55 lines
2.2 KiB
C
55 lines
2.2 KiB
C
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/*******************************************************************************
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* Copyright (c) 2021 Deeplearning4j Contributors
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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*******************************************************************************/
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//
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// @author AbdelRauf
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//
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#ifndef LIBND4J_HELPERS_CTCLOSS_H
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#define LIBND4J_HELPERS_CTCLOSS_H
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#include <ops/declarable/helpers/helpers.h>
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#include <graph/Context.h>
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namespace sd {
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namespace ops {
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namespace helpers {
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/**
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* @brief Implementation of CTC loss function
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* References:
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Connectionist Temporal Classification - Labeling Unsegmented Sequence Data
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with Recurrent Neural Networks:
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[Graves et al., 2006](https://dl.acm.org/citation.cfm?id=1143891)
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([pdf](http://www.cs.toronto.edu/~graves/icml_2006.pdf))
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*
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* @param block Context
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* @param logits NDArray {BATCH_LEN, FRAME_LEN, CLASS_LEN }. log softmax of rnn output. It should include a blank label as well.
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* @param targetLabels NDArray {BATCH_LEN, MAX_TARGET_LEN}
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* @param logitsLengths NDArray {BATCH_LEN} Length of input sequence in logits
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* @param targetLabelLengths NDArray {BATCH_LEN} Length of label sequence in labels
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* @param logLosses NDArray {BATCH_LEN} or EMPTY. if empty it will be skipped. negative log probabilities of loss
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* @param gradients NDArray {BATCH_LEN, FRAME_LEN, CLASS_LEN } or EMPTY. gradients
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* @param blankIndex index of the blank label in logits
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*/
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void ctcLoss(graph::Context& block, const NDArray &logitsInput, const NDArray &targetLabels, const NDArray &logitsLengths, const NDArray &targetLabelLengths, NDArray &logLosses, NDArray &gradients, int blankIndex);
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}
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}
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}
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#endif // LIBND4J_ADDBIAS_H
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