensorType({DT_INT64}))
- .INPUT(labels_values, TensorType({DT_INT32}))
- .INPUT(sequence_length, TensorType({DT_INT32}))
- .OUTPUT(loss, TensorType({DT_FLOAT, DT_DOUBLE}))
- .OUTPUT(gradient, TensorType({DT_FLOAT, DT_DOUBLE}))
- .ATTR(preprocess_collapse_repeated, Bool, false)
- .ATTR(ctc_merge_repeated, Bool, true)
- .ATTR(ignore_longer_outputs_than_inputs, Bool, false)
- .OP_END_FACTORY_REG(CTCLoss)
-
- } // namespace ge
-
- #endif //GE_OP_CTC_OPS_H
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